Proceedings of the 14th European Conference on Knowledge Management Kaunas University of Technology, Lithuania 5-6 September 2013
Edited by Brigita JaniĹŤnaitÄ— and Monika Petraite Kaunas University of Technology, Kaunas, Lithuania
Volume One A conference managed by ACPI, UK www.academic-conferences.org
7th European Conference on Information Management & Evaluation 12‐13 September 2013 Sopot, Poland
9th International Conference on e‐Learning 26‐27 June 2014 Santiago, Chile
See the website for latest dates & venues www.academic‐conferences.org
15th European Conference on Knowledge Management 4-5 September 2014 Santarem, Portugal
7th European Conference on Game Based Learning 3‐4 October 2013 Porto, Portugal
13th European Conference on Information Warfare & Security 3‐4 July 2014 University of Piraeus, Greece
European Conference on Social Media 10‐11 July 2014 Brighton, UK
10th International Conference on Intellectual Capital and Knowledge Management 24‐25 October 2013 Washington, DC, USA 12th European Conference on e‐ Learning 30‐31 October 2013 Sophia Antipolis, France 9th European Conference on Management, Leadership & Governance 14‐15 November 2013 Klagenfurt, Austria
International Conference on Cloud Security Management 17‐18 October 2013 Seattle, USA
8th European Conference on Innovation & Entrepreneurship 19‐20 September 2013 Brussels, Belgium
13th European Conference on Research Methods Date and Venue tbc
14th European Conference on e‐ Government 12‐13 June 2014 Brasov, Romania
5th International Conference on Information Management and Evaluation Date and venue tbc
6th European Conference on Intellectual Capital 11‐12 April 2014 Trnava, Slovak Republic
2nd International Conference on Innovation and Entrepreneurship 6‐7 February 2014 Bangkok, Thailand 2nd International Conference on Management, Leadership and Governance 20‐21 March 2014 Wellesley, Massachusetts, USA 9th International Conference on Cyber Warfare & Security 24‐25 March 2014 (formally ICIW) West Lafayette, Indiana, USA
Proceedings of the 14th European Conference on Knowledge Management ECKM 2013 Volume One Kaunas University of Technology Kaunas Lithuania 5-6 September 2013 Edited by Prof. Dr. Brigita JaniĹŤnaitÄ—, Prof.Dr. Asta Pundziene Prof. Dr. Monika Petraite
Copyright The Authors, 2013. All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors. Papers have been double-blind peer reviewed before final submission to the conference. Initially, paper abstracts were read and selected by the conference panel for submission as possible papers for the conference. Many thanks to the reviewers who helped ensure the quality of the full papers. These Conference Proceedings have been submitted to Thomson ISI for indexing. Please note that the process of indexing can take up to a year to complete. Further copies of this book and previous year’s proceedings can be purchased from http://academic-bookshop.com E-Book ISBN: 978-1-909507-40-1 E-Book ISSN: 2048-8971 Book version ISBN: 978-1-909507-38-8 Book Version ISSN: 2048-8963 CD Version ISBN: 978-1-909507-41-8 CD Version ISSN: 2048-898X The Electronic version of the Proceedings is available to download at ISSUU.com. You will need to sign up to become an ISSUU user (no cost involved) and follow the link to http://issuu.com Published by Academic Conferences and Publishing International Limited Reading UK 44-118-972-4148 www.academic-publishing.org
Contents Paper Title
Author(s)
Page No.
Preface
vii
Committee
viii
Biographies
xi
Using Neuromarketing Studies to Explore Emotional Intelligence – as a key to the Buying Decision Process
Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau
1
Enabling Knowledge Sharing in an Academic Environment: A Case Study
Versavia Ancusa, Razvan Bogdan and Oana Caus
9
Filling the Knowledge gap: How Relevant is University Programmes to Industry Needs?
Nicolene Barkhuizen
17
Embedding Knowledge Management in Public Sector Procurement – Redesigning for the Knowledge Economy
Denise A. D. Bedford
25
Topology of Knowledge and Information in the Transportation Sector
Denise A. D. Bedford1 and Lisa Loyo
35
Collaborative Solutions Quick&Clean: The SFM Method
Marco Bettoni, Willi Bernhard and Nicole Bittel
44
Intra-Organisational Knowledge Sharing: Scenarios and Corresponding Strategies
Madeleine Block and Tatiana Khvatova
52
Organizational Culture vs. Structure: An Academic Case Study
Razvan Bogdan, Versavia Ancusa and Oana Caus
61
Entropy vs. Organizational Learning and Dynamic Capabilities: The Thermodynamic Analogy
Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova
69
A new Marketing Audit Tool for Knowledge Intensive Business Services
Ettore Bolisani and Enrico Scarso
74
Emotional Knowledge: The Hidden Part of the Knowledge Iceberg
Constantin Bratianu and Ivona Orzea
82
Managerial Factors of Organizational Learning for Sustainable Development
Valentina Burksiene and Palmira Juceviciene
91
Capturing Safety Knowledge: Using a Safety-Specific Exit Survey
Christopher Burt, Cassandra Cottle, Katharina Näswall and Skye Williams
99
Knowledge Management in Defence
Barry Byrne and Frank Bannister
106
A Framework for Improving an Organizational Memory Information System’s Deployment Architecture
Osvaldo Cairo and Oscar Ojeda Galicia
117
The KAMET II Methodology: A Real Process for Knowledge Generation
Osvaldo Cairó and Silvia Guardati
124
Knowledge management capabilities in family firms
Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez
131
Relationship Between Perceived Organizational Support, Self-Efficacy, Subjective Norms and Knowledge Sharing
Delio Ignacio Castaneda and Manuel Fernández Ríos
140
The Value of Extended Framework of TAM in the Electronic Government Services
Juan-Gabriel Cegarra-Navarro, Stephen Eldridge, Eva Martinez-Caro and Maria Teresa Sanchez Polo
148
i
Paper Title
Author(s)
Page No.
A Context-Aware Architecture for the Management of Laundry Business Processes
Ufuk Celikkan and Kaan Kurtel
159
Modeling Organizational Intelligence Based on Knowledge Management in the Technical and Vocational Training Organization of Tehran
Hossein Chenari, Fattah Nazem, Mahmood Safari
167
An Introduction to STRIKE: STRuctured Interpretation of the Knowledge Environment
Sally Eaves and John Walton
174
Ipe Revisited: Validating a Multidimensional Model of Individual Knowledge Sharing Influences
Sally Eaves
184
Simulation of Space Operation - A Study on Learning in Control Rooms
Anandasivakumar Ekambaram, Brit-Eli Danielsen, Liz Helena Froes Coelho and Trine Marie Stene
194
The Role of Knowledge Management and Innovation in Challenging Times – A View on the Leisure Boat Industry
Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen
202
Knowledge Sharing Challenges in Developing Earlystage Entrepreneurship
Tiit Elenurm and Anne Reino
211
A Systematic Review and Comparison of Knowledge Management-Frameworks
Nora Fteimi and Franz Lehner
219
Organizational Characteristics That Influence the way Middle Managers and Their Subordinates are Available to Each Other
Zoltán Gaál, Lajos Szabó, and Anikó Csepregi
227
A Knowledge-Based Reference Model to Support Demand Management in Contemporary Supply Chains
Sotiris Gayialis, Stavros Ponis, Ilias Tatsiopoulos, Nikolaos Panayiotou and Dimitrios-Robert Stamatiou
236
Loosely-Coupled Networks of Knowledge Production and Diffusion
Gianna Giudicati and Massimo Riccaboni
245
The Factors of Knowledge Sharing in a SelfOrganisation Based System
Kristina Grumadaite
254
Mapping Research Community and Interests in KM: A Case of JKM
Meliha Handzic and Nermina Durmic
262
Developing a Knowledge Strategy Using Tacit Knowledge Measurement: Implications for the Balanced Scorecard Innovation and Learning Perspective
Harold Harlow
270
Applying the Concept of Communities of Practice: An Empirical Study of Innovative Collaboration Between Academia and Industry
Päivi Iskanius and Ilpo Pohjola
278
A Scientifically Grounded Model to Reduce Knowledge Loss in Organisations
Thomas Jackson, Paul Parboteeah and Nicola Wilkinson
287
Knowledge Management, Call Centres and Customer Satisfaction: A Case Study From the Transport Sector
Mahsa Jahantab and Alexeis Garcia-Perez
295
Social Media in Knowledge Management – Overcoming Fundamental Knowledge Problems
Harri Jalonen
300
Customer Experiential Knowledge Management (CEKM) - Concept Proposition and Research Framework Development
Dhouha Jaziri Bouagina and Abdelfattah Triki
307
ii
Paper Title
Author(s)
Page No.
MNCs Innovation, Reverse Knowledge Transfer and Firm Absorptive Capacity
Daniel Jimenéz-Jimenéz; Micaela Martínez-Costa and Raquel Sanz-Valle
315
Peculiarities of organization’s knowing
Habil. Palmira Juceviciene and Vyda Mozuriuniene
323
The Dimension of Smart Specialisation in the Business System
Robertas Jucevicius and Aukse Galbuogiene
333
The Effectiveness of Storytelling in Transferring Different Types of Knowledge
Marcela Katuščáková and Martin Katuščák
341
Impact of Knowledge Management Practices (KMPs) on Competitive Advantage in Pharmaceutical Firms
Radwan Kharabsheh and Ayman Aqrabawi
349
The Impact of Knowledge Management Practices on Organizational Performance
Aino Kianto, Paavo Ritala, Mika Vanhala and Henri Inkinen
356
Creating Banks’ Competitiveness by Proper Identification and Usage of Intangibles – Survey Results
Monika Klimontowicz
362
Effective Knowledge Sharing Through Social Technologies
Jaroslava Kubátová
372
The Manufacturer, the Screener, the User, and the Scientist: Producing and Circulating Information and Knowledge About Equipment
Monique Lortie, Angel Alberto Toyos Alvares, Steve Vezeau and Maud Gonella
380
387The Importance of Emotional Inte397lligence in Effective Leaders404hip Skills: The Case of Romanian S413oftware Development C421ompanies
Edit Lukacs, Sofia David and Alexandru Capatina
387
Information Technology: An Enabler for Trust-Building, Knowledge Sharing and Knowledge Transfer to Enhance Absorptive Capacity
Athar Mahmood Ahmed Qureshi and Nina Evans
397
Applying a Technology Acceptance Model to Test Business e-Loyalty Towards Online Banking Transactions
Eva Martinez-Caro, Gabriel CepedaCarrión, and Juan-Gabriel Cegarra-Navarro
404
Knowledge Management for Organizational Innovation: A Multinational Corporations Perspective
Micaela Martínez-Costa, Daniel JimenézJimenéz and Raquel Sanz-Valle
413
Expatriates’ Influence on Knowledge Sharing: An Empirical Study With International Portuguese Companies
Dora Martins
421
Intellectual Capital: A Valuable Resource for University Technology Commercialisation?
Kristel Miller Sandra Moffett Rodney McAdam and Michael Brennan
429
Reconceptualising knowledge transfer practices in the South African public sector
Peter L Mkhize
438
Knowledge Worker From the Perspective of Their Managers
Ludmila Mládková
446
Strategies for KM Implementation: UK Case Study Perspectives
Sandra Moffett
453
Motivating key Employees Towards Knowledge Sharing - Research Findings and Suggested Solutions
Mieczysław Morawski
462
iii
,
Volume Two Improved Information Sharing in Supply Chain Environment Using Knowledge Management Technologies
Edrisi Muñoz, Elisabet Capón-García, José M. Laínez, Antonio Espuña and Luis Puigjaner
472
Institutional Wiki: Evolving Public and Private Knowledge in MPMG
Lilian Noronha Nassif and Daniel Silva Carnevalli
482
Validation of the Scale of Knowledge Management Assessment in the Technical and Vocational Training Organization of Tehran
Fattah Nazem, Hossein Chenari and Omalbanin Sadeghi
490
Organisational Knowledge and Human Capital: A Conceptualisation for the Non-Profit Sector
Olimpia Neagu
496
Theorising a new Concept: ‘Micro Intellectual Capital’ (MIC) Using Knowledge From Inside the Classroom
Gary Oliver
506
Analysis of Awareness and Priorities, Focused on Intellectual Capital Among Slovak Companies
Ján Papula, Jana Volná, Anna Pilková, Jaroslav Huľvej
517
Towards Born-Global Innovation: the Role of Knowledge Management and Social Software
Jan M. Pawlowski
527
The Importance of Language Knowledge in International Companies
Corina Pelau, Irina Purcarea and Stelian Stancu
535
Linking External and Internal R&D and experience based Knowledge Flows for Innovation via Organisational Design Elements
Monika Petraite
543
The Role of Rational, Emotional and Spiritual Knowledge in Customer Relationship Management
Carmen Petrisoaia and Nicolae Al. Pop
552
Decision-Making Processes Based on Emotions in Universities as Learning Organizations
Magdalena Platis
560
Inter-Organizational Knowledge Transfer for Supply Chains in Crisis
Stavros Ponis and Epaminondas Koronis
569
Institutional Planning of Knowledge Generation
Evgeny Popov, Maxim Vlasov, Anna Yu.Veretennikova
577
Knowledge Audit: Findings From a Case Study in the Energy Sector
Gillian Ragsdell, Steve Probets, Ghosia Ahmed and Ian Murray
584
Shared Knowledge: Eliminating the “Ba”
Thomas Schalow
594
Correlation Between Individual Knowledge and Organizational Learning Process
Christian-Andreas Schumann and Claudia Tittmann
600
Heuristic for Unscheduled Public Transport Navigation System
José Sendra Salcedo and Osvaldo Cairó Battistuti
607
On Some Knowledge Issues in Sciences and Society
Dan Serbanescu
616
Using the SECI Model to Analyze Knowledge Creation in Students’ Software Teams
Mzwandile Shongwe
626
Do it Like the European Union (EU) Does: The Applicability of EU Knowledge Cost Management to Start ups
Evangelia Siachou and Dimitris Apostolidis
634
Use and Acceptance of Learning Platforms Within Universities
Boyka Simeonova, Pavel Bogolyubov and Evgeny Blagov
642
iv
The Relationship between Knowledge Management and Employees' Empowerment in Justice Administration of Tehran Province
Faezeh Sohrabi, Alireza Chenari, Fattah Nazem, Mohamad Farahzadi and Masoumeh Bahmanabadi
652
Software Agent Societies for Process Management in Knowledge-Based Organization
Anna Sołtysik-Piorunkiewicz and Mariusz Żytniewski
661
Innovation and Sustainability: Two-Sided Knowledge Management by an Ice-Cream Producer
Inga Stankevice and Birute Slaustaite
670
Business Innovative Environment as a Prerequisite for a Long-run Competitive Advantage
Marta Christina Suciu and Cristina Andreea Florea
678
The Creative Society, Urban Revitalisation in the Creative Economy and Society: The Romanian Case
Marta-Christina Suciu and Mina FaneaIvanovici
686
Strategic Innovation – Access Path Towards a New Paradigm of an Academic Career Management
Marta-Christina Suciu, Irina Dumitrescu and Andrei Dumitrescu
692
Success Factors in Knowledge Sharing Behaviour Among Student Bloggers
Nor Intan Saniah Sulaiman, Mazlan Mohd Sappri, Mohd Syazwan Abdullah and Nazean Jomhari
702
Innovation, Knowledge and Incompetence: The Case of the Eurozone Macroeconomic Policies
Eduardo Tomé
712
Competence Management in Industrial Engineering Departments in the Czech Republic
David Tuček and Jaroslav Dlabač
722
Economic Evaluation of the Level of Knowledge Services in Selected OECD Countries
Zuzana Tučková and David Tuček
732
A Three-Dimensional Model of Identifying Barriers to Knowledge Management
Anna Ujwary-Gil
741
From KM Evaluation to Developing Evaluative Capability for Learning
Christine van Winkelen and Jane McKenzie
750
Profiling the Intellectual Capital of Italian Manufacturing SMEs: An Empirical Analysis
Chiara Verbano and Maria Crema
758
The Obligatory Passage Point: Abstracting the Meaning in Tacit Knowledge
John Walton
769
New Knowledge Creation by Collaborating GoalOriented Experts: Methodology and Models
Igor Zatsman and Pavel Buntman
776
Knowledge-Intensive Business Services (KIBS) and Their Role in the Knowledge-Based Economy
Malgorzata Zieba
785
Late Submission
793
Characteristics of Decision Problems In Innovation Process Planning
Magdalena Jurczyk – Bunkowska
795
Can Knowledge be Reliably Measured?
Rumniak Paweł
805
Insights into Knowledge Sharing in the Dubai Police Force
Dr Ibrahim Seba, Professor Jennifer Rowley and Dr Rachel Delbridge
814
PHD papers
823
Knowledge Management and Creative Thinking Framework Integrated in Training of Future Students
Andra Badea, Gabriela Prostean, Adrian Adam and Olivia Giuca
825
The Importance of Play in Overcoming Fears of Entrepreneurial Failure
Ramona Cantaragiu and Shahrazad Hadad
833
v
The Role of Emotional Intelligence Efficiency in Multinational Financial Institutions
Elizabeth Lorena Croitor (Tcaciuc), Cristian Valentin Hapenciuc, Livia Elena Blanariu (Vranciu) and Daniela Mihaela Sandu (Neamtu)
840
Knowledge Sharing and Channel Choice: Effects of the new way of Working
Arjan de Kok, Bart Bellefroid and Remko Helms
849
Job Evaluation for Knowledge-Based Organizations
Paweł Fiedor
860 ,
Towards a Decision Approach for the Characterization of Potential
Sahar Ghrab, Ines Saad, Faiez Gargouri and Gilles Kassel
868
Knowledge Management Influence on Innovation: Theoretical Analysis of Organizational Factors
Ingrida Girniene
877
Developing Knowledge Management Capabilities in Social Enterprises: UK Experience
Maria Granados, Vlatka Hlupic, Elayne Coakes and Souad Mohamed
886
Research Regarding the Informational System (Information and Knowledge) Required for an Environmental Manager
Ionut Viorel Herghiligiu , Luminita Mihaela Lupu and Bogdan Budeanu
896
The Impact of Emotional Knowledge on key Aspects of the Economy
Andrei-Alexandru Morosan, Gabriela Arionesei, Paul-Panfil Ivan and CristianValentin Hapenciuc
905
Factors for Knowledge Sharing Behaviour to Develop Trust in Professional Organisations Environment
Salah Rana, Malcolm Crowe and Abel Usoro
914
Knowledge Sharing as a Problem of the Individual Nature of Knowledge
Vaclav Reznicek, Zdenek Smutny, Jaroslav Kalina and Alexander Galba
920
DataTalks: A Unified Knowledge Pool in SaaS and Mashup Systems
Sasha Mile Rudan, Dino Karabeg and Alf Martin Johansen
926
Data Mart With Lean Six Sigma Concept for Performance Level Assessment in Knowledge Management Framework
Jevgeni Sahno, Eduard Shevtshenko and Tatjana Karaulova
932
What is Your Organization’s IQ? – A Practical Tool to Gauge Enterprise Intelligence
Evren Satıcı and Özalp Vayvay
942
Intra-Organizational Cooperation and Knowledge Sharing: A Comparison of Slovak LIS University Departments
Peter Steranka
950
The Role of Individual Factor in Knowledge Sharing Behavior Among Profit Oriented Webloggers
Ruzleeta Zakaria, Nor Intan Saniah Sulaiman, Haslinda Ibrahim, Mohd Syazwan Abdullah, and Nerda Zura Zabidi
961
1
Work In Progress Paper
969
A Knowledge Sharing System Based On Structured And Unstructured Knowledge
vi
Leandro Ramos da Silva and Nizam Omar
971
Preface These proceedings represent the work of researchers presenting at the 14th European Conference on Knowledge Management (ECKM 2013). We are delighted to be hosting ECKM at the Kaunas University of Technology.The conference will be opened by David Snowden of Cognitive Edge in the UK, who will talk about “Sense-making and Knowledge Management”. The second day will be opened by Soumodip Sarkar from the Univeristy of Evora, Portugal and will address “Osmosis and Knowledge flows in Entresutra”. ECKM provides an opportunity for academics concerned with current research and for those from the wider community involved in Knowledge Management, to present their findings and ideas to peers from the KM and associated fields. ECKM is also a platform for face to face interaction with colleagues from similar areas of interests. The conference has a wellestablished history of helping attendees advance their understanding of how people, organisations, regions and even countries generate and exploit knowledge to achieve a competitive advantage, and drive their innovations forward. The range of issues and mix of approaches followed will ensure an interesting two days. 221 abstracts were initially received for this conference. However, the academic rigor of ECKM means that, after the double blind peer review process there are 97 academic papers, 17 PhD research papers and 1 Work in Progress paper published in these Conference Proceedings. These papers reflect the continuing interest and diversity in the field of Knowledge Management, and they represent truly global research from some 46 different countries, including Algeria Australia, Austria, Bahrain, Boznia and Herzegovina, Brazil, Canada, Colombia, Costa Rica, Czech Republic, Denmark, Ethiopia, Finland, France, Germany, Hungary, India, Iran, Ireland, Israel, Italy, Japan, Jordan, Lithuania, Malaysia, Mexico, New Zealand, Norway, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, South Africa, Spain, Sweden, Switzerland, Taiwan, Thailand, The Netherlands, Tunisia, United Kingdom, the USA and Vietnam. We hope that you have an enjoyable conference. Prof. Dr. Brigita Janiūnaitė Head, Department of Educational Science, Faculty of Social Sciences Programme Chair Prof.Dr. Asta Pundziene, Vice Rector for Research Prof.Dr. Monika Petraite, Dean, Faculty of Social Sciences Co-Conference Chairs Kaunas University of Technology, Kaunas, Lithuania September 2013
vii
Conference Committee Conference Executive Prof.Dr. Asta Pundziene, Kaunas University of Technology, Kaunas, Lithuania Dr.Monika Petraitė, Kaunas University of Technology, Kaunas, Lithuania Prof. Dr. Brigita Janiūnaitė, Kaunas University of Technology, Kaunas, Lithuania Doc.Dr. Jurgita Sekliuckiene, Kaunas University of Technology, Kaunas, Lithuania Prof.Habil.Dr. Palimra Juceviciene, Kaunas University of Technology, Lithuania Prof. Habil.Dr. Robertas Jucevicius Kaunas University of Technology, , Lithuania Doc.Dr. Gintare Tautkeviciene, Kaunas University of Technology, Lithuania Doc.Dr. Svetlana Sajeva, Kaunas University of Technology, , Lithuania Mini Track Chairs: Dr Alexeis Garcia-Perez, Coventry University, UK Dr Anikó Csepregi, University of Pannonia, Hungary Amani Shajera, University of Bahrain (UOB), Bahrain Dr Sandra Moffett, University of Ulster, Belfast, UK Dr Kristel Miller, Queens University, Belfast, UK Dr Christine van Winkelen, Henley Knowledge Management Forum, UK Professor Jane McKenzie, Henley Knowledge Management Forum, UK Prof.Dr.Constantin Bratianu, Academy of Economic Studies, Bucharest, Romania Gintare Tauteviciene, Kaunas University of Technology, Kaunas, Lithuania Dr Jan M. Pawlowski, University of Jyväskylä, Jyväskylä, Finland. Dr. Stavros T. Ponis, National Technical University of Athens (NTUA), Greece Dr. Epaminondas Koronis, University of Lincoln, UK Prof.dr. Marta-Christina Suciu, Academy of Economic Studies Bucharest, Romania Assistant Prof. dr. Evangelia Siachou, Hellenic American University, Greece Committee Members The conference programme committee consists of key individuals from countries around the world working and researching in the Knowledge Management and IS community. The following have confirmed their participation: Mahmoud Abdelrahman (Manchester Business School, UK); Habib Abubakar (African Development Bank Group, Tunisia); Pichamon Adulavidhaya (Bangkok University, Thailand,); Dr Ali Alawneh (Philadelphia University, Jordan); Dr Abdallah AlShawabkeh (University of Greenwich, UK,); Prof. Dr Eckhard Ammann (Reutlingen University, Germany); Albena Antonova (Sofia University, Bulgaria,); Dr Nekane Aramburu (University Of Deusto, San Sebastian, Spain); Dr Derek Asoh (Ministry of Government Services, Ontario , Canada); Associate Professor George Balan (Romanian-German University, Romania); Dr Joan Ballantine (University of Ulster, UK); Dr Pierre Barbaroux (French Air Force Academy / Research Center of the French Air Force, France); Dr Mary Basaasa Muhenda (Uganda Management Institute, Uganda); Prof. Dr. Aurelie Aurilla Bechina Arnzten (College University of Bruskerud, Norway); Prof Julie Béliveau (University of Sherbrooke, Canada); Dr. David Benmahdi (Université Paris 8, France,); Asst Professor Maumita Bhattacharya (Charles Sturt University, Albery, Australia); Prof. Dr. Markus Bick (ESCP Europe Wirtschaftshochschule Berlin, Germany); Heather Bircham-Connolly (University of Waikato, Hamilton, New Zealand); Dr Claudia Bitencourt (Universidade do Vale do Rio dos Sinos , Brazil); Pavel Bogolyubov (Lancaster University Management School, UK,); Karsten Bohem (University of Applied Sciences, Kufstein, Austria); Dr Ettore Bolisani (University of Padua, Vicenza, Italy); Prof Ionel Bostan (University of Iasi, Faculty of Economics, Romania); Andreas Brandner (KM-Net Austria, Austria); Prof Constantin Bratianu (Academy of Economic Studies, Bucharest, Romania, Romania); Dr Antonio Juan Briones (Universidad Politécnica de Cartagena, Spain); Prof Elisabeth Brito (University of Aveiro, ESTGA, Portugal); Sheryl Buckley (Unisa, South Africa); Dr Dagmar Caganova (Slovak University of Technology, Slovakia); Prof. Leonor Cardoso (University of Coimbra, Portugal); Professor Sven Carlsson (School of Economics and Management, Lund University, Sweden); Dr Gabriel Cepeda Carrion (Universidad de Sevilla, Spain); Dr David Cegarra (Universidad Politécnica de Cartagena, Spain); Dr Juan-Gabriel Cegarra-Navarro (Universidad Politécnica de Cartagena, Spain); Daniele Chauvel (SKEMA Business School , France); Satyadhyan Chickerur (M.S. Ramaiah Institute of Technology, Bangalore, , India); Alfred Chinta (University of Bolton, UK); Ana Maria Correia (Universidade Nova de Lisboa, Portugal); Dr Bruce Cronin (University of Greenwich Business School, UK); Dr Reet Cronk (Harding University, Searcy, Arkansas, USA); Anikó Csepregi (University of Pannonia, Department of Management, Hungary,); Roberta Cuel (University Of Trento – Faculty Of Economics, Italy); Dr Farhad Daneshgar (University of New South Wales, Australia); Dr Ben Daniel (University of Saskatchewan, Saskatoon, Canada); Prof Monica De Carolis (University of Calabria, Italy); Prof Annunziata De Felice (University of Bari, Italy); John Deary (Independent Consultant, UK & Italy); Dr Paulette DeGard (The Boeing Company, Seattle, USA); Dr Izabela Dembinska (University of Szczecin, Poland); Dr Charles Despres (Conservatoire des Arts et Metiers, Paris, France); Zeta Dooly (Waterford Institute of Technology , Ireland); Prof Dr Heinz Dreher (Curtin University, Perth, Australia); Dr Yan Qing Duan (Luton Business School, University of Luton, UK); Nasser Easa (University of Stirling, Scotland, UK); Sally Eaves (Sheffield Hallam University, UK); Professor John Edwards (Asviii
ton Business School, UK); Dr Anandasivakumar Ekambaram (SINTEF, Norway); Jamal El Den (Charles Darwin University, Australia); Dr Steve Eldridge (Manchester Business School, , UK); Isaac Enakimio (University of Greenwich/Kent and Medway Health Informatics, Kent,); Dr Scott Erickson (Ithaca University, USA); Mercy Escalante (Sao Paulo University, Brazil); Nima Fallah (University of Strasbourg, France); Dr Doron Faran (Ort Braude College, Israel); Dr Péter Fehér (Corvinus University of Budapest, Hungary); Dr Silvia Florea (Lucian Blaga University, Romania,); Dr Andras Gabor (Budapest University of Economic Sciences and Public Administration, Hungary); Brendan Galbraith (University of Ulster, UK); Elli Georgiadou (Middlesex University, UK); Dr Lilia Georgieva (Heriot-Watt University, UK); Gerald Guan Gan Goh (Multimedia University, Melaka, Malaysia); Dr Andrew Goh (International Management Journals, Singapore); Dr Miguel González-Loureiro (University of Vigo, Spain); Dr Loganathan Narayansamy Govender (University of Kwazulu-Natal, South Africa); Francesca Grippa (Scuola Superiore ISUFI, University of Salento, Italy); Norbert Gronau (University of Potsdam, Germany); David Gurteen (Gurteen Associates, UK); Dr Leila Halawi (Quinnipiac University, Hamden, USA); Linda Cathrine Hald (NTNU, Norway); Dr Matthew Hall (Aston Business School, UK); Associate Professor Meliha Handzic (International Burch University, Bosnia and Herzegovina); Dr. Harold Harlow (Wingate Univeristy, USA); Deogratias Harorimana (Southampton Solent University, , UK); Dr Mahmoud Hassanin (Pharos University,Alexandria, Eygpt); Prof Igor Hawryszkiewycz (University of Technology, Sydney, Australia); Dr Ciara Heavin (University college cork, Ireland,); Dr Peter Heisig (Leeds University Business School, UK); Remko Helms (Universiteit Utrecht, The Netherlands); Dr Ali Hessami (Vega Systems Ltd., UK); Dr Eli Hustad (University of Agder, Norway); Fahmi Ibrahim (Glasgow Caledonian University, UK); Dr Thomas Jackson (Loughborough University, UK); Dr Harri Jalonen (Turku University of Applied Sciences, Finland); Prof. Brigita Janiunaite (Kaunas University of Technology, Lithuania); Dr Daniel Jimenez (Universidad de Murcia, Spain); Prof. Palimra Juceviciene (Kaunas University of Technology , Lithuania); Prof. Robertas Jucevicius (Kaunas University of Technology , Lithuania); Selvi Kannan (Victoria University, Melbourne, Australia); Dr Silva Karkoulian (Lebanese American University Beirut Campus, Lebanon); Dr Sarinder Kaur Kashmir Singh (University Malaya, Malaysia,); Dr Marcela Katuščáková (University of Žilina, Slovakia); Prof. Dr. Turksel Kaya Bensghir (TODAIE-Public Administration Institute for Turkey and the Middle East, Turkey); Dr. Radwan Kharabsheh (Hashemite University, Jordan); Dr Prof Aino Kianto (Lappeenranta University of Technology, Finland); Monika Klimontowicz (University of Economics in Katowice, Poland,); Ute Klotz (Lucerne University of Applied Sciences and Arts, Switzerland); Dr Andrew Kok (Western Cape Government, South Africa); Dr Bee Theng Lau (Swinburne University of Technology, Australia); Rongbin W.B Lee (The HongKong Polytechnic University, Hong Kong); Prof. Dr Franz Lehner (University of Passau, Germany); Jeanette Lemmergaard (University of Southern Denmark, Denmark); Prof Ilidio Lopes (Polythenic Institute of Santarém, Portugal); Prof Monique Lortie (Universit du Qu bec Montreal, Canada); Dr Maria de Lourdes Machado-Taylor (CIPES, Portugal); Dr Agnes Maciocha (Institute of Art, Design, and Technology, Ireland); Avain Mannie (Dept of Finance, Port Elizabeth, South Africa); Prof Virginia Maracine (Academy of Economic Studies, Bucharest, Romania); Dr Farhi Marir (London Metropolitan University, UK); Prof Maurizio Massaro (Udine University, Italy,); Fiona Masterson (National University of Ireland, Galway, Ireland); Florinda Matos (ISCTE-IUL, Lisbon, Portugal); Prof Jane McKenzie (Henley Business School, United Kingdom); Dr. Dalila Mekhaldi (University of Wolverhampton, UK); Dr Robert Mellor (Kingston University, UK); Prof. Dr. Kai Mertins (Fraunhofer-IPK, Germany); Dr. Anabela Mesquita (ISCAP - Politechnique Institute of Porto, Portugal); Kostas Metaxiotis (National Technical University Athens, Greece); Dr Antonio Leal Millan (Universidad de Seville, Spain); Dr Kristel Miller (Queens University, Northern Ireland); Dr Sandra Moffett (University of Ulster, Londonderry, UK); Prof Samuel Monteiro (University of Beira Interior, Portugal,); Dr Mahmoud Moradi (University of Guilan, Iran); Dr Arturo Mora-Soto (Carlos III University of Madrid, Madrid,); Prof Oliver Moravcik (Slovak University of Technology, Slovakia); Aboubakr Moteleb (B2E Consulting, UK); Aroop Mukherjee (King Saud University, Saudi Arabia); Dr Birasnav Muthuraj (New York Institute of Technology, Bahrain); Arash Najmaei (MGSM, Australia); Dr Elena Irina Neaga (Loughborough University, UK); Dr. Gaby Neumann (Technical University of Applied Sciences Wildau, Germany); Dr Emanuela Alia Nica (Center for Ethics and Health Policy (CEPS) and University "Petre Andrei" Iasi, Romania); Dr Cristina Niculescu (Research Institute for Artificial Intelligence of the Romanian Academy, Romania); Klaus North (FH Wiesbaden, Austria); Dr Jamie O'Brien (St. Norbert College, USA); David O'Donnell (Intellectual Capital Research Institute of Ireland, Ireland); Gary Oliver (University of Sydney, Australia); Dr. Ivona Orzea (Academy of Economic Studies, Romania,); Dr Kaushik Pandya (Birmingham College, UK); Dr Paul Parboteeah (Loughborough University, UK); Jan Pawlowski (University of Jyväskylä, Austria); Dr Corina Pelau (Academy of Economic Studies, Bucharest, Romania); Monika Petraite (New York Institute of Technology, Lithuania); Rajiv Phougat (IBM, USA); Prof Paulo Pinheiro (Universidade da Beira Interior, Portugal); Prof Mário Pinto (Polytechnic Institute of Porto, Portugal,); Professor Selwyn Piramuthu (University of Florida, Gainesville, USA); Dr Gerald Polesky (IBM. 11425 N. Bancroft Dr, Phoenix, USA); Dr John Politis (Neapolis University, Pafos, Cyprus); Dr Nataša Pomazalová (Faculty of Economics and Management University of Defence, Czech Republic); Dr Stavros Ponis (National Technical University Athens, Greece); Prof Asta Pundzienė (Kaunas University of Technology , Lithuania); Dr Lila Rajabion (Penn State University, Mont Alto, USA); Prof Thurasamy Ramayah (Universiti Sains Malaysia, Malaysia); Dr M S Rawat (DCAC, University of Delhi, India); Dr. Carlos Raymundo (UPC, Peru); Prof. Dr. Ulrich Reimer (University of Applied Science St. Gallen, Switzerland); Dr Ulrich Remus (ACIS Department, University of Canterbury, New Zealand); Dr Alexander Richter (Bundeswehr University Munich, Germany); Gerold Riempp (EBS, Germany,); Eduardo Rodriguez (IQ Analytics, Ottawa, Canada); Dr Inès Saad (Amiens School of Management , France); Dr. Josune Sáenz (University of Deusto, San Sebastián, Spain); Prof. Lili Saghafi (Canadian International College, Egypt,); Mustafa Sagsan (Near East University, Nicosia, Northern Cyprus, Cyprus); Prof. Svetlana Sajeva (Kaunas University of Technology , Lithuania); Dr. Kalsom Salleh (Faculty of Accountancy, University Technology MARA, Malaysia); Dr. María-Isabel Sanchez-Segura (Carlos III University of Madrid, Spain,); Dr. Antonio Sandu (Mihail Kogalix
niceanu University,Romania); Prof Helena Santos-Rodrigues (IPVC, Portugal); Prof Dan Savescu (Transilvania University of Brasov, Romania); Dr Ousanee Sawagvudcharee (Stamford International University (Phetchaburi Campus) Thailand); Enrico Scarso (Università Degli Studi Di Padova, Italy); Dr Christian-Andreas Schumann (University of Zwickau, Germany); Prof. Jurgita Sekliuckiene (Kaunas University of Technology , Lithuania); Dr Maria Theresia Semmelrock-Picej (Klagenfurt University, Austria); Amani Shajera (University of Bahrain, Bahrain,); Dr Mehdi Shami Zanjani (University of Tehran, Iran); Peter Sharp (Regent’s College, London , UK); Dr Michael Shoukat (UMUC, USA); Dr Evangelia Siachou (Hellenic American University , USA); Dr Kerstin Siakas (Alexander Technological Educational Institute of Thessaloniki, Greece); Prof Umesh Kumar Singh (Vikram University, Ujjain, India); Dave Snowden (Cognitive Edge, Singapore); Dr Siva Sockalingam (Glasgow School for Business and Society, UK); Prof.Dr. Marta-Christina Suciu (Academy of Economic Studies Bucharest, Romania); Christine Nya-Ling Tan (Multimedia University, Melaka, Malaysia); Dr Llewellyn Tang (University of Nottingham Ningbo , China); Prof. Gintare Tautkeviciene (Kaunas University of Technology , Lithuania); Dr Sara Tedmori (Princess Sumaya University for Technology, UK); Claudia Thurner-Scheuerer (Community Manager of Plattform Wissensmanagement,Know-Center, Graz, Austria); Dr Eduardo Tomé (Universidade Lusiada, Portugal); Dr Zuzana Tuckova (Tomas Bata University in Zlín, Czech Republic); Prof Alexandru Tugui (Alexandru Ioan Cuza University, Romania); Geoff Turner (University of Nicosia, Cyprus); Andras Vajkai (University of Pécs, Hungary); Dr Changiz Valmohammadi (Islamic Azad University-South Tehran Branch, Iran); Dr Christine van Winkelen (Henley Business School, University of Reading, UK); Professor Jose Maria Viedma (Polytechnic University of Catalonia, Spain); Maria Weir (Independent Consultant, Italy); Christine Welch (University of Portsmouth, UK); Florian Welter (IMA/ZLW & IfU - RWTH Aachen University, Germany,); Anthony Wensley (University of Toronto, Canada); Dr Sieglinde Weyringer (University of Salzburg, Austria); Roy Williams (University of Portsmouth, UK); Dr Lugkana Worasinchai (Bangkok University, Thailand); Prof Les Worrall (University of Coventry, UK); Dr Mohammad Hossein Yarmohammadian (Isfahan University of Medical Sciences, Iran)
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Biographies Conference Co-Chairs Prof.Dr. Asta Pundziene holds doctor degree in Social Sciences (organizational psychology), defended at Vytautas Magnus University. The beginning of the career was in Vytautas Magnus University in 1993 with the responsibilities of the Administrator of the Pedagogical studies programmes. From 1996 till 1999 Asta was the Project Manager in the Centre for Vocational Education and Research at Vytautas Magnus University. From 1999 till 2003 Asta was Vice-Director of the Centre for Vocational Education and Research at Vytautas Magnus University. From 2003 till 2004 – National Seconded Expert (END) at the European Training Foundation (ETF) in Turin, Italy. From 2004 until 2006 the Director for Change Management Programme at ISM University of Management and Economics. From 2006 until 2011 Asta was the Head of the Intellectual Capital and Business Competence Department, Editor of the Baltic Journal of Management. Since 2011 to present Asta is the Vice Rector for Research at Kaunas University of Technology. Main research interests are in Change management, Human recourse development, and Career development. Prof.Dr. Monika Petraite is a dean at the Faculty of Social Sciences, and also Full Professor at the Institute of Business Strategy, Kaunas University of Technology, Lithuania. She holds doctor degree in Social Sciences (management and administration) from Kaunas University of Technology. The research focus is on innovation management (networking, open innovation, new product development, knowledge management for innovation), R&D in business and NTB firm creation, high tech (knowledge based) entrepreneurship, high tech business strategies (especially small globally born businesses), enhancement of knowledge and innovation culture and design of knowledge intensive organizations. She is a senior researcher in the national programmes for innovation and innovation cultures research, and leads a scientific group on Innovation research.
Programme Chair Dr. Brigita Janiūnaitė is professor and Head of the Department of Educational Studies at the Institute of Educational Studies, Faculty of Social Sciences, Kaunas University of Technology. She has supervised 11 PhD theses. She also is Executive Editor of the journal ‘Social Sciences’ and member of the Board of the Lithuanian Educational Research Association. Brigita Janiūnaitė is an expert of the European Science Foundation. She is a committee member of International Conference of Intellectual Capital, Knowledge Management and Organisational Learning. Her research is focused on the issues of change management and social innovation implementation; development of innovative culture at individual and organizational level; higher education; curriculum development. She is actively involved in international and national research and study projects and evaluation of study programmes. Among her publications is a monograph on ‘Educational Innovation Implementation’ (2004, in Lithuanian) and research study ‘Citizen’s innovative culture’ (2007, in Lithuanian) and “Organization innovation culture” (2011). She was elected a Visiting Fellow at St.Edmund’s College, University of Cambridge, in 2007.
Keynote Speakers Dave Snowden is the founder and chief scientific officer of Cognitive Edge. His work is international in nature and covers government and industry looking at complex issues relating to strategy, organisational decision making and decision making. He has pioneered a science based approach to organisations drawing on anthropology, neuroscience and complex adaptive systems theory. He is a popular and passionate keynote speaker on a range of subjects, and is well known for his pragmatic cynicism and iconoclastic style. His company Cognitive Edge exists to integrate academic thinking with practice in organisations throughout the world and operates on a network model working with Academics, Government, Commercial Organisations, NGOs and Independent Consultants. He is also the main designer of the SenseMaker® software suite, originally developed in the field of counter terrorism and now being actively deployed in both Government and Industry to handle issues of impact measurement, customer/employee insight, narrative based knowledge management, strategic foresight and risk management. Prof. Dr. Soumodip Sarkar received his PhD in Economics from Northeastern University, Boston in 1995. He is currently Dean of Graduate Studies at the University of Évora, Portugal where he is also the coordinator of the Program in Entrepreneurship and Innovation and a professor in the Department of Management. He is also a researcher at CEFAGE-UE and his research interests are innovation, entrepreneurship and international business. The author of Innovation, Market Archetypes and Outcome (2007 – Pringer Verlag); Empreendedorismo e Inovação (2007 - Escolar Editora) and Entrepreneurial Innovator (2008 – Elsevier Campus), Professor Sarkar has published papers in several scientific journals and is in the editorial board of four international scientific journals. The project leader in many Portuguese and European projects, Soumodip holds copyrights to the integrated innovation model developed by him along with simulation software. xi
Mini Track Chairs Prof.Dr.Constantin Bratianu is professor of Strategic Management and Knowledge Management at the Faculty of Business Administration, Academy of Economic Studies, Bucharest, Romania. He is Director of the Research Centre for Intellectual Capital, Academy of Economic Studies, Bucharest. He is a member of the American Academy of Management, Southern Association of Management, USA, and International Association of Knowledge Management. He published over 30 books, and over 200 papers in international journals and international conference proceedings. His main academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Dr Anikó Csepregi is an assistant professor at University of Pannonia, Department of Management in Hungary. Her main fields of interest include knowledge management and competence management. She has published several articles and presented her work at national and international conferences. She is an editorial board member of knowledge management journals and a committee member of knowledge management conferences. She takes part in an international knowledge management research group with research partners from Bulgaria, Croatia and Romania. Dr Alexeis Garcia-Perez holds a PhD degree in Information and Knowledge Management from Cranfield University, UK. His research focuses on the development of sustainable Knowledge Management strategies and tools to improve collaboration within organisations. He has successfully completed Knowledge Management projects with the UK Ministry of Defence and with global engineering companies such as General Electric (GE) Energy, Siemens Industrial Turbomachinery and Converteam UK. Alexeis is currently a lecturer at Coventry University. He has also worked for Cranfield University and the University of Bath in the UK. Dr Epaminondas Koronis is a Senior Lecturer at the University of Lincoln, UK and a visiting scholar at George Washington University and the University of Cyprus. He holds degrees in Business, Organization Studies and he has been awarded his PhD from Warwick Business School, UK. In the past, his research and consulting experience have focused on the areas of Knowledge Management, Crisis Management, Organizational and Supply Chain Resilience and he has published papers and book chapters on Knowledge and Outsourcing and Crisis Management. Professor Jane McKenzie has worked with the Henley Knowledge Management Forum since its inception in 2000. She has carried out applied research with this community of knowledge and learning professionals into a wide variety of topics, ranging from improving internal and external collaboration and the use of social media, to decision making, leadership and improving conversations. Jane has collaborated with academics and leading practitioners from around the world and has published extensively in academic and practitioner journals. Dr Kristel Miller is a Lecturer in Management at Queens University, Belfast. Her research interests lie in the areas of absorptive capacity, knowledge transfer and innovation within knowledge intensive contexts. She has publications in the area of knowledge transfer and technology commercialisation within Universities. Dr Sandra Moffett is a Senior Lecturer of Computer Science with the University of Ulster’s School of Computing and Intelligent Systems, Magee Campus. She is a core member of the Ulster Business School Research Institute. Her expertise on Knowledge Management contributes to her being one of the UK leading authors in this field. She has received a number of research awards and citations for her work. External funding has enabled Dr Moffett to undertake extensive quantitative/qualitative research to benchmark KM implementation within UK companies. Dr Jan Pawlowski works as Professor in Digital Media - Global Information Systems at the University of Jyväskylä, Finland jan has a Masters' Degree and Doctorate in Business Information Systems (University of Duisburg-Essen). He is a Professor of Digital Media with the specialization "Global Information Systems". This includes the research coordination of several national and European projects. Main research interests and activities are in the field of Global Information Systems, E-Learning, Modeling Learning-related Processes, Procedural Models, Learning Technology Standardization, Quality Management and Quality Assurance for Education, and Mobile / Ambient Learning. Actively involved in research organizations (AACE, GI, IEEE) and in standardization organizations (DIN, CEN, ISO/ IEC JTC1 SC36). Jan is also the acting chair of the CEN/ISSS Workshop Learning Technologies.
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Dr Stavros T. Ponis holds a Dipl. Ing. Degree (1996), and a Ph.D. (2000) in mechanical engineering from the National Technical University of Athens (NTUA), Greece. He has also conducted post doc research (2006-2008) on the field of Knowledge Management and Logistics to support Virtual Enterprise Networks. He is an Assistant Professor of Supply Chain Management in the Section of Industrial Management & Operations Research at NTUA. He has more than 70 publications in fully reviewed scientific journals, International Conferences’ Proceedings and the Commercial Press in the areas of Supply Chain Management, Knowledge Management, Production Planning and Control, Business Process Modeling, Networked and Virtual Enterprises, and their supporting Information Systems. Prof Dr Marta-Christina Suciu is a full professor and PhD supervisor at the Academy of Economic Studies Bucharest, Romania. Her main topics of interest are; Knowledge & innovative based society and economy; Creative & Innovative Management; Knowledge Management and Innovation; Intellectual Capital. She is actively involved in supporting these topics as a trainer, a PhD and Post PhD supervisor and as a researcher. She is coordinator of the national research project IDEI 1224 dedicated to the topic of “Creative economy & knowledge–based society. Challenges and opportunities for Romania”, 2007-2010. Assistant Prof Dr Evangelia Siachou holds a Ph.D. in Knowledge Management from Athens University of Economics and Business, an M.Sc. in Industrial Relations and Personnel Management from the London School of Economics (LSE) and a Bachelor’s degree in International and European Studies from Panteion University of Athens. Her past work experience include among others the Human Resource Department of CDE under the aegis of European Commission in Brussels. She joined the faculty of Hellenic American University in 2010 as an Assistant Professor of Human Resources and Management and currently serves as the Coordinator of the BSBA Program. Dr Christine van Winkelen has worked with the Henley Knowledge Management Forum since its inception in 2000. She has carried out applied research with this community of knowledge and learning professionals into a wide variety of topics, ranging from improving internal and external collaboration and the use of social media, to decision making, leadership and improving conversations. Jane has collaborated with academics and leading practitioners from around the world and has published extensively in academic and practitioner journals.
Biographies of Presenting Authors Dr. Mohd Syazwan Abdullah graduated with a PhD (Computer Science) from University of York, UK in 2006 and works in the areas of knowledge management, knowledge engineering, knowledge management technologies, knowledge-based systems and information engineering. Currently he holds the post as a senior lecture/deputy director at the School of Computing at Universiti Utara Malaysia. Adrian Adam received the Engineer degree (1990) in Engines with Internal Combustion from the politehnica University of Timisoara, Faculty of Mechanics. He is currently PhD Student in the Department of Management from the politehnica University of Timisoara, Romania. Ghosia Ahmed is a PhD student at Loughborough University’s Department of Information Science. Her research draws attention to the largely unexplored area of ‘knowledge security’. Ghosia is aiming to identify and address the intrinsic clash between knowledge sharing and information security practices, in order to nurture secure knowledge sharing in organisations. Versavia Ancusa received her PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. She is currently a Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Ancusa’s main research interests are affective computing, fault tolerance and reliability, complex networks. Dimitris Apostolidis holds a Ph.D and a M.A in International Relations from Boston University, Boston, Massachusetts, and a B. Sc in Accounting and Finance from the American College of Greece, Athens, Greece. At Hellenic American University he has been teaching undergraduate and graduate courses in business and humanities and currently serves as Coordinator of Student Affairs. Andra Badea received the Master degree (2011) in Competitiveness Management and Engineering from the politehnica University of Timisoara, Faculty of Management in Production and Transport, section: Engineering and Management. She is currently PhD Student in the Department of Management of the politehnica University of Timisoara, Romania.
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Frank Bannister is a Associate Professor, information systems, Trinity College, Dublin. Prior to becoming academic worked in Irish civil service and PricewatershouseCoopers as management consultant. Researches e-government, e-democracy, on-line privacy and trust and IT value and evaluation, particularly public sector. Co Director, Permanent Study Group on eGovernment within European Group on Public Administration. Editor-Electronic Journal of e-Government; Fellow- Trinity College, Dublin; member-Institute of Management Consultants, Ireland; Fellow-Irish Computer Society; Chartered Engineer. Nicolene Barkhuizen is an Associate Professor and Head of the Department of Industrial Psychology, North-West University, and Mafikeng Campus in South Africa. She is the programme leader of an established research focus area on Talent Management. Nicolene has more than 60 peer reviewed publications which includes a book, chapters in textbooks, conference proceedings and journal articles. Denise Bedford is currently a Goodyear Professor of Knowledge Management, Kent State University. She Teaches courses in economics of information, intellectual capital management, semantic analysis methods, communities of practice, and other knowledge management topics. Research interests include communities of practice, use of semantic analysis methods and technologies, multilingual architectures, business rules engineering, search architectures and governance models, intellectual capital and knowledge economies. Marc Bettoni is Director of Research & Consulting at the Swiss Distance University of Applied Sciences (FFHS) focusing on Knowledge Cooperation and e-Collaboration. Since 1981 contributions to Radical Constructivism. From 1977 to 2005 researcher, engineer and lecturer with industrial and academic organisations in the domains of machine design, engineering education, IT development, knowledge engineering and knowledge management. Madeleine Block is a doctoral student at the Faculty of Social Sciences and Business Studies at the University of Eastern Finland in Kuopio. Her main field of interest is knowledge management; the current research is related to the issues of understanding knowledge sharing within organisations. Razvan Bogdan received his PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. He is currently Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Bogdan’s main research interests are in dependability of computer systems, human-machine interfaces, embedded systems, complex networks. Pavel Bogolyubov is a Management and Business Development Fellow at Lancaster University Management School, UK. Pavel’s First degree in Physics was at Herzen University in St. Petersburg, Russia, and MBA from Bradford School of Management, UK. Pavel has spent ten years working in various Continuous Improvement roles in FMCG multinationals across Europe. Research interests are centred on “softer” aspects of Web 2.0 and its role in KM. Ettore Bolisani (“Laurea” Electronic Engineering, Ph.D. Innovation Studies - University of Padua) is Associate Professor at the Department of Management and Engineering (University of Padua). In 1997 he was UE TMR visiting research fellow at the University of Manchester, where he conducted a research project on the developments of Electronic Commerce. His research centres on ICT management and Knowledge Management. He was Chair of the European Conference on Knowledge Management held at the University of Padua in 2009. He is founder member and president of IAKM (International Association for Knowledge Managment) Constantin Bratianu is professor of Strategic Management and Knowledge Management, UNESCO Department for Business Administration and Director of the Research Center for Intellectual Capital, Bucharest University of Economic Studies, Romania. He is founding editor of the international journal Management & Marketing. His academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Valentina Burksiene – dr. of social sciences, a lecturer at Klaipeda University, Faculty of Social Sciences. Valentina research interests are organizational learning, knowledge creation, sustainable development, strategic planning, public administration. More than years practice if public administration and strategic development Christopher Burt is an Associate Professor of Industrial and Organizational Psychology at the University of Canterbury, New Zealand. His research focuses on trust, including the relationship between trust and employee safety, developing safetyspecific trust in new recruits, and the influence of trust on employee voicing. He has published over 70 journal papers. Osvaldo Cairo is a tenured professor of ITAM since 1988. He is the author of more than 50 articles published in international journals and conferences and 10 books published with McGraw-Hill, Pearson, Springer, and Alfaomega. He is a member of the Mexican National System of Researchers, and participates in evaluation committees for CONACYT, CONICET, and United Nations. xiv
Ramona Cantaragiu is a PhD candidate at the Bucharest University of Economic Studies where she studies individual and institutional instances of academic entrepreneurship in social sciences universities. She is an Editorial Assistant for the international peer-reviewed journal Management & Marketing. Challenges for the knowledge society and she also holds seminars on business management and entrepreneurship. Antonio José Carrasco-Hernandez (antonioc@um.es) is a Professor of management at the University of Murcia (Spain). His current research focuses on the relationships among innovation, human resource management and family firms. He has recently published in Family Business Review, Management Research and The Electronic Journal of Knowledge Management. Delio Ignacio Castañeda PhD (Cum Laude) in Organizational Behavior: Universidad Autónoma de Madrid, Spain. Master (with Distinction) in Education: University of Manchester, England. Psychologist: Universidad Católica de Colombia. At the moment Associate Professor at Pontificia Universidad Javeriana and invited professor in the fields of Knowledge Management and Organizational Behavior. Dr Juan Gabriel Cegarra is associate professor of the Business Administration Department of the Universidad Politécnica de Cartagena (Spain). His research interests are on the use of knowledge management to help small and medium businesses to become more competitive. As a lecturer within the Business Administration Department, he has supervised two national projects and three PhD candidates in the domain of knowledge management. Ufuk Celikkan MSc. and PhD. degrees from North Carolina State University, Raleigh, USA. Worked as Advisory Software Engineer in Server and Software Divisions of IBM, Austin, Texas and then in Smart Card Division of Gemalto Inc. also in Austin, Texas. Currently Assistant Professor in the Department of Software Engineer at Izmir University of Economics, Turkey. Maria Crema is a Phd Student of Innovation Management at Department of Management and Engineering of University of Padova (Faculty of Engineering). Her main research areas are: innovation management and risk management. Hossein Chenari is M.A. holder in MBA. He has published 20 papers in the field of computer science. He has been the head of department of Computer Graphics in Applied and Scientific University, Branch No. 24. He is the author of the 3 reference books about Graphic Softwares. Elizabeth Lorena (Tcaciuc) Croitor is from Suceava, who are a licensed in the economy and are in the final year doctoral specialization Economics. She has worked four years in banking and sales disciplines are collaborating on Marketing and Economics from the University Stefan cel Mare Suceava Dr. Anikó Csepregi is an Assistant Professor at University of Pannonia, Hungary. Her main fields of interest include knowledge management and competence management. She has published articles and presented her work at national and international conferences. She is an editorial board member of KM journals and a committee member of KM conferences. Arjan de Kok is PhD researcher at Utrecht University in The Netherlands. His research topic is ‘The New Way of Working and the role of ICT in the implementation of NWOW’. Arjan de Kok has over 20 years experience as organization & ICT consultant in engineering and maintenance environments. Dr Rachel Delbridge is Senior Lecturer in Information and Communications. Her teaching and research interests are in information and knowledge management, learning, teaching and student performance and achievement. Jaroslav Dlabač is a graduate of Tomas Bata University in Zlin. He is now Senior Consultant in API Slaný and External Assistant Professor at the Tomas Bata University in Zlin, Department Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlín. Andrei Dumitrescu is an Associated Professor at the Mechanical and Electrical Engineering Faculty, Petroleum-Gas University of Ploiesti. He holds a PhD in Mechanical Engineering from the same University and is a member of the Association of Managers and Economic Engineers from Romania. His research activities include project management and production systems engineering. Sally Eaves is a Senior Manager in the IT and Telecommunications Sector with certifications in ITIL, Prince2 and Six-Sigma. A committed ‘practitioner‐researcher’, she is engaged in collaborative, intersectional projects with Sheffield Hallam University with whom she obtained a Distinctive MSc in IT and Management in 2012. Interests include knowledge management, intellectual capital and methodological innovation.
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Anandasivakumar (Siva) Ekambaram works as a research scientist at SINTEF – Technology and Society, Productivity and Project Management, Trondheim, Norway. He obtained his doctoral degree, which focuses on project management and knowledge transfer in organizations, from the Norwegian University of Science and Technology (NTNU). Besides his research work, he is involved in teaching activities at NTNU. Tiit Elenurm is head of the entrepreneurship department at the Estonian Business School. Ph. D. in 1980 for the dissertation “Management of the Process of Implementation of New Organizational Structures”. Author of more than 110 research publications. Research interests include knowledge management, innovative entrepreneurship and international transfer of management knowledge. Paweł Fiedor is from Poland. He obtained Master of Science degree in Information Management from Cracow University of Economics (Kraków, Poland) in 2010. He is currently a PhD candidate in economics therein. He works in financial industry, the press and education. His research interests include economics of information, econophysics and knowledge management. Nora Fteimi studied Information Systems (Wirtschaftsinformatik) at Otto-Friedrich University of Bamberg in Germany. Currently she works as a PhD researcher at the Chair of Information Systems II of the University of Passau in Germany. Her fields of research and interest are particularly knowledge management, business intelligence and process modeling. Alexander Galba graduated from cybernetics at Faculty of Mathematics and Physics, Charles University in Prague. Currently, he makes business in ICT and works at the Department of Systems Analysis, University of Economics, Prague, where he deals with business informatics. Aukse Galbuogiene is a doctoral student and the junior researcher at the Department of Strategic Management, Kaunas University of Technology. She is doing a PhD in the field of the development of Smart Business Systems. Smart specialisation is also an important dimension in her research. Oscar Ojeda Galicia holds master degree in Information Technology and Management, defended at Instituto Autónomo de México (ITAM). From 2002 till 2003 –Web Master Developer at AVAYA, México. From 2003 untill 2008 – Systems Management Engineer and Systems Management Leader at Telcel. Since 2010 to present – IT Executive at Mexico’s Ministry of Energy. Dr Alexeis Garcia-Perez is a Lecturer in Business Information Systems at Coventry University teaching and doing research on Knowledge Management. Experience includes collaborations with industry in elicitation of knowledge from experts from different domains. Member of IT Section of International Federation of Library and Information Professionals (IFLA) and founding member of International Association for Knowledge Management (IAKM). Faiez Gargouri is a Professor at the High Institute of Multimedia and Computer System of Sfax (Tunisia). Hi is now the headmaster of MIRACL Laboratory. Sahar Ghrab is a PhD student in the MIS (Modelisation Information System) laboratory (Amiens-France) and in the MIRACL (Multimedia, InfoRmation Systems and Advanced Computing Laboratory) laboratory (Sfax Tunisia). Ingrida Girniene is a Lector and PhD student in the Faculty of Communication, Vilnius University, and Vilnius, Lithuania. Dissertation topic: “Influence of knowledge management expressions on the organization: innovation aspect”. She has a master degree in International Communication. Practical experience: working as business information and communication manager. Scientific experience: participation in the international and national conferences. Olivia Giuca received the PhD. Degree (2012) in mechanical engineering from the „Politehnica” University Of Timisoara. She Is Currently Assistant Professor In The Department Of Management From The Politehnica University Of Timisoara, Romania. Gianna Giudicati is currently working as Knwoledge Management Specialist in eni SpA. She had her PhD in 2012 in “Economics and Management – Behavioral Studies in Management and Organizations” at University of Trento (Italy) and spent her abroad period at Harvard University-IQSS (Boston). Her fields of research covers knowledge management, innovation, social influence, and social-network methods. Maria Granados from Colombia is a PhD Candidate and Visiting Lecturer in Business Information Management and Operations at University of Westminster in London, with over nine years experience in the private, social economy and academic sectors. Her research interests and publications are in social enterprises, enterprise networks, knowledge management and sociotechnical evaluations.
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Kristina Grumadaite is a PhD student of Management and Administration at the Faculty of Social Sciences of Kaunas University of Technology. Main research interests: self-organisation based systems, organizational creativity and emotional intelligence. kristina.grumadaite@ktu.lt. Shahrazad Hadad is a first year PhD student at the Bucharest University of Economic Studies researching the field of Corporate Social Entrepreneurship. She is currently a seminar teaching assistant for the following courses: Corporate Entrepreneurship and Challenges of Growth, Decision Making Processes, and Customer Relationship Management. She is an Editorial Assistant for the international peer-reviewed journal Management & Marketing. Challenges for the knowledge society. Meliha Handzic is a Professor of Management and Information Systems, International Burch University, Sarajevo and Suleyman Sah University, Istanbul. PhD from University of New South Wales, Sydney. Research interests lie knowledge management and decision support. Meliha has published extensively on these topics in leading journals. Meliha is currently on executive board of IAKM and serves as regional editor (Asia-Pacific) for KMRP. Professor Dennis Harlow has been a vice president, director and senior manager executive for world class companies such as IBM, GE and Qualcomm in a management career that spans 25 years. He has developed over 20 new products based on technologies such as GIS, GPS GSM and CDMA(wireless). He holds a patent in GPS technology. He has published over thirty Knowledge Management and entrepreneurship articles in leading international business journals/conferences . Dr Remko Helms is an assistant professor at the Department of Information and Computing Science at Utrecht University where he teaches Knowledge Management. His researches focus on on knowledge sharing networks and social media. Dr Helms is co-founder of the International Association for Knowledge Management and departement editor for Connected Scholars at the Association of Information Systems. Ionut Viorel Herghiligiu Currently I am a PhD student in the last year at “Gheorghe Asachi” Technical University from Iasi, Romania and in the first year at University of Angers, ISTIA, France. The title of my PhD thesis is “Research On The Environmental Management System As A Complex Process At Organizations Level” Henri Inkinen, M.Sc. (Econ. & Bus. Adm.) is a Doctoral Student at the Technology Business Research Center (TBRC) at Lappeenranta University of Technology. His research interests are in the areas of intellectual capital and knowledge management practices. He has been involved with these issues through his work experience within knowledge-intensive industries. Dr Päivi Iskanius is Adjunct Professor at the University of Oulu, Department of Mechanical Engineering. Her research fields are supply chain management, information management, logistics, networking, project business management, agile business, and e-business applications. She is also interested in innovation management, knowledge management and change management issues. Currently, she has over 120 research publications in these areas. Prof. Thomas W Jackson (PhD) holds a chair in Information and Knowledge Management and is the Director of the Centre for Information Management. Research areas are Email and Information Retrieval, Knowledge Management, including their combination to realise a Natural Language Processing Email Knowledge Extraction system that has the world’s best f-ranking measure. Mahsa Mahmoud Jahantab received is PhD student doing Knowledge Management research at the Faculty of Engineering and Computing of Coventry University, UK. She has completed a BSc in Electrical Engineering from American University in Dubai (AUD) in 2008 and an MSc in Engineering Project Management at Coventry University in 2010 with outstanding results. Harri Jalonen works as Research project group leader and Principal lecturer at Turku University of Applied Sciences. Doctoral degree in knowledge management from Tampere University of Technology. Long-term research experience dealing with knowledge and innovation management issues in different organizational contexts. Recent research focused on fuzziness of innovation and role of social media in innovation processes. Kalina Jaroslav graduated from applied informatics. Currently, he is PhD student at the Faculty of Informatics and Statistics, University of Economics, Prague. He deals mainly with modelling. Dhouha Jaziri Bouagina is a doctoral student in Marketing at high institute of management of Tunis (ISG, Tunis, URMR research centre), University of Tunis. Her research concerns the customer experience and the knowledge management. She is interested in the tourism field research. Daniel Jiménez-Jiménez is a Lecturer Professor of management at University of Murcia (Spain). He has a PhD. in Management and MA in Human Resource Management from University of Murcia. Research focuses on relationships among innovaxvii
tion, human resource management and knowledge management. He has recently published in Personnel Review, Industrial Marketing Management, International Journal of Operations and Production Management, The Electronic Journal of Knowledge Management, British Journal of Management and Journal of Business Research. Palmira Juceviciene Ph. D., Habil. Dr., full professor at Kaunas University of Technology. Palmiria research interests are individual and organizational learning, knowledge creation and management, learning organizations and regions, human resource development, higher education. Dr. Juceviciene has published more than 200 scholarly articles and 10 books. Palmira is a Consultant in individual and organizational learning, learning organizations and regions, human resource development. Robertas Jucevicius is a Professor and Director of Business Strategy Institute at Kaunas University of Technology, Lithuania. Robertas has a PhD in Economics and Habilitated Doctor in Management. He is also a visiting fellow at the University of Cambridge (UK), as well as Fulbright (USA) and Wallenberg (Sweden) fellow and the member of the Council for National Progress of Lithuania. Magdalena Jurczyk-Bunkowska studied production management at Warsaw University of Technology, where she received a PhD title in 2004. Currently, she works at Opole University of Technology as a researcher and lecturer. She was a member of Polish Academy of Science. Now, her fields of research and interest are innovation management especially operational approach covering innovation process planning. Martin Katuščák is a PhD. student at the University of Žilina. Masters graduate of the Comenius University in Bratislava, specialised in comprehensive processing of written cultural and scientific heritage. He worked for 7 years in the Slovak National Library as a digital librarian participating in European projects and as a national expert in digitisation and digital preservation. Marcela Katuščáková is a Lecturer at the University of Žilina. Masters and PhD. graduate of the Comenius University in Bratislava. She is working in research and education, specializing in information and knowledge management, scientific collaboration, storytelling and text mining. She has worked in the field of knowledge management implementation in research projects such as the Memory of Slovakia and KNIHA SK. Dr. Radwan A. Kharabsheh is a lecturer in international business and the assistant dean, international affairs at the Hashemite University in Jordan. His research interests include organizational learning, knowledge management and international joint ventures. He is member of ANZIBA and ANZMAC and the Sydney University Centre for Peace Studies and Conflict Resolution. Tatiana Khvatova Ph.D., is currently employed as an Associate Professor for the Institute of Economics and Engineering at St.-Petersburg State Polytechnical University. Presently the research is focused on knowledge management, innovation policies, and innovation systems. Other disciplines of interest include cross-cultural management and using technologies in education. Monika Klimontowicz, Ph.D, is a lecturer at University of Economics in Katowice. Her latest research focuses on the role of intangibles in the process of achieving banks’ competitive advantage. Her interests include business strategy, innovation, knowledge and intellectual capital. She has been working as a marketing manager and business consultant. Epaminondas (Nodas) Koronis is a Senior Lecturer at University of Lincoln and a Visiting Scholar at the George Washington University and the University of Cyprus. In the past he has undertaken executive positions in pharmaceutical corporations and consulting roles in Greece, UK and USA working with Deloitte and Reputation Lab, leading crisis and reputation management projects for large organizations. He holds a PhD from Warwick Business School (University of Warwick). His works have been published in academic journals, edited volumes while he has presented his research and frameworks in academic and professional conferences. Jaroslava Kubátová, Ph.D. id an Associate Professor at the Philosophical Faculty of Palacký University in Olomouc, Czech Republic. Since January 2002 – to date: Head of the Department of Applied Economics. Areas of Expertise: Human Capital Management and Knowledge Management with ICTs utilization. Cooperation with scientific organizations: European Association for Security, Czech Society for Systems Integration. Kaan Kurtel has been a Professor at the Department of Software Engineering at Izmir University of Economics since 2002. He obtained his MSc in Computer Engineering from Ege University, in 2005 and his PhD degree in Computer Science from Trakya University, Turkey, in 2009. His research interests include software engineering and web technologies. Prof. Dr. Franz Lehner has been assistant professor at the Institute for Organizational Research at the University of Linz, Austria, since 1986. In 2004 he accepted a call to the University of Passau where he holds now the Chair for Information Systems xviii
(Wirtschaftsinformatik) since April 2004. His research is focusing on E-Learning as well as Information and Knowledge Management Monique Lortie Ph.D., is tenure professor at Université du Québec à Montréal in ergonomics; her initial background is in industrial engineering. She is in charge of the knowledge transfert strategic arm for the Réseau de Recherché en Santé et Sécurité au Travail (RRSSTQ) Lisa Loyo is the Manager for Information Services at the Transportation Research Board. She has a broad range of professional experience ranging from ESL instructor to research librarian and trainer for a database vendor. Before joining TRB she worked at TRB’s parent organization, the US National Academies in their IT and Communications offices for ten years specializing in search, metadata and information architecture, working on projects to improve the search experience and navigation on a number of websites. In June of 2010 she moved from the IT division to TRB to manage the TRB’s library and research databases, including the TRID Database. Edit Lukacs is Associate professor at the Faculty of Economics and Business Administration of “Dunarea de Jos” University of Galati, Romania. She finished her PhD in Management in 2001. Since then, her didactic and research activity is focused on Management science, particularly on Human Resource Management and Intercultural Management. Dr. Lukacs participated in and completed different training courses in the field of professional counseling, psychological assessment of human resources and has also experience as team member or coordinator in different projects (TEMPUS, PHARE, POS-DRU). Dr Eva Martínez Caro is an assistant professor of operations management in the Business Management Department, Universidad Politécnica de Cartagena (Spain). She served as the Head of the e-Learning Center of the Universidad Politécnica de Cartagena for 5 years. She is actually Vice Dean of the School of Industrial Engineering. Her current research interests include knowledge management, technology-based learning environments and technology management. Micaela Martínez-Costa is a Lecturer Professor of management at the University of Murcia (Spain). Her current research focuses on the relationships among Knowledge Management, Total Quality Management, EFQM and Innovation. She has recently published in Journal of Knowledge Management, International Journal of Operations and Production Management and Total Quality Management. Dora Martins did her PhD thesis on expatriates’ management on Portuguese companies and continues researching this topic. She has also attended several international conferences and she has presented the results of recent investigation issues on Portuguese expatriates/repatriates. She teaches in degree and master human resources management studies for national and international courses. Professor Jane McKenzie is Director of the Henley KM Forum, having actively contributed to the community since 2000. Her interests are summarised as: "How connections and contradictions affect knowledge work and learning capacity in organisations". She has written three books and many papers often jointly with Dr Christine van Winkelen. Kristel Miller is a lecturer in management at Queens University, Belfast. Her research interests lie in the areas of absorptive capacity, knowledge transfer and innovation within knowledge intensive contexts. She has publications in the area of knowledge transfer and technology commercialisation within Universities. Peter Mkhize completed his PhD in 2012. He is currently working for University of South Africa as a senior lecturer. He has published few journal and conference papers on e-Learning and knowledge management. Among other research interests is human capital development, social networks, communities of practice. Ludmila Mládková works as an associate professor at the University of Economics Prague, Faculty of Business Administration, and Department of Management. She specializes in knowledge management, management of knowledge workers and managerial leadership. Her activities involve lecturing, writing and work with Ph.D. students. Sandra Moffett Senior Lecturer of Computer Science, University of Ulster’s School of Computing and Intelligent Systems, Magee Campus. Sandra is a Core member of Ulster Business School Research Institute. Expertise on KM contributes to her being one of UK leading authors in this field. Sandra has a Number of research awards and citations. External funding enabled her to undertake extensive quantitative/qualitative research to benchmark KM implementation within UK companies. Mieczysław Morawski, scientific discipline: management science; workplace: Wroclaw University of Economics; position: professor since 2008; number of publications: 120, in this book: 11; research in the field: personal aspect of knowledge management, knowledge-based organizations, talent management non-work interests: travel the world, international politics, forecasts the development of civilization. xix
Andrei-Alexandru Moroşan is a second year PHD student, focusing particularly on aid economics (manifested in Romania as EU structural funds). He is a junior teaching assistant of the Faculty of Economics and Public Administration - Department of Economics, Business Administration and Tourism, "Stefan cel Mare" University of Suceava. Dr. Vyda Mozuriuniene from Comfort Heat Ltd is the Managing Director; Vyda has a Ph.D. in Management. Research interests – knowledge creation and management, process management, strategic management. Vyda is a Consultant in the areas of organization’s knowledge management, process management, and franchise. Dr. Mozuriuniene has published 4 scholarly articles. Edrisi Muñoz Mata MSc. Industrial Engineering, Instituto Tecnológico de Orizaba, Mexico. Doctor of Philosophy in Chemical Process Engineering, Universitat Politècnica de Catalunya (UPC) in Spain. Researches KM through development of ontologies and management frameworks for decision-making support in different areas. Member of Centro de Investigación en Matemáticas A.C (CIMAT), Mexico and collaborates with UPC as part of research team, participating in different Mexican/European research projects. Lilian Noronha Nassif received BS degree in Computer Science from PUC-MG, in 1990; received MS degree in Public Administration in 1997’ received PhD in Computer Science from Federal University of Minas Gerais, in 2006, Brazil. Currently she is a Director of technology at public Ministry of Minas Gerais. Fattah Nazem is an Associate Professor. He has been vice-president of the research department for the last five years. His research interests are in the field of Higher Education Management. He has written 2 books and 98 articles. He is Chief Executive of the Quarterly Journal of Educational Science. Olimpia Neagu Associate Professor at “Vasile Goldiş” Western University of Arad, Romania. I am teaching European Economy and Marketing. My interest and research areas are: human capital and economic development at micro- and macroeconomic level, determinants and consequences of human capital investments, european economy, human resources –human capital management, brain drain, knowledge management. Oscar Ojeda Galicia holds master degree in Information Technology and Management, defended at Instituto Autónomo de México (ITAM). From 2002 till 2003 –Web Master Developer at AVAYA, México. From 2003 untill 2008 – Systems Management Engineer and Systems Management Leader at Telcel. Since 2010 to present – IT Executive at Mexico’s Ministry of Energy. Gary R Oliver researches/teaches at The University of Sydney. Gary has held appointments in public corporation, with government at federal and state levels, and in retailing. PhD in economics, Master of Commerce, He has a Master of Education (Higher Education), Bachelor of Arts degree and Graduate Diploma in Social Science obtained (2012). Gary Specialises in higher education effectiveness, and researches in sharing information and knowledge (knowing). Originated field of microintellectual capital. Ivona Orzea is Assistant Professor of Knowledge Management, UNESCO Department for Business Administration, and a member of the Research Center for Intellectual Capital, Bucharest Academy of Economic Studies, Romania. She is former Associate editor for the international journal Management & Marketing. Her academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Ján Papula is an associated professor at Faculty of Management Comenius University in Bratislava, Slovak republic, where he works as a teacher and researcher since 2002. His research activities are focused on the topics of strategic management development particularly in relation to resource-oriented approach and strategies to build sustainable competitiveness. Dr Paul Parboteeah is a Research Associate in the School of Business and Economics at Loughborough University. His research spans several areas including the application of autopoiesis to KM, data quality, information management in local government and sport informatics. He is currently creating a swimming demand analysis and prediction tool for the UK. Corina Pelau is university lecturer at the Academy of Economic Studies, Bucharest Romania, at the Department for Business Administration - UNESCO. Her main research interests are marketing-controlling, customer relationship management and consumer behavior. Since October 2010, she is postdoctoral researcher in the program “Performance and excellence in postdoctoral research in Romanian economics science domain”. Carmen Petrisoaia In 2008, I obtained the Bachelor in Business Administration in French at the Academy of Economic Studies from Bucharest and two Years later I graduated the Masters. I was an Erasmus student in France, at Université de Haute Alsace between in 2006. In 2012, I had a 6 months scholarship at Université de Picardie Jules Verne. xx
Anna Pilková, MBA. is an associated professor at Faculty of Management Comenius University in Bratislava. She leads the national research team Global Entrepreneurship Monitor (coordinated by Global Entrepreneurship Research Association). Her research interests are mainly Entrepreneurship and Value Based Management. She has several years of experiences in the banking industry. Magdalena Platis is a Professor of Microeconomics, Macroeconomics and Marketing having an experience for more than 20 years. Magdalena is Involved in projects related to labour market, entrepreneurship and quality assurance. Area of interest: possibilities of integrating the practical placement in the curriculum, of developing internships and extra-curriculum activities, of industry-university connections. Dr Steve Probets is a Lecturer in the Department of Information Science at Loughborough University. He is interested in socio-technical systems and the interplay between technology and working practices. Much of this research has been focussed on the publishing sector, though he has supervised a number of postgraduate students in the wider KM area. Gabriela Proştean received the Ph.D. degree (2003) in industrial engineering from the Technical University” Gh. Asachi”, Iaşi, Romania. She is currently Professor in the Department of Management from the Politehnica University of Timisoara, Romania. Her research interests include project management, artificial intelligence, and electrical engineering. Athar Qureshi graduated with honours degree in computer sciences, Masters in ICT Management and is now pursuing his PhD in knowledge management. He started his academic career with research and teaching assistantship, lectureship and consultation. Along with his academic commitments, Athar also advises some not-for-profit academic associations. Dr Gillian Ragsdell Is a Senior Lecturer in Knowledge Management and Director of Research Degree Programme in the Department of Information Science at Loughborough University. Her interest in knowledge management practices has taken her into a wide variety of organisations; recent examples are from the voluntary sector and the energy industry. Salah Aziz Rana is the PhD research student in University of the West of Scotland. His area of research is organisation learning and knowledge sharing behaviour in organisations. He has already published a paper on Reinforcement Programming for function approximation in IEEE Xplore conference in 2012. Vaclav Reznicek graduated from information management at the Faculty of Informatics and Statistics, University of Economics, Prague. Currently, he is internal PhD student at the Department of Systems Analysis, Faculty of Informatics and Statistics, University of Economics, Prague. His doctoral thesis deals with the issue of human knowledge. Paavo Ritala, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta University of Technology, and an Academic Director of Master’s Programme in Strategy, Innovation and Sustainability. His main research interests are in the areas of inter-organizational networks, business models, knowledge management and innovation. Professor Jennifer Rowley is Professor of Information and Communications. She has researched and published extensively in information and knowledge management, higher education, and marketing. Her current research focuses on knowledge management, digital marketing, and entrepreneurship and innovation. Sasha Mile Rudan is a PhD candidate at the Oslo University and Entrepreneur at Serbia. His parallel research and involvement in online collaborative social system development helps him to keep his research relevant. His current research is on Trans-Technical Systems; systems that are in whole with their consumers and multi-type of activities marshaling through them. Pawel Rumniak, Adjunct in the Department ofCorporate accounting and Controlling Doctor if Econiomcs Sciences. Co-author of books on accountancy, cost accounting, managerial and controlling accounting. Numerous research papers on corporate management related subjects (accounting and controlling) Research work in finace and accouting. Ines Saad is an assistant professor in the department of Computer and Information System at Group Sup de Co Amiens Picardie. She is a researcher within the MIS Laboratory at the University of Picardie Jules Verne. Jevgeni Sahno is a PhD student of Tallinn University of Technology in Estonia. The main research directions are: Knowledge Management and Information Systems in manufacturing companies. Jevgeni is working in Estonia ABB Company of motors and generators on the position of process development engineer. The main responsibilities are: development of business process and information system, integration of PDM and ERP system.
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José Sendra Salcedo is student of Computer Engineering and Applied Maths undergraduate programs at Instituto Tecnológico Autónomo de México (ITAM). From 2010 to 2011- Systems Management Engineer at ITAM. Since 2011 to present – Administrative Chief of engineering magazine holaMundo. Evren Satici is pursuing his PhD studies in Marmara University Istanbul in Knowledge Management area. He is also working as Global Project Manager in Ericsson. Prior to his current job, he was a management consultant working on sales, marketing and organizational development areas helping companies in Middle East and Africa region. He speaks Turkish and English. Enrico Scarso (Ph.D. Industrial Innovation - University of Padua) is Associate Professor of Engineering Management at the Department of Management and Engineering, University of Padua (Italy). His research interests are in the area of technology and knowledge management, with a focus on knowledge-intensive business services in local innovation systems. He has published in International Journal of Technology Management, Technovation, International Journal of Electronic Commerce, Journal of Knowledge Management, International Journal of Knowledge Management, Knowledge Management Research and Practice. He is founder member and secretary of IAKM (International Association for Knowledge Managment) Thomas Schalow is a professor in the department of Economics and Information Science at the University of Marketing and Distribution Sciences in Kobe, Japan, where he has taught for the past fifteen years. He has also previously lectured at the National University of Singapore. His Ph.D. is from Princeton University. Christian-Andreas Schumann studied Industrial Engineering, ‘Chemnitz University of Technology’ (CUT). Doctor’s degree 1984 and 1987. Appointed associate professor plant planning and information processes, CUT (1988). Professor business and engineering information systems (1994) and Dean for distance learning at, University of Applied Sciences Zwickau. Currently director of ‘Centre for New Forms of Education’ and of Institute for Management and Information. Dr Ibrahim Seba is a police officer with the Dubai Police Force. His PhD research centres on knowledge management and sharing in police forces. José Sendra Salcedo is student of Computer Engineering and Applied Maths undergraduate programs at Instituto Tecnológico Autónomo de México (ITAM). From 2010 to 2011- Systems Management Engineer at ITAM. Since 2011 to present – Administrative Chief of engineering magazine holaMundo. Touhid Shiralipoor. Graduate of (M.A)In Education Planning. Two articles in the Journal of Research. 3 years teaching experience at the Islamic Azad University-Roudehen Branch. Four years of research experience in the field of management Mzwandile Muzi Shongwe. Is a Lecturer in the department of Information Studies, University of Zululand, South Africa. I am a PhD candidate in the department of Information Studies, University of KwaZulu- Natal, South Africa. My research interests are knowledge management, knowledge management systems and mobile technologies. Evangelia Siachou PhD. in Knowledge Management from Athens University of Economics and Business, an M.Sc. in Industrial Relations and Personnel Management from London School of Economics (LSE) and Bachelor’s degree in International and European Studies from Panteion University of Athens. Joined faculty of Hellenic American University (2010) as Assistant Professor of Management and currently serves as Coordinator of BSBA Program. Boyka Simeonova Doctoral student at School of Management, Royal Holloway, University of London. Two Masters Degrees with Distinction – the MSc Business Computing at University of Westminster in London, UK and Master’s in e-Management at Technical University of Sofia in Bulgaria – also Bachelor’s Degree in Public Administration. Researches Knowledge Sharing, Communities of Practice, and Web 2.0 Technologies. Zdenek Smutny graduated from applied informatics and media studies. Currently, he is internal PhD student at the Faculty of Informatics and Statistics, University of Economics in Prague where he deals with the problems of social informatics. Anna Sołtysik-Piorunkiewicz, Ph.D. and Mariusz Żytniewski, Ph.D. are employed at the University of Economics in Katowice as lecturers on Faculty of Informatics and Communication, at Department of Informatics. They are taking part in the research into computer science, systems analysis and computer system design, management information systems, software agents and knowledge-based organizations. Faezeh Sohrabi University of Azad Islamis Education Management Department, Roudehen, Iran. Faezeh has a MA in education management. Design and implementation IWA2 for schools and education organizations; Implementation ISO9001 for organizations. Faezeh is the Director of Education at the School of Education in Tehran for 5 years and a Quality Assurance manager for 2 years. xxii
Dimitrios-Robert I. Stamatiou is a Ph.D. candidate in the School of Mechanical Engineering in the National Technical University of Athens, Section of Industrial Management and Operational Research. He has a degree in Financial and Management Engineering. His academic interests are business process modeling and engineering, supply chain management, project management and systems reliability. Inga Stankevice PhD candidate and junior research assistant at the Department of Strategic Management, Department of Land Management, Kaunas University of Technology (Lithuania). Research stays at Bergen University (Norway), University of Geneva (Switzerland), University of Nottingham Business School (UK). Inga is a member of DRUID Society, has 20 publications, 10 scientific awards, participated in 7 research projects. Peter Steranka is a Lecturer at the University of Žilina. He’s a University of Žilina Masters graduate. He’s working at the Department of Mediamatics and Cultural Heritage and focusing his research activities in information/knowledge management and scientific collaboration. Currently finishing the dissertation thesis named Application of collaboratory principles in Library and information studies. Marta-Christina Suciu is full professor and PhD supervisor on Academy of Economic Studies Bucharest, Romania. Her main topics of interest are: Knowledge based society; Creative & Innovative Management; Knowledge Management; Intellectual Capital. She supports these topics also as a trainer (5 courses on the Post PhD School & on the Master level) and as PhD and Post PhD supervisor. Eduardo Tome made is PhD in Economics in 2001, with a Thesis on the European Social Fund. Since then we has worked in several Portuguese private universities. He published more than 20 papers in peer-reviewed Journals and attended more than 40 International conferences presenting papers. We run MSKE 2009, ECKM 2010, MSKE 2011 and UFHRD Europe 2012 at Lusiada University in Famalicão (North of Portugal). Adelfattah Triki has a PhD in Marketing, University of Northumbria, Newcastle (1998). Between 1986-87 he was at Boston University as a Fulbright Scholar. He is a Senior Lecturer of Research Methodology of Marketing Management and of Negotiation Techniques, Graduate School of Business Administration of Tunis University. He is Involved in company training and in consulting for private as well as public enterprises. He is also a Director of ARBRE (Applied Research in Business Research and Economics). David Tuček is a graduate of Brno University of Technology. He is now Associate Professor at the Tomas Bata University in Zlin, Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlín and vicerector for social affairs, Affiliation: Tomas Bata University in Zlin, nám. T.G. Masaryka 5555, 76001 Zlín, Czech Republic. Zuzana Tučková PhD. doctoral studies programme, economics and business management, Tomas Bata University (TBU) Zlín. Practical experience in project management dealing with services. Solver of POST-DOC grant project no. 402/09/P406 named “Knowledge Intensive Services – their meaning and characterization” and co-author grant project no NT 12235-3/2011 “Application of modern calculation methods for optimization of costs in health care” registered at Internal grant agency of Ministry of Health Czech Republic (IGA MZ ČR). Dr. Anna Ujwary-Gil has a PhD from Warsaw School of Economics, College of Management and Finance. Anne is a Fellow of Foundation Scholarship and Training (Norwegian Funds). She is Currently Editor-in-Chief of Journal of Entrepreneurship, Management and Innovation. In 2010, book entitled "Intellectual Capital and Market Value of a Company" (Ch&Beck, Warsaw 2009) received a prestigious award granted by Polish Academy of Sciences. Mika Vanhala, D.Sc. (Econ & Bus. Adm.) is a post-doctoral researcher in Knowledge Management at School of Business, Lappeenranta University of Technology, Finland. His primary research interest is the relationship between HRM practices, organizational trust and organizational performance. Mika’s research has been published in Personnel Review and Management Research Review. Dr Christine van Winkelen has worked with the Henley Knowledge Management Forum since its inception in 2000, project managing and leading collaborative research projects. She was the Director for five years. She has published extensively in academic and practitioner journals, co-authoring “Understanding the Knowledgeable Organization” and “Knowledge Works” with Professor Jane McKenzie. Chiara Verbano is an Associate Professor of Business and Engineering Economics at the Faculty of Engineering of the University of Padua. Her major research interests are the fields of risk management and R&D management.
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Anna Yu. Veretennikova attended The Ural State Technical University (Russia, Yekaterinburg), Faculty of Physics and Technology; Specialty - Management of Innovations. She Graduated in 2008. From 2007-2010 she was at The Business School of the Ural State Technical University (Russia, Yekaterinburg), the manager. From 2010-2013 she was at the Institute of Economics, Ural Branch of the Russian Academy of Sciences (Russia, Yekaterinburg), Junior Research Fellow. Her research interests are the knowledge economy, institutional economics. John Walton is a Principal Lecturer in the Department of Computing, Sheffield Hallam University. He teaches on Postgraduate degrees in the UK, the Middle East and the Far East. His research focus is the interface between strategy and knowledge management not wealth creation but also in the regeneration of post-industrial regions. Ruzleeta Zakaria is currently a PhD candidate in Decision Sciences at School of Quantitative Sciences, Universiti Utara Malaysia, Kedah, MALAYSIA. I received a Master degree in Decision Sciences and Bachelor degree in Business Administration also at Universiti Utara Malaysia by year 2000 and 2003. My research is focused on knowledge sharing among profit oriented webloggers in Malaysia. Igor Zatsman has the PhD (Information-Computer Science). Currently, he is the head of research department at the Institute of Informatics Problems of the Russian Academy of Sciences. He has the highest research diploma, obtained after the PhD. Research interests are in the fields of Cognitive Informatics, Modeling Emerging Meanings Processes and Their Tracing by Computer. Malgorzata Zieba PhD, Eng. is an assistant professor at the Faculty of Management and Economics of Gdansk University of Technology, Poland. She has taken part in several national and international projects. Her scientific interests oscillate around knowledge management and modern concepts of management in organizations. She has a record of around 30 publications in these areas.
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Using Neuromarketing Studies to Explore Emotional Intelligence – as a key to the Buying Decision Process Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau The Bucharest Academy of Economic Studies, Bucharest, Romania nicolae_al_pop@yahoo.com ana.iorga@gmail.com corinapelau@yahoo.com Abstract: The recent dynamics of neuroscience is enabling and fostering the interface of this domain with others, such as: biology, sociology and economy. The complexity of market mechanisms in general and of the buying decision in particular increased considerably, demanding thus more sophisticated investigation instruments. During the last decade, neuromarketing has been in search of its own identity on the ambiguous field of market research. Starting from the works of Ale Smidts, the paper aims to position neuromarketing as an independent research field. The author reviews the different opinions articulated by specialists throughout the contemporary literature, emphasizing neuromarketing’s capability of addressing the invisible side of neuronal connections that are situated inside the brain. Starting from Salovey and Mayer’s definition of emotional intelligence (EI), this paper reviews the anatomical and physiological foundations of the brain activity that generates the EI. We analyze the neuromarketing concepts and instruments that enable specialists to comprehensively study people’s unconscious reactions that lead them to buy or reject a product that could satisfy their needs. Thus, the physiological neuronal data acquired enables us to better understand externally triggered emotions and the way they interact in order to generate the buying decision. The whole approach is circumscribed to the relationship marketing framework that relies on creating, developing, maintaining and perpetuating interpersonal ties between all players in the market, in order to improve the image of a service, brand or company. We will look then at the difference between emotions and moods and analyze how they impact our behavior. Emotions are high‐intensity but transient manifestations while moods represent rather insidious changes in our state of mind, changes that might or might not be easily identified and traced back to their origins. Neuromarketing research techniques (represented by electroencephalography (EEG), magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), eye‐ tracking glasses (ET) and the galvanic‐skin response (GSR)) bring valuable insights regarding the neural substrates of EI and allow researchers to seize the ephemeral interaction between different brain structures during the decision making process. We will further discuss the findings of our original research that studied the impact of packaging on consumers’ emotional reaction. The research tested the impact of several elements of the packaging layout (color, shape, label and message positioning) for different packaging of competing brands in the honey market. The research was conducted at the Doctoral School of Marketing from the Bucharest University of Economic Studies. The research results where later used in crafting the product‐positioning strategy for several products from the company’s portfolio. Conclusions and further discussion topics will then be inferred and detailed. Keywords: neuromarketing, neuroimaging, emotional intelligence, relationship marketing, new product design
1. Introduction The more thorough the decision‐making process responsible for the consumer behavior, the higher the chances of better meeting demand. Knowledge management studies both the way people acquire knowledge and the process itself. The access to knowledge is possible both rationally – using deductive and inductive reasoning – and emotionally – throughout a wide range of stimuli. Our emotional intelligence allows us to direct our attention and actions towards a certain behavior. The more we develop this sort of intelligence, the stronger our self‐control, allowing us to better control our decisions. Part of the human behavior, more precisely the methods consumers use to express purchase or dismissal decisions towards goods or services that could satisfy their needs – which is known as the purchase and consumption behavior –, represents a vast field of study for marketing investigations. Consequently, research in this area has seen a spectacular boost lately. Studies from the second half of the 20th century emphasized the exploration of investigation methods in areas as clinical psychology, psycho‐sociology and even sociology (Evrad et al., 2009). More recent studies, issued at the beginning of this century, bring about a fresh perspective: scientists now look deeper into the human nature; they investigate subconscious reactions that take place at a neuronal level, when consumers are exposed to different market stimuli fighting for their attention. The impressive advances in neurosciences fostered the better understanding of the behavioral mechanism. (Georges and Badoc, 2011).
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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau Neuromarketing acts as an interface between several disciplines. It covers incontrollable and unseen moods and processes that trigger the reactions influencing the purchase decision in a favorable or unfavorable manner (Constensen, 2011). Neuromarketing research explores the way the human brain handles information (Rouellet and Droulers, 2010), in order to facilitate the various courses of action that are possible in an integrated marketing communication (Bruhn, 2007). Neuromarketing research is now compulsory or advisable in a hypercompetitive market that is becoming increasingly more globalized. The more insightful the research into the human subconscious, the more various the activation tools available in the pursuit of product sale.
2. The anatomical substrate of emotions We humans are able to express a wide range of emotions, often swinging from rage to happines, thus covering the whole spectrum. Emotions are often easily desciphered when watching one’s face and there are studies that show that facial expressions can have an emotional impact upon the viewer and even influence the evaluation of an outcome (Ho et al., 2012). Furthermore, emotional faces can induce „approach or avoidance behaviors” (Chen and Bargh, 1999) and even endow physical objects with negative or positive values (Winkielman et al., 2005). But what do emotions look like in the brain? Are they as easily distinguishable when looking at the brain, as they are when reading one’s face? For a decade already, there have been numerous neuroimaging studies that attempted to identify the neural circuits intrinsic to emotions, whether positive or negative ones. Of the available technologies, most of the studies used fMRI and positron emission tomography (PET), as these neuroimaging tools allow researchers to study brain structures situated deep in the brain. One of the theory proposed was that of two systems that facilitated the existence of two completely opposite emotions or behaviors: the approach and withdrawal behaviors (Cacioppo and Gardner, 1999; Davidson, 1995; Gray, 1994; Lang et al., 1990). The approach behavior is linked to the occurence of positive emotions (like self‐ contentment or excitement) while the withdrawal behavior is generated by negative, rejection‐like emotions that are induced by a stimulus (for example anxiety or repulsion). The theory proposes that these two systems rely on somewhat independent neural circuits. We will further review the most important components of those circuits and look at some studies that shed light on them. The prefrontal cortex (PFC) is one of the areas that plays a major role in the occurence of emotions (both positive and negative) and also in the decision making process. Several studies have shown that patients with left PFC damage had a higher rate of depression‐related symptoms than those with right PFC lesions (Gainotti, 1972; Sackeim et al., 1982; Robinson et al., 1984), thus implying that the left PFC was involved in the occurence of positive affect. This finding is supported by studies performed on healthy subjects, revealing a stronger left hemisphere activation for stimuli that generate positive emotions and higher right hemisphere activation for stimuli that generate negative emotions (Davidson et al., 1990; Davidson, 1992, 1995, 1998). Other studies performed by Bechara and his team suggested that bilateral damage of the ventromedial PFC was responsible for patients’ impairment in forseeing the subsequent consequences of their behavior, while they were able to assess the implications of immediate recompense or penalty (Bechara et al., 1994). Furthermore, those patients were unable to anticipate risky behavior (Bechara et al., 1997; Bechara et al., 1996). It is therefore believed that the ventromedial PFC is instrumental in predicting future emotional outcomes as consequences of current behavior. The amygdala is another neural structure that plays an important role in regulating emotions, especially in the negative ones and in learning associated to unpleasant stimuli. There are several studies that highlight the involvement of the amygdala in the facial recognition of fear (Adolphs et al, 1995 and 1996; Calder et al., 1996; Broks et al., 1998), where patients that had bilateral amygdala lesions were unable to identify fear expressions from the facial expressions that they were exposed to. Nevertheless, they had no problem in recognizing other facial emotions. Amygdala’s role in identifying hints of fear is not limited to facial expressions, as a study performed by Scott et al. (1997) showed that patients with bilateral amygdala damage were also unable to recognize the vocal cues of fear. Other brain structures involved in processing emotions are:
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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau
Ventral striatum – higher activation was evidenced in the nucleus accumbens, putamen and caudate, in studies that focused on addictive behavior: the brain impact of cocaine on cocaine addicts (Breiter et al., 1997) or the impact of nicotine infusion on smokers (Stein et al., 1998), thus highlighting the importance of the dopaminergic mesolibic system in regulating addictive behavior and positive emotions (Koch et al., 1996; Koob, 1992; Koepp et al., 1998).
Anterior cingulate cortex (ACC) – is believed to be involved in situations that require focusing on one’s emotional reactions rather than focusing on the given context (Lane et al., 1997; Posner, 1995).
Insula – is involved in regulating emotions associated with autonomic, visceral manifestations (Cechetto and Saper, 1990). A large part of the amygdala is dedicated to processing gustatory stimuli, therefore its activation when subjects are faced with facial disgust emotions (Phillips, et al., 1997).
3. Moods and emotions Salovey defined EI as „the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them and to use this information to guide one’s thinking and actions” (Salovey and Mayer, 1990). It is therefore assumed that people are able to understand their emotions, rationalize them and control their behavior. Emotions lay at the foundament of interpersonal relations and represent the main motivator for our behavior (Dolan, 2002). They have a strong influence on our reasoning and decision making process and are often exhibited as stereotyped attitudes, easily revealed through facial expressions (James, 1890). According to Salovey, people with a high EI quotient are able to supress their negative emotions „appreciative of the fact that temporarily hurt feelings or emotional restraint is often necessary in the service of a greater objective” (Salovey and Mayer, 1990). The brain regions that regulate the negative emotions’ inhibitory mechanisms are the amygdala, the orbitofrontal (OFC) and lateral prefrontal (PFC) cortices (Blair and Cipolotti, 2000; Davidson, et al., 2000a; Davidson et al., 2000b; Mitchell and Blair, 2000; Raine et al., 1998). Moods, on the other hand, are insidious, internal mental states, characterized by low intensity, indefinite duration and nespecific manifestations. They are often difficult to correlate with the stimuli that caused them and they influence our perception of surrounding events. For example, studies have shown that moods affect the way people perceive advertising messages (Martin, 2003; Martin and Lawson, 1998) and that the impact of moods on information processing is gender‐related (Martin, 2003). Positive moods are associated with creative thinking, enhanced attention and imaginative problem solving (Rowe et al., 2007). Nevertheless, they can also have a negative impact on cognitive processes, as people are easily distracted when they are in a good mood. (Biss et al., 2010). The negative impact is only present when the message that requires processing is incongruent with the positive mood, in other words it threatens to change the mood (Ziegler, 2010). Negative moods have quite the opposite impact on cognitive processes, as they are associated with depression, low self‐esteem and even nonspecific somatic manifestations. Research has shown that people usually perceive objects or events that are consistent with their moods (Niedenthal and Setterlund, 1994), thus displaying selective attention.
4. Emotions and decision making Although we have been taught that we should carefully analyze each option when making decisions and that we should rationally weight the pros and cons, recent research revealed that almost 95% of the decision‐ making process is undertaken at the subconscious level of our minds (Zaltman, 2003). In other words, not only that we are not aware of the process, we can’t even influence it from a rational standpoint. Kahneman describes the mind as a cohabitation of two cognitive processes, which he calls „System 1” and „System 2” (Kahneman, 2011). System 1 represents the subconscious mind, which is automatic, reacts fast and relies on well‐known patterns while System 2 symbolizes conscious cognitive processes that take longer to operate and require direct attention. System 1 operates with stereotypes and is highly influenced by emotions. It is in charge with automatic actions that don’t require conscious processing everytime they are performed (like writing or driving). System 2, on the other hand, is indispensable in the learning process, when aquiring new skills requires a lot of attention and focus. For example, learning to drive a car requires an active System 2, while driving to the office on the same route for several years already most often relies on System 1. System 2
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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau operates with concepts, abstract representations and is responsible for the „rational” assesment of our decisions. We can therefore infer that companies that want to persuade consumers should appeal to their subconscious mind (System 1) through memorable and simple messages (like jingles or rhyming slogans), that trigger an emotional rather than rational response. This hypothesis is supported by the findings of Bechara and his colleagues, that introduced the „Somatic Marker Hypothesis’’ concept in order to explain the impairment that patients with ventromedial prefrontal (VM) damage exhibited when required to make certain decisions (Bechara, 2004). In his research he found out that damage of the VM cortex (a prefrontal area that includes the OFC) affects the proper encoding of emotional or psihosomatic impulses, while cognitive processes are intact. Still, patients with VM damage have difficulties in organizing their daily routine or in selecting their friends (Bechara et al., 2000a; Bechara et al., 2002). Furthermore, patients with VM damage were unable to make advantageous decisions while performing a gambling task (Bechara et al., 2000b) that required selecting between immediate versus deffered reward or punishment (Bechara, 2004). When performing the same task while their skin conductance was measured, VM‐damaged patients showed no anticipatory skin conductance response (SCR) before making a selection, whereas the control group displayed SCR activity before making any decisions, with higher values preceding the risky decisions (Bechara et al., 1996). The above evidence strongly supports the theory according to which emotions (or somatic signals) play a major role in regulating the decision making process.
5. Honey packaging case study Throughout communication, researchers are trying to understand the hidden features underlying the decision‐ making process, with emotions genesis and their role in the process as the central pieces of their study. Research on the consumer goods’ market validates the assumption that most buying decisions are made unconsciously. Moreover, it shows that packaging is one of the elements that trigger emotional responses. The objective of the study was to evaluate the emotional reaction that product packaging had on the consumers and to measure the extent to which it influenced their purchasing behavior. We chose to study honey packaging, as the products in this field are rather undifferentiated and it was a challenge to see whether some packages performed better than the others.
5.1 Methodology There were 44 participants to the research, segmented based on age (2 age groups: 50% of participants <40 years of age and 50% of participants >40 years) and gender (equal split among men and women). We used the following equipment:
14‐channel EEG headset – records the electrical activity of subcortical neurons. Measures the decrease in the alpha band amplitude (alpha band is dominant when the subject is awake but in a relaxed mood). The sensors are applied on the scalp and, in order to increase conductance, we used a saline solution.
Eye‐tracking glasses (ET) – a pair of googles especially‐designed for research purposes. They feature a small camera that’s oriented towards the participant’s eye and traces the pupilar movements. They allow researchers to see where do people look first, what are the elements that gain the most attention, the order in which the elements of the layout are perceived, etc.
Galvanic Skin Response sensor (GSR) – placed on the skin, it measures variations in skin conductance. Doesn’t offer information regading the positive or negative valences of the emotions, therefore it needs to be associated with the EEG.
5.2 Research design The participant was first asked to fill‐in a short questionnaire regarding demografic segmentation (age, gender) and consumption behavior (frequency, preffered brand, etc) and then was wired to the research equipment. Before the actual research started, there was a calibration phase, that insured that the data that was collected was accurate. The participant was asked to watch the images that appeared on the screen in front of him, trying as much as possible not to move.
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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau At about half of the testing time, the research was intrerrupted and the respondent was asked to perform a Stroop Test. The objective of this test was to assess whether the respondent was focused enough in order to take part in the second part of the study without negatively influencing the quality of the aquired data. Along with the packaging, we also studied a store shelf simulation, in order to observe the consumer’s purchasing behavior and assess our product’s performance compared to its competition. The whole research procedure lasted about 30 minutes.
5.3 Interpreting the results Each of the three techniques measures specific reactions. We will briefly describe each of them. EEG measures Relevance – the level of emotional and rational motivation towards a message. It shows whether a communication message (e.g. TV commercial or product packaging) manages to convey messages and ideas that are relevant to the target and the extent to which the target identifies itself with the featured characters, situations or points of view. Relevance is measured by analyzing the brain activity and reflects the intensity of the subconscious reactions – emotional involvement and motivational tendencies towards a message or brand. GSR measures the Activation, or short‐term emotion. It reflects the level of excitement induced by a promotional offer or a brand promise. It shows whether the participants at the study have been stimulated by the communication message and whether they are willing to take action. GSR is considered to be a predictor of purchase behavior. Activation is measured based on peripheral stimulation and measures the degree of arousal produced by a product or a brand promise. It shows whether the subjects are emotioned, tense or ready to take action. ET glasses measure Attention and collect data regarding the layout (or video) elements that draw attention. They provide information about where are people looking first and for how long and estimate how much attention are the participants giving to the critical elements of the communication material. Furthermore, they can predict which words, graphical elements or layout objects determine Relevance and Activation.
5.4 Conclusions The honey packaging that was studied manages to determine a positive reaction (represented by the red band on the upper recording line, see Figure 1) but it requires a long time to do that (the positive reaction appears after three seconds of staring at the product). There is no positive emotion in the first seconds after the exposure and there is no activation (represented by the purple recordings on the lower band). Therefore, the packaging has a poor shelf performance and is probably losing sales to its competitors, as it is not able to determine rapid positive emotion and activation.
Figure 1: Emotional engagement induced by the honey packaging Regarding the shelf simulation, the studied product doesn’t manage to draw the costumers’ attention in the first seconds and therefore loses sales to other brands. Figure 2 shows the recording of the customers’ gaze
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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau while in front of the shelf. The red recording represents the younger people’s gaze pattern while the blue line represents the recording for older people. It can be easily noticed that older people have a rather linear and predictive attention pattern while younger people are more unpredictable in their visual flow. This represents a big opportunity for the studied brand to grab attention from its competitor and take the second position in the attention distribution pattern.
Figure 2: Customers’ visual pattern in front of the shelf Furthermore, it seems that only older people develop a positive reaction to the packaging, while the younger audience doesn’t get emotionally engaged with the product. This is an issue that needs to be addressed through redesigning the packaging and crafting the communication message more carefully in order to engage with the younger segment of the target.
6. Recommendations The brand and the packaging have a big potential of establishing an emotional bond with the customers but the current design needs a longer time to draw attention, compared to its competitors. According to our findings, the positive reaction only appears in the older segment of the target. The younger population, on the other hand, has a neutral response to the packaging, thus showing no emotional engagement whatsoever. We believe that this issue can be addressed through a packaging facelift and through developing a communication campaign focused on emphasizing the beenfits of honey consumption. Further research regarding the elements of the label is needed in order to assess which design version has the most impact on the viewers (in terms of colours, fonts and graphical elements used). Furthermore, regarding the shelf simulation study, further research is needed in order to assess whether the same attention pattern in young people is preserved given that the product order is changed. These findings are of general interest and have practical applicability in the advertising and marketing fields, as they can be extrapolated to a wide range of industries, starting from FMCG to all consumer goods. A highly nutritive product with a good prospect for market expansion, both in Romania and abroad, honey should be better marketed. Romania’s rich honeybee flora represents an opportunity that should be exploited throughout a better positioning. Aiming to assess and direct the main features that should be included on honey packaging, this study could also be considered a humble attempt to stimulate honey products consumption.
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Enabling Knowledge Sharing in an Academic Environment: A Case Study Versavia Ancusa, Razvan Bogdan and Oana Caus Politehnica University of Timisoara, Timisoara, Romania vancusa@cs.upt.ro razvan.bogdan@cs.upt.ro oana.caus@cs.upt.ro Abstract: Knowledge sharing is the foundation of the human society. Without it, the progress would be hampered and new technologies and ways to improve lives would be threatened. Resistance is the most often cited reason why knowledge sharing does not succeed. The wilfulness of the subjects to share and the methods used to receive and transmit the knowledge are crucial elements in assuring high quality knowledge sharing and a low resistance to it. Our aim is to determine a spectrum of positive behaviours and methods that can be used to improve knowledge sharing in an academic environment. This setting is deeply rooted in knowledge sharing, as the only valid method towards progress is based on intensive collaboration and enthusiastic exchange of ideas. However, in our research we found out that generally, this is not the case with our students. We set out to determine which factor is then more important to emphasize: the tonality (affecting the wilfulness) or the modality (involving the methods used to communicate) in order to maximize the variety of shared reasoning. We devised a series of experiments by using 96 volunteer students and 2 teachers. All the students expressed their modality preferences by using a VARK (Visual, Auditory, Reading, and Kinaesthetic) test. The teachers prepared appropriate level lectures that involved one or more learning modalities and compiled them in a cohesive course. The tonality varied from classical academic style (class‐room lectures) to a very informal approach by using social networks to present the current course and assignments. At the end of the course the students answered a questionnaire to assess their subjective opinion regarding the efficiency of their learning. Concluding the course all the students took an exam that included questions in order to determine the knowledge from each lecture. The tonalities and modalities of low‐scoring answers were from the same lectures that the students expressed their discontentment with. Because the two results have good overall consistency this leads us to promote several tonalities and modalities as ways to maximize knowledge sharing in our academic environment. Keywords: knowledge sharing, tonality, modality, VARK, social networks, academic environment
1. Introduction Humans are, by definition, social beings, hence the inherent need to interact. Every social act in the human society is based on communication whereas interaction can be perceived as an ensemble of verbal and non‐ verbal behaviours, whose joint purpose is to exchange knowledge. There are other means to enhance one’s own knowledge such as self‐study, observation, inference, etc., yet, communication remains the base of successful knowledge sharing. Although purposeful knowledge sharing is an important tool to make progress, this practice is not as common and widespread as expected. Information hoarding is the major obstacle in knowledge sharing. Although data exchange is part of any communication, the perceived quality of information varies greatly. One’s own subjective opinion can lead to information hoarding, and due to the communication flow, may limit the resourcefulness of others. This proves to be of crucial importance, especially in academic environments, where both open information exchange and creativity are needed for the successful accomplishment of the learning and research systems. Although many studies have found several causes for resistance to knowledge sharing, a less explored avenue is the one related to different communication styles. Due to the unique individuality of each party involved, their internal representation by the subject and the context of knowledge sharing are different. If we take this into account, can we improve knowledge sharing? The paper is structured as follows: the literature review offers a survey of knowledge sharing techniques; the research design presents the parameters of the study, followed closely by the findings described under the heading results and discussion. In the conclusion, several guidelines are proposed that ensure a higher emotional response and an increased knowledge transfer.
2. Literature review Knowledge sharing is a priceless asset that fosters the knowledge exchange among a spectrum of communities. It brings the creation and sustainability of competitive advantages (Miller & Shamsie, 1996). In
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Versavia Ancusa, Razvan Bogdan and Oana Caus spite of that, research has shown that some individuals are prone to resist sharing their knowledge (Ciborra & Patriota, 1998), (Bock & Kim, 2002). In state‐of‐the‐art literature (Davenport & Prusak, 2000), (Partridge, 2013) socialization was proposed as a deterrent of information hoarding. The location for socialization may be a physical place (water cooler, cafeteria, etc.) or a virtual one (telephone, Intranet, Internet or social networks). The same idea is further described in (Webster, et al., 2008) where Dr. David Zweig argues that knowledge sharing is based on three principles, namely Make it Safe, Make it Count, Make it Social. The first principle (“Make it safe”) aims at showing that creating a safe environment in a communication network is of vital importance in knowledge sharing. The climate where individuals are collaborating should be based on the reassurance that they will be at no risk for the ideas and knowledge that are shared. Being worried that other people will find out that you aren’t perfect or being afraid that some repercussions are going to take place can be addressed by creating a proper setting. The second principle (“Make it Count”) suggests a reward system that should be focused on the act of sharing. This view is a controversial one as the reward system can be seen as a demotivating factor in some cultures or by certain personality types (Gurteen, 2007). The last principle (“Make it Social”) states that creativity and information sharing significantly increase in a social context. Zweig argues that knowledge sharing in itself is a social experience; therefore humanity should be highly prized as the social space creates a reward by the act itself. As previously presented, successful knowledge sharing is based on inter‐human communication (Figure 1). Although communication is proven to have a strong, universal, nonverbal component (Ekman & Friesen, 1969), the context and representation system of each individual involved in the communication act, are just as important as the nonverbal component. The nonverbal component is considered responsible for 50‐70% of the communication exchange, while the context and representation stand for 20‐30%, leaving the actual information with an insubstantial percentage of 10‐20% (Ekman & Friesen, 1969). Assuming the reality of a digital world in which we can rely less on the nonverbal component, the context and representation system begin to play a crucial role in communication.
Figure 1: Overview of the communication structure The representation system of individuals is highly dependent on all senses (Druckmann, 1988). The total number of senses can, nonetheless, be under debate (Robinson & Aronica, 2009). Although a system comprising at least five senses (VAKOG ‐ visual, auditory, kinaesthetic, olfactory and gustatory) is considered to be comprehensive enough, there are at least three others to consider: equilibrioception, thermoception and nociception. However, the question arises if all these senses are important when it comes to communication. There are several research papers that suggest that this is a valid hypothesis (van Servellen, 2009) (Downar, et al., 2002), however, with the added caveat that not all senses are equally important. The representation system, or as it may be otherwise known, the sensory modalities used in communication have been subjected to extensive studies (Druckmann, 1988), (Hawk & Shah, 2007), (van Servellen, 2009), (Wolfe, et al., 2011). As shown in (Downar, et al., 2002), the representation system has clear biological connections with the neuronal pathways. This makes it highly quantifiable by means of MRI but the exposure to radiation is undesirable for an extended period. Consequently, in order to assess sensory preferences, there are several available methods (Bandler & Macdonald, 1989). Of these methods, Neil Flemming’s VARK test is among the most widely‐spread, given its simplicity and efficiency when testing academic performance attributes (Leite, et al., 2009). This
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Versavia Ancusa, Razvan Bogdan and Oana Caus provides easy means to measure the modalities in which communicators carry a dialog, yet it does not address the socio‐cultural suprasystem. According to (van Servellen, 2009) the socio‐cultural suprasystem in which communication is performed can be identified as one of the functional components of the communication process and it has two sub‐components: the environment and the interpersonal context. The information exchange is influenced mutually by these two, but the most easily controllable is the environment. The previously presented principles: “make it safe” and “make it social” offer, in fact, ways to influence the environment and the interpersonal context, thus influencing the whole communication context. It’s worth mentioning that the most debated principle “make it count” does not directly influence any structure in Figure 1. In academic communication, the environment can be usually perceived in connection with its formality. The formal approach is most frequently used in academic settings, in the form of direct teaching, but informal approaches have been widely tested as well (Ellis, 1982), (Cooper & Others, 1990), (Kaufman, et al., 1997), (Peklaj, 2006). The former includes inquiry‐based learning, cooperative learning and media‐based learning. Although these ideas have been advanced for several decades, the technological advancement has lately changed our possibilities in implementing informal approaches. According to a study by Intel (Intel Corp., 2012), in 2012, in an Internet minute, 1.3 million videos are viewed on YouTube, 6 million views of Facebook pages and 277,000 Facebook logins are performed, more than 320,000 Twitter accounts are created and 100,000 tweets are published; additionally 20 million photo are viewed and 3000 photos uploaded on Flickr and 6 new Wikipedia articles are published – all in just one minute. In the same study of Intel Corp., the current number of networked devices is estimated to equal the total globe population and expected to double by the end of 2015. The deduction that follows these data is that we live in a society in which networks, networking and interaction through networked devices becomes more and more ubiquitous. Working with this hypothesis, it is clear that the amount of information an individual is immersed in every single minute is massive and it is only going to increase. Another part of our working hypothesis is the academic environment and the requirements of such a profession. As an educator, besides teaching, part of the job is to make sure that students have the information they need, ready to be assimilated. Bringing together these ideas, it becomes obvious that: (a) you have to go where your students go – namely involving social networks and (b) you have to work to make information as attractive and easy to assimilate as possible in order to survive information‐distracting sources. In the context of sensory modalities, this implies knowledge transfer between the educators’ internal sensorial representation of information and the students’ internal representation, while taking into account the context in which this takes place. With regard to the large assortment of networks available to choose the social network to pursue for our experiment, we have taken into account the largest social network site – Facebook. More and more people, mainly adolescents, are creating for themselves an on‐line “life” that intersects with their real life and Facebook is a means to an end for them. This new “life” creates many learning opportunities coined as “emerging digital learning styles” (Saeed & Yun, 2008). In December 2012, Facebook marked more than 1 billion active users (Facebook Corp., 2013); though considering its teaching potential, we may observe a cautious approach from educators. While Facebook was created in 2004, only in 2006 research started focusing on the possible advantages of using it as an instrument for teaching (Mathews, 2006). Since then, many authors and Universities have considered that teacher training programs should incorporate a guide to using Facebook to connect with the students (Muñoz & Towner, 2009), (Fogg Phillips, et al., 2009). The precise methods used to connect with the students via Facebook vary, but there are several choices: profile page for the teacher, group page for the class, replicating web course functions on Facebook or incorporation of Facebook Applications into current pages (Muñoz & Towner, 2009). Using a social network site raises the problem of etiquette. The discussion of best practice policies is a very ardent one. Many viewpoints, especially from the “Old” World (Robinson, 2012) are against the use of
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Versavia Ancusa, Razvan Bogdan and Oana Caus Facebook by teachers, citing as main reasons the dangers of inappropriate behaviour and the necessity to maintain a distance between students and teachers. Many schools do not allow Facebook access, prohibit social‐media contact between staff and students or even forbid their teachers to have a Facebook account. On the other side of the Atlantic, Stanford and Berkley are among the front‐runners for using Facebook as an instrument for teaching. For the first time ever, in 2007 a class at Stanford (Standford Persuasive Tech Lab, 2013) created an application on Facebook, being closely followed by another class, this time from Berkley. All the undergraduate students enrolled in 2008 at Stanford University were active on Facebook. A study in another American University (Jackson & Porter, 2009) showed that at the end of 2008, more than 90% of the students checked Facebook every day, twice as often as their educational e‐mail. Stanford University marked another first by publishing its first course on Facebook, in 2009. Confirming this trend, the U.S. Department of Education through their 2010 U.S. National Technology Education Plan, entitled “Transforming American Education: Learning Powered by Technology” is asking to apply “the advanced technologies used in our daily personal and professional lives to our entire education system to improve student learning.” The social‐media policy is set by each university and is more casual in the US, as well as updated periodically in order to manage the emerging realities of social media. One important contention related to using Facebook regards the copyright of the materials posted. Facebook owns all the data posted by users until users delete it. This means that all the courses (slides, videos, photos) and student assignment posted are owned by Facebook and that may violate the university’s copyright claim on it. A way to circumvent this situation would be by posting links to external resources. Another discussion is around the term “friend” – in Facebook context it does not literally mean “friend”, it would be more like a “contact” or “Aristotelian version of a utilitarian friend”. It is impossible to have 300 very good friends, but the term “friend” creates a negative reaction from people that do not understand the digital meaning of the word. A factor not usually taken into consideration is the fact that many companies nowadays look at the future employee’s web presence and the Facebook account comes definitely under scrutiny. By linking Facebook and teaching, prospective employers can see workmanship, involvement and thus motivate even further students to interact positively on Facebook. To conclude, we claim that Facebook is just a communication medium that connects people, with privacy controls that can be used to separate and layer private and professional life experiences; it is convenient as it provides digital records, generates fast responses and is widely spread (1 billion active users in December 2012), thus making it a formidable tool for education.
3. Research design This paper presents an experiment conducted during the academic years 2011 – 2012 and 2012 ‐ 2013 at “Politehnica” University of Timisoara, while teaching the “Fault‐tolerance of Computer Systems” course to 4th year and final year students enrolled in the Computers and Information Technology Bachelor program. The course registered a total of 96 students and was conducted in both digital and real‐life classroom forms, using a Facebook closed group and traditional academic settings.
Figure 2: Controlled research variables (values presented in italics) in the communication structure
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Versavia Ancusa, Razvan Bogdan and Oana Caus It should be mentioned that there is no official Facebook policy of the University, but the former Chancellor and other high‐level teachers have accounts and befriend students, without any quandary. A Facebook group, however, allows members to post on the blackboard without them having to be friends with each other. It is our belief that in doing this, we maintain a more considerate level of privacy for everybody involved, to be layered with the privacy settings on each person’s profile. New courses were posted each week, using different approaches (YouTube video, Facebook notes, external link to slides/ articles, audio files, animations) and thus mapping various modalities (visual, auditory, kinaesthetic or reading). The tonality of the posts / actual lectures varied from informal to highly formal academic lectures and readings. Referring to Figure 1, our research varied the parameters presented in Figure 2; basically, we controlled the environment and the representation system. After the end of the course students were asked to express their opinion and submit it via an anonymous questionnaire, thus making it a safe environment to knowledge sharing, as suggested by Dr. David Zweig in (Webster, et al., 2008). The questionnaire was designed to assess students’ subjective viewpoint regarding their learning efficiency. Each question was duplicated in two different ways, as a means to ensure a more accurate measurement. We also included a free‐comment section that proved to add valuable insight. The final exam included several items and each item was correlated with a specific teaching modality. Our aim was to test the ability, preference and assimilation for each major modality (V, A, R, K) in two different contexts: formal and informal.
4. Results and discussion The initial students’ assessment using VARK has led to the data presented in Table 1. There was a marked preference for auditory and reading modalities. These two preferences could be approximated by a normal distribution (kurtosis and skewness close to 0). It should be noted that no student obtained a maximum possible score (16) at any category. Moreover, the mean suggests limited capabilities for modelling data: 25% for visual, 38.5% for auditory, 40.31% for reading, 35.81% for kinaesthetic. Data dispersion (taking into account range and sample variance) for the visual modality is reduced compared to the auditory and kinaesthetic modalities. Interestingly, the reading column presents a medium dispersion because it may imply all the three senses, as we found in the comments section of the final questionnaire in the first year of the experiment. One of the students described the reading as “speaking the text in my head”. After further investigation with the students from the second year of the experiment, their description of reading varied and was usually a composite of the other senses. The internalization of these processes – converting the reading into modalities – varied greatly and often the students could not explain the process. Table 1: General statistic data after VARK testing
Data Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Confidence Level (95.0%)
V 4.00 0.26 4.00 4.00 1.75 3.07 0.80 0.63 8.00 1.00 9.00 0.53
A 6.16 0.39 6.50 7.00 2.60 6.74 0.10 0.32 12.00 1.00 13.00 0.79
R 6.45 0.35 6.00 5.00 2.32 5.37 ‐0.15 0.58 9.00 3.00 12.00 0.70
K 5.73 0.40 6.00 6.00 2.63 6.90 0.70 0.75 12.00 1.00 13.00 0.80
The final exam consisted of a written individual paper in which students had to answer several problems. The problems reflected parts of the course that were taught using different modalities. We converted the percentage of correct answer from each question to a percentage in the VARK analysis. The data are presented in Table 2.
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Versavia Ancusa, Razvan Bogdan and Oana Caus Table 2: General statistic data after exam items Data
V
A
R
K
Mean
4.32
6.27
6.08
5.13
Standard Error
0.68
0.42
0.58
0.46
Median
2.40
6.78
7.11
5.63
Mode
0.00
8.80
8.89
6.93
Standard Deviation
4.28
2.66
3.69
2.93
Sample Variance
18.35
7.10
13.61
8.57
Kurtosis
‐0.58
‐0.47
‐1.20
‐1.30
Skewness
0.89
‐0.76
‐0.40
‐0.31
Range
12.80
9.60
10.67
9.53
Minimum
0.00
0.53
0.00
0.07
Maximum
12.80
10.13
10.67
9.60
1.37
0.85
1.18
0.94
Confidence Level (95.0%)
At the beginning of the course, there was a marked preference for auditory and reading modalities and the final exam showed that lectures that promoted those preferences had the highest rate of correct answers. This comes to show the importance of modality preference pre‐checking prior to the actual beginning of teaching. Regarding tonality, the Facebook environment versus traditional location for the course, the final questionnaire revealed that the on‐line portion of the course was not easier to graduate than the more traditional part as students found the same level of difficulty, but it was easier to ask details, easier to retrieve information and much easier to understand than the traditional methods. Of the total of 96 students, 47.92% checked their Facebook account more than once a day, 37.5% checked their account once a day, 8.3% entered their account once every two days and the remaining 3 persons accessed the platform at least once a week.
Figure 3: Course reflection – students’ poll data (5 – highest, 1 – lowest) When asked to describe their opinion in relation to the interaction during the course in comparison (Figure 3) with more traditional teaching methods, the ease and rapidity of access as well as the ease of interaction were particularly appreciated, while loss of privacy was not a concern for students. It should be noted that the interaction with the teacher was not as important as the overall ease of interaction. In supporting this, we should mention that in more than one occasion, when questions were posted by students, other students replied with the answer, the teacher intervening only when more clarification was needed. This aspect is highly significant to individuals’ human development: they learn to promote a positive digital citizenship while developing a sense of teamwork. Also, this introduces collaborative learning, proven by other professionals
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Versavia Ancusa, Razvan Bogdan and Oana Caus (Bruffee, 1999), (Cohen, et al., 2004) to be one of the most efficient learning methods. On the other hand, in terms of question answering, the traditional setting is highly dependent on the teacher and questions can be asked only during the course or office hours. With respect to the types of materials used during this course (Figure 4), the video was the most enjoyed, followed closely by informal notes, using Facebook notes and pdf course slides. The least liked by the students was the scientific article, though interestingly it was the only type of material that did not receive a “totally reject’ vote.
Figure 4: Students evaluation of information presentation methods In terms of the material tone, more informal methods like video recordings and Facebook notes were enjoyed the most, the least enjoyable being, again, the scientific article.
5. Conclusions After conducting experiments for two years, the authors advance the following guidelines: prior testing using VARK (or a similar tool) is essential, followed by splitting students into groups based on their preferences (e.g.: visual group, auditory group, etc.). Students should be allowed to choose between groups if their preferences score high enough. A special mention concerns teacher’s intervention, namely the teacher must ensure students that one group or the other is not better/worse. Furthermore, it is helpful to keep the groups flexible, as one student may “migrate” from one group to another. This is highly probable to happen with students that have several strong modalities. These groups are now ready to perform various collaborative learning techniques because using the same modality will provide faster concept understanding and integration. As a teacher, remember to present the concept using modality‐specific words and teaching aids to each of the groups. Another academic targeted conclusion is that test items should be presented in all modalities, since understanding requirements is the first step towards finding the solution to a problem. Individuals with low scores in a modality may find it difficult to adapt the internal representation of the test item to their best modality.Regarding the opposition academic vs. social network settings, we have discovered that Facebook usage favours more informal teaching methods that achieve a higher emotional response from students. This enables adequate premises for deepening the learning process, which is, unquestionably, our mission as educators.
References Bandler, R. & Macdonald, W., 1989. Insider's Guide to Submodalities. U.S.: Meta Publications. Bock, G. W. & Kim, Y. G., 2002. Breaking the myths of rewards. Information Resources Management Journal , 15(2), pp. 14‐ 21. Bruffee, K. A., 1999. Collaborative Learning: Higher Education, Interdependence, and the Authority of Knowledge.. Baltimore, MD: Johns Hopkins University Press. Calvert, G. A., Spence, C. & Stein, B. E., 2004. The Handbook of Multisensory Processes. Cambridge, Massachusetts (United States): MIT Press.
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Versavia Ancusa, Razvan Bogdan and Oana Caus Ciborra, C. & Patriota, G., 1998. Groupware and teamwork in R&D: limits to learning and innovation. R&D Management, 28(1), pp. 1‐10. Cohen, E. G., Brody, C. M. & Sapon‐Shevin, M., 2004. Teaching Cooperative Learning The Challenge for Teacher Education. First ed. Albany, NY: SUNY Press. Cooper, J. & Others, A., 1990. Cooperative Learning and College Instruction: Effective Use of Student Learning Teams, Long Beach, CA: California State University Academic Publications Program, CSU Chancellor's Office. Davenport, T. H. & Prusak, L., 2000. Working Knowledge: How organizations manage what they know. Boston, MA: Harvard Business School Press. Downar, J., Crawley, A. P., Mikulis, D. J. & Davis, K. D., 2002. A Cortical Network Sensitive to Stimulus Salience in a Neutral Behavioral Context Across Multiple Sensory Modalities. J Neurophysiol, Volume 87, pp. 615‐620. Druckmann, D., 1988. Enhancing Human Performance: Issues, Theories, and Techniques. 1st ed. Washington, D.C.: National Academy Press. Ekman, P. & Friesen, W. V., 1969. The repertoire of nonverbal behavior: Categories, origins, usage, and coding. Semiotica, Volume 1, pp. 49‐98. Ellis, R., 1982. Informal and formal approaches to communicative language teaching. ELT Journal, 36(2), pp. 73‐81. Facebook Corp., 2013. News. [Online] Available at: http://newsroom.fb.com/content/default.aspx?NewsAreaId=22[Accessed 03 2013]. Fogg Phillips, L., Baird, D. & Fogg, B., 2009. Facebook for Educators. [Online] Available at: http://facebookforeducators.org [Accessed January 2013]. Gurteen, D., 2007. Building a Knowledge Sharing Culture. [Online] Available at: http://www.gurteen.com/[Accessed 03 2013]. Hawk, T. F. & Shah, A. J., 2007. Using Learning Style Instruments to Enhance Student Learning. Decision Sciences Journal of Innovative Education, 5(1), pp. 1‐19. Intel Corp., 2012. What happens in an Internet minute. [Online] Available at: http://scoop.intel.com/what‐happens‐in‐an‐ internet‐minute/ Jackson, M. & Porter, A., 2009. Facebook Groups for Teaching & Learning?. [Online] Available at: http://assett.colorado.edu/ Kaufman, D., Sutow, E. & Dunn, K., 1997. Three Approaches to Cooperative Learning in Higher Education. The Canadian Journal of Higher Education La revue canadienne d’enseignement supérieur, XXVII(2), pp. 37‐66. Kerr, M. S., n.d. Lecture notes on Social & Emotional. [Online] Available at: http://faculty.txwes.edu/mskerr/files/3304_ch2.htm [Accessed June 2012]. Leite, W. L., Svinicki, M. & Shi, Y., 2009. Attempted Validation of the Scores of the VARK: Learning Styles Inventory With Multitrait–Multimethod Confirmatory Factor Analysis Models. Educational and Psychological Measurement, Volume 70, pp. 323‐339. Mathews, B. S., 2006. Do you Facebook? networking with students online. College & Research Libraries News, Volume 37, pp. 306‐307. Media trend, 2012. Markets By Country ‐ Europe – Romania. [Online] Available at: http://www.newmediatrendwatch.com Miller, D. & Shamsie, J., 1996. The resource‐based view of the firm in two environments: The Hollywood film studios from 1936 to 1965. Academy of Management Journal, 39(3), pp. 519‐543. Muñoz, C. L. & Towner, T. L., 2009. Opening Facebook:How to Use Facebook in the College Classroom. Charleston, South Carolina, s.n. National Research Council (U.S.). Committee on Techniques for the Enhancement of Human Performance, 1988. Enhancing Human Performance: Issues, Theories, and Techniques. 1 ed. Washington: National Academy Press. Partridge, A., 2013. Why Your Organization Should Support a Knowledge Sharing Culture. [Online] Available at: http://blogs.adobe.com/captivate/2013/01/why‐your‐organization‐should‐support‐a‐knowledge‐sharing‐ culture.html [Accessed 03 2013]. Peklaj, C., 2006. Cooperative activity and its potential for learning in tertiary education. Horizons of Psychology, 15(3), pp. 37‐50. Robinson, C., 2012. Teachers warned over befriending pupils on Facebook. [Online] Available at: http://www.guardiannews.com/uk‐home Robinson, K. & Aronica, L., 2009. The Element: How Finding Your Passion Changes Everything. Reprint ed. s.l.:Penguin Books. Saeed, N. & Yun, Y., 2008. Using Learning Styles and Preferences to Incorporate Emerging E‐Learning Tools in Teaching. Santander, Spain, Eighth IEEE International Conference on Advanced Learning Technologies ICALT '08. , pp. 967‐971. Standford Persuasive Tech Lab, 2013. Psychology Of Facebook. [Online] Available at: http://captology.stanford.edu/projects/psychology‐of‐facebook.html[Accessed 2013]. van Servellen, G., 2009. Communication Skills for the Health Care Professional: Concepts, Practice, and Evidence. Second Edition ed. Boston: Jones & Bartlett Publishers. Webster, J. et al., 2008. Beyond Knowledge Sharing: Withholding Knowledge at Work. Greenwich, CT: JAI Press. Wolfe, J. M. et al., 2011. How does our search engine “see” the world? The case of amodal completion. Atten Percept Psychophys, Volume 73, p. 1054–1064.
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Filling the Knowledge gap: How Relevant is University Programmes to Industry Needs? Nicolene Barkhuizen North‐West University, Mmabatho, South Africa nicolene.barkhuizen@nwu.ac.za Abstract: The past two decades have seen a proliferation of publications debating the roles of Human Resource Management (HRM) practitioners in the South African work context. These publications highlighted a great deal of confusion and uncertainty relating to the contributions of HRM practitioners in the workplace. Higher Education Institutions should therefore examine their roles and academic programmes to ensure that a new generation of HRM practitioners are adequately prepared and relevant for the workplace. The main objective of this research was to analyse the content of the undergraduate HRM programmes as currently being offered at a merged South African Higher Education Institution. This research first aimed to analyse the similarities and differences between the programmes. Secondly this research aimed to compare the curricula of the merged institution with the undergraduate HRM curricula of other South African HEIs. Finally this research aimed to determine the extent to which the programme contents are in line with the competency requirements for HRM practitioners in the workplace. A case study approach was followed in this research. This case involved the comparison of three undergraduate programs focusing on HRM in a merged higher education institution. In addition the programmes of the current institution were also compared with seven other South African Higher Education Institutions (HEIs) that offer a Bachelors Degree in HRM. The institutions were chosen based on their access and availability of information as well as their status in the field of HRM. These HEIs also represented newly formed South African comprehensive universities as well as traditional higher education institutions. Curriculum data such as yearbooks and subject guides were analysed. The findings for the merged institution showed that the undergraduate programme in HRM differed significantly in terms of the content offered. This presents some significant challenges in the alignment of programmes across the three campuses of the institution which is a requirement of the Department of Higher Education and Teaching. Students are thus unable to move between the three campuses in terms of studying HRM. Only one campus offers HRM on all three year levels whereas the other two campuses seem to focus more on Labour Relations. This is limiting the students on the latter campuses in terms of pursuing a further professional career in HRM. Similar results were observed between the HRM programme offerings of the other HEIs. The knowledge contents of the current HRM programmes only meet the new competency requirements for HRM professionals to some extent. Keywords: human resource management, undergraduate curricula, higher education institutions, mergers, workplace competencies
1. Introduction A country's international competitiveness and growth of the knowledge community depends on its population having a strong and sustainable higher educational sector. South African higher education institutions in particular are expected to play a critical role in human resource development and stimulate innovation in a ‘knowledge economy’ (Council of Higher Education – CHE, 2011; Baloyi & Phago, 2012). The South African higher educational landscape however has undergone significant changes post 1994. The collapse of apartheid has lead to the transformation and re‐structuring of higher education institutions with the aim of correcting historical inequalities (Chipunza & Gwarinda, 2010; Lalla, 2009). As a result the number of higher education institutions were reduced and placed into three categories: universities, universities of technology and comprehensive/ merged institutions (Muller, 2008). Comprehensive universities emerged as result of a merger between the technicon and the traditional university (Reddy, 2004). Bester and Scholtz (2012) maintain that the transformation of higher education in South Africa has resulted in an ongoing need to reflect critically on the relevance and responsiveness of higher education curricula. Comprehensive universities for example are expected to offer a diverse range of university programmes (i.e. vocational, career‐focused, professional and general/formative) of both the university and technicon type (Reddy, 2004. This posed a number of thought provoking and provocative questions: How will programme diversity be maintained? At what levels is integration possible and desirable? Where is it possible to construct articulation pathways, and what form will they take (CHE, 2004)? To this end comprehensive and merged institutions have to consider whether to retain, redesign, consolidate or discontinue existing qualifications or alternatively develop new qualifications (Muller, 2008). Qualification structures should therefore be developed that will allow comprehensive and merged institutions to define their roles within the restructured South African higher educational landscape (Baloyi & Phago, 2012; Higgs & Keevy, 2009).
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Nicolene Barkhuizen Against this background, the main objective of this research was to analyse the content of the undergraduate Human Resource Management (HRM) programmes as currently being offered at a merged South African Higher Education Institution. This research first aimed to analyse the similarities and differences between the programmes. Secondly this research aimed to compare the curricula of the merged institution with the undergraduate HRM curricula of other South African HEIs. Finally this research aimed to determine the extent to which the programme contents are in line with the competency requirements for HRM practitioners in the workplace. This research is motivated from the fact that the Department of Higher Education and Training requires all merged HEIs to present curricula that are similar in content (Baloyi & Phago, 2012). Therefore the need to do an in depth analyses of the types of modules that are offered as part of the undergraduate programmes in HRM and the possible implications for vertical and horizontal articulation. In addition universities are expected to produce workplace ready individuals who can lead, produce new knowledge, see new problems and imagine new ways of approaching old problems (CHE, 2011; Heerde & Murphy, 2009; Nduna, 2012; Njozela, 2012). This research thus aimed at answering the following research questions:
What are the similarities between the undergraduate HRM programmes as offered by a merged South African HEI?
What are the differences between the undergraduate HRM programmes as offered by a merged South African HEI?
How do the current curricula offered by the merged institution compare with undergraduate HRM curricula of other HEIs?
To what extent do the current programme offerings of the merged institution comply with the competency requirements for HR Professionals in the workplace?
In what follows next a brief description of the competency requirements for HRM Practitioners is presented. Thereafter the methodology used to answer the empirical research questions and the results are presented, ending with a discussion and, finally, the conclusion and value‐add of the research.
2. Theoretical framework 2.1 Competency requirements for HRM practitioners Since its inception nearly a century ago, the field of HRM has been subjected to immense scrutiny by questioning its value add to organisations (Ulrich, 2011). Applied within the South African context, the past two decades have seen a proliferation of publications which highlighted the confusion and uncertainty regarding the exact contributions of HRM practitioners in the workplace. Higher Education Institutions should therefore examine their roles and academic programmes to ensure that a new generation of HRM practitioners are adequately prepared and relevant for the workplace (Bester & Scholtz, 2012; Maila, 2012; Meyer & Bushney, 2008). Some research for example showed that HEIs are failing to produce workplace ready graduates (CHE, 2011; Pop & Barkhuizen, 2010). Generally, organisations are not able to use new graduates to fill their skill requirements because of a lack knowledge, skills and experience. Applied within the field of HRM, this can be a result of the role confusions that exist between Industrial Psychologists and HRM Practitioners. The primary task of IO Psychology is the application of psychological principles and research to workplace phenomena (Rothmann & Cilliers, 2007; Schreuder & Coetzee, 2010) whereas Human Resource Management involves a more strategic approach to acquire, develop and manage people in the organisation (Ulrich, 2011). According to Schreuder and Coetzee (2010) Industrial Psychologists are mostly fulfilling the roles of HRM practitioners in the workplace as opposed to their own envisaged roles. This situation can be explained by the fact that some universities in South Africa still accept an academic dispensation where I/O Psychology is taught under the discipline of HRM (Rothmann & Cilliers, 2007; Schreuder & Coetzee, 2010). The new qualification mix in comprehensive and merged institutions also seems problematic as far as the programme outcomes for HRM are concerned. Technicons traditionally focused on practical career‐focused
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Nicolene Barkhuizen and work‐integrated learning that combined theoretical knowledge with applied competence (CHE, 2011). University qualifications provided general formative and career‐orientated/ professional education that focused on teaching and in‐depth research. A study comparing both types of qualifications in a comprehensive university, showed that only minor differences existed in terms of the knowledge and skills acquired, teaching and learning methods and assessment procedures (Barkhuizen, Goosen, van Loggerenberg & Malan, 2009). None of the two qualifications focused on the development of technical skills. Merged institutions on the other hand have to deal with programme standards and the subsequent development of common curricula across all delivery sites (Goddard, 2009). Research evidence suggest that the mergers of HEIs did not result in the “favourable” environment that the South African government envisaged and have left scholars with numerous challenges and obstacles relating to curriculum design and alignment (Baloyi & Phago, 2012; Ntshoe, 2012). These results have important implications for the type of HRM practitioners that comprehensive and merged universities produce for the labour market as well as compliance with professional HRM standards. The SABPP is the professional body for the registration and competency guidance of HRM practitioners in the South African workplace (Meyer, 2012). The SABPP recently launched a new competency model for HR professionals in the workplace (Meyer, 2012). The competencies include amongst others Leadership and Personal Credibility, Organisational Capability, Solution Creation and Implementation, Interpersonal and Communication Skills and Citizenship for the future. From the model it is clear that HR Professionals at the basic level already need to possess the necessary business acumen, soft and technical skills to execute HRM roles in the workplace effectively (Meyer, 2012). This new competency model fills an important gap as a recent survey among HRM practitioners showed that only 20% of South African organisations have a HRM competency model in place (Knowledge Resources, 2011). In addition most of the organisations surveyed utilise HRM competency models that do not take the South African labour market context into account. Furthermore, in many incidences the considerable lack of soft and technical skills training and work integrated learning practices at the undergraduate level are key reasons why organisations have to implement internship programmes to make graduates more workplace ready (Pop & Barkhuizen, 2010). One of the key goals in the establishment of comprehensive Institutions was to introduce work or career‐focused orientation in some programmes with the possibility of cooperative or in‐service learning (CHE, 2011). Comprehensive institutions and merged institutions are required to contribute to students’ ‘graduateness’ in various forms and should thus focus on “Programmes that promote graduates’ successful integration into the world of work and that enable graduates to make meaningful contributions in contexts of development” (CHE, 2011: 3). The effectiveness of work integrated learning programmes in the transfer of work related knowledge and subsequent increase in graduate employability has been widely documented (CHE, 2011; Eigst, 2009; Griesel & Parker, 2008; Pop & Barkhuizen, 2010). The implementation of WIL programmes however will require innovative curricular, teaching, learning and assessment practices (CHE, 2011). In sum, the above discussion highlighted the challenges relating to the knowledge acquisition of HRM practitioners and the subsequent impact thereof on their ability to perform their envisaged roles in the workplace. This section also showed the important role of HEIs in providing sound teaching and learning practices for HRM graduates that comply with the competency requirements of professional registration bodies.
3. Research method A case study approach was followed in this research. This case involved the comparison of three undergraduate programs focusing on HRM in a merged higher education institution. The institution came into existence as a result of a merger between a traditional South African university and two historically disadvantaged universities. The newly formed higher education institution consists of three campuses. All three campuses offer postgraduate programmes in HRM which flows from the undergraduate programmes. The undergraduate programmes are presented over a period of three years. Each year is divided into two semesters with modules presented over 14 weeks per semester. In addition the programmes of the current institution were also compared with seven other South African Higher Education Institutions (HEIs) that offer a Bachelors Degree in HRM. These institutions were chosen based on the access and availability of information and also their status in the field of HRM. These HEIs also
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Nicolene Barkhuizen represented newly formed South African comprehensive universities as well as traditional higher education institutions. Data was collected and analysed with a view to identifying similarities and/or differences in programs traditionally offered by the three campuses. This research was executed over three phases. Phase 1 include a document analyses on the content of all the HRM undergraduate and postgraduate programmes as currently presented by the merged institution. Curriculum data such as yearbooks and subject guides were analysed.. Phase 2 includes interviews with stakeholders (i.e. academics, employers, HRM professional bodies) and Phase 3 surveys (academics, employers and students). This paper reports on the document analyses of the comparison between the programmes under investigation.
4. Findings 4.1 Comparison of the current undergraduate curricula at the merged institution The findings of the analyses are reported next. Tables 1 to 3 display the similarities and differences of the undergraduate curricula as presented on the three campuses per academic year. The analysis of the undergraduate programme for the first year of study is reported in Table 1 below. Table 1: Comparison of undergraduate curricula – first year of study Modules 1 2
3 4 5 6
Campus 1 IOPS111 (Intro to IOPS) HRM 111 (Intro to HRM)
X X X IOPS121 (Ergonomics & OH) HRM 121 (Functions of HRM) X X X X
7 8 9 10 11
Campus 2 IOPS 111 (H) (Intro to IOPS) Labour Relations Management 111 (H) (Intro to Workplace Relations) X X X IOPS 121 (H) (Ergonomics & OH) Z
Campus 3 IOPS111 (Intro to IOPS) Labour Relations Management 111 (Intro to Workplace Relations)
X X X X
X X X X
X X X IOPS121 (Ergonomics & OH) Z
X indicates similarities in modules across the three campuses Z indicates similarities modules between Campuses 2 and 3 The findings in Table 1 show that the modules presented over the three campuses are mostly similar in the first year of study. There are no differences in the modules presented on Campuses 2 and 3. Campus 1 presents Human Resource Management whereas the other two campuses focus on Labour Relations Management in the first semester and Psychology in the second semester. Campus 1 presents a basic introduction to HRM and the functions thereof. The findings of the analysis of the undergraduate programme for the second year of study are reported in Table 2 below. Table 2: Undergraduate curricula – second year of study Modules 1
3
Campus 2 IOPS 211 (H) Personnel Psychology Labour Relations Management 211 (H) Occupational Management Z
4 5
X
Z X
2
Campus 1 IOPS212 (Consumer Psyc) HRM 211 (Training and Development)
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Campus 3 IOPS 211 (H) Personnel Psychology Labour Relations Management 211 (H) Occupational Management Z Z X
Nicolene Barkhuizen Modules 6 7 8
9 10 11 12
Campus 1 Y IOPS221 (Career Psyc) HRM 221 (Performance Management and Rewards) X Y Y
Campus 2 IOPS221 (H) (Occupational Psyc) Labour Relations Management 221 (H) (Work Group Dynamics) Z X
Campus 3 Y IOPS221 (H) (Occupational Psyc) Labour Relations Management 221 (H) (Work Group Dynamics) Z X Y Y
X indicates similarities in modules across the three Campuses Y indicates similarities in modules between Campus 1 and 3 Z indicates similarities modules between Campuses 2 and 3 The findings in Table 2 showed that the modules presented on Campus 2 and 3 in the second year are mostly similar. Again there are significant differences between the modules offered on Campus 1 compared with other two campuses. Campus 1 is the only campus offering Human Resource Management whereas the other two campuses are presenting Labour Relations Management. Campus 1 presents Training and Development and Performance Management and Rewards Management as key HRM functions. The findings of the analysis of the undergraduate programme for the third year and final year of study are reported in Table 3 below. Table 3: Undergraduate curricula – third year of study Modules 1 2
3 4 5 6 7
8 9 10
Campus 1 IOPS311 (Organisational Psyc.) Human Resource Management 311 (Employee Relations) X
Campus 2 IOPS 311 (H) Organisation Psychology Labour Relations Management 311 (H) Theory & Practice of LR X
Campus 3 IOPS 311 (H) Organisation Psychology Labour Relations Management 311 (H) Theory & Practice of LR X
X IOPS321 (Psyc & Research Meth) Human Resource Management 321 (Stragic Human Resource Management) D D
Z X IOPS321 (H) (Psyc & Research Meth) Labour Relations Management 322 **
Z X IOPS321 (H) (Psyc & Research Meth) Labour Relations Management 322 **
D LARM321 (H) Z
D LARM321 (H) Z
X indicates similarities in modules across the three Campuses Y indicates similarities in modules between Campus 1 and 3 Z indicates similarities modules between Campuses 2 and 3 The findings in Table 3 showed that the modules presented on Campus 2 and 3 in the second year are mostly similar. Again there are significant differences between the modules offered on Campus 1 compared with the rest of the campuses. Campus 1 is the only campus offering Human Resource Management whereas the other two campuses are presenting Labour Relations Management. Campus 1 presents an Introduction to Labour Relations Management as well as module of Strategic Human Resource Management. Table 4 below presents a summary of the results in Table 1 to 3. The results in Table 4 show that in general there are significant differences in the module offerings of Campus 1 compared with Campus 2 and 3. The module contents of the Campus 2 and 3 are more aligned. Campus 1 is the only campus that focuses on HRM for all three academic years. Campus 2 and 3 only includes on introductory module on HRM in the second year of study. Furthermore campuses 2 and 3 focus more on
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Nicolene Barkhuizen Labour Relations Management on all three year levels whereas Campus 1 only presents one module Labour Relations Management on third year level. Table 4: Comparison of the results of the analyses of the undergraduate curriculum Year 1 Year 2 Year 3
Comparison Campuses 1 and 2 % % Similarities Differences 85% 15% 33% 67% 30% 70%
Comparison Campuses 1 and 3 % % Similarities Differences 85% 15% 58% 42% 30% 70%
Comparison Campuses 2 and 3 % % Similarities Differences 100% 0 75% 25% 90% 10%
The results of the analyses also showed that none of the three campuses offer work integrated learning as part of the undergraduate curricula. The results also revealed a lack of soft skills and technical skill training as part of the undergraduate curricula. Finally the results showed that Campus 1 to some extent comply with the theoretical part of the competencies required from the SABPP but not the practical part. Campuses 2 and 3 comply with the requirements of the SABPP as far as competence in employment relations is concerned.
4.2 Comparison between other South African Higher Education Institutions The results of the comparative analyses between the seven HEIs showed the following:
Less than half of the HEIs that were involved in the analyses offer separate undergraduate qualifications in Human Resource Management and Industrial Psychology.
Two of the HEIs offered Industrial Psychology and Human Resource Management as one qualification.
One of the HEIs in the sample offers an undergraduate qualification in Human Resource Management, but 80% of the modules include contents relating to the field of Industrial Psychology.
Four of the HEIs included in the analyses present modules with HRM content but label it as Industrial Psychology Modules.
The analyses also showed that there is a discrepancy in terms of the type of modules offered per year of study at the different Higher Education Institutions.
Most of the HEIs investigated offered commerce modules such as such as Business Management, Economics, Stats, Accounting, Computer Literacy, and Law are a common trend in the Commerce qualifications.
Interestingly however most of the HEIs do not focus or address contemporary HRM issues such as Talent Management, Diversity Management, Organisational Behaviour, Remuneration Management, Organisational Development and Change Management, Strategic HRM as part of their programme offerings.
5. Discussion Human Resource Management is a profession in rapid transition. This means that we need to take stock of what we teach our students in order to prepare them adequately for the workplace. The main focus of this research was to investigate the similarities and differences in the undergraduate curricula as presented in a merged institution and whether the current programme offerings are relevant to workplace requirements. From the results it is evident that the undergraduate programmes as currently being presented on the three campuses are about 80% the same in content in the first year of study. The results further indicated indicate that there are major differences in the programme as students’ progress to their second and third year of study. This is problematic as it first becomes challenging to align the programme across the three campuses which is a requirement of the Department of Higher Education and Training (Muller, 2008). Secondly students are unable to move between the three campuses in terms of studying Human Resource Management. Campus 1 is the only campus that includes Human Resource Management as part of its curriculum across all three academic years whereas the other two campuses seem to focus more on Employment Relations. This is limiting the students on Campuses 2 and 3 in terms of pursuing a further professional career in Human Resource Management as they have limited exposure to the basic principles of Human Resource Management.
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Nicolene Barkhuizen Likewise the students on Campus 1 are limited in terms of their career progress in Labour Relations Management. The results further showed that there is limited consistency in undergraduate curricula offerings in HRM as offered by other Higher Education Institutions in South Africa. As with the curricula in the merged institution other universities also seem to include Industrial Psychology as an integral part of the Human Resource Management Programme (see Rothmann & Cilliers, 2007; Schreuder & Coetzee, 2010). This in turn can lead to an identity crisis for both HRM Practitioners and Industrial Psychologists relating to their envisaged roles in the workplace. The results further showed a the lack of more strategic HRM modules such as Diversity Management, Remuneration Management, Organisational Development and Change Management in most of the undergraduate curricula of the South African Higher Education Institutions under investigation. This is in contrast with some of the basic workplace competencies as highlighted by the SABPP (Meyer, 2012). One can argue that most HEIs may reserve these modules for postgraduate qualifications. However, it is important to note that very few undergraduate students pursue a postgraduate qualification in HRM. As a result employment opportunities are limited for HR undergraduate students as they do not meet workplace requirements. Campus 1 focuses to a limited degree on some of the modules that are highlighted as part of the competency model of the SABPP. The results further showed that none of the three campuses have a work‐based component as part of the undergraduate programme offerings. This is in contrast with the requirements of the Department of Higher Education (CHE, 2011). The findings of this research provided valuable inputs into curriculum redesign and alignment in a merged institution as well as the different South African HEIs. In addition, the findings of this research also contribute to the development of HRM programmes that are more aligned with employer needs. As regards the programme offerings of the current institution it is recommended that Campuses 2 and 3 include HRM Modules on all three levels of the undergraduate programme to provide students with a more thorough foundation to enter postgraduate programmes in HRM. It is also advisable that these Campuses align the curriculum content with the requirements of the SABPP. Moreover it is also recommended that all three campuses introduce a work‐based learning component into the undergraduate curricula to enhance the employability of undergraduate students. This research had some limitations. First the findings of the results cannot be generalised to all South African Higher Education Institutions as only seven institutions were included in the analyses. Secondly this paper was only limited to document analyses. The envisaged research in phases 2 and 3 will allow for a more detailed opinion of the relevant stakeholders on the current curriculum offerings of the three campuses. In conclusion this research showed that there are vast differences not only in the undergraduate curricula in HRM offered at one merged comprehensive institution but also across institutions in South Africa. This is problematic as it can limit student movement to pursue further postgraduate studies at other South African HEIs. In addition, the naming of the HRM programmes as well as the modules can be confusing. For example in the case where modules offered content in Human Resource Management, it was labelled as Industrial Psychology. This contributes to the confusion as to what the roles of Industrial Psychologists and HRM practitioners should be. There should thus be a clearer differentiation between what is offered in Industrial Psychology and what should be offered in Human Resource Management.
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Nicolene Barkhuizen Goddard, K. (2009) “Some observations on higher education in the Humanities in South Africa with special reference to Nelson Mandela Metropolitan University as a post‐merger institution”, South African Journal of Higher Education, Vol 23, No. 2, pp. 293‐308. Griesel, H. and Parker, B (2008) Grappling with youth employability in South Africa. Employment, growth and development initiative, Pretoria: HRSC Press. Heerde, J. and Murphy, B. (2009) Work Integrated Learning: An Annotated Bibliography of published refereed journal articles (2000 – 2008). Higgs, P. and Keevy, J. (2009) “Qualifications frameworks in Africa: A critical reflection”, South African Journal of Higher Education, Vol 23, No. 4, pp. 690–702. Knowledge Resources (2011) National HR Survey. Pretoria. Lalla, V. (2009) The impact of the Merger on the Employees of Tswane University of Technology, Unpublished Masters Thesis, University of Pretoria. Maila, M. W. (2012) “Re‐thinking complex, fluid and contradictory knowledge(s) in higher education”, South African Journal of Higher Education, Vol 26, No. 6, pp 1159–1169. Meyer, M. (2012) HR Competency Model. www.sabpp.co.za Meyer, H.M. & Bushney, M. (2008) “Towards a multi‐stakeholder‐driven model for excellence in higher education curriculum development”, South African Journal of Higher Education, Vol 22, No. 6, pp 1229–1240. Muller, J. (2008) In search for coherence: A conceptual guide to curriculum planning for comprehensive universities, Report prepared for the SANTED project, Centre for Education policy development, University of Cape Town, Cape Town. Njozela, D. (2012) “Mental models’ that students possess about Work Integrated Learning (WIL) with reference to the new curriculum framework”, South African Journal of Higher Education, Vol 26, No. 2, pp 249–267. Ntshoe, I. (2012) “Reframing curriculum and pedagogical discourse in universities of technology”, South African Journal of Higher Education, Vol 26, No. 2, pp 198–213. Pop, C.A., and Barkhuizen, E.N. (2010) “The relationship between skills training and retention of graduate interns in a South African Information, communication and technology company”, Literacy Information and Computer Education Journal, Vol 1, No. 2, pp 113‐122. Rothmann, S. and Cilliers, F.v.N. (2007) “Present challenges and critical issues for research in Industrial/Organisational Psychology in South Africa”, South African Journal of Industrial Psychology, Vol 33, No 1, pp 8‐17. Schreuder, D., and Coetzee, M. (2010) “An overview of industrial and organisational psychology research in South Africa: A preliminary study”, SA Journal of Industrial, Vol 36, No 1, pp 1‐11. South African Qualifications Authority (2012) www.regqs.saqa.org.za Ulrich, D. (2011) “Celebrating 50 years: An Anniversary Reflection”, Human Resource Management, Vol 50, No. 1, pp. 3‐7.
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Embedding Knowledge Management in Public Sector Procurement – Redesigning for the Knowledge Economy Denise A. D. Bedford College of Communication and Information, Kent State University, Kent Ohio, USA Dbedfor3@kent.edu Abstract: There is a perception in the public, political and trade discourse that private sector procurement performs “better” than does public sector procurement. This research considers whether this perception is justified. This paper proposes a conceptual framework for assessing Issues that influence procurement performance. The framework takes into account the organization’s business goals, its procurement principles, the design of its procurement capability, the intellectual capital or knowledge that are used to support procurement operations, and the use of knowledge management methods. To represent these factors, the framework adapts the conceptual framework proposed by McElroy (2002), leverages Andriessen’s (2005) characterization of intellectual capital, and adopts Bedford’s (2012) description of the practice of knowledge management. The results, though preliminary and exploratory, suggest that factors which are more often practiced in the private sector than the public sector contribute to higher performance. Keywords: Private sector procurement, public sector procurement, knowledge management, intellectual capital management, procurement life cycle, procurement principles
1. Research context Procurement is defined as the acquisition of goods and services from an external source. Procurement is an enabling activity. Procurement is an essential business capability of all organizations, regardless of whether their financial position is for-, not for- or non-profit. Organizations across all economic sectors procure products and services to fulfill their business goals. It provides day to day institutional support for those business activities that deliver value to the organization’s stakeholders. How well procurement performs may influence how well the organization can deliver to its stakeholders and how well it can achieve its business goals. There is a perception in the public, political and trade discourse that private sector procurement performs “better” than does public sector procurement, and that procurement in the private sector is much easier to perform than it is in the public sector. Is this perception justified? If not, what is the reason for this perception? This research focuses on knowledge management factors that may influence procurement performance in any kind of organization.
1.1 The research questions This paper proposes a conceptual framework as a foundation for assessing factors that might influence procurement performance (Figure 1). The framework takes into account the organization’s business goals, its procurement principles, the design of its procurement capability, the intellectual capital or knowledge that is used to support procurement operations, and the use of knowledge management methods. To represent these factors, the framework adapts the conceptual framework proposed by McElroy (2002), leverages Andriessen’s (2005) characterization of intellectual capital, and adopts Bedford’s (2012) description of the practice of knowledge management. This research explores whether differences in five factors can be associated with variations in procurement performance. The five factors are:
Issue 1: The alignment of the procurement capability with the organization’s business goals
Issue 2: The alignment of procurement principles and business goals
Issue 3: The design of the procurement capability and its alignment with procurement principles
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Denise A. D. Bedford
Issue 4: The extent to which the procurement capabilities leverage appropriate forms of business focused intellectual capital?
Issue 5: The extent to which the procurement capability leverages knowledge management strategies and methods.
The research further considers how we might leverage these factors to improve procurement performance in the future.
1.2 Literature review The literature provides several perspectives on procurement relevant to this research. These citations are illustrative rather than exhaustive. There is extensive treatment of procurement process improvement methods in the literature (Bovis 2010) (Drobrzykowski Hong and Park 2012) (Frodell 2010) (Guth 2010). Many recent authors and practitioners have compared public and private sector procurement methods (Amaral Saussier Yvrande-Billon 2009) (McKenzie and Culliford 2011) (Smith 2011) (Tadelis 2012) (Teng and Liao 2011). While there is little direct discussion of knowledge management in the procurement literature, aspects of knowledge management are addressed, including use of collaboration methods (Allal-Cherif and Maira 2011) (Gunther and Scheibe 2006) (Nakata and Im 2010) (Plane and Green 2011). The influence of culture and ethics in procurement receives attention (Ntayi 2012) (Saini 2010) (Brandmeier and Rupp 2010) (Brandon-Jones Ramsay and Wagner 2010). The value of intellectual capital is treated (Brandmeier and Rupp 2010) (Ordanini and Rubera 2008). The use of smart knowledge technologies is also covered in the procurement literature (Webb 2010). Despite this coverage, there is no conceptual framework for the use of knowledge or knowledge management in procurement.
2. Research methodology The research methodology involves a manual review of six use case scenarios to explore what role the five factors might have played in achieving a positive procurement outcome. We chose six use cases based on a common procurement activity – the selection and acquisition of semantic technologies to meet a business goal. Each of the organizations considered the same set of tools which were available on the commercial market. Each procurement process was unique to the organization. Organizations made different choices and had different procurement and implementation outcomes. Controlling the context allows us to manage other variables and to focus on the five factors.
2.1 Issue 1: Alignment of procurement with organization’s business goals For most organizations, procurement is an enabling capability. This means it provides internal products and services to those business activities that deliver value to stakeholders – to core and operational business activities. As such, procurement should always be aligned with the organization’s business goals. This is the case regardless of whether we are talking about public or private sector procurement. We want to know whether procurement activities that achieve good outcomes have strong alignments with business goals at the organizational level. We want to know whether there are variations in alignment of goals and activities between public and private sector procurement activities. Do public and private sector organizations working in these sectors have common or different goals? Private sector business goals may focus on gaining market share, meeting consumer demands, generating profits, achieving financial goals, meeting shareholder and stakeholder expectations – in short anything related to doing business in the private economy. Public sector goals are to promote competition, support open access to markets, to safeguard the public funds, serve the public good, and uphold the public trust. Exploratory Expectation: Variations in performance may be expected where procurement activities are not well aligned with an organization’s business goals.
2.2 Issue 2: Alignment of public and private sector procurement principles Procurement is guided by governing principles which support and align with business goals. Given the expectation of different business goals, we also expect differences in procurement principles. Public sector
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Denise A. D. Bedford procurement principles derive from legal and regulatory frameworks. They include: accountability, consistency, effectiveness, efficiency, fair dealing, integrity, legality, informed decision-making, responsiveness, and transparency. Public sector principles derive from legal and regulatory sources, and from public policy.. In the past thirty years, the public policy focus on cost efficiency has influenced public sector procurement decisions. The strong public policy focus on low cost rather than high value may be causing a rift in alignment between public sector organizationsâ&#x20AC;&#x2122; business goals and procurement principles.In sharp contrast, there are no legislative or regulatory requirements that govern private sector procurement processes. Private sector procurement principles derive from the business conduct and practices of the organization, and may include accountability, mutual respect, teamwork and integrity. Whereas public policy drives principles for public sector organizations, stakeholders and corporate policies drive private sector procurement principles. Exploratory Expectation: Variations in performance may be expected where there are misalignments between business goals and procurement principles.
2.3 Issue 3: intended design of procurement capability to support business goals The procurement process is essentially the same in private and public sector organizations (Figure 3). However, there may be variations in how procurement activities are carried out within organizations, and how the procurement function is designed to support the organization. Larger organizations may have centralized procurement capabilities, whereas smaller organizations may assign procurement tasks to an individual along with other responsibilities. Some organizations may embed procurement officers within business units to ensure strong support for business needs. Public sector organizations may intentionally separate these activities to reduce a risk of corruption and to ensure transparency. Private sector organizations, though, are more likely to embed procurement officers within business units to ensure procurement decisions do reflect business goals and needs. Private sector procurement officers may have strong subject matter ties to the market, an advantage that those organizations would leverage. Exploratory Expectation: Variations in performance may be observed depending on whether or not the procurement capability is designed to support business.
2.4 Issue 4: use of knowledge in procurement activities Knowledge, in the form of intellectual capital, is a fundamental capital asset for both private and public sector st organizations in the 21 century knowledge economy. Organizations that leverage their intellectual capital work smarter than those that see their intellectual capital as billets or salary expenses. Andreissen (2005) has defined intellectual capital to include human knowledge (tacit knowledge, skills, attitude), structural knowledge (explicit knowledge, procedural knowledge, culture), and relational knowledge (networks, reputation, brand). We suggest there are three types of intellectual capital of value to procurement: (1) subject matter knowledge â&#x20AC;&#x201C; knowledge of the product or service that is being procured, its status in the market, and of procurement sources; (2) knowledge of procurement principles and processes; and (3) knowledge of laws and regulations that govern the procurement process. In the private sector environment, the subject matter knowledge is the most highly valued of the three. Private sector procurement relies on knowledge of markets, players, risks, quality of products, and a deep understanding of the nature of the products. Relational capital â&#x20AC;&#x201C; who you know and what they know - is very important in the private sector. Business intelligence and networks are essential. Subject matter experts are more likely to drive the procurement decision. Subject matter experts are more likely to lead a procurement process with procurement personnel supporting the business lead effort. From a business perspective, this represents higher procurement performance. In the public sector environment, all three types of knowledge are valuable. Given the public policy influence and the regulatory environment, knowledge of laws and regulations carries high value. Subject matter knowledge may carry a lesser value than in the private sector. A preference for procurement-rather than subject matter expertise may produce suboptimal business decisions, and lead to lower procurement performance. Where the goal is to acquire a product or service at the lowest cost and in the most transparent
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Denise A. D. Bedford manner, the product chosen may not be best aligned with business goal. In the public sector, the procurement office is likely to take the lead, with input provided from subject matter experts. This aligns with principles and procurement activity design. It may not result in an effective procurement result from a business perspective. Exploratory Expectation: Variations in procurement performance may be attributed to greater or use of subject matter expertise and lesser procurement knowledge.
2.5 Issue 5: Use of knowledge in procurement activities For the purpose of this research we adopt Bedfordâ&#x20AC;&#x2122;s (2012) description of the scope of knowledge management practice. As McElroy (2002) suggests, aligning knowledge processes with procurement processes will lead to improved performance. Each step in the procurement life cycle can benefit from knowledge management methods, regardless of the type of organization or the economic sector. Private sector organizations have the flexibility and incentive to integrate these methods into their procurement practice as they are not bound by legal, regulatory and policy constraints. Knowledge management methods are not as widely used in public sector procurement due to preference for cost efficiency over business value. In addition, regulatory compliance processes may be resistant to new methods.
Table 1: Alignment of Knowledge Management Methods and Procurement Life Cycle Procurement Life Cycle Stage
Knowledge management factor
Research Expectation
Business Requirements Analysis
Structural capital management, organizational learning, communities of practice and collaboration, knowledge embedded business, knowledge technologies
Business goal aligned, higher quality requirements, increased business buy-in, fewer failed or siloâ&#x20AC;&#x2122;d procurement efforts
Market & Supplier Research
Organizational learning, relational capital management, communication, organizational learning
Improved understanding of markets, alignment of requirements with solutions
Procurement Strategy Development
Structural capital management, communities of practice and collaboration
Procurement strategy supports rather than drives business needs
Solicitation - Evaluation Process Management
Structural capital management, relational capital management, communities of practice and collaboration, organizational learning, knowledge technologies, knowledge assessment and evaluation
Business driven selection, extensive internal-external learning, best choice for value results, fewer failed implementations
Procurement DecisionContract Negotiation
Structural capital management, organizational communication
Higher business confidence in and satisfaction with decision
Procurement Award
Communities of practice, organizational culture and communication, knowledge embedded business
Higher probability of successful implementation
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Denise A. D. Bedford There may be dependencies between Issues 3 and 5. The ability to leverage knowledge management methods may depend the design of the procurement capability. Exploratory Expectation: Greater use of knowledge management methods may contribute to increased procurement performance.
3. Research data This exploratory research is designed to determine whether these factors can be observed to have an effect on procurement performance. We explored the role these factors might play in six use cases drawn from practical experience. While the use cases do not constitute a reliable sample from which to generalize, they provide insights into the behavior of the five issues. Three use case scenarios represent private sector organizations. Three represent public sector organizations. The use cases represent for profit, non-profit and not for profit organizations. Each has represents different business goals, procurement principles, procurement designs, and approaches to knowledge management. Each use case is summarized below. Use cases are described generically and anonymously.
3.1 Use Case 1. Non-profit large public sector organization Use Case 1 represents procurement in a large non-profit public sector organization. This organization has more than 200 years of information in archival preservation. For this organization the procurement of semantic technologies could support effective access to millions of historical records. The procurement goal was to acquire the most effective solution at the most affordable price. To achieve this goal, the agency brought in a team of information management experts and put the procurement requirements and evaluation tasks in their hands. Although this agency is in the public sector, this division clearly operates in a businessoriented manner. The procurement experts were supportive but did not run or dominate the procurement process. In addition, the business team was well trained in procurement rules and guidelines and were able to build those considerations into the lifecycle without sacrificing business knowledge or expertise. This organization made good use of knowledge management methods, including participation in and leveraging knowledge of communities of practice. The organization reviewed the technology market, consulted with communities of practice and user groups for different technologies prior to formulating requirements, and considered the knowledge architecture implications of different choices. The organizational learning was initially constrained due to heavy reliance on a published industry review of commercial products. This constraint was overcome by the use of external subject matter expertise. The fact that the business team demonstrated a strong knowledge of the market, and had strong knowledge of and respect for the procurement process helped them to gain the trust of both management and procurement. As a result, they were able to lead the procurement effort and ensure an successful result.
3.2 Use Case 2. Large non-profit public sector academic organization Case Study 2 represents a procurement action in a large non-profit academic environment. This organization sought a solution to support cross-organization digital archiving and business-oriented access to historical and current records. The organization has very well designed administrative business process. Records management for selected processes was well managed according to professional disciplines (e.g. financial data management, human resource management, etc.) but there was not a single enterprise solution supporting robust access to archived records. The organization has a tradition of independent decision making and independent and uncoordinated procurement activities. This is an enterprise level solution, but individual business managers need to buy into and adopt the solution to support their unitâ&#x20AC;&#x2122;s work. Enterprise level goals are formulated at the highest level of the administration and adopted by business units. Defining business goals bottom-up and through consensus building methods is challenging due to the organizational culture of independence. In this case, business goals for the procurement were based on the needs of the business critical units. In this case, external consultants and faculty members with relevant expertise were called in to advise the enterprise and business critical unit managers. Enterprise level requirements had to take precedence in order to satisfy the universityâ&#x20AC;&#x2122;s goals for cross-organizational support and access. The enteprirse level manager driving the procurement was well versed in procurement methods and policies and was able to ensure they were integrated into the requirements and selection process. Because business drove the process, an effective decision was made. It was very important, though, to bring in external expertise on
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Denise A. D. Bedford the state of the market. The implementation was effective in meeting the enterprise goals even if it might not meet the needs of all business units.
3.3 Use Case 3. For-profit small private organization Use Case 3 represents a complex but low budget procurement action in a medium sized not for profit organization that is operating within increasing budget constraints. The organization’s primary stakeholders are medical professionals and secondary stakeholders are the general public. The procurement action was undertaken by one small unit whose primary role was to manage the organization’s information. This use case focuses improving access to a collection of historical publications. The business unit was responsible for setting business goals. Procurement principles were established at the organization level. However, the overall low budget for the project supported a simple procurement process. This use case was interesting because it involved multiple in depth consultations with academic experts, and a strong working relationship with a selected vendor. The internal subject matter expertise was pertained to the content of the historical collection, not to procurement. There was a broad opportunity and strong incentives to leverage knowledge management methods. The business team solicited subject matter expertise throughout the project. A small private company can ill afford to make a bad decision. Resources are much more scarce in this size of an organization than in larger organizations. There is a smaller baseline against which to recover from a bad decision. The incentive to go with a “safe” procurement decision is strong. This organization crafted a procurement approach to achieve an affordable and effective procurement decision. The business unit drove the procurement decision, though the organization managed the procurement process. The process was ideally suited to the context because the “seller” and the “buyer” were able to work closely to define a solution that met the buyer’s expectations. The result has been successful on several levels. Not only did the deliverable meet expectations, but both parties were able to learn through the process. Both the buyer and the seller expanded their capacity to work in this area. The seller has had an opportunity to expand the performance of their products. The buyer has had an opportunity to share experience with other small and medium-sized organizations. In this case it was very important for the business units to be in control of the procurement decision, and to have the flexibility to refine requirements as the project moved forward.
3.4
Use Case 4. Not for Profit Public Sector Organization
Use case 4 represents a formal procurement effort to acquire semantic technologies to support the consistent generation of metadata across the organization. For this organization transparency and fair process are critical to maintaining its international reputation. While an overall matrix of weighted factors determined the final selection, financial considerations were heavily weighted. This use case represents a traditional public sector procurement design and illustrates traditional procurement roles. The organization had internal subject matter experts who defined the business requirements and assembled the team of stakeholders who would evaluate proposals and make a recommendation to the procurement office. A bottom-up business requirement and recommendation process worked well for both selection and for implementation. Had there not been subject matter experts involved in defining the business requirements and had those requirements not reflected knowledge of the market, there would have been a different result. Because the process allowed stakeholders to be involved in the decision making process, there was widespread adoption of the solution in the implementation phase. Because there were internal experts in semantic technologies, there was strong knowledge of the market. The procurement experts managed all communication with external stakeholders and providers. Ultimately, procurement made the procurement decision but it was in line with the recommendations of the business units. In the end, the selection supported business goals because the subject matter experts defined the requirements. In the end, the implementation was successful and there was broad adoption of the solution. Because the procurement process is tightly scripted, as is the case in most public sector organizations, it was not possible to leverage many knowledge management methods.
3.4 Use Case 5. Large global for-profit private sector organization Use Case 5 represents a large, global, for-profit organization. This organization competes in a global product market, provides products and service around the world, has sales offices in most countries. Operates in multiple legal and commercial jurisdictions. Its primary business goals are profit, market share, product quality
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Denise A. D. Bedford and assurance. The organization is interested in achieving best value for the dollar. For this organization, the procurement of semantic technologies would support enterprise level access to content stored in multiple repositories. Relevant subject matter expertise includes several hard and applied scientific disciplines. While there is extensive expertise in the core business areas, internal subject matter expertise on semantic methods and technologies is scarce. While procurement may be driven by business units and subject matter experts, the organization does not have the needed expertise to make an effective decision. In this case, the organization wisely leveraged knowledge management methods to obtain external subject matter expertise. Extensive internal consultations were conducted to understand the semantic needs and practices of the critical business units. External consultations drew in a broad set of viewpoints, including vendors and current users of the technologies. For this procurement to be successful, though, it must be usable in several business contexts. The procurement process must allow for extensive stakeholder involvement and signoff, and a learning context similar to that described in Use Case 2.
3.5 Use Case 6. Quasi- for and not for profit global private sector organization This organization is a not for profit organization which serves the private sector. To better support its private sector stakeholders, this organization often adopts private sector methods of working. While this is a not-forprofit organization, profit or at least lowest cost solution is an important business goal. The organization also values its networks and maintains its knowledge of the market through its network contacts. This may or may not provide an accurate picture of the market. If there is no validation of network-acquired product information, the selection may not be optimal. The organization has a low tolerance for solutions that take more than six months to implement, and prefers solutions that are sufficient rather than robust. The business goals by definition will result in a different kind of decision than we have seen in the other five use cases. While a procurement team is in place, business units drive the procurement process and make the procurement decision. Given the time-sensitiTTvity of business decisions, broad input and consultation are generally not sought. Knowledge management methods are not typically leveraged to improve the procurement decision. This organization considered semantic technologies as a quick solution for cross enterprise access to information. In this case the business experts driving the program did not prepare a robust set of business requirements to drive the procurement process. Because the procurement process was driven by business managers, the procurement decision was ineffective. In the end, the solution implemented was not successful. In the end the use of financial resources did not support business goals. In this case, procurement was a weak function and the business unit did not fill the gap.
4. Influence of issues on procurement results Keeping in mind that this is exploratory work intended to set a foundation for a larger research effort, we offer observations about the influence of the five factors on procurement results. A summary of the role of the five factors in each use case is provided in Tables 2a-2b. Four of the six use case scenarios resulted in effective procurements and effective choices. What these use case scenarios had in common are the alignment of procurement capabilities with business goals (Issue 2), design of procurement capabilities to support business goals (Issue 3), and the dominant use and reliance on business-subject matter expertise (Issue 4).
Table 2a: Observations of role of Issues by Use Case No.
Sector
Issue 1
Issue 2
Issue 3
1
Public Sector
Department level
No explicit procurement principles
Segregated from business units
2
Public Sector
No alignment
Enterprise level principles; not tied to goals
No standard design, integrated into business units
3
Private Sector
Company level
Fully aligned with business goals
Tasked to one person, aligned with goals and
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Denise A. D. Bedford No.
Sector
Issue 1
Issue 2
Issue 3 principles
4
Public Sector
Company and Division Level
Enterprise level principles not tied to goals
Strictly defined at enterprise level, procurement lead activities at certain dollar level
5
Private Sector
Company and Division Level
Fully aligned with business goals
Driven by business needs integrated with business unit level
6
Private Sector
Organization and Division Level
Fully aligned with business goals
Driven by business needs integrated with business unit level
Table 2b: Observations of role of issues by Use Case No.
Issue 4
Issue 5
Result
1
Procurement knowledge prevails; SME is solicited
Some use in later stages of life cycle
Effective and efficient procurement, effective choice
2
SME knowledge drives but is internal to organization
Some use in later stages of life cycle
Effective procurement, effective choice
3
Pulled through external network, focused on subject matter expertise
Extensive use throughout the life cycle
Effective procurement, effective choice
4
Subject Matter Expertise leveraged; Final decision made by procurement
Little use throughout the procurement process
Effective procurement, ineffective
5
Subject Matter Expertise leveraged; External expertise leveraged
Extensive use throughout the lifecycle
Effective procurement, Effective choice
6
Subject Matter Expertise predominates; External expertise heavily used
Moderate use throughout the life cycle
Ineffective procurement, ineffective choice
Issue 1. Alignment with Business Goals Business goals are critical for a successful procurement result. We can only judge the goodness of a procurement decision by how well it aligns with an organization’s business goals. Our experience in this limited set of use cases suggests that where the procurement is not aligned – formally or informally – with business goals, there is a lower probability of success. The base of use cases must be expanded to
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Denise A. D. Bedford include a broader range of products and services, and greater variation in the business areas supported by the procurements. Issue 2: Procurement Principles. Where principles are grounded in regulatory and legal issues, there is not strong alignment with business goals. While it is important to align with regulatory and legal issues in the public sector organization, these do not have to be driving forces. Every public sector organization has a business mission which should be reflected in its procurement principles. Our observation from the limited number of case studies is that public policy priorities have constrained public sector procurement principles. This is a way of working that has developed in response to public policy pressures. It is not an absolute constraint for public sector procurement. It is possible to balance public sector business goals and procurement principles. This alignment sets the stage for procurement designs, use of knowledge and knowledge management methods. Expanded future research must also include greater variation in size of organizations and value of the procurement decision. Issue 3: Procurement Capability Design. Where procurement principles are dominant and outweigh business goals, there may be a tendency to segregated procurement activities, and to routinize the process. Flexibility st of process design and location supports the 21 century business need for agility and results in positive outcomes. Embedding procurement in business operations seems to align with positive outcomes. Where procurement is readily and easily available to business units, business can drive the design and placement of procurement capabilities. Issue 4: Use of Knowledge. The role of subject matter knowledge appears to be very important to achieving positive procurement outcomes. When subject matter expertise is not available internal to the organization, the organization should make every effort to acquire it externally. Externally sought advice should be solicited within the context of business goals, not simply knowledge of markets. While it is important to ensure that procurement knowledge is accessible to every procurement effort, this does not mean that procurement officials must manage or control the effort. This also suggests an opportunity to rethink how we package and make procurement knowledge available. Procurement knowledge may be transformed into knowledge bases through semantic analysis and supported by role-based and problem-oriented searching. Procurement managers must respect the knowledge of subject matter experts. Issue 5. Use of Knowledge Management Methods. This was a very limited set of use cases from which generalizations cannot be made. And, there are inherent restrictions to how knowledge management methods may be used in the formal procurement portion of the process. However, we can draw observations from the use cases which suggests that where knowledge management methods are built into the requirements portion of the process, a stronger and more effective choice will be made.
5. Research results and observations The results, though preliminary and exploratory, do not support the perception that private procurement, by definition, performs at a higher level than does public sector procurement. The results would tend to suggest that it is not the private or public sector nature of organizations, nor is it the for-, not-for or non-profit status that leads to successful procurement. Rather, the results suggest that procurement performance will be greater where Issues 2, 3, ad 4 are observed in an organization. It appears to be the case that these factors are more often observed in private than in public sector organizations. Three of the private sector organizations and one public sector organization which exhibited these characteristics reported positive procurement outcomes. Two public sector organizations did not demonstrate these characteristics and did not achieve an effective outcome. Observations for these three factors are summarized below. In this limited research there was not sufficient evidence of the use of knowledge management methods within the procurement life cycle to draw any conclusions about their effect on procurement performance. However, we have learned enough about the interplay of issues to begin an open conversation with procurement actors across the world. The results of this exploratory research are a broad based survey on the role of these five issues in successful procurements.
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Denise A. D. Bedford Further investigation into each of these three issues is needed to develop a deeper understanding of their role in achieving effective and efficient procurement results. The next step in this research effort will be to extend the research to a larger set of organizations to expand the representation of types of organizations, to extend the case studies to represent a broader range of procurement activities, and to deepen the review of knowledge management methods in each case. We believe that further research based on these exploratory observations may psuggest best practice approaches for procurement design.
References Allal-Cherif, O. and Maira, S. (2011). “Collaboration as an Anti-Crisis Solution: the Role of the Procurement Function,” International Journal of Physical Distribution & Logistics Management Vol. 41, No. 9, 860-877. Amaral, M., Saussier, S. and Yvrande-Billon, A. (2009). “Auction Procedures and Competition in Public Services: The Case of Urban Public Transport in France and London,” Utilities Policy Vol. 17, 166-175. Andriessen, D. (2005). “Making Profit from Intellectual Capital,” Intellectual Capital Conference, Jakarta, March 8, 2005. Bovis, C. (2010). “Public-Private Partnerships in the 21st Century,” ERA Forum Vol. 11, 379-398. Brandmeier, R.A. and Rupp, F. (2010). “Benchmarking Procurement Functions: Causes for Superior Performance,” Benchmarking: An International Journal Vol. 17, No. 1, 5-26. Brandon-Jones, A., Ramsay, J., and Wagner, B. (2010). “Trading Interactions: Supplier Empathy, Consensus and Bias,” International Journal of Operations & Production Management Vol. 30, No. 5, 453-487. Drobrzykowski, D. D., Hong, P.C. and Park, J.S. (2012). “Building procurement capability for firm performance:a servicedominant logic view,” Benchmarking: An International Journal Vol. 19, No. 4/5, 567-584. Frodell, M. (2010). “Criteria for Achieving Efficient Contractor-Supplier Relations,” Engineering, Construction and Architectural Management Vol. 18, No.4, 381-393. Gunther, E., and Scheibe, L. (2006). “The Hurdle Analysis. A Self-evaluation Tool for Municipalities to Identify, Analyse and Overcome Hurdles to Green Procurement,” Corporate Social Responsibility and Environmental Management Vol. 13, 61-77. Guth, S. (2010). “Implementing Best Practices: The Procurement Maturity Model,” 96th ISM Annual International Supply Management Conference, April 2010. (Accessed online at: http://www.ism.ws/files/Pubs/Proceedings/2010ProcCHGuth.pdf on April 1, 2013). MacKenzie, N. and Culliford, S. (2011). “What Now for Public Sector Procurement?” Business Insights (Accessed online at: http://www.uk.atoscosulting.com/en- uk/business_insights/points_of_view/what_now_for public_sector_ procurement/default.htm on April 1, 2013). McElroy, M. (2002). The New Knowledge Management. Routledge, 2002. Nakata, C. and Im, S. (2010). “Spurring Cross-Functional Integration for Higher New Product Performance: A Group Effectiveness Perspective,” Journal of Product Innovation Management Vol. 27, 554-571. Ntayi, J. M. (2012). “Emotional Outcomes of Ugandan SME Buyer-Supplier Contractual Conflicts,” International Journal of Social Economics Vol. 39, No. ½, 125-141. Ordanini, A. and Rubera, G. (2008). “Strategic Capabilities and Internet Resources in Procurement: A Resource-Based View of B-to-B Buying Process,” International Journal of Operations & Production Management Vol. 28, No. 1, 27-52. Plane, C.V. and Green, A.N. (2011). “Buyer-Supplier Collaboration: The Aim of FM Procurement?” Facilities Vol. 30, No. ¾, 152-163. Saini, A. (2010). “Purchasing Ethics and Inter-Organizational Buyer-Sup;lier Relational Determinants: A Conceptual Framework,” Journal of Business Ethics Vol. 95, 439-455. Smith, G.C. (2011). “Leveraging Private Sector Practices in the Public Sector,” Supply Chain Quarterly 3 2011. (Accessed online at: http:www.supplychinquarterly.com/topics/procurement/201103Public/ on April 1, 2013) Tadelis, S. (2012). “Public Procurement Design: Lessons from the Private Sector,” International Journal of industrial Organization Vol. 30, 297-302. Teng, W. and Liao, T.-T. (2011). “Exploration of Market Competition in Governmental Procurement on the Basis of Supplier Segments,” Systems Engineering Procedia Vol. 2, 406-411. Thompson, M. (1996). ”Effective purchasing strategy: the Untapped Source of Competitiveness,” Supply Chain Management Vol. 1, No. 3, 6-8. Webb, J. (2010). “Private Sector Procurement Expertise Can Lower Government Spend,” (Accessed online at: http://www.procurement-iu.com/blog/2010/7/private_sector_procurement_expertise_can _lower_government_spend on April 1, 2013).
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Topology of Knowledge and Information in the Transportation Sector Denise A. D. Bedford1 and Lisa Loyo2 1 Goodyear Professor of Knowledge Management, Kent State University, Kent Ohio 2 Manager, Information Services, Transportation Research Board, National Academy of Sciences, Washington DC Dbedfor3@kent.edu lloyo@nas.edu
Abstract: Transportation is an important economic sector, a professional area of practice and a robust academic discipline. The knowledge and information that is produced and consumed in transportation comes from research, from development, teaching and learning, and everyday practice. Transportation is also a multifaceted discipline â&#x20AC;&#x201C; drawing from engineering, chemistry, physics, materials science, computer science, finance, policy development, project management, etc. Transportation has legislative, regulatory and policy implications at the international, national, state and local level. The transportation information environment is complex, reflecting these facets, levels and perspectives. Managing, finding, accessing and preserving transportation information is a challenge. This research explores the full landscape of transportation information, including informal primary, primary, secondary and tertiary information. This research leverages a methodology developed for the Library of Congress to produce a richly populated topology of knowledge and information produced and consumed in the transport discipline. The topology provides a comprehensive framework that can be used by knowledge and information managers working in transport for strategic planning, and for the development of tools to support multifaceted access to knowledge and information in the field. Keywords: Information topologies; transportation information; information types; information scatter; information organization; knowledge management
1. Research challenge and goal Transportation is a complex discipline. The discipline is broad in its coverage of modes of transportation, including air, rail, road, water, cable, and space. It has a broad scope in terms of the aspects in which it interacts with society, including (1) transportation policy analysis, formulation and evaluation; (2) transportation planning; (3) interaction with the political, socioeconomic and physical environment; (4) transportation infrastructure finance, ownership and access; (5) design, management and evaluation of transportation systems; (6) constituencies and stakeholders; and (7) regulatory systems). The project life cycle introduces new stakeholders, new roles and new types of information that are not traditionally managed by libraries and information centers. The international, national, regional, state and local aspect of its implementation also contributes to its broad scope. The discipline is deep in terms of the range of activities performed by transportation stakeholders. Consider, for example, the tasks involved in two important transportation life cycles â&#x20AC;&#x201C; the transportation research life cycle, and the transportation project life cycle. The simple representation of the two life cycles (Figure 1) illustrates the richness of the transportation information environment. Research, project planning, construction, maintenance and operations give rise to many roles, many different areas of expertise, and many types of impacts. The transportation project life cycle has a long path from ideation to research to implementation, and ultimately to impacts on peoplesâ&#x20AC;&#x2122; everyday lives. There are many stakeholders involved in both of these life cycles. The environment in which transportation information is produced, consumed and managed is complex. Managing transportation information is not a trivial task, though (Baldwin 2007) (Borin and Hua 2008) (Cambridge Systematics 2013) (Corbin 2007) (CTC & Associates 2006) (Dresley 1998) (Evans 2007) (Harder and Tucker 2003) (Ingbar 2010) (Lefchik Beach and Holt 2007) (MacDonald 2007) (Oman 2007) (Osif 2000). st Transportation information professionals face a new challenge in the 21 century. The challenge in 2013 to define a methodology that leverages but adapts the traditional information management methods to apply to st information needs in the 21 century. Technology now makes it possible for everyone working in the discipline of transportation to create, find, use and manage data and information before it reaches the traditional primary published state. Informal primary information represents all of the original ideas, data, source th information that a stakeholder might use to do their work. In the 20 century, this type of information would not have been in the purview of the professional information management professional. Informal primary information in the discipline of transportation might include data collected by the geologist evaluating a site,
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Denise A. D. Bedford and Lisa Loyo crash site information captured by first responders or law enforcement, traffic engineer, the coast guard personnel patrolling shorelines, the railroad engineer collecting data about track quality, traffic flow and congestion data recorded by traffic controller, or air traffic control and monitoring data. What was traditionally considered purely informal information may now be accessible to peers, research or work teams, or even publicly available on the Web. Who manages this traditionally informal information is changing. The owners and creators of informal primary information are now de facto information managers. Before transportation information professionals can take up this new challenge, though, they need to have a “big picture” of today’s transportation information landscape. This research paper takes up that challenge. Transportation Research Life Cycle
Transportation Project Life Cycle
Figure 1: Two Life Cycles of Import to Transportation
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Denise A. D. Bedford and Lisa Loyo
2. Research methodology This research builds leverages innovative work completed under contract for the Library of Congress (Carroll Bedford Jones 1991). The intent of that innovative work was to lay the foundation for services that might be provided by a national digital library that would support undergraduate science, technology, mathematics and engineering (NENGIS) (National Research Council 1998). It was important to understand the information landscape in order to develop a picture of these services. Like any library, the proposal began with collection development and management policies. An extensive search was conducted for a model, a methodology and/or a well defined landscape of the field of science, technology, engineering and mathematics information types and sources. No existing models, methods or landscapes were found. To fill this need, a comprehensive review of the formal and informal information sources serving the field, a methodology was developed and validated within the scientific, engineering, and information science communities. A five-step methodology was proposed based on well-established collection development policy methods used in academic and research libraries (Baughman 1977) (Baldwin 1973) (Ferguson Grant and Rutstein 1988) (Munroe 2004) (White 2008). It was important to begin with a methodology that would align with the Library of Congress’ approach to collection development and management. The five steps in the methodology included: (1) identification of stakeholders and roles that involved the production or consumption of information; (2) high level framework for categorizing information types; (3) defining breakout categories of information by types of systems that may support them; (4) elaboration of brand name types and sources for each category; and (5) validation of the topology with stakeholders; and (5) extensive validation of the structure through consultation with stakeholders. Step 1. Collection development methods begin with a description of stakeholders and their information needs. The original research team conducted extensive interviews with scientists and engineers at the national level to develop the stakeholder framework (Step 1). The interviews provided valuable input to the coverage and structure of the information topology. The new methodology was an extension of the tradition in that it focused on what stakeholders produced as well as what they consumed. It also considered how and where stakeholders stored and accessed the information they produced. This extension leads to the creation of a new layer in the traditional model. Step 2. It was apparent to the research team and through interviews as early as 1991 that it would be necessary to expand the traditional library collection development model’s characterization of three layers of st information (Figure 2 – Traditional Model) to include a fourth layer - informal primary types (Figure 2 – 21 Century Model). Primary information includes original materials – materials that contain raw, original or unevaluated information. Primary sources have not been formally or officially filtered through interpretation, condensation, or evaluation by a second party. Primary information traditionally has included journal articles, books, reports, patents, theses, diaries, letter, photographs, and so on. Secondary information is information about primary information which has been modified, extracted, or rearranged for a particular audience or purpose. Secondary information sources might include biographies, histories, reviews, textbooks, indexes or bibliographies. Tertiary information is a distillation or collection of information, for example encyclopedias, almanacs, guidebooks, handbooks, abstracting and indexing services or sources. This was an important discovery in 1991 for information professionals who were trying to adapt collection development policies to the new environment. However, this expansion introduced many new collection and management challenges. In an invited paper Lynch (1998) identifies some of these challenges, including ownership, quality, discoverability, access and persistence. The observation continues to be important today, and particularly so for the field of transportation. Step 3. The Library of Congress project team identified 25 categories of information sources to support the lower level framework. These categories are identified in Tables 1 through 4.
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Denise A. D. Bedford and Lisa Loyo st
Traditional Model
21 Century Model
Figure 2: Models of Information Types Table 1: Informal Primary - Functional Category Breakdown and Descriptions Functional Category R&D Informal Records Research Data Policy Decision Systems Authoring & Composition
Description Personal records systems, Interpersonal communication systems, Group communication systems, Administrative systems, Informational announcement systems. Experimental data acquisitions systems, Observational data acquisition systems, Computation science results, Research planning Policy formulation, Policy discussion, Policy analysis Data organization systems, Manuscript development systems, selection and review systems
Table 2: Formal Primary - Functional Category Breakdown and Descriptions Functional Category Preliminary Communication Publishing Group Communication R&D Management Statistical Information Stakeholder & Market Information Product Information Policy & Legal Information Infrastructure Information
Description Preliminary formal reporting, Preliminary formal discussion Serials, Dissertations and theses, Research publications, Monographic publications, Conferences and meetings, Workshop and seminars, Trade shows and exhibits, Partnership programs Research proposals, Ongoing research and contracts information, Research financial information, Organizational research information, Proprietary information systems, Organizational records systems Demographic information, Resource data Survey research, Communications research, Professional statistics Manufacturer information, Production and maintenance information, Engineering and process design information, Engineer and process control information, Engineering and process data Legislative and policy information, regulatory information, Monitoring and compliance information Infrastructure status and condition information, Infrastructure planning information, Infrastructure finance information, Infrastructure economic models and information, Infrastructure communications, Infrastructure reports,
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Denise A. D. Bedford and Lisa Loyo Intellectual Property Information Compatibility Information Education & Training Information
Patent information, Trademarks, Copyright applications, Copyright registries, Domestic patents, Foreign patents Proprietary standards, De facto standards, Industry standards, National standards, International standards, Product specifications, Construction specifications Educational materials, Lectures, Education awareness information
Table 3: Formal Second - Functional Category Breakdown and Descriptions Compilation Systems Surrogation Systems Analysis & Evaluation Delivery Systems Technology Transfer Secondary Market Research Customized Information Systems
Biographical information, Historical information, Ready reference, Directories, Inventories, Formal instructional information, Bibliographic systems, Scientific metadata, Library catalogs, Search systems, Vocabulary systems, Knowledge organization systems Peer review information, Evaluated scientific data, Evaluative communication systems, Synopsis and reporting information Online bookstores, Interlibrary lending/borrowing systems, Information brokers and subscription services Technology descriptions, Transfer experiences, Transfer investigations, Translation information Market research, Market surveys, Reference centers, Search strategies, Canned Queries, Reference Q&A, FAQs, Executive information, Corporate management information
Table 4: Formal Tertiary - Functional Category Breakdown and Descriptions Secondary Compilation Sources Secondary Surrogation Systems Archiving Systems
Current awareness information, Update services, SDI services Information referral, Management information systems Document preservation, Records management, Artifact preservation
Step 4. The research team then populated the framework with references to individual and brand name sources for scientific and engineering disciplines generally. Step 5. Finally, the methodology and the topology were further validated through focus groups held at the National Institutes of Standards and Technology in 1991. In 1997, the methodology was put through a further test at the University of Southern California where it anchored initial brainstorming for a digital science and engineering library.
3. Research results In this paper, the Kent State University and National Academy of Sciences collaborative research team reports on the use of the Library of Congress methodology to develop an information topology for the field of transportation. The research is now in Step 5 – the validation of the framework and topology an open national and international survey.
3.1 Step 1. Identification of transportation information stakeholders An important starting point for the research was understanding the discipline from a stakeholder perspective. The universe of stakeholders helped us to see the full landscape of information sources, products and services. We began with two lists. The first list was a classified list, arranged by the nature of the user’s relationship to transportation (Table 5), including individuals who: Table 5: Transportation Stakeholder Roles Stakeholder Relationship to Transportation Do transportation work Support those who do transportation work Develop transportation policy, finance and planning
Stakeholder Example Train conductors, Air traffic controllers, Port authority officials, Aircraft maintenance teams, Freight engineers, Pilots, Law enforcement… Local government officials, Librarians, Machinery manufacturers, Geologists, Chemists, First responders… Legislators, Local government officials, Policy analysts, Infrastructure economists, Transport economists, Infrastructure banks, Private financial institutions, City planners, Regional economic advisers….
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Denise A. D. Bedford and Lisa Loyo Stakeholder Relationship to Transportation Apply transportation to everyday business and living Teach and learn transportation Study transportation science and transportation policy
Stakeholder Example Rail passengers, Automobile drivers, Truckers, Cyclists, Pedestrians, Flight attendants… Professors, Teachers, Research institutes, Private corporate research, Professional associations, Consultants, Students…. Professional associations, Students, researchers, Policy analysts, Legislators, Regulatory agencies, Inspectors
The second list considered the level of stakeholder scientific or technical expertise. For example, an aeronautical engineer has greater expertise in aeronautics than does a high school science teacher or the general public deciding whether to fly or take a train from New York to Los Angeles. This second perspective helped us understand the different levels of synthesis and interpretation transportation information might take on, and the systems through which it might need to be filtered and accessed. Both of these lists were used to identify types of information that would be produced or consumed in the normal course of a stakeholder’s day.
3.2 Step 2. Build out a high level framework for the topology st
The research team leveraged the expanded model (Figure 2 – 21 Century Model) to include a fourth information type to represent the extended information environment of transportation stakeholders. The extension of the traditional library collection development framework provided a more accurate representation of the types of transportation information produced and consumed by stakeholders today. It also provides a more accurate representation of the degree of originality of transportation information, and of the level of expertise required of users of transportation information.
3.3 Step 3. Define low level category structure The next step in the research process involved identifying the categories of information within each of the four layers. The original structure proposed to the Library of Congress and NENGIS included twenty-five categories organized by types of information systems. The original model was tested for use in the transportation discipline through a rigorous review of the transportation literature, interviews with information professionals, through a rigorous review of sources referenced in transportation research, to transportation policy documents, and everyday references to transportation information.
Figure 4: Transportation Information and Knowledge Topology Functional Category Breakdown The categories were cross-checked against the stakeholder lists (Table 1). . The resulting topology for the transportation discipline validated the original twenty-five categories in the Library of Congress foundation, but added one new category – Infrastructure Information. This new category was added to the Secondary
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Denise A. D. Bedford and Lisa Loyo Information layer. The research team believes that while the category name may vary, the new category will be relevant for all other scientific and technical disciplines. In addition to testing and adapting the categories, the research team expanded the scope of the original descriptions. For example, Commercial Product Information was expanded to include documentation for, maintenance reports and parts information for all forms of transportation machinery (Carroll Bedford and Jones 1991). As Figure 4 suggests, twelve categories – a majority of categories - aligned with Formal Primary Information. Seven of the functional categories represent Secondary Information. Tertiary information has the fewest categories – three. While research to date indicates that Informal Primary includes only four categories, we expect further breakdowns as we complete the validation in Step 5.
3.4 Step 4. Mapping transportation information to the topology The final working version of an information topology should illustrate specific information sources, products and services in each functional category. Ideally, the topology produces an information inventory that information management professionals can use to develop strategic plans for managing transportation information. The research team undertook an extensive review of transportation literature to validate the categories and to begin to build out the full topology. The literature review surfaced 518 examples. The research team was able to map each type to a class without confounding. Table 6 illustrates the distribution of examples across the four high level classes. Functional Category Informal Primary Formal Primary Formal Secondary Formal Tertiary Total Examples
Number of Examples 105 297 80 36 518
Table 6: Distribution of Transportation Information Types Discovered in the Literature Review Examples of formal primary information sources predominated in the transportation research literature. Informal Primary sources were referenced more frequently than either formal secondary or formal tertiary. The researchers expect that the results of the literature review will reflect the use patterns of individual respondents in the open survey. The final survey results will be presented as both a visual representation of the topology and a classified inventory.
3.5 Step 5. Validation and elaboration of the topology with transportation stakeholders While the proposed topology is grounded on a strong precedent, it is important to validate the model with stakeholders from the transportation discipline. To this end, the research team has developed an open survey instrument (http://kentstate.qualtrics.com/SE/?SID=SV_739VBN3O1eCDCAt ). The survey follows the structure of the topology. The survey offers respondents the opportunity to describe the kinds of information they use, the frequency with which they use them, and to provide specific examples. The survey is on-going. The results will be used to further populate the Transportation Information and Knowledge Topology. The final version of the topology will be presented at a future Transportation Research Board Annual Meeting.
4. Findings and observations The exploratory research produced a working framework and a graphical representation of an information topology for the transportation discipline. The topology is comprised of four layers, representing (1) Informal Primary Information; (2) Formal Primary Information; (3) Secondary Information; and (4) Tertiary Information. Twenty-six functional categories were identified across the four layers. The categories were useful for organizing individual and name brand information sources, products and services. The methodology that was developed by Carroll Bedford and Jones in 1992 proved to be robust. This is only the second formal application of the conceptual methodology and framework. The research team believes that the application of the framework and methodology to the transportation discipline provided another rigorous test. The researchers noted that the first step – identification of stakeholders – continues to be a critical step in defining the scope of the topology. The research team plans to test the framework against other science and technology disciplines in the future.
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Denise A. D. Bedford and Lisa Loyo The research team has begun an open and public survey-based validation of results with stakeholders from the transportation discipline. We expect the survey results will provide an extended inventory of specific sources, products and services. We expect the extended inventory to uncover examples that will help us to further elaborate the categories aligned with the Informal Primary layer. One challenge that remains is to provide an easily navigable view of the topology when it is fully populated with individual sources and brand name systems. A fully populated topology includes thousands of references. The current representation of the topology is a wall-sized poster. A digital map of the survey-validated results will be displayed at the ECKM 2013 conference. We believe that the resulting topology provides a comprehensive view of the transportation information landscape. The goal of the research was to develop an information topology that could be used by transportation information professionals to expand the application of information management practices. We believe that the topology will serve this purpose. The full graphic presentation enables an information professional to identify functional categories of value to his/her stakeholders, to define policies and methods that are suited to his/her stakeholders’ specific sources, products and services. In the future, we believe that transportation information professionals will use the topology to scope the services that might be supported by transportation libraries. Our hope is that the topology will help transportation information professionals to meet the challenge. Ultimately, we hope the topology will enable stakeholders in the discipline to develop a common understanding and mental model of the information landscape.
References Baldwin, C. A. (1973). Library use by civil engineers at the Minnesota department of highways. University of Minnesota, 1973. Baldwin, J. C. (2007). “Making Information Accessible: Beyond the Internet" TRB 86th Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.dot.state.mn.us/library/PDF/TRB-2007-Baldwin-Final.pdf Bullis, D. R. and Smith, L. (1975). Looking back, moving forward in the digital age: a review of the collection management and development literature, 2004-8. Library Resources and Technical Services Vol. 55, No. 4, 205-220). Carroll, B. J., Bedford, D. A. D., and Jones, K. A. (1992). Interim Report. Identification & Graphical Representation of Major S&T Information Systems Project. Science and Technology Information Special Project Team Briefing to Dr. William W. Ellis, Associate Librarian for Science and Technology, Library of Congress. March 27. 1992. Cambridge Systematics (2013). Transportation Research Board. Improving Management of Transportation Information. Draft Interim Report. Case Studies and Examples. NCHRP 20-90. Committee for a Future Strategy for Transportation Information Management Transportation Research Board (2006). st Transportation Knowledge Networks: A Management Strategy for the 21 Century. Special Report 284. National Academies of Science. Corbin, J. M. (2007). “Information Flow: Key to Traffic Engineering”. TRB 86th Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.dot.state.mn.us/library/PPT/Corbin-TRB 2007.ppt CTC & Associates LLC (2005). Transportation Information Management. Transportation Synthesis Report. Wisconsin Department of Transportation, 2005. Dresley, S. C. (1998). Value of Information and Information Services. Publication No. FHWA-SA-99-038. Prepared for the Office of Technology Applications, Federal Highway Administration, 1998. Evans, R. (2007). Beyond Google – Finding the Transportation Information You Need. Presentation for the DRI Research Connections Series. September 26, 2007. Harder, B.T., and Tucker, S. L. (2003). Scoping Study for a National Strategic Plan for Transportation Information Management. Final Report. Project No. 20-7/Task 142. National Cooperative Highway Research Program, Transportation Research Board, National Research Council, 2003. Ingbar, E.E. (2010). A Case Study of Enterprise Historic Resources Information Management in Large Transportation Agencies MTI Report 09-06. Mineta Transportation Institute, College of Business San José State University, 2010. Lefchik, T., Beach, K., and Holt, M. (2007). Development of a National Geotechnical Data Management System for Transportation Applications”. TRB 86th Annual Meeting, Monday, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.diggsml.com/system/files/TEL+GeoCongress+2006+GMS+v1.pdf Lynch, C. (1998). Some Technical and Economic Issues in the Design of a National Library for Undergraduate Science, Mathematics, pp. 90-94 in Developing a Digital National Library for Undergraduate Science, Mathematics, Engineering and Technology Education. Report of a Workshop. Retrieved online on May 15, 2013 at: http://www.nap.edu/catalog.php?record_id=5952
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MacDonald, D. B. (2007). Improving Information Accessibility TRB 86 Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.wsdot.wa.gov/NR/rdonlyres/78501AAA-8851-41C9-8F19074A04B428E2/0/KnowledgeManagement.pdf Munroe, M. and Ver Steeg, J.E. (2004). The decision-making process in Conspectus evaluation of collections: the quest for certainty. Library Quarterly Vol. 74 No. 2, 181-205. National Research Council (1998). Developing a Digital National Library for Undergraduate Science, Mathematics, Engineering, and, Technology Education. Report of a Workshop. National Academy Press, Washington, D. C. 1998. Oman, L. (2007). "Improving Access to Information Resources at Washington State DOT" TRB 86th Annual Meeting, January 22, 200 Retrieved online on March 31, 2013 at http://www.dot.state.mn.us/library/PPT/oman-informationresources.ppt Osif, B. A. (2000). Transportation Information: a Review of Grey Literature by Format, Language and Availabilityâ&#x20AC;?, International Journal on Grey Literature Vol. 1 Issue: 1, pp.12 â&#x20AC;&#x201C; 17. White, H. D. (2008). Better than brief tests: coverage power tests of collection strength. College & Research Libraries Vol. 69, No. 2, 155-174.
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Collaborative Solutions Quick&Clean: The SFM Method Marco Bettoni, Willi Bernhard and Nicole Bittel Swiss Distance University of Applied Sciences (FFHS), Brig, Switzerland marco.bettoni@weknow.ch willi.bernhard@ffhs.ch nicole.bittel@ffhs.ch Abstract: The SFM method (Solution Finder Model) is a structured, formal procedure to be applied during interactions in small, medium or large multidisciplinary groups where there is a need to collaboratively develop shared solutions of a high quality standard (“clean”) and in a short period of time (“quick”). The SFM was developed within the context of various successful knowledge management projects, where different kinds of knowledge‐intensive problems or tasks (such as specification, conception, design etc.) had to be solved collaboratively by a multidisciplinary group. The first part of the paper will explain the SFM by describing its theoretical foundations, terminology, components and principles, the procedure for applying it and examples of practical application. The second part will then describe 3 cases in which the SFM has been applied for developing a solution to 3 kinds of knowledge‐intensive problems: design, specification and conception. The first example features the collaborative design of a Community of Practice by potential members of the planned community who interact in the context of a series of design workshops. The second example includes employees from all over the company who interact in terms of the specification of ideas within the context of a collaborative online ideas management system. Last but not least, the third example is the conception of a didactical model for analysing logfiles in learning management systems. At this point, the reader will have enough information to apply the method to his/ her own cases. In the conclusion, we will briefly look ahead to further planned research covering theoretical foundations and experimental investigations, especially at SMEs. Keywords: collaborative problem solving, knowledge‐intensive tasks, multidisciplinary collaboration, communities of practice, SME
1. Introduction Today enterprises increasingly need to be flexible and quick in revising, updating and extending their business practices and processes. Such reorganization processes can be considered as knowledge‐intensive, in the sense that they “involve human judgment and experience, complex decision making, and very often, creativity. In fact, they are now being recognized as the most important processes for organizations today (Davenport, 2005)” (Marjanovic & Freeze, 2012). The high numbers of tasks, their unpredictable nature, and the difficulty of remodelling the entire knowledge of the domain are further aspects of knowledge‐intensive processes.
1.1 Some knowledge‐intensive processes In this sense, processes or tasks like requirement specification, system modelling or interaction design can be regarded as knowledge‐intensive, especially in those cases where the experience of stakeholders from many departments or groups (multidisciplinary collaboration) is needed and must be combined in order to generate a shared solution. Furthermore, as regards the resources involved, it is important to consider that since a large group of people collaborating simultaneously on the same task has a high specific cost (cost/hour), there is a compelling need for efficient interactions; last but not least, the interactions also need to be effective, particularly in the sense that, regardless of the short time available, the quality of the solution must nonetheless be high. This is where the SFM method for knowledge‐intensive tasks comes in with its value proposition: its procedure is simple (lightweight), it can be executed in a short space of time (quick), it is designed to guarantee a high quality of the solution (clean) and it allows and promotes multidisciplinary collaboration in groups of any size.
1.2 Analogy with the Harvard negotiation method In a famous story about negotiation, the essential difference between interests and positions (Fisher, Ury & Patton 1991) is illustrated by two children holding one and the same orange, bringing it to an adult and stating: “I want it!” The adult asks them to explain the reason why they want the orange. One child is hungry and wants to eat it; the other instead needs to bake a cake and wants to have the orange because he needs grated peel for the recipe. Negotiation succeeded! By focusing on the complementary interests (needs) rather than on the conflicting positions (solutions), both children gain a much better solution: orange to eat and orange for
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Marco Bettoni, Willi Bernhard and Nicole Bittel the grated peel (Schwarz et al., 2005, p. 145). In this distinction between interests and positions, which forms the foundation of the famous Harvard model of negotiation, one can see a strong analogy with the distinction that the SFM makes between needs, objectives and solutions in the context of solutions development and supports the author’s conviction that their model also has inherent potential and could become equally successful on a large scale.
2. SFM method The essential, core characteristic of the SFM, which has its theoretical foundations in cybernetics, system engineering and radical constructivism, is the idea of the unity of 3 relevant elements: needs, objectives and solutions. The term unity refers here to the guiding principle of SFM: in order to find a high quality solution, the 3 elements should always be explicitly connected to build a coherent triad (the unity). This is accomplished by determining the 3 elements and their 3 relations (R1: need Ù objective; R2: objective Ù solution; R3: solution Ù need) in a suitable manner. The SFM is constituted in essence by a set of basic principles or ideas, divided into two groups. The first group are structural principles which determine the model of a structure which allows thoughts and ideas to be ordered in a specific, peculiar way; this structural model (which is the “what” of the method, the substance of the tool) is the reason why the method has been allocated the term “model”. The second group are procedural principles which determine how to obtain a structure which complies with the structural principles in a concrete situation; this part is the “how” of the method, the “know‐how” needed for using the structural model in a situation where a solution must be conceived.
2.1 SFM structural principles When one considers the multiplicity and variety of all aspects that determine a solution, she suddenly understands that if, on the one hand, looking at them and taking all of them seriously contributes to obtaining a very good, complete solution, on the other hand, this approach would require a lot of work on many different items and this would present an obstacle to an efficient and effective solution development, especially when this development must happen collaboratively and in a short space of time. Since the authors wanted (and needed) their method to be not only clean (high quality) but also able to deliver results within a short time frame (quick), they had to find a different solution. Intuitively, their approach was to search and identify the smallest required set of elements determining a solution, i.e. an essential set. This search was conducted based on the background of their experience and their theoretical interest in the fields of cybernetics, system engineering and radical constructivism (Bettoni 1990; Bettoni 1991; Bettoni & Bernhard 1993; Bettoni 1997). As a result they devised and formulated the following 4 principles, i.e. the “Tetractys” of their method:
The Triadic principle: there are three essential elements to any solution and they must form a unity.
The Connectivity principle: in order to form a unity , the three essential elements must be connected with each other one by one, thus forming three essential connections.
The Interdependence principle: each connection between two elements is a connection of interdependence.
The Solution principle: one of the elements must be a solution (to our problem) and the two further essential elements, with which it has interdependence, are the need (something we are missing) and the objective (what we can attain).
By combining these principles, we obtain the following model of a structure (see Figure 1) where we see three main paths for moving between the nodes which correspond to three main uses of the SFM method:
Path P1 from need to objective to solution = goal‐oriented problem solving
Path P2 from solution to objective to need = goal‐oriented solution analysis
Path P3 from solution to need = justification.
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Figure 1: SFM method ‐ the structural model This structure can be used to organise a set of thoughts (and related statements) generated in the search for a solution to a problem; specifically, the ordering of the statements (that we call “triadic order”) will be achieved by operating in terms of a triadic sequence composed of three specific elements :
Need: the first SFM‐element, a need, can be anything we are missing: new interests, hopes, concerns, dissatisfaction with a situation, defects to be corrected, new wishes to be supported, etc. which, in general, can be met or satisfied by more than one solution. For example, when dealing with knowledge and learning, the focus could be on knowledge needs; in this case, to identify a knowledge need, the question to ask is: “what do we need or wish to know? (know what?)”. When we identify needs we are on a functional level.
Objective: The second SFM‐element, the objective, comes in because a need is usually not an end in itself: the goal it aims at can be used to achieve some effect (goal, objective). When the need is given, in order to identify a related objective the question to ask is: “what effect should be achieved in order to satisfy the need?” Then, when the objective has been found, the question of “why this objective?” is answered by the needs connected to it. In this step, we move from the specific functional level of the needs to the general, explanatory level of the objectives (rationale).
Solution: Finally, the third SFM‐element, the solution, is the instrument, tool or method that enables you to reach the objective and satisfy the related need. A solution should be an answer to the question: by which measures (means) can the objective (end) be attained? In this step, we move from the explanatory level to an instrumental level. Vice versa the question of “why this solution?” is answered by the objectives and the needs connected to it.
According to SFM the triadic order of the given thoughts or statements is obtained by identifying in the given set of thoughts one or more unique combinations of three fundamental elements, i.e. a solution to a problem, a need in terms of the essence of the problem to be solved and an objective as the rationale for the need. As a result of organising a set of statements based on this structural model, a diagram of a solution system emerges which we call a “Solution Map” (see Figure 3) where each element can have multiple connections.
2.2 Exploring the SFM on a practical example The SFM is used as an analytical tool, where the starting point appears in form of a problem for which you want to find a solution. This little example shows how the method works:
Problem (starting point): “I'm hungry”
You may think, that “eat” is the solution to the given problem. But this is only the case if “I’m hungry” is the need and “be satisfied” is the objective.
But if the objective is “to reduce weight”, then the solution will be “do not eat” and the need occurs still as “I’m hungry”.
It is also possible, that “I’m hungry” is the objective, then the need can be “loss of appetite” and a solution could be “serious sport”. It is also possible, that “I’m hungry” is a solution, then “treatment of anorexia” could be the need and “eat” would be the objective.
As shown in the example above, “I’m hungry” can be need, objective or solution. By applying the Solution‐ Finder‐Method, you will easy find the combination that best fits to your case.
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2.3 Procedural principles As the name “Solution Finder” suggests, in general the SFM method can be applied to any situation in which a solution needs to be found. We will later see a situation of Collaborative Design (case A, section 3.1) in which the contributions of a multidisciplinary group of people resulting from three World Café sessions in a “Problem Meeting” needed to be structured and systematised in order to make the best use of them during the following “Solution Meeting”. In another situation called Collaborative Specification (Case B, section 4.1), we will see how in various phases of an online collaboration, a group of employees contribute to the development of an idea with a great variety of statements made during online discussions. At a certain point in the ideas development process (phase 4), the solution ideas need to be compared and evaluated. Finally we will see a situation of Conceptual Modelling (Case C, section 5.1) in which a great variety of statements originating both from theory (e‐Learning functions) and from practice (e‐Learning requirements) had to be integrated into a consistent model. In all these cases, there is a search for solutions, the collection of a wide variety of contributions to this search and the need to use the available materials in the best possible way in order to find what we are searching for (see Figure 2). Wide variety of solution-related statements
SFM Method
Best quality, quick solutions
Figure 2: Generic application case In Case A, the procedure, a variation of the Grounded Theory approach (Charmaz 2006), was as follows. First of all, due to the authors’ underlying epistemology, before the meetings they had decided to facilitate the sessions and collect data in an unstructured way (unstructured interaction). In fact, they hold a constructivist point of view (von Glaserfeld 1995) and believe that, in order to make the most sense of the participants’ contributions, you have to approach their world from their own perspective and reify these contributions in our documents based on their own terms. Secondly, during the Problem Meeting the authors’ team collected detailed notes of the individual statements which the participants had contributed in three different sessions: 1) actual situation, 2) vision & feasibility, 3) priorities. Since they as the facilitators, following their unstructured interaction approach, did not use predefined questions and did not have any hypotheses about the possible contributions, the content of the notes is similar to those which can be obtained as part of unstructured interviews (Zhang & Wildemuth 2009). Coding of the material was carried out between two meetings in terms of the concepts of our Solution Finder Model; the analyst read the statements from the minutes, demarcated segments within them by comparing similar expressions (similarity of content and category) and then labelled each segment with a "code"; codes were mainly “need”, “objective” and solution”, but also other words or short phrases that emerged as frequent categories when various statements were collected into a cluster. Next are examples of statements taken from the minutes of a Problem Meeting (August 2011); first comes the statement number, as second the person’s acronym, third is the statement and finally the code (N= need, O= Objective, S=Solution, D=Defect, M=Measure):
09, SK, “Information about HW parts is missing”, D
10, CS, “for magnets we need a database”, S
13, JA, “each employee has data and should be able to upload them”, N
15, JA, “it was planned to manage data with a CMS”, M
62, ME, “avoid that anyone calls the development team for support”, O
66, SC, “Tools that we have developed should gain better visibility”, O
73, DM, “we have lot of tools but application oriented information is missing”, N
90, RS, “Contact persons could be found if we had a directory appropriately organized”, S
After the coding and ordering of the statements into clusters with the same code, the analyst was able to compile triads each composed of a need, an objective and a solution following the structural model presented above (Figure 1). An example of a small part of such a solutions map is reproduced in Figure 3.
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Marco Bettoni, Willi Bernhard and Nicole Bittel In Case B and C, the authors were basically able to use the same fundamental approach except for some variations needed to adapt the procedure to the different settings. In case B, one main difference was that the statements analysed, interpreted and coded originated from postings in discussion forums, i.e. from asynchronous, written interactions; in case C, the origin of the statements was different, resulting from a literature search and analysis by a researcher and requirements elicitation by means of an online survey, workshops and face‐to‐face interviews. who in the unit is responsible for data who in the unit is responsible for subject
avoid jumping from person to person for 1 question
who is working on the dossier competence about subject is in NaC
Tria
YELLOW TOOL (internal contacts)
increase transparency of people involved
contact person for registration in NaC
need?
objective?
solution?
NaC = National Company
Figure 3: Solution map case A (excerpt)
3. Case A: Collaborative design At a pharmaceuticals company, an SME (for reasons of discreteness we will call it “Phar AG”) with its headquarters in Switzerland and about 30 worldwide independent national offices, the “Phar International Regulatory Affairs” (PIRA) department based at the company’s headquarters oversees and supports drug registration processes worldwide in collaboration with the aforementioned national offices. The drug registration process is the process of preparing, submitting and correcting a drug application for obtaining approval of its use from the national consumer protection agency of the specific country in which the drug will be sold. Success in registration projects depends heavily on having an optimal flow of information, and the increasing internationalisation of Phar AG had created new demands on their communication and collaboration processes, particularly knowledge‐sharing. After evaluating various kinds of knowledge management solutions, it was the concept of an Online Community of Practice (CoP) that the authors proposed which raised the interest of PIRA. After its launch, the CoP generated a new means of collaboration within the PIRA department. All employees dealing with the registration of pharmaceutical products were able to collaborate worldwide in forums and wikis, for example discussing new legislative requirements or developing a shared FAQ about them. In addition, documents could be shared and viewed worldwide on the platform. Finally, the CoP enabled transparency: by means of a wiki using personal profiles designed according to the “Yellow Tool” concept (Bettoni, Bernhard et al. 2007), it was easy to find out who was working on what subject, where the expertise was available and how to contact the person.
3.1 Needs and objectives As preparation for the actual participatory design of the community elements (domain, community and practice, see Wenger et al. 2002, p. 27 ff.), the authors conceived two full‐day meetings: a so‐called “Problem Meeting” and a “Solution Meeting” for dealing with actual situation, visions, feasible solutions and priorities in two stages. Since both meetings required the participation of employees representing the major groups that would become members of the CoP, finally what came together was a multidisciplinary team of people with a
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Marco Bettoni, Willi Bernhard and Nicole Bittel variety of nationalities, backgrounds, experiences, roles, tasks and countries of affiliation. Based on this diversity and with the objective of making the meeting effective (relevant outcomes) and efficient (limited time), an adapted version of the “World Café” was selected as main method of interaction. It was between the aforementioned two meetings of this project that the SFM was invented (end of 2007). In fact, since each of the three World Café sessions (actual situation, visions, and priorities) had delivered a huge and complex mix of statements belonging to a variety of categories, simply listing these statements in the minutes or also organising them in a huge mind‐map would have caused the reader to become lost. In order to facilitate the activities planned in the solution meeting, a very good orientation knowledge had to be provided, something like a structured, systematic view of the outcomes of the problem meeting. But how to structure such a huge, complex, intertwined mix of statements? Which system could be used to bring order to this variety? By applying the SFM method to itself, we could say: the SFM has been the solution that builds a stable triad together with the needs and objectives of this case.
4. Case B: Collaborative specification Like the previously mentioned pharmaceutical company, the Swiss Distance University of Applied Sciences (FFHS) is also an SME with about 260 employees; nearly 60 of them (administration, technical services, research, education managers) have a permanent contract and about 200 lecturers have a part‐time, teaching contract. In 2008, the Board of Directors at the FFHS sought ways to encourage employee participation in the development and improvement of the university; ideas management was selected as the most promising opportunity and the Research Management Unit (RMU) of the FFHS (which at that time included the first two authors of this paper) was allocated the responsibility for conceiving, designing, implementing and running this new initiative and developed an innovative, collaborative model of enterprise ideas management based on a human‐centred approach and supported by a Moodle online space (Bettoni, Bernhard et al. 2010).
4.1 4.1 Needs and objectives The innovative ideas management process, based on the authors’ approach called “Seven Phases Tendril” (Op. cit., Table 1) supports not only the conventional process (submission of ideas, testing, decision, award) but also a specific, facilitated and collaborative “cultivation process” which serves to unfold an individual idea and further develop it (together with the idea‐giver) during the course of an online collaborative process (e‐ collaboration) leading to a workable, shared solution. How does it work? The online collaboration is enabled by a suitably designed and equipped Moodle space. After publishing the new idea in a news forum and forming a group of employees interested in that specific issue and wishing to contribute to its development, the group interacts via a specific discussion forum and is guided by a facilitator through up to 7 phases of the ideas development process. Phase 2 is a convergent thinking phase which results in a mind‐map that visualises a more detailed understanding of the problem to be solved and of related tasks in its branches and nodes. Phase 4 is the filtering process, where ideas from phase 3 are structured and evaluated. The convergent thinking style of phase 4 allows criticism and leads to results ready for phase 5 where improvements will be the goal. How can one evaluate the solution ideas derived from phase 3? Similarly to case A, we have here a situation in which a wide variety of statements originating from discussions about the idea under development (in this case online discussions, not f2f) have to be put in some kind of order. Since we need to compare the various solutions as part of the evaluation, what was needed here was generalisation knowledge in the sense of a structure or framework in which all items to be evaluated can be placed (interpreted) as specifications of the same generic paradigm. A suitable generic paradigm for this was found in the SFM structural model (Fig. 1) by considering that a great part of the contributions could be viably interpreted as direct or indirect assertions either about needs or about objectives or solutions.
5. Case C: Conceptual modelling When teaching and learning are supported by learning management systems (LMS), then the logfiles (user interaction traces) of the LMS offer opportunities for understanding the activities of students and teachers; this understanding then provides a good basis for devising ways of improving the quality of teaching and learning. Unfortunately, the logfiles provided by a LMS are seldom used; one of the main reasons for this
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Marco Bettoni, Willi Bernhard and Nicole Bittel shortcoming is the fact that data is not aggregated from a didactical perspective. As a contribution to overcoming this difficulty, an inter‐university team (directed by the main author of this paper) has developed MOCLog, a monitoring system that helps to analyse the logfiles of the LMS Moodle by interpreting the data based on a suitable didactical model that we call “MOCLog model” (Mazza, Bettoni et al., 2012). Unlike case A and B, in which the sources of the highly diverse statements to be organised were of a synthetic type (group discussions), in this case C, the sources are of an analytical type, namely the analysis of research literature and a requirements analysis that were performed as a basis for the creation of the MOCLog model.
5.1 Needs and objectives Based on the research review and requirements analysis, the development of the model began by creating a concept map that had the function of clarifying the concepts involved and their relationships. Next it became evident that one needed to integrate theory and practice with the aim of producing a solution: a) theory in the shape of a framework of didactical objectives and related means obtained from our literature review; and b) practice in the shape of stakeholder requirements (obtained from the requirements analysis) and LMS metrics (log codes, logfile entry formats) of the Moodle system. As a consequence, the question that had to be answered here was of a methodological type: which set of concepts and which methodology would allow the integration of theory and practice available in the form of a very diverse set of statements provided by two analytical sources? As in the previous two cases A and B, the SFM method has been the solution that builds a stable triad together with the needs and objectives of this case C.
6. Conclusion The SFM method originated from the need to solve an unexpected problem which arose during a consulting project (case A). It was further developed in the context of similar knowledge‐intensive processes like that of case A (collaborative design) as well in new types of knowledge‐intensive processes like collaborative specification (case B) and conceptual modelling (case C). As a result of these and other successful project experiences, we have now at our disposal a practical method which promises to have the potential to become a major tool of organisational consulting for enterprises which increasingly need be flexible and quick in collaboratively revising, updating and extending their business practices and processes. The next steps that the authors are planning consist of developing an explicit theoretical foundation, revising the method by adapting it to this explicit foundation and after that, evaluating its application in practical cases. For the theoretical inquiry, it is planned to extend the existing theoretical foundations by looking in particular at various theories of needs (Maslow, Herzberg, McClelland etc.), at action research (actor‐network theory, theory of structuration, etc.) and knowledge management research (Bettoni 2005).
Acknowledgements We would like to thank Gabriele Schiller for her contributions to the first applications of the SFM method that we successfully implemented in the context of collaborative community of practice design workshops (consulting projects 2007‐2010).
References Bettoni, M. (1990) "Cognition, Semantics and Computers", in: R.A. Zwaan, D. Meutsch (eds.) Computer Models and Technology in Media Research, 65‐98, Elsevier Science Publ., Amsterdam. Bettoni, M. (1991) "Cybernetics Applied to Kant's Architecture of Mind", In: G. Funke (Hrsg.) Akten des 7. Internationalen Kant‐Kongress, vol. II.2, 723‐741, Bouvier Verlag, Bonn. Bettoni, M. & Bernhard, W. (1993) "General Purpose Enterprise Simulation with MASTER". In:G.W. Evans et. al. (eds.), Proc. of the 1993 Winter Simulation Conference, WSC '93, 1290‐1295, Los Angeles. Bettoni, M. (1997) "Constructivist Foundations of Modeling. A Kantian Perspective", Intern. Journal of Intelligent Systems, Vol.12, No. 8, 577‐595, New York, 1997. Bettoni, M. (2005) “Wissenskooperation – Die Zukunft des Wissensmanagements”. Lernende Organisation – Zeitschrift für Systemisches Management und Organisation, No. 25, May/June 2005, pp. 6‐24. Bettoni, M., Bernhard, W., Borter, F., Dönnges, G. (2007) The Yellow Tool – Making Yellow Pages More Social and Visible. In: Martin, B., Remenyi, D. (eds.) Proc. of the 8th European Conference on Knowledge Management, ECKM 2007, Consorci Escola Industrial de Barcelona (CEIB), Barcelona, Spain, Sept. 6‐7, 2007, 118‐124.
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Marco Bettoni, Willi Bernhard and Nicole Bittel Bettoni, M., Bernhard, W., Eggs, C. & Schiller G. (2010) Idea Management by Role Based Networked Learning. In: E. Tomé, Proc. 11th European Conference on Knowledge Management, Universidade Lusíada de Vila Nova de Famalicão, Portugal, 2‐3 September 2010, Vol. 2, pp. 107‐116. Reading: Academic Publishing Ltd. Charmaz, K. (2006) Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. London: Sage. Fisher, R., Ury W. L. & Patton, B. (1991) Focus on interests, not positions. In Getting to YES: negotiating agreement without giving in (2nd Ed.). Penguin Books USA Inc.: New York, NY. pp. 40‐56. Mazza, R. Bettoni, M., Faré, M. & Mazzola, L. (2012) MOCLog – Monitoring Online Courses with log data. In: S. Retalis & M. Dougiamas (eds.) Proc. of the 1st Moodle Research Conference, Heraklion, Crete, Greece, Sept. 14‐15, 2012, pp. 132‐ 139. Davenport, T. (2005), Thinking for a Living, Harvard Business School Press, Boston, Massachusetts. Marjanovic, O. & Freeze, R. (2012), Knowledge‐Intensive Business Process: Deriving a Sustainable Competitive Advantage through Business Process Management and Knowledge Management Integration. Knowl. Process Mgmt., 19: 180 ‐ 188. doi: 10.1002/kpm.1397. Schwarz et al. (2005) The Skilled Facilitator Fieldbook. San Francisco: Jossey‐Bass. von Glasersfeld, E. (1995). Radical Constructivism: A Way of Knowing and Learning. London: Falmer Press. Wenger, E., McDermott, R., & Snyder, W. (2002). Cultivating Communities of Practice: A Guide to Managing Knowledge. Boston: Harvard Business School Press. Zhang, Y. , & Wildemuth, B. M. (2009). Unstructured interviews. In B. Wildemuth (Ed.), Applications of Social Research Methods to Questions in Information and Library Science (pp.222‐231). Westport, CT: Libraries Unlimited.
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Intra‐Organisational Knowledge Sharing: Scenarios and Corresponding Strategies Madeleine Block¹ and Tatiana Khvatova² ¹Faculty of Social Sciences and Business Studies, University of Eastern Finland, Kuopio, Finland ²Institute of Economics and Engineering, Saint‐Petersburg State Polytechnical University, Saint‐Petersburg, Russia madeleineblock@gmx.net tatiana‐khvatova@mail.ru Abstract: In the knowledge management literature knowledge and knowledge sharing issues are widely discussed; however, a comprehensive understanding of how intra‐organisational knowledge sharing actually occurs has not been reached yet. Therefore, nurturing the theoretical foundation for intra‐organisational knowledge sharing analysis and actualisation is relevant and of particular importance. Contemporary theoretical research into intra‐organisational knowledge sharing predominantly focuses on how knowledge sharing functions, whether on asking why it does not happen naturally, and finding appropriate solutions. In this article three inherent characteristics of intra‐organisational knowledge sharing are examined from systemic perspective, and further, corresponding strategies for knowledge sharing within organisational environment are developed. At first, a classification of knowledge and its relevance for knowledge sharing within organisational context is discussed. Organisation is understood as a social system, and it becomes plausible that a subsystem such as knowledge sharing cannot be organised and controlled mechanically; it rather reflects a complex system. Accordingly, the starting point of our analysis represents two specific characteristics which must be addressed by any type of analytic‐deliberative process: complexity and uncertainty. Ambiguity, which is particular for complex systems, is added as the third characteristic. Analysis of the interrelations and dynamics between those three features creates the ground for a much better understanding of the relationships and patterns of intra‐organisational knowledge sharing. Subsequently, the reasons why such features as complexity, uncertainty and ambiguity appear are investigated, and based on this the boundary scenarios of intra‐organisational knowledge sharing are developed. Beyond, scenarios are not studied separately; they are context‐related towards organisational subsystems and elements. As a result, four knowledge sharing strategies corresponding to the organisational environment are proposed: linear, complex, high uncertainty and high ambiguity knowledge sharing strategies. Keywords: knowledge sharing; organisation; complexity; uncertainty; ambiguity
1. Introduction Intra‐organisational knowledge sharing often refers to enterprises´ ability to create knowledge in order to develop new products and services. According to Nonaka and Takeuchi (1997, p. 71), knowledge creation within organisations is a process which facilitates individual knowledge, and shares it organisationally wide. On the other hand, organisations are influenced by the environment, e.g. market competition, and they are stimulated to discover and mobilise knowledge `on‐the‐spot´ (cf. Nonaka and Nakeuchi 1997, pp. 85). In current knowledge management and knowledge sharing literature the focus of research mainly lies on the influencing factors of knowledge sharing. Not considering all relevant things, this focus inherits the danger of a `too narrowed picture´. This paper aims at bringing knowledge sharing closer to reality by enlarging the view of intra‐organisational knowledge sharing. We suggest studying knowledge sharing as a complex subsystem of its superior system organisation from systemic perspective. Here, organisations are studied as social systems characterised by more precisely (formally) defined targets and more differentiated structure in comparison with other social systems such as, for example, family (cf. Endruweit 2004, pp. 21‐22). The organisation’s internal environment, as any complex system, is characterised by such features as complexity, uncertainty and ambiguity which are the challenges confronting and hindering intra‐organisational knowledge sharing. These challenges are related to the state and quality of the available knowledge and to the different targets among organisational members including the management. Before studying those three features of complex systems related to knowledge sharing in more detail, knowledge sharing within organisations is discussed.
2. Central insights into knowledge sharing within organisations In this chapter, the guiding question is: what actually makes knowledge sharing a complex system? How is knowledge sharing characterised?
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Madeleine Block and Tatiana Khvatova According to systemic thinking, every system is a subsystem of another larger system, and at the same time every system in turn consists of subsystems. In this paper the relevant system is knowledge sharing which is embedded in its superior complex system organisation, and organisations in turn are subsystems of larger systems such as society and economy. In other words, the complex social system organisation influences and is influenced by its subsystem of knowledge sharing. Nowadays, the process‐oriented view on knowledge sharing has become accepted in scientific literature. The general mode of knowledge sharing process is similar in every knowledge management initiative and, as described in Figure 1, consists of three phases: a) initiating and sending, b) social interaction, and c) receiving and applying knowledge. For a successful knowledge sharing process all three phases are equally important. Difficulties in one of those three phases lead to hindering or rather breaking the knowledge flow, even so the other two parts of the knowledge sharing process are operating optimally. The human ‐ as original carrier of knowledge ‐ occupies the central role in the phases `initiating and sending knowledge´ and `receiving and applying knowledge´ of the knowledge sharing process. The `social interaction´ phase reflects mainly social relations within networks of organisations.
Figure 1: Three phases of knowledge sharing process (own composition; cf. Köhne 2004, p. 64) In the `initiating and sending´ phase an organisational actor intends to get or to provide knowledge. Basically, the knowledge sharing process can be initiated by the sender or by the receiver (cf. Köhne 2004, pp. 64). If the sender (e.g. management, expert) initiates the process, s/he pushes knowledge to potential receivers expecting that receivers can use that knowledge. According to this push‐principle, knowledge sharing suits for central storage and distribution of the stored knowledge within the organisation (cf. North 1998, pp. 237). Accordingly, the biggest disadvantage of the push‐principle is the danger of intensive circulation of non‐ relevant knowledge. It can happen that employees receive too much of irrelevant knowledge or too little relevant knowledge. As a result, receivers might be overloaded by information which inhibits the employees’ willingness to accept this approach; thus, transaction costs increase. On the other hand, the process of knowledge sharing can be initiated by the receiver according to the pull‐principle (cf. Probst and Romhardt 1998, pp. 237). It means that the receiver localises what kind of knowledge is relevant. Therefore, the probability that one gets the relevant knowledge is higher, and employees are more likely to accept this approach. However, the availability of the required knowledge and the infrastructure are the important preconditions for the pull‐principle. Moreover, at first the receiver has to understand that there is a deficit of knowledge; otherwise, no knowledge sharing takes place. Both principles have disadvantages; therefore, some scholars advise to combine them (e.g. North 1998), while others (e.g. Probst et al. 1999) point out that the pull‐principle should be preferred because of the higher degree of acceptance by the counterparts and greater probability that the shared knowledge will be used. The initiating and sending phase is essential for knowledge sharing and demands the support by the management. The management decides on how, and to which extent knowledge sharing process is vitally developed within organisations. We argue that knowledge sharing initiatives should be oriented or rather interlinked with the organisational target. In the phase of `social interaction´ knowledge is actually shared through interaction between at least two actors with the help of information and communication technology (cf. Köhne 2004, p. 65). Only one‐sided knowledge transfer does not happen in practice; thus, knowledge sharing reflects bilateral knowledge flows between the sharing partners (the sender and receiver positions´ are reciprocal). Therefore, the phase of
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Madeleine Block and Tatiana Khvatova `receiving and applying knowledge´ follows. In this phase the receiver (individual or group) takes in knowledge, interprets it. This experience leads to modification and/or enlargement of their knowledge base (cf. Köhne 2004, p. 65). Certainly, such bilateral knowledge flows stimulate the combination and creation of knowledge for both receiver and sender. This brings us back to the conclusion of Nonaka and Takeuchi (1995, 2004) who argue that the process of organisational knowledge sharing and creation is a dynamic and iterative process. Concluding, knowledge sharing takes place in the social environment and the quality of knowledge sharing process depends on the involved human beings, and the capability of involved actors to share and to apply knowledge play significant role. Therefore, knowledge sharing process cannot be looked at separately from its nearest environment; it is embedded in the organisational environment. This circumstance underlines our suggestion to examine knowledge sharing with the help of system approach as a subpart of organisations. Beyond, intra‐organisational knowledge sharing takes place on the individual, group and organisational levels reflecting different social layers with their own interests which can contradict each other.
3. Research into knowledge sharing perception As pointed out in chapter two, intra‐organisational knowledge sharing is mainly a social process supported by information and communication technology. Therefore, knowledge sharing is closely connected to human beings and thus, the decision whether to take actively part in the action knowledge sharing is made by them. At this stage, we would like to refer to Renn (2008, p. 93) and emphasise that `human behaviour is primarily driven by perception and not by facts´. Recent studies in the field of brain research have uncovered especially deep insights into explaining human perception. Human beings perceive things with the help of their five senses (seeing, smelling, tasting, hearing and touching). Their perception is also influenced by individual thoughts, feelings, memories and social as well as cultural background. Things are perceived because they differ. If the world were single‐coloured, human being would not have any criteria for this single colour (cf. Ebeling et al. 2012, p. 27). In other words, every individual perceives and creates own reality which in turn determines the pattern of perception and interpretation and filters for information suiting to own world (Figure 2).
Figure 2: Human perception process (own composition) Superimposed onto knowledge sharing, it means that based on their perception, individuals give their own meaning to information and unconsciously communicate their reduced perception in the form of information to others. This may explain why misinterpretation and misunderstanding in communication often happen. In recent studies, brain researchers highlight the significant meaning of social environment for the perception process. Empirical studies could prove that `soft facts´, related to social relationships such as working environment, are an important biological health factor (cf. Bauer 2008, p. 33). From the neuropsychological point of view, human´s perception and also the brain itself are dependent on social relationships (cf. Bauer 2008, p. 71). In other words, social relationships have an impact on human´s subjective perception, while perception lays the ground for action. Further, individual and social factors that shape the knowledge sharing perception are discussed. Knowledge sharing reflects a social process among actors of organisations. In organisations social relationships are based on structures of mutual dependencies which make the actors vulnerable to each other´s actions such as knowledge sharing which is inherently risky. In the context of knowledge sharing, risk refers to the potential for giving benefit to another without receiving something similar valued or expected in return. The uncertainty of a risky exchange depends on the amount and quality of knowledge that an actor has for
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Madeleine Block and Tatiana Khvatova estimating the probability of the outcome. For example, missing knowledge can be about the partner´s intentions or past behaviour (cf. Kollock 1994, pp. 317‐318), or the shared knowledge can reflect just not the (full) truth. On the other hand, if risk is absent, trust is irrelevant because there is no vulnerability. However, organisations and their personnel cannot possess all and true information; therefore, the notion of uncertainty and risk is always present. According to our presumption of humans acting with bounded rationality and aiming at maximising their individual interests, knowledge sharing refers to an action that is stimulated by the returns they expect to get, and is not based on the wish just to share with somebody (cf. Esser 2000, pp. 149). As far as knowledge in the core is an interpretation of experience and perception arising from the environment, the sharing of knowledge between individuals gets very complex and ambiguous. Furthermore, the perception process within organisations is complex because there is abundance of information, plurality of views and interests. However, organisations create a picture and develop the dominating patterns which act as filters and influence, change or even hinder individual’s perception. For example, if individuals perceive the organisation as a machine in which the attention is given to permanent functioning, this perception becomes a normal pattern for individuals within that organisation. On the other hand, if employees perceive the organisation as supportive and vital system, in which central patterns are immanent responsibility and openness, then this can become normal for the organisational members as well (cf. Ebeling 2012, pp. 42). Every employee incorporates pictures of organisation, management and working together. Those perceptions of individuals do not change easily, only if individuals change their perception by themselves. This in turn can only happen through experience. Ideally, individual perceptions harmonise with the collective perception which supports and utilises individual differences. Accordingly, every individual with own perceptions would be ready to discover different perceptions, and the management would support an open and fearless sharing of perceptions (and further information) among organisational members. For a comprehensive knowledge sharing management it is necessary to consider perceptions. What can be the criteria for classifying knowledge sharing perceptions? From this study, we can conclude that knowledge sharing process and its perception are characterised by three features: complexity, uncertainty and ambiguity. The term complexity refers to a ‘multifaceted web of causal relationships where many intervening factors interact to affect the outcome of an event or an activity’ (WBGU 2000, pp. 194, in Renn 2008, p. 186). Complexity supposes difficulties of identifying and assessing causal links between a multitude of potential causal agents and specific observed effects while the causal relationship between them are known (cf. Renn 2008, p. 75). The nature of this difficulty can be illustrated by continuum of a complexity scale. On the one end of the complexity scale, knowledge is more explicit and formalised, few factors of the environment interact, and the pathway of knowledge sharing is well understood and linear. On the other end there are highly complex relationships between the environmental factors, which are also multiple. Change in one or two factors might have an effect on the whole system of knowledge sharing. The second feature of knowledge sharing process is uncertainty. Uncertainty refers to a lack of clear understanding and confidence about the postulated cause‐effect relationships (RG, page 165). In studying knowledge sharing it is essential to realise that held knowledge, for example, about the organisational environment is always incomplete and selective. It is not possible to track all relationships among employees or predict with high probability, for instance, a cultural clash. Human knowledge in general is dependent upon assumptions, assertions and predictions (cf. Funtowitz and Ravens 1992, in Renn 2008, p. 75). Furthermore, human´s decision whether to take actively part in knowledge sharing is connected with uncertainties related to receiving benefit. Ambiguity is the third recognised feature of knowledge sharing process and refers to multiple possible interpretations of things. For example, actors perceive input and outcome of knowledge sharing controversially. In regard to knowledge sharing among organisational members, ambiguity plays an important role because differences in how individuals value some input or outcome of knowledge sharing system are difficult to reconcile and a consensus might be hard to find (cf. Renn 2008, p. 186). Probably certain knowledge sharing situations are usually characterised by a mixture of those three features. Table 1 shows two main types of knowledge sharing systems: a) sequential knowledge sharing referring to routine work and b) complex knowledge sharing in which the characteristics of complexity, uncertainty and ambiguity are quite present and require to plan and schedule flexible knowledge sharing systems.
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Madeleine Block and Tatiana Khvatova Table 1: Knowledge sharing systems with regard to the main knowledge sharing characteristics Type of knowledge sharing system Sequential knowledge sharing system Complex, flexible knowledge sharing system
Explanation
Characteristics
Linear process taking place in pre‐determined time and space with defined outcome, for instance, a product Knowledge pieces and flows can follow different roots with undefined outcome or a variety of different outcomes
Relatively low level of complexity, uncertainty and ambiguity High complexity, relatively high level of uncertainty and ambiguity
In linear processes, knowledge plays a less significant role for new developments, but rather as direct productivity power. Linear processes refer to routine with low level of complexity, uncertainty and ambiguity because they are well‐known and usually easy to quantify. In opposite, for flexible complex processes knowledge gets a different meaning. In this context, knowledge and the sharing of knowledge among organisational members is the prerequisite of process development and creating various different outcomes. Depending on organisations´ target, they may lay the focus of attention on sequential or flexible knowledge sharing systems.
4. Development of corresponding knowledge sharing strategies The knowledge management literature provides different strategies and methods for the actualisation of knowledge sharing. Basically, there are two central strategies of knowledge sharing. They regard to Nonaka´s and Takeuchi´s conceptualisation and aim at facilitating either explicit knowledge or tacit knowledge (e.g. Bauer et al. 2007, Mentzas et al. 2001, Hansen et al. 1999). Those are:
Strategy of codification: sharing of codified, explicit knowledge;
Strategy of personalisation: sharing of mainly tacit knowledge through face‐to‐face contacts within social networks.
According to the strategy of codification, knowledge is codified and stored in databases which allow organisational members to easily access and (re‐) use the accumulated knowledge (cf. Hansen et al. 1999, pp. 107).). On principle, information technology systems for storage and transfer of explicit knowledge are the basis for the strategy of codification. The advantage of this strategy is clearly the feature that once codified knowledge can be theoretically reused oftentimes. By this, employees enlarge their individual knowledge base. On the other hand, employees need to be willing to codify their knowledge and to use the knowledge of others. But why employees should explicate their knowledge, which is often a time‐consuming process, when its codification does not generate a direct benefit for them? Beyond, for human beings the explication of individually held knowledge, for example, expressing thoughts and ideas, is difficult and limited. From the organisational point of view, disadvantages of codifying knowledge are connected with the risk of overlooking much valuable knowledge besides codified knowledge and the circumstance that stored knowledge becomes quickly overdue while it is detached from certain situation (cf. Huysman and de Wit 2004, pp. 83‐86). On the contrary, the strategy of personalisation refers especially to knowledge sharing between people. `Knowledge is closely tied to the person who developed it and is shared mainly through direct person‐to‐ person contacts.´ (Hansen et al. 1999, p. 107). Therefore, the strategy of personalisation concentrates more on sharing tacit knowledge and is based on the network of experts and communities of practice. There are appropriate organisational pre‐conditions to be made, for example, mentoring, discussion forums, chatting rooms or creation of communities of practice. The advantage of the strategy of personalisation is that it is generally easier to put sharing of knowledge into practice, because of closer relations. On the other hand, the main disadvantage in regard to the strategy of codification is that for every sharing process the knowledge has to be provided newly which means that the scalability and, therefore, the reuse of knowledge is comparably little. Both theories narrow the view on sharing either explicit or implicit knowledge, but as, for example, Polanyi (1985, p. 36) stated, knowledge inherits both of these forms which are interwoven with each other. We argue that it is not helpful to separate knowledge, for example, into explicit and implicit, and this separation cannot lay the foundation of designing knowledge sharing strategies. In this paper, we propose to develop strategies according to the three main characteristics of knowledge sharing system: complexity, uncertainty and ambiguity. So, we offer the following four scenarios:
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Strategy for sequential, linear knowledge sharing process;
Strategy for knowledge sharing with high complexity;
Strategy for knowledge sharing with high uncertainty;
Strategy for knowledge sharing with high ambiguity.
The strategy for sequential and linear knowledge sharing processes aims at optimising clear routes with defined outcome and at making sure that the process is running within accepted and determined frame. The knowledge is mainly explicated in forms of standards, and instructions. Therefore, there is little uncertainty about the process, other´s behaviour or potential harm because those situations are well‐known to the actors involved. This strategy is applied to mass production, for example, car production where knowledge is understood just as a production input factor (cf. Renn 2008, pp. 189‐191). Furthermore, we differ between three strategies for complex knowledge sharing system with the emphasis on one of the three main features: complexity, uncertainty and ambiguity. The first knowledge sharing scenario with high complexity but low uncertainty and ambiguity refer to complex problems linked to specific causal paths. This strategy needs more systemisation and experience in order to get an overview of the complex relationships behind. In this case, specific actions may mislead, complexity demands complex methods (cf. Renn 2008, pp. 191‐193). Knowledge sharing scenario of high uncertainty but less complexity and ambiguity, refers to too little information, for instance, about the counterpart´s behaviour or about the potential risk or output of knowledge sharing. Accordingly, uncertainty can be reduced by increasing complexity through acquisition of additional information. The central issue is finding an adequate balance between investing all efforts (costs) to acquire wide‐ranged information keeping cautious about uncertainty. Alternatively, one can try to coexist with uncertainties taking certain efforts, trusting that additional damages will be reasonable and learning to be more flexible and adaptive to surprises. In this context, the question arises: what is reasonably justifiable? What are the suitable instruments for dealing with high uncertainty? In regard to knowledge sharing, it can be asked how much uncertainty one is willing to accept (cf. Renn 2008, pp. 193‐197) The third scenario characterised by high ambiguity requires attention to different and conflicting targets and perceptions. In regard to knowledge sharing, ambiguity is very present because knowledge sharing requires at least two actors and thus, there are multiple views and targets among organisational members. In order to illustrate how the suggested general strategies of knowledge sharing can be applied in real life, let us consider an example of university landscape in Russia. A short introduction to the context is needed in order to understand the degree of complexity, uncertainty and ambiguity of the knowledge sharing process. At the moment Russia’s education system as a whole is experiencing tremendous reforms and downsizing when departments and the whole universities are merging, obsolete connections between people and departments are disassembled and then assembled again, but in a new order. During the last 5‐7 years university life in Russia has turned from a ‘safe harbour’ into a turbulent environment; professors are now required to be not only knowledgeable, but also entrepreneurial, modern, mobile, international, etc. Furthermore, there is an increasing number of subjects taught at the same time, sometimes in both native and foreign languages; growing interdisciplinary approach of subjects which are getting more and more interwoven with each other; emerging distance‐learning and vocational programmes of different kinds. Another trend – developing ICT based learning, introducing e‐learning platforms in educational institutions. These circumstances suggest that explicit and especially tacit knowledge exchange between people is needed – to keep track of the networks trying to preserve relationships and expertise. The abovementioned features prove that the knowledge sharing process within universities in Russia is highly complex. Knowledge sharing process in a university is also uncertain which means, according to the definition given earlier, that there is no clear understanding about the cause‐effect relationships within the system. People are uncertain about getting benefit which discourages them from knowledge sharing. The third feature of knowledge sharing process – ambiguity – is very present. When we speak about teachers and their intellectual property, which is e‐books, PowerPoint slides, case studies, it is always hard to find a consensus about what is more valuable in knowledge sharing because perceptions highly differ. The well‐known peculiarity of Russian
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Madeleine Block and Tatiana Khvatova society is low trust among people of the same organizational level and low trust of people to the management (to the government) (cf. House et al. 2004). According to the survey of Levada Center held in 2010, two thirds of the respondents answered that one should not trust the majority of people and be careful. Younger people aged 25‐ 39 with higher education were especially cautious (71% said one should not trust to people). This partly explains the results of another survey held in a business school in Saint‐Petersburg (Russia) showing why many attempts to introduce e‐learning and to make teachers upload their teaching materials to the platforms fail: many people think that their materials will be used by somebody else (cf. Khvatova and Lichy 2012, p. 97). In the same survey most people stated that they would share knowledge in the e‐learning system if they received monetary benefits from that. This example also emphasizes the ambiguity of knowledge sharing process in universities. So, we observe that all three features of knowledge sharing process are present in the university environment. However, in our opinion, ambiguity is the highest influencing dimension in the discussed context. It is very much combined with uncertainty. People are mostly afraid that their knowledge is misused, that they do not get anything valuable in return for sharing their knowledge, or they transfer their competence to others and become redundant, etc. What can be recommended to make the knowledge sharing work? Usually in systems with high degree of ambiguity a socially acceptable development path should be chosen which means ‘resolving value conflicts and ensuring fair treatment of concerns and visions’ (Renn 2008, p.188). The consensus should be reached through stakeholder dialogs aimed at harmonizing organizational targets with members’ own interests. There are probably various perceptions of unfairness in the distribution of benefits linked to the risk of being in the end the foolish among the organisational members. Therefore, a consensus considering all interests is difficult or rather impossible to put into practice because of the plural views of organisational members. However, the different views of the involved actors need to be reflected to be able to find a solution which is accepted by at least the critical mass or to find an agreement on a certain objective with which everybody would agree. Finally, the goal might be to find an appropriate objective and consensus between those who believe the knowledge sharing is worth doing and those who believe it is not, due to various reasons. How to determine the basic conditions and to harmonise organisational targets with members´ own interests? In this connection, organisational value and norm system seems to play an important role. In regard to knowledge sharing it means that the main task in reducing ambiguity is to find regulatory norms, values and rules acceptable for most of the involved actors. It is a search for a win‐win strategy perceived as giving benefit to all parties within organisations. One option is to emphasise the mutual benefits which are brought by knowledge sharing as a vision which in turn is conditioned by the acceptance of the shared values and vision by all the actors. An alternative is to provide bonuses to potential sufferers of knowledge sharing process, for example, to employees who are mainly involved in routine work and cannot actively participate in knowledge sharing in sense of learning and applying situational and problem‐related knowledge. In particular, this strategy requires involvement and communication which would help to search for solutions dealing with the interests and values of organisational members and to resolve conflicts among them. In this context, face‐to‐face methods tend to be more suitable for the sharing of knowledge which come along with higher information richness and reduce the ambiguity of implicit knowledge. Ambiguity is usually coupled with high degree of uncertainty and complexity and thus, must be combined with the other two strategies (cf. Renn 2008, pp. 197‐199).
5. In conclusion In this paper the angle of view for studying knowledge sharing within organisations has been turned away from focusing on common types of knowledge (explicit and implicit knowledge) towards understanding knowledge sharing as a subsystem of complex social system of organisations. The focus of this study is put on inherent features of knowledge sharing which are complexity, uncertainty and ambiguity. Based on those features, we developed strategies for managing intra‐organisational knowledge sharing. Figure 3 shows graphically the four knowledge management strategies. The first strategy (I) regards knowledge sharing process with very low level of complexity, uncertainty and ambiguity and thus, represents one of the extreme strategies. Such linear processes demand only routine procedures for knowledge sharing with specialised knowledge acting as direct production input factor as, for example, in mass production. High complexity is a result of many interacting factors given by the environment. For high complex knowledge
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Madeleine Block and Tatiana Khvatova sharing process with low uncertainty and ambiguity (II) the causal relationships between the factors are known and there are little ambiguous opinions. If uncertainty is high in knowledge sharing process while complexity and ambiguity are low (III), the strategy proposes to prepare organisational members for unknown and unpredictable happenings. Furthermore, the uncertainty can be reduced by increasing the information base as well as transparency within the process and among the roles and duties of the employees. In the fourth case (IV), the ambiguity is high, which goes along with high uncertainty and complexity; otherwise, such a plurality of views would not exist. This strategy represents the other extreme case of possible knowledge sharing strategies. Ambiguity reflects conflicts of interests and values which need to be reconciled, for example, with vest of a knowledge sharing culture represented by the management who give example of knowledge sharing and transparency of decision‐making.
Figure 3: `Knowledge sharing cube´: knowledge sharing strategies and the features of complexity, uncertainty and ambiguity It is difficult or rather impossible to control complex economic and social systems because today´s actions lead to unknown future results and to possible clashes of different perceptions and targets. We consider that knowledge system is not an autonomous system, but rather connected to other organisational subsystems and beyond. A starting point for future studies would be researching into different states and the dynamics of knowledge sharing system. In this context, oscillations may occur due to environmental influences or delays in applying strategies and methods. Another fruitful way of further research would be determining proper instruments based on the formulated strategies which could serve as a guideline for organising an iterative process of navigation through the complex and dynamic system of knowledge sharing within organisations. In particular, we consider that development of effective communication instruments for managing knowledge sharing is relevant.
References Bauer, J. (2008) Das Gedächtnis des Körpers. Wie Beziehungen und Lebensstile unsere Gene steuern, 2nd edition, Munich: Piper Verlag. Ebeling I., Vogelauer, W., Kemm, R. (2012) Die Systemisch‐dynamische Organisation im Wandel. Vom fließenden Umgang mit Hierarchie und Netzwerk im Veränderungsprozess, Bern, Stuttgart, Wien: Haupt Verlag. nd Endruweit, G. (2004) Organisationssoziologie, 2 edition, Stuttgart: Lucius & Lucius. Köhne, M. (2004) Die Bedeutung von intra‐organisationalen Netzwerken für den Wissensaustausch in Unternehmen, Bamberg: Difo‐Druck. Esser, H. (2000) Soziologie. Spezielle Grundlagen, Band 3, Soziales Handeln, Mannheim: Campus Verlag. Hansen, M.T., Nohria, N., Tierney, T. (1999) `What´s your Strategy for Managing Knowledge?´, Harvard Business Review, vol. 77, no. 3, pp. 105‐116. House et al. (2004) Culture, Leadership, and Organizations: the GLOBE study of 62 societies, Thousand Oaks: Sage Publications. Huysman, M., de Wit, D. (2004) `Practices of Managing Knowledge Sharing: Towards a Second Wave of Knowledge Management´, Knowledge and Process Management, vol. 11, no. 1, pp. 81‐92.Nonaka, I. and Takeuchi, H. (1995) The Knowledge‐Creating Company: How Japanese Companies Create the Dynamics of Innovation, New York: Oxford University Press.
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Madeleine Block and Tatiana Khvatova Khvatova, T. and Lichy, J. (2012) `Exploring Technology to Modernize Undergraduate Teaching´, proceedings of EDiNEB International Conference `The Role of Business Education in a Chaotic World´, Haarlem, the Netherlands, May 2012, pp. 93‐99. th Levada Center (2010) Analytical Center of Yuri Levada, Аналитический центр Юрия Левады, viewed 11 of May 2013, URL=www.levada.ru. Nonaka, I. and Takeuchi, H. (1997) Die Organisation des Wissens. Wie japanische Unternehmen eine brachliegende Ressource nutzbar machen, Frankfurt am Main: Campus Verlag. North, K. (1998) Wissensorientierte Unternehmensführung: Wertschöpfung durch Wissen, Wiesbaden: Gabler. Polanyi, M. (1985) Implizites Wissen, Frankfurt am Main: Suhrkamp, translated by Horst Brühmann (original version `The Tacit Dimension´, 1966). Probst, G.B., Romhardt, K. (1998) Bausteine des Wissensmanagements – ein praxisorientierter Ansatz, in: Handbuch Lernende Organisation, Wiesbaden: Gabler, pp. 129‐143. Probst, G.B., Raub, S., Romhardt, K. (1999) Wissen managen – Wie Unternehmen ihre wertvollste Ressource optimal nutzen, rd 3 edition, Wiesbaden: Gabler. Renn, O. (2008) Risk Governance. Coping with Uncertainty in a Complex World, London, Sterling: Earthscan.
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Organizational Culture vs. Structure: An Academic Case Study Razvan Bogdan, Versavia Ancusa and Oana Caus Politehnica University of Timisoara, Timisoara, Romania razvan.bogdan@cs.upt.ro vancusa@cs.upt.ro oana.caus@cs.upt.ro Abstract: In order to implement knowledge management in an organization, a first step is assessing the readiness. The readiness is directly influenced by the organization culture, structure and infrastructure. This paper aims to assess the first two factors in a particular case, the Politehnica University of Timisoara (UPT). Due to the fact that the organization structure is well‐defined, our efforts centred mainly in determining the organizational culture. The UPT, due to the various faculties and administrative divisions has created a non‐linear organizational culture. Apart from the established way of assessing organizational culture, the Organizational Culture Profile (OCP), based on Q‐sort, we focused on analysis of social networks interactions in order to determine organizational culture. We correlated the collected data with the age distribution, in order to investigate possible discrepancies. In the organizational structure the most influential were higher level academics with an older bias. Unlike the organizational structure, on a cultural level, the most influential were middle level, young to middle age individuals that showed the highest availability for communication. This non‐congruency was even further illustrated when paired with student‐teacher relationship data. The same middle level individuals had the highest communication strength, thus the highest influence on the students. Even the total number of connections indicated the same individuals as the most influential. An interesting fact implied the gender distribution. While in the organizational structure there is a clear partiality towards the males, in the organizational culture there is no such bias, both sexes being (almost) equally influential. Further analysis including all the data, put under scrutiny the readiness for knowledge management in UPT. As a result, a guideline and several tactics are proposed in order to improve the readiness. Keywords: social network analysis, organizational culture, organizational readiness, number of connections, centrality, communication strength, influence
1. Introduction Knowledge management (KM) readiness was previously defined (Mohammadi, et al., 2009) as successfully adopting, using and benefiting from knowledge management in a certain organization, department or team work. Readiness is an attribute of organization’s ability in attaining all these factors. It should be applied in the early planning strategies of the knowledge management approaches. Previous papers like (Holt, 2000) state that readiness is an essential precondition for an organization that aims at succeeding when faced with organizational change. In order to successfully implement KM plans, organizations need to assess if they are properly prepared to face such a challenge. KM initiatives involve costly investments in the infrastructure, as well as in personnel. Failure to assess organizational KM readiness might cause major time and money loss. “Politehnica” University of Timisoara has benefited recently from major investments in the infrastructure with budgets of approx. 12 million Euros in the past 3 years. The new library construction as well as the material base revitalization guarantees that the infrastructure is up‐to‐date and favourable to implementing knowledge management. The university’s hierarchical structure is well‐defined and can be modelled using a tree topology, with the Chancellor as the top node. Essentially, it is a classical rigid structure which underwent only minor changes in the past 50 years. These changes relate more to the addition of new branches (such as new faculties or departments), yet they do not alter the original nature of the structure. On the other hand, the university culture has undergone a definite transformation process especially in the last 24 years, since the fall of the communist regime. Fuelled by the new cultural influences of the West, the social aspects have slowly changed. Those changes reach now a point in which a knowledge management system is needed and this paper aims at evaluating if the current situation is compatible with such a capitalist practice. This paper is structured as follows: the literature review offers a survey of knowledge management techniques used to asses readiness, the research design presents the parameters of the exploration, followed closely by the results and discussion of the study. In the end, in the conclusion section several tactics are proposed in order to improve readiness.
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2. Literature review The readiness of an organization is a guideline for the management in order to establish if the organization is ready to face and implement assorted KM initiatives (Desouza & Raider, 2006). A spectrum of studies proposes various methods to be used in order to assess the readiness of different organizations. A study related to the USA air force readiness for successful KM implementation is presented in (Trent, 2003). The research method presented in this article is based on Change Content Variables, Process Variables, Contextual Variables and Individual Variables. Each of these parameters is following different degrees of change that occur in the organization during the KM implementation. In (Holt, et al., 2004), individual, context, content, process measures and KM attitudes are taken into consideration in order to assess KM readiness. In 2009, (Mohammadi, et al., 2009) proposed a study to determine KM readiness based on five organizational antecedents for effectiveness such as vision for change, infrastructure, structure, support for change and culture of knowledge. Further on, (Jalaldeen, et al., 2009) suggests that organizational readiness can be assessed by taking into consideration both organizational and individual factors. Beig et al. (2011) advance a modality of assessing KM readiness in a learning environment based on 10 dimensions that should be considered: knowledge and learning strategy, learning dynamics, organizational culture, technological infrastructure, organizational structure, customers, partners and suppliers (external sources of knowledge), tacit and explicit knowledge process, collective learning‐based incentives, performance and knowledge sharing. In all these cases, two main coordinates are assessed: structure and culture, and based on the correlation of the two, a conclusion is drawn. Table 1 presents the clustering of the previous studies’ parameters into the structure and culture columns. A third column was added to present the mixed variables, such as support for change that needs both culture and structure assistance. Table 1: Structure and culture categories in KM readiness studies Study (Trent, 2003) (Holt, et al., 2004) (Mohammadi, et al., 2009) (Jalaldeen, et al., 2009) (Beig, et al., 2011)
Structure‐related process variables, contextual variables context, content, process measures various structure measurements organizational factors organizational structure, customers, partners and suppliers, collective learning‐based incentives, performance and knowledge sharing
Culture‐related individual variables
Other / mixed change content variables
individual measures, KM attitudes culture of knowledge
individual factors tacit and explicit knowledge process, learning dynamics, organizational culture
support for change, infrastructure knowledge and learning strategy, technological infrastructure
While usually organisational structure is easily measured, assessing organizational culture can be viewed as a problem of evaluating the interrelationships’ exceptional structure among different individuals and programs. Qualitative methods such as interviews of the employees and/or observations of their interactions are most commonly used in measuring organisational culture. More traditional KM approaches include General Demographics, Organizational Culture Assessment Instrument (OCAI), Organizational Culture Profile (OCP) and Organizational Commitment (OC). Lately, due to the development of virtual interactions, Social Network Analysis (SNA) is also a valuable instrument in assessing organisational culture. Table 2 presents a methods summary. While General Demographics is a simple, indirect, yet effective method of statistically assessing the respondents’ profile; OCAI, OCP and OC need direct interaction with the employees. The survey complexity varies among these three methods and there are several pointers (Kulkalyuenyong, 2012) that such direct approaches might not be extremely accurate. Conversely, SNA is an indirect approach that measures employees’ past interactions, thus providing a more truthful cultural context image.
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Razvan Bogdan, Versavia Ancusa and Oana Caus Table 2: Methods used to assess organisational culture – a comparison (modified from (Kulkalyuenyong, 2012)) Methods General Demographics OCAI OCP Organizational Commitment Social Network Analysis
Collection methodology Database access – statistical pack Employees survey – sort 100 items Employees survey – sort 28/40/54 items Employees survey – answer 6 questions Social network access and SNA tool
Purpose To know respondents’ profile To test current and preferred organizational culture type To test employees’ perceived organizational culture To test employees’ commitment level To quantify past employees’ interactions
In (Lurie, et al., 2009) the authors have taken into consideration three possible settings: team function, interdisciplinary composition of advisory committees and relationships between key function directors. Applying social network analysis reveals precise aspects from team functioning and proves summary descriptions of the various departments’ interdisciplinary degree. When applied to relationships realm, SNA emphasizes potential problem regions in dealings among academic departments. Measuring such aspects in an objective way, if SNA is not applied, is a difficult endeavour. Waldstrøm (2003) argues that one of the social networks main contents is the cultural aspect as it is responsible for the values transfer and general information flow. Furthermore, the author emphasizes that social networks are the main information carriers that assure the organizational culture’s adjustment and maintaining. For this reason, identifying and defining social networks in an organization is highly important. Social networks in organizations are compared in (Krackhardt & Hanson, 1993) with a living organism’s nervous system, where the bones stand for the formal organization, while the organization’s formal and informal structures have been presented as the de jure and the de facto correspondingly. It has been discussed in (Waldstrøm, 2003) that in state‐of‐the‐art literature there is a dichotomy regarding formal/informal structures in organizations, described as official/unofficial, prescribed/emergent issues. These terms can be used interchangeably to a large extent, therefore formal structures and social networks are primarily used among organizational terminology. The formal structures are mainly normative due to the fact that the individual’s position in the formal organization is determined by a certain structure, namely the organizational chart. Conversely, the social network has a descriptive property because such networks can be just observed and influenced at best. The informal organization is dependent both on formal structure and organization culture (Stevenson & Bartunek, 1996). However, it has been proved that there is a slice of difference between organizational culture and the informal organization: “An organisation’s culture develops over time, is slow to change, and is reinforced by the practice of people recruiting others whom they ‘like’. The informal organization, by contrast, is quick to grow and transmute according to changing circumstances and the interaction of individuals within the organisation” (Waldstrøm, 2003).
3. Research design In order to evaluate the university’s structure, this study used the Human Resources Department data to plot an organisational chart of the management level, adding to that network, data regarding the age and gender of each individual. The data was also analysed using traditional statistical analysis. The university culture was assessed using two avenues: OCP and social networks. The OCP test was taken by a statistically significant fraction of the employees using an on‐line form. For the social network assessment the authors used a Facebook application developed for academic purposes (snacorse.com/getnet) in order to capture one’s network of friends. Several colleagues allowed the capture of their networks and using only university‐related data from them. The social networks were plotted using a dedicated tool, Gephi, which additionally allowed to determine clustering as well as several other pertinent coefficients (centrality, betweeness). Both data sets were correlated in order to render a comprehensive cultural dimension picture.
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4. Results and discussion The university’s upper and middle level general demographics statistical data is presented in Table 3. When split between the administrative and the strictly academic community, the data paints a clear picture of the imbalance between those two. The research and teaching management community is highly male dominated (90.16%), while the administrative group is much more balanced (46.34% males). Table 3: Upper and middle level general demographics statistics Parameter
Whole university
Administrative
Research & teaching
Male subjects
74
19
55
Female subjects
29
22
7
Age Mean
54.70
50.56
57.48
Age Median
57.00
51.00
59.00
Age Standard Deviation
8.53
8.46
7.43
Age Kurtosis
‐0.19
‐0.78
0.75
Age Skewness
‐0.73
‐0.48
‐1.00
Age Range
35
31
34
Age Minimum
32
32
33
Age Maximum
67
63
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The age marks another division between the two communities. Mean values are, to some extent, the same, although the kurtosis parameter suggests a significant difference in the distribution of values. As presented in Figure 1, the comparative age histogram shows that academia management falls highly in the aged category and the following generation of management is not yet developed. Meanwhile, although the administrative community presents a peak at around 60, the next age generations are starting to develop more freely.
Figure 1: Comparative age histogram between the administrative and teaching & research communities In order to fully understand what caused such differences inside the same organisation the Organizational Culture Profile (OCP) 40 cards version was used in order to test the employees’ perceived organizational culture, and the average results are presented in Table 4. The most important dimensions are stability (r=.85 p<0.05), performance orientation and competitiveness. The results seem to be conflicting since stability is not the best environment for competitiveness. Moreover, innovation, which should be one of the leading dimensions in an academic environment, does not make Top 3. Another dimension which one would expect to matter in an academic environment – social responsibility – ranks only 4th. The supportiveness, which knowledge sharing readiness measures, ranks only 5th among the cultural dimensions of OCP. The results from OCP were in some way ambiguous and therefore further study of our colleagues’ social networks was required.
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Razvan Bogdan, Versavia Ancusa and Oana Caus Table 4: Median OCP 2 30
37 10 38 Most Characteristic
4 24 22 26
3 14 34 27 15 39 9
36 5 17 33 16 32 12 8 29 35 25 19 23 15 28 Neither Characteristic Nor Uncharacteristic
1 7 18 31
21 11 6 13 40 Least Characteristic
Legend: 1. Adaptability 2. Stability 3. Being reflective
21. Decisiveness 22. Being competitive 23. Being highly organized
4. Being innovative 5. Being quick to take advantage of opportunities 6. Taking individual responsibility
24. Achievement orientation 25. Having a clear guiding philosophy 26. Being result‐oriented
7. Risk taking 8. Opportunities for professional growth 9. Autonomy
27. Having high performance expectations 28. Being aggressive 29. High pay for good performance
10. Being rule‐oriented 11. Being analytical 12. Paying attention to detail 13. Confronting conflict directly
30. Security of employment 31. Offers praise for good performance 32. Being supportive 33. Being calm
14. Being team‐oriented 15. Sharing information freely 16. Being people‐oriented
34. Developing friends at work 35. Being socially responsible 36. Enthusiasm for the job
17. Fairness 18. Not being constrained by many rules 19. Tolerance
37. Working long hours 38. Having a good reputation 39. An emphasis on quality
20. Informality
40. Being distinctive / different from others
In Figure 2 the university structure is plotted using complex networks. Node colour is used to represent age: the darker the node, the greater the age. The node size is linearly correlated with the closeness node centrality, i.e.: “the efficiency of each vertex (individual) in spreading information to all other vertices” (Okamoto, et al., 2008). The complex network was rendered using a Force Atlas layout which facilitates the cluster visualization. No further manual adjustments were used to present the layout. In order to depict data, Gephi (www.gephi.org) was used.
Figure 2: University’s complex network
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Razvan Bogdan, Versavia Ancusa and Oana Caus On the right side of the network is the administration community whereas the teaching and research group is on the left side. The largest node represents the Chancellor and is shown to be the only way of interfacing the administration and academia. Using a type of analysis characteristic of complex networks, the number of nodes versus node degree was plotted and Figure 3 shows the result. The power‐law distribution, characteristic to real‐life systems is, as expected, identifiable.
Figure 3: The number of nodes versus node degree It can be observed that the university’s chancellor has the utmost node degree meaning that is highly linked. Subsequently, the vice‐chancellors cover the following node degree values. The obtained distribution shows a skewed node‐degree distribution in which most nodes have only few links. The contrast is represented by the chancellor and vice‐chancellors who are extremely linked. This shows that, in the organizational structure, the most influential are the higher level academics with an older bias. In Figure 4 we mapped the structure with the upper and middle level management’s gender. Node size is proportional with closeness centrality and a community detection favourable layout was used.
Figure 4: University managements’ complex network correlated with gender
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Razvan Bogdan, Versavia Ancusa and Oana Caus In the administrative community, similar levels of management (denoted by similar node sizes) show a balanced gender distribution, while in the academia community, the females tend to have low‐level management positions. The previously found imbalance using demographics distribution is added a new dimension when using the complex networks representation. The “glass ceiling” in the academia is depicted fairly obvious. Using SNA to study the organisation culture, we analysed a number of Facebook complex networks from our colleagues, both from research and administrative staff. The aim of these experiments was to determine the most influential individuals from a cultural point of view and not from the organizational structure. Two Facebook representations are presented in Figure 5. Dark nodes represent females, light nodes males. Node size is again correlated with closeness centrality. No clear separation can be seen between the administrative and teaching & research community. The gender distribution is relatively balanced, notwithstanding the size of one’s social network.
Figure 5: Various social networks It should be mentioned that the most influential individuals were the young to middle age ones who have the highest availability for communication. Almost none of the university’s higher‐level management is present in the network. A further analysis of these networks reveals that the same non‐congruency is maintained when paired with student‐teacher relationship. The highest communication strength is maintained by the middle level individuals. Therefore the highest influence on students can be claimed by the middle level academics.
5. Conclusions After conducting the previously‐presented experiments, it can be noted that the administrative part is ready to implement knowledge management whereas the teaching and research community is not yet ready for such initiatives. In order to improve this status, several guidelines can be suggested and targeted at the academia, where the rift between culture and structure is most severe. Since change starts at the top, the higher management team should be more available for communication with the middle and low level communities. This might be obtained through: classical all‐hands meetings, higher‐management discussions with low‐level structures/departments and effective dialogues between HR staff members and academic and administrative staff. Social networks such as Facebook can be an important tool in improving communication and openness between various hierarchy levels. Another point to be addressed is the employees’ age distribution. In this respect, this study proposes the creation of programs that allow responsibilities to be assumed by any university staff member and, equally important, that encourage younger personnel to express opinions, proposals and act on them properly. Envisaged changes should not be implemented all at once, a certain gradual increase would allow for a gentle inter‐generation exchange. A key‐point in implementing this measure is to create a safe environment in which anyone can speak their mind. By doing this, the gender bias should also be solved since a safe environment provides equal opportunities for both females and males to succeed.
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Acknowledgements The authors would like to thank Mrs Nicolina Adamescu, UPT staff member, for the provision of the human resources data and all university fellows that spent precious time answering quizzes and allowing permission to use their Facebook networks images.
References Beig, L., Mirian, M. S., Ghazi, T. M. S. & Kharrat, M., 2011. A Framework for the Assessment of Knowledge Management Readiness of an organization while transferring into a Learning Organization. Passau, Germany, Proceedings of the 12th European Conference on Knowledge Management, pp. 74‐87. Desouza, K. C. & Raider, J. J., 2006. Cutting Corners: CKOs and Knowledge Management. Business Process Management Journal, 12(2), pp. 125‐135. Holt, D., 2000. The Measurement of Readiness for Change: A Review of Instruments and Suggestions for Future Research. Toronto, Canada, The Annual Meeting of TheAcademy of Management. Holt, D. T., Bartczak, S. E., Clark, S. W. & Trent, M. R., 2004. The Development of an Instrument to Measure Readiness for Knowledge Management. Hawai, IEEE Computer Society. Jalaldeen, R., Karim, N. & Mohamed, N., 2009. Organizational readiness and its contributing factors to adopt KM processes: A conceptual model.. Communications of the IBIMA, Volume 8, pp. 128‐136. Krackhardt, D. & Hanson, J. R., 1993. Informal networks: The company behind the chart. Harvard Business Review, 71(4), pp. 104‐113. Kulkalyuenyong, P., 2012. Analysis of Organizational Culture and Commitment to the Ministry of Public Health under the Central Administration: A Comparative Study of Service Agents and Policy Agents, School of Public Administration, Chulalongkorn University, Thailand: PhD Thesis. Lurie, S., Fogg, T. & Dozier, A., 2009. Social network analysis as a method of assessing institutional culture: three case studies. Academic Medicine, 84(8), pp. 1029‐1035. Mohammadi, K., Khanlari, A. & Sohrabi, B., 2009. Organizational Readiness Assessment for Knowledge Management. International Journal of Knowledge Management, 5(1), pp. 25‐45. Okamoto, K., Chen, W. & Li, X.‐Y., 2008. Ranking of closeness centrality for large‐scale social networks. Changsha, China, Proceedings of the 2nd International Frontiers of Algorithmics Workshop (FAW'2008). Stevenson, W. B. & Bartunek, J. M., 1996. Power, Interaction, Position and the Generation of Cultural Agreement in Organizations. Human Relations, 49(1), p. 75. Trent, M., 2003. Assessing organization culture readiness for knowledge management implementation: the case of Aeronautical systems, Ohio: Air university. Waldstrøm, C., 2003. Understanding Intra‐organizational Relations through Social Network Analysis, Department of Organization and Management Aarhus School of Business: PhD Thesis.
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Entropy vs. Organizational Learning and Dynamic Capabilities: The Thermodynamic Analogy Pavel Bogolyubov1, Evgeniy Blagov2 and Boyka Simeonova3 Dpt. of Management Learning and Leadership, Lancaster University Management School, UK 2 Dpt. of Information Technologies in Management, Graduate School of Management, St. Petersburg University, St. Petersburg, Russia 3 School of Management, Royal Holloway, University of London, London, UK p.bogolyubov@lancaster.ac.uk blagove@gsom.pu.ru Boyka.Simeonova.2010@live.rhul.ac.uk
1
Abstract: The paper offers a theoretical framework bringing together the matters of organizational knowledge, dynamic capabilities, organizational learning, knowledge creation and innovation by drawing parallels with thermodynamics and informatics and making use of such concepts as entropy, chaos and disorder, equilibrium and uncertainty. The idea of entropy originated in the XIX century as a means of explaining the basic principles governing the operation of – at the time – steam engines, but gradually developing into one of the most fundamental concepts in modern Physics. Being effectively a measure of disorder in a system (and thus, in its original sense, explaining the system’s inefficiency through the dissipation of ‘useful’ energy), it made its way into quite a few other fields, often quite remote from thermodynamics, wherever the notions of uncertainty and/or chaos and disorder could be made use of. In informatics and cybernetics, for example, it is used to describe how the act of acquiring information reduces uncertainty (e.g., if one checks out the weather forecast, their own predictions of the next day’s weather are likely to become somewhat more accurate in probability terms). In economics and sociology it was in use, sometimes avoiding the direct application of the term, from mid‐XX century, appearing in the works of scholars such as Shannon and Weaver, Pareto, Capecchi, Möller, McFarland, Carvat and Kucera as well as others, leading to the formulation of the unified Social Entropy Theory in 1990 ((Bailey 1990)). Somewhat surprisingly, no examples of its use can be found in the area of organizational knowledge and capabilities; it would appear that the leap somehow has not yet been made. In this paper we attempt to bridge the gap by highlighting the analogy between an organization and a black box process with inputs, internal process and outputs, not entirely dissimilar from Carnot’s engine. It, in turn, lets us draw parallels and make a number of propositions concerning the relationships between capabilities, learning, knowledge and other related matters. The resulting framework allows further elaboration in two directions, both towards the development of more advanced mathematical apparatus and its operationalization with high applied potential. Although relying to a degree on some basic knowledge of scientific concepts and making fairly limited use of mathematical notation, the paper is aimed at the general audience and, hopefully, will be of interest to scholars and practitioners alike. Keywords: entropy, organizational learning, learning organization, organizational capabilities, dynamic capabilities
1. Introduction: The use of entropy and related concepts in social sciences Although originally a natural sciences concept, entropy, as well as related matters such as equilibrium, uncertainty, information and various re‐formulations of uncertainty measures avoiding the direct use of the term (e.g., such as Shannon and Weaver’s H measure ‐ (Shannon and Weaver 1949) has been used in economics and sociology beginning from the first half of the XX century. For example, Pareto’s work on equilibrium (Pareto 1935) has arguably paved the way for the development of the field, and it became quite popular in functionalism (e.g., (Parsons and Shils 1951)). The application of the entropy in the statistical sense begun in the 1960s (Coleman 1964) and gradually intensified through the work of such sociologists as Capecchi, Möller, McFarland, Charvat and Kucera and so on (Capecchi and Möller 1968), (McFarland 1969), (Charvat and Kucera 1970) to give a fairly random few examples. Several decades of development culminated in formulation of the unified Social Entropy Theory in 1990 (Bailey 1990). It is, however, somewhat surprising that despite its close link to the general systems theory and the popularity of the systems approach to organizational learning ‐ first and foremost due to Senge’s work (Senge 1992), as well as the connection with the information theory, entropy as a concept remains virtually unused in relation to the organizational learning. To the best of our knowledge, so far there have been only two papers published on it: (Bingquan, Likai et al. 2009) used an entropy‐like approach to measuring the learning organization’s effectiveness, and the other one (Xueguo 2008), apparently uses a similar approach towards organizational
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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova learning, although it is only published in Mandarin in a journal that does not appear to be in wide circulation in the West. In this paper, we attempt to bridge the gap and to outline a number of possibilities for the use of entropy and the related concepts based on thermodynamics, statistical mechanics and information theory, to describe and measure various processes associated with organizational learning.
2. Entropy: the basic definitions The concept of entropy developed in the mid‐XIX century with the advent of a branch of physics called thermodynamics – a field (in its classical form), according to Merrian‐Webster’s Dictionary ‐ ‘that deals with the mechanical action or relations of heat’ (Anonymous 2012). At the beginning, the thermodynamic understanding of entropy came out of Carnot’s work related to the ideal ‘heat engine’ – a machine (steam engines originally) that utilises a flow of thermal energy from a heat reservoir to a heat sink, producing mechanical work as a consequence, and where entropy increases if a portion of the energy is made unavailable to produce work. Closer to the end of the century the work of Boltzmann on developing the statistical mechanics’ understanding of entropy begun treating it as a measure of order or disorder, and this is still a popular understanding of its fundamental meaning (Anonymous 2012). The ‘disorder’ meaning of the concept could be more easily explained by examining the following formula for a system with a set of i discrete energy states Ei (the so‐called Gibbs entropy):
where S stands for entropy, kB is Boltzman’s constant, pi is a probability of the system to be in the given state, and the summation is across all possible states. As follows from the formula, the entropy is at zero if the only one state is possible ‐ i.e., the perfect order, and it reaches maximum if all states are equally probable, i.e., p1=p2=…=pn=1/n. Putting together the two definitions of entropy, we would arrive at a conclusion that the more chaotic a system is, the greater becomes its ability to distribute energy evenly making it unavailable to do the work. Arguably one of the most fundamental laws of physics is the second law of thermodynamics which states that the entropy of closed system cannot decrease, or: ∆S ≥ 0 (2) In other words, a closed system will always gravitate towards the state of the maximum disorder. Another understanding of entropy came later on from the information theory (discrete Shannon entropy ‐ (Frigg and Werndl 2010):
which, the obvious exclusions of the constant and the logarithm’s base, is identical to (1). The probabilities included in this formula, although somewhat open to interpretation, mean the ‘belief’ that a system can be found in a particular state, the word itself being employed here in a ‘justified true’ meaning, rather than anything more subjective. The meaning of the information science’s definition of entropy follows directly from the formula: the more we know about the system, the more certain we can be about its state, thus acquiring information leads to a reduction of uncertainty and, as a consequence, entropy. If we don’t have any information about the system, all states are equally probable, p 1=p2=…=pn=1/n, and the entropy is at its maximum value, S(P)=log n; conversely, if we have acquired enough data to be certain about its state, only one pi=1, and S(P) = 0.
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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova
3. The application of the concepts to organizational learning In order to illustrate the possibilities the thermodynamic analogy opens up, we shall refer to the mathematical metaphor suggested by (Winter 2003)_ENREF_14, as cited in (Vera, Crossan et al. 2011). To illustrate it, we shall use a crude schematic representation of a model organization as an entity that takes resources (A), processes them (B) and produce outputs (C) (Fig. 1):
Inputs (A)
Resource processing (B)
Outputs (C)
Figure 1: The schematic representation of a firm (Winter 2003), defines operational capabilities as such B that leads to constant C, i.e., C’s first derivative being zero (although it’s worth pointing out that it is the A/C ratio that we are predominantly interested in, i.e., we would be expecting the same outputs from the same inputs): If a company exhibits dynamic capabilities, it should be able to produce more outputs with constant inputs, and the derivative of the A/C ratio over the time will be non‐zero: which conceptually equates to single‐loop learning, i.e., that the organization is getting better and doing its ‘day job’. Should things go really well, they will challenge their fundamental assumptions and will also become better at learning how to improve, thus leading to the second derivative being greater than zero: What is important, however, is the obvious similarity between the representation on Fig. 1 and Carnot’s heat engine: both have some inputs (heating up the heat reservoir), a recombination process (heat transfer from the reservoir to the sink) and the output (mechanical work). The thermodynamic analogy – the Carnot engine metaphor, basic principles of thermodynamics and especially, the application of the entropy as a concept allows us to come up with a number of propositions: P1: In an organization that acts as a closed system – i.e., without significant amounts of information and knowledge exchange with the outside world – the entropy will increase over the time and eventually reach its maximum. This is what Argyris referred to as ‘dry rot’ (Argyris 1970), although we would rather relate it to a notion of spontaneous organizational forgetting/unlearning without making a value judgement. This leads to: P2: In an organization as a closed system, the operational capability will deteriorate over the time: unless counteracted with external inputs decreasing system’s entropy, i.e., negentropy
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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova P3: The organizational learning of any kind in a ‘closed’ company is impossible, and it requires interaction with the outside world, which closely resonates with such models of learning organization as, e.g., Dixon’s (Dixon 1999), which relies heavily on external acquisition and internal dissemination of knowledge and challenges the approaches such as Kaizen, whereby operational improvements are expected to originate predominantly from within P4: An influx of information and knowledge from outside the company will decrease the entropy and increase capabilities, thus leading to (5), but not necessarily (6), as well as that P5: In the long run, that is to say, beyond the timeframes of mere fluctuations, the only innovation possible is that of the open kind, i.e., the process of innovation requires a sufficient degree of negentropy brought from the outside. Following the Carnot’s Theorem that states that no engine can work in the same conditions more efficiently than the ‘ideal’ one, the following can be proposed: P6: Theoretically, there is an upper limit for the operational capability (expressed in the A/C ratio) in the set of given circumstances.
4. Challenges, limitations and further steps The propositions outlined above are theoretical and rely on a rather idealistic view on organizations as closed systems, which is hardly a reality (Bailey 1990). In this sense, given that virtually any social system will be open to a degree, it would be more useful to think about it in terms of a dynamic equilibrium between the influx of knowledge and learning from the outside and the organizational forgetting/unlearning, whereby the sum total of the two will be zero, thus approximating the closed system state. Furthermore, at this stage we are not making a distinction between the definitions of entropy arising from thermodynamics, statistical mechanics and information theory, and although a fair amount of work has been done to prove fundamental similarities between the three ‐ e.g. (Frigg and Werndl 2010)_ENREF_8, we are fully aware of the differences between them. Instead of elaborating on it, we are making use of the understanding of entropy as a measure of disorder and its link to (in)efficiency of a system in terms of its capability of producing outputs. The question arising from this is that of the link between the degree of orderliness in an organization and its capabilities. Does it mean that a rigidly structured organization will have better capabilities than a ‘free‐form’ one? The intuitive answer would be a no, or at least a not necessarily, although whether this is true and the reasons for that – one way or another – would need further development. There is also the question of emergence and self‐organization, which may potentially link to such matters as swarm intelligence, neural networks and all phenomena related to chaos; e.g. (Gleick 1987). Besides, all points discussed above relate to the ‘classical’ thermodynamics and ignore its non‐equilibrium variety, which in itself poses a number of questions and has a variety of exciting opportunities to explore, such as the applicability of phase transitions metaphor and so on. The next challenge for all propositions would be testing them, which will inevitably involve their operationalization. How exactly can entropy and the flows of knowledge and learning be measured? What can the practical implications be? What are the applicability boundaries, apart from the obvious limitations of the model? All these represent potential areas for further research.
References Anonymous. (2012). "Definition of Entropy." Retrieved 23/10, 2012, from http://oxforddictionaries.com/definition/english/entropy?q=entropy. Anonymous. (2012). "Definition of Thermodynamics." Retrieved 23/10, 2012, from http://www.merriam‐ webster.com/dictionary/thermodynamics. Argyris, C. (1970). Intervention Theory and Method: a Behavioral Science View. Reading, Mass., Addison‐Wesley. Bailey, K. D. (1990). Social Entropy Theory. New York, State University of New York Press. Bingquan, H., B. Likai, et al. (2009). Evaluation of learning organization applying the entropy method. 2nd International Conference onPower Electronics and Intelligent Transportation System (PEITS). Capecchi, V. and F. Möller (1968). "Some Applications of Entropy to the Problems of Classification." Quality and Quantity 2: 63‐84.
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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova Charvat, F. and J. Kucera (1970). "On the Theory of Social Dependence." Quality and Quantity 4: 325‐353. Coleman, J. (1964). Introduction to Mathematical Sociology. New York, The Free Press. Dixon, N. (1999). The Organizational Learning Cycle: How We Can Learn Collectively. London, Gower Publishing. Frigg, R. and C. Werndl (2010). Entropy – A Guide for the Perplexed. In Probabilities in Physics. B. C. and S. Hartmann. Oxford, Oxford University Press. Gleick, J. (1987). Chaos: Making a New Science, Vintage. McFarland, D. D. (1969). "Measuring the Permeability of Occupations Structures: and Information‐Theoretic Approach." American Journal of Sociology 75: 41‐61. Pareto, V. (1935). The Mind and Society. New York, Harcourt, Brace. Parsons, T. and E. A. Shils (1951). Toward a General Theory of Action. New York, Harper and Row. Senge, P. M. (1992). The fifth discipline: the art and practice of the learning organization, Century Pubs. Shannon, C. and W. Weaver (1949). The Mathematical Theory of Communication. Urbana, The University of Illinois Press. Vera, D., M. Crossan, et al. (2011). A Framework for Integrating Organizational Learning, Knowledge, Capabilities, and Absorptive Capacity. Handbook of Organizational Learning and Knowledge Management. M. Easterby‐Smith and M. Lyles. Chichester, John Wiley and Sons. Winter, S. (2003). "Understanding Dynamic Capabilities." Strategic Management Journal 24: 991‐995. Xueguo, X. (2008). "Study on the Evaluation of Organizational Learning Based on Entropy Value." Contemporary Economy & Management 11.
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A new Marketing Audit Tool for Knowledge Intensive Business Services Ettore Bolisani and Enrico Scarso Department of Management and Engineering, University of Padua, Vicenza, Italy ettore.bolisani@unipd.it enrico.scarso@unipd.it Abstract: The paper focuses on knowledge marketing in Knowledge‐Intensive Business Services (KIBS) companies. Marketing is a special challenge for KIBS, and requires a shift from traditional strategies – generally applied to manufacturing sectors and mostly based on the classic notion of marketing mix (i.e., product, price, promotion, and place) – to new approaches that stress the importance of customer‐provider interactions. Since KIBS mainly deliver knowledge (embedded in services, consulting activities, and problem solving capability), marketing activities must communicate the company’s ability to manage knowledge exchanges with customers effectively. Integral part to the implementation of an appropriate marketing strategy is the need for companies to audit their marketing activities. Marketing audit has its place in the management literature but is generally targeted to manufacturing or retailing companies. In light of this, the paper proposes a novel approach to marketing audit for knowledge‐based companies that focuses on relational and cognitive capabilities, and consists of a questionnaire‐based tool subdivided in sections, each of which considers a particular stage of the customer‐provider relationship. It is assumed that the effective delivery of these services requires intense and continuous exchanges of knowledge between customer and provider, and must be connected to the specific business environment (in terms of markets, competitors, etc.). Consequently, the marketing capability of a company is seen in terms of its ability to fruitfully interact with customers in the conditions of the particular operating environment. The questionnaire can help executives of KIBS companies to self assess the “marketing positioning” of their firms. Due to its easiness of use, it is particularly suitable for small companies. The paper describes the particular example of a questionnaire developed for ICT services firms. This tool has been tested with two small companies, and the results of this assessment are reported. Keywords: knowledge marketing, marketing audit, knowledge‐intensive business services, ICT companies, knowledge exchanges
1. Introduction The paper deals with marketing approaches adopted by Knowledge‐Intensive Business Services (KIBS) companies. According to the extant literature, unique features denote these companies (Strambach, 2008; Muller and Doloreux, 2009; Landry et al, 2012): these strongly affect the effectiveness of their marketing strategies. First, their main production input and output consist of knowledge, directly delivered under the form of consulting, or embedded in artefacts and services. Second, their business is mostly based on the exploitation of knowledge possessed by their employees. Third, the provision of knowledge‐intensive services requires an in‐depth interaction between supplier and user, who are both involved in cognitive exchanges and learning processes (Bettencourt et al, 2002). Fourth, services are generally delivered under the form of a process of problem solving in which KIBS companies adapt their knowledge to the specific requirements of individual clients. Fifth, they often act as interfaces between the global sources of knowledge and the cognitive needs of end users (Smedlund, 2006). Sixth, their innovative capability is directly connected to the acquisition, processing, capitalisation and delivery of new knowledge (Amara et al., 2009). As highlighted in previous studies (Bolisani and Scarso, 2012a; Bolisani et al, 2012), these features make marketing a special challenge for KIBS, and call for a shift from traditional marketing strategies – generally applied to manufacturing sectors and mostly based on the classic notion of marketing mix (i.e., product, price, promotion, and place) – to new approaches that stress the importance of customer‐provider interactions (see e.g. the new “service‐dominant” paradigm of marketing proposed by Vargo and Lusch, 2004). Indeed, since KIBS mainly deliver knowledge (embedded in services, consulting activities, and problem solving capability) to their clients, marketing activities should communicate a company’s ability to provide valuable knowledge to customers. Integral part to the implementation of an appropriate marketing strategy is the need for companies to adopt proper procedures to audit all the aspects of their marketing activity. In light of this, the paper proposes a novel approach to marketing audit for KIBS companies, which focuses on their peculiarities. Especially, it considers their relational capabilities, i.e. the capabilities to provide valuable knowledge to customers
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Ettore Bolisani and Enrico Scarso throughout the whole trading relationship. The approach consists of a questionnaire‐based tool subdivided in sections, each of which focuses on a particular stage of the typical customer‐provider relationship. It is assumed that the effective delivery of services requires an intense exchange of knowledge in repeated interactions between customer and provider. Accordingly, the marketing capability of a KIBS company is evaluated in terms of its capability to fruitfully interact with customers, in relation to the particular environment (i.e., markets, competitors, etc.) in which it operates. The questionnaire can help company executives to self assess their “marketing positioning”; due to its easiness of use, it is particularly suitable for small companies, as many KIBS are. The paper presents a particular version of the marketing audit tool specifically developed for ICT services. The tool has been tested with two small companies. The results of this assessment are reported, and its application prospects are discussed. The paper articulates as follows. In the next section, the main notions and tools of marketing audit are briefly recalled. The third section discusses the significance of a relational marketing approach for KIBS companies, and how the adoption of this approach can influence the design of appropriate marketing audit tools. The following sections describe the audit tool developed in this study, how it has been built, and tested. The last section proposes a final evaluation of the work conducted so far.
2. Marketing audit Marketing audit (MA) is an established notion that dates back to late 1950s (Schuchman, 1959), when the first definitions and elements (goals, issues, types and contents) were given. MA can be defined as a comprehensive, systematic, independent and periodic examination of a company’s marketing environment, goals, strategies and activities, for determining problematic areas and opportunities, and for recommending an action plan to improve the company’s marketing performance (Kotler et al, 1977). This definition points out that MA: a) is broad, covering all marketing aspects of a company; b) should be conducted by an independent person; c) is systematic, since it involves an orderly sequence of steps; d) should be performed periodically. MA bases on a three‐step procedure consisting of: a) setting its objective and scope; b) getting the data; c) preparing and presenting the report. The second step, collecting the data, is generally the most time‐spending. Over the years, MA has evolved, and has assumed a prominent place in the marketing management literature (Rothe et al, 1997). However, even though evaluating the marketing effectiveness of an organisation can be important both for manufacturing and service companies, the current state of the art of the marketing discipline generally neglects the latter (Pimenta da Gama, 2011). Little attention is given to the peculiar characteristics of services, with the only remarkable exception of Berry et al (1991) who developed an integrative audit framework for service marketing (i.e., ISME ‐ Index of Services Marketing Excellence). Beyond any judgement on the usefulness of this framework, an unquestionable contribution of these authors is that they underline the need for a novel approach to MA that takes into account the distinctive characteristics of services.
2.1 MA tools The most popular marketing audit tools consist of a checklist of diagnosis questions that are submitted to one or several “key people” in a company. These questions can be open‐ended or closed‐ended (often Likert‐type), and range from a few dozen to more than 1,000 (Wilson, 2002). Questions are often grouped into categories or topic areas, in relation to the main aspects on which one wants to focus the assessment. There is no consensus about these aspects, and different authors propose different dimensions of analysis (see e.g., Berry et al, 1991; Kotler et al, 1977; McDonald, 1982; Wilson, 2002). As well underlined by Pimenta da Gama (2012), the logic behind the creation of a checklist is the effort to offer a comprehensive set of questions covering all the aspects of marketing that may need improving. In principle, the more detailed and complete a list of question is, the more likely the relevant points are covered. However, too many questions can require much time to be answered, and what’s more the analysis becomes complex. A trade‐off between easiness of use and completeness must be sought. In addition, it is extremely difficult to design a checklist that works well in all situations, and local adaptations to the single case might be necessary. Finally, it must be noted that almost all the checklists that can be found in the literature are based on the traditional manufacturing marketing logic that refers to the well established 4Ps approach.
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3. KIBS, knowledge marketing, and implications for MA To develop a checklist that can be appropriate to KIBS companies, it is first necessary to recall some distinctive features of those firms. First of all, as the literature stresses widely, delivering a knowledge‐intensive business service requires several interactions between client and provider, during which continuous knowledge exchanges occur (Figure 1). The nature of these interactions is affected by the knowledge‐intensive nature of those services that produces information asymmetry, so that clients can be unable to fully evaluate the quality of service delivered. This raises special challenges for marketing. In particular, as Bagdoniene et al (2007) and Aarikka‐Stenroos and Jaakkola (2012) affirm, KIBS companies should adopt a “relationship marketing” approach. This means understanding the dynamics of supplier‐customer relationships, how they evolve, and what factors affect their development, with the ultimate purpose of re‐organising of the company’s processes, and re‐framing the traditional marketing approach based on the 4Ps. Secondly, many KIBS companies (and particularly those considered in this paper) have a very small size, and this impacts significantly on their marketing approaches and activities, including auditing.
Figure 1: Knowledge exchanges between KIBS and clients (from: Martinez‐Fernandez and Miles, 2006) Useful suggestions to re‐frame the traditional marketing approach can be drawn from the recently proposed “service‐dominant” (SD) logic (Vargo and Lusch, 2004) that considers services (defined as the primary unit of any economic exchange) as the application of specialized knowledge and skills for the benefit of clients. This logic suggests that what a firm provides to clients is not simply manufactured outputs, but rather knowledge inputs of a continuing value‐creation process (Lusch et al, 2008). In view of that, the goal of any company is to customize its offering and, by recognising that clients are always value producers, to maximise their involvement in the customisation effort, to better fit their needs. Conforming to this logic, marketing is more than just a functional area of a company: it represents a firm’s distinctive capability, whose functions are to identify and develop the company’s core competences, and deliver them as value propositions that offer potential competitive advantage. Accordingly, building useful relationships with clients, where intense knowledge exchanges occur, becomes vital. In the SD logic, all employees are involved in delivering services, with the ultimate goal of satisfying the costumer, and this extends marketing well beyond the marketing department (Ballantyne and Varey, 2008). Ultimately, the proponents of the SD logic claim that the role of marketing should consist of managing communicative interactions and facilitating key relationships and knowledge exchanges with clients. Accordingly, companies should focus on the value‐in‐use that their products/services can have for their clients rather than just on their features (Payne et al, 2008). This requires understanding the client’s value generating process, and implies a reversal of the traditional “making, selling and servicing” approach, to a “listening, customising and co‐creating” approach, where encounter processes play a crucial role. To sum up, the capability to acquire and share knowledge with clients becomes integral to any marketing process. When it comes to MA, three aspects should be considered. Firstly, it is unlikely that small companies (as KIBS often are) can resort to independent external auditors or consultants. Hence, it is essential that they can utilise
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Ettore Bolisani and Enrico Scarso methods and tools directly on their own. Secondly (and consequently), a MA tool should be as simple as possible, both in data collection and interpretation. So, it would be preferable to have a checklist with a limited number of easy‐to‐answer questions. Thirdly, the goal of MA should be not to push all marketing activities towards a “maximum score”: as a matter of fact, and especially considering the small size of KIBS, it is not always true that “more is better”. On the contrary, in some situations, to push marketing efforts over a certain threshold can be even counterproductive, or in any case uselessly expensive.
4. Building a MA tool for KIBS In this section, we present a version of the new tool that was compiled for a particular category of KIBS, i.e. ICT services. The MA tool illustrated here is based on the points previously discussed and in particular the following:
marketing is a process that involves all the stages of a provider‐customer relationship; an analysis of each of these stages is therefore essential;
in each stage, providers must have the capability to deliver valuable knowledge inputs to customers (so that they can utilise them profitably) and to “learn” from customers (i.e., to acquire fresh knowledge from them);
knowledge exchanged concerns not only technical aspects (e.g. features of the delivered services, or customer requirements) but also to managerial or relational issues (for example: how clients assess the delivered services, how they select providers, how much they consider reputation as a key element, etc.).
Based on these points, a checklist of questions was prepared. The purpose of this checklist is to enable a self‐ assessment by companies for revealing weak areas and opportunities of improvement, and facilitating adjustment of marketing strategies to strengthen provider‐customer relationships. The design of the MA tool was based on the following steps: a) Building a model of interactions and knowledge exchanges during the typical relationships between ICT companies and their clients that occur in the services delivery process; for this purpose, it was possible to exploit the results of previous studies (Bolisani and Scarso, 2012b); b) Identification of a number of “critical areas” for MA. Specifically, the ICT delivery process was split into different stages, ranging from the early formulation of a sales strategy to the after‐sales activities; each stage is characterised by specific relational issues that call for appropriate marketing approaches, where the firm needs to acquire knowledge from the market and to deliver knowledge to clients; c) For each stage, formulation of a number of questions that assess the capability and maturity of relational marketing by a company; d) Once a preliminary version of the MA checklist was ready, a test was run with two pilot companies. The checklist was tested by two small‐sized ICT services firms. This helped to evaluate its easiness of use and usefulness, and to correct errors; e) A final version of the tool (which was named “AUTOMARK”) was then compiled. AUTOMARK consists of a questionnaire with around 80 questions that can be submitted to a company executive (or to more executives) in a single company, and serves as a self‐diagnosis tool for ICT services marketing. Actually, when the design of AUTOMARK was being considered, different options arose. The first was to evaluate answers to questions in absolute terms. This approach is popular in MA tools and consists of measuring the maturity of a company by calculating “how high” the marks in each question and/or in all questions are. In other words, it is assumed that a company can be successful only if it excels in all areas. We considered this approach unsuitable. First of all, KIBS are often small companies, so it is unlikely or difficult that they can reach top ranks in all areas: hence, this way of using AUTOMARK can be misleading. Secondly, it may be useless (and costly) to reach top marks in all marketing activities, because their usefulness and effectiveness may depend on peculiar market conditions or competitive environments. In other words, it is not always true that “more is better”.
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Ettore Bolisani and Enrico Scarso The second option was to perform a benchmarking analysis. This means that the same questionnaire has to be submitted to several companies with similar characteristics (for example, in the case of ICT services, ERP producers in the same market). In this case, a company can assess its relative positioning and marketing capabilities in comparison with others. This is a potentially interesting approach, but difficult to perform: it is, in fact, necessary that several companies accept to use the same MA tool and that they share their answers. The third option was to apply MA as a standalone tool, employed in the single company. This means that the questionnaire is used as a self‐diagnosis tool. Although it does not assess the absolute or relative positioning of a company compared to others, its usefulness is that it allows to measure the way a company’s marketing activities are aligned to its own expectations or perceptions of “what should be done” in a particular market or environment. For reasons of convenience and simplicity, the last option was preferred. So, AUTOMARK can be seen as a self‐ diagnosis MA tool that allows a single company to assess its relational marketing capabilities compared to its own expectations or perceptions of what should be done in that particular environment.
5. AUTOMARK: Description and use The questionnaire consists of two symmetric parts (Table 1). The first part regards the marketing activities, tools, and approaches that currently characterise the company, and particularly: the way knowledge is exchanged from and to the clients, the way this knowledge is used to implement marketing‐related activities and sell services, the way marketing usefulness is measured, etc. The second relates to the way markets and competitive environments (and, consequently, marketing requirements deriving from the environment) are currently seen by the company executives. Each part splits into 8 sections that focus on the different stages of a provider‐customer relationship, namely (see appendix; the complete questionnaire is omitted for reasons of space, the authors can be contacted for further details):
knowledge about competitive environment
markets and marketing/commercial strategy
commercial image
first contact with clients
customer needs
proposal formulation
implementation of a service/product/solution
after‐sales
Table 1: Structure of AUTOMARK Questions regarding the company’s actual approaches to relational marketing 1. collection of knowledge about market/environment 2. marketing/commercial strategy 3. commercial image 4. management of first contacts with clients 5. collection of customer needs 6. proposal formulation 7. implementation of service/product/solution 8. after‐sales activities
Questions regarding the relational needs in the market/environment where the company operates 1. complexity of knowledge about environment 2. complexity of market 3. relevance of image in markets 4. importance of first contacts with clients 5. difficulty of collecting customer needs 6. difficulty of proposal formulation 7. complexity of services/products/solutions 8. relevance of after‐sales relationships
The questionnaire is designed to be self‐used in a single company that is willing to understand how its relational marketing activities are actually implemented and conducted, and how they match the company’s perceptions of the competitive environment. For example, the average marks given to the section “collection of customers needs” in the first part measure the way knowledge about customers needs is currently collected by the company: approaches used, tools implemented, procedures followed, etc.; conversely, the average marks given to the corresponding section in the second part (“difficulty of collecting customer needs”)
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Ettore Bolisani and Enrico Scarso measure how this issue is considered to be important given the particular environment where the company operates. If the marks are comparable, this means that the company’s marketing strategy is aligned with the “requirements” that come from the market; if marks of the first part are higher, the company has invested “too much” in these activities than it might be required; if they are lower, the company should invest more. Each section is compounded by a number of questions (between 4 and 7). To each question, respondents are requested to express the number (ranging from 1 to 7 in a Likert scale) that best represents the appropriate answer. The questionnaire can be submitted to just one company executive (for example, the sales director or the marketing director), or to different executives in the same company (for example, part 1 of the questionnaire can be submitted to the sales director, and part 2 to the CEO, etc.). Average marks are then calculated for each sub‐section, and compared to one another as previously described. The tool easily allows to build a radar chart, which is a powerful way to display the results of the analysis (as an example, see Figure 2). The radar chart presents the average marks for each section listed in Table 1: it is possible to compare the assessments of the internal relational marketing activities with those of the perception of the external environment, point by point. These results can be used by executives to verify the alignment of marketing strategies to the perceived external environment, and to take corrective actions. It can also be used as a tool to promote self awareness in the company, and can more generally be seen as an opportunity for discussing the state of the company with employees.
Key of questionnaire sections: 1 = knowledge about environment 2 = markets & commercial strategy 3 = commercial image 4 = first contact with clients 5 = customer needs 6 = proposal formulation 7 = implementation of a service/product/solution 8 = after-sales Plain line = company’s internal activities Dotted line= perception of the environment
Figure 2: Example of radar chart resulting from a test of AUTOMARK self‐assessment
6. Testing and results The questionnaire was initially discussed with a consultant that highlighted critical questions that may have been difficult to understand by a typical ICT executive. Since the questionnaire should be used by company executives with no assistance, it is important that questions are clearly understood. From the discussion, it also emerged that questions in the questionnaire should be randomly mixed, in order to reduce the possibility that the answer given to a question influences the answer to the following one of the same section. The first complete version of AUTOMARK was then tested with an ICT services company, but in presence of one of the researchers. This highlighted residual understanding difficulties and minor errors. After that, AUTOMARK was revised and submitted to a second company, where 3 executives (CEO, marketing director and communications director) compiled the questionnaire independently from one another. The results made it possible to correct minor mistakes and to revise an entire section that provided contrasting results.
7. Conclusion The assumption on which AUTOMARK is based is that KIBS companies must necessarily enhance their relational marketing capabilities in order to successfully place their knowledge‐based services on the market. Implementing relational marketing in an SD logic implies that companies have to develop capabilities and tools
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Ettore Bolisani and Enrico Scarso to exchange knowledge with customers effectively during the various stages that generally compound the service delivery process. Compared to other MA tools, AUTOMARK is still a questionnaire, but its setting is different. Instead of a focus on the classic 4Ps and, more generally, the typical activities that characterise marketing in manufacturing, AUTOMARK takes into account the specific knowledge‐based interactions that occur between a KIBS company and its clients. Having said that, the tool has some limitations. First of all, it is designed for ICT services specifically: other categories of KIBS need different questionnaires. In any case, AUTOMARK can represent a “model” for the development of other versions, all based on the same guidelines. In addition, the tool has been tested with two companies so far. There is therefore the need for more testing to verify if it represent the true state of affairs and to improve the tool accordingly. In particular, although we are talking about ICT companies, nonetheless these can be very different to one another, and so can be marketing approaches. The capability of AUTOMARK to assess different companies effectively has to be demonstrated. Finally, it should be remembered that AUTOMARK is a self‐diagnosis tool. Hence, its results have not a value “in absolute”, but can only be intended as alarm signals that must inspire a discussion in the company. More than number themselves, it is this discussion that can provide managers with ideas for improving relational marketing activities of their companies.
Appendix: Details of AUTOMARK questions Questions regarding the company’s current approaches to relational marketing collection of knowledge about market/environment seven questions about the capability of companies to collect knowledge of the competitive environment, the resources used for that, and how this knowledge is employed marketing/commercial strategy five questions about the centrality of marketing in the company, and the resources used for this commercial image four questions about how the commercial image of the company is made explicit, and how this knowledge is transmitted to clients management of first contacts with clients seven questions about how the company seeks and manages contacts with new clients collection of customer needs six questions about how knowledge about customer needs is collected and capitalised internally proposal formulation five questions about how the elements of knowledge of markets and clients are transferred into a formally structured commercial proposal that must be understandable by clients implementation of service/product/solution four questions about how company and clients interact and exchange knowledge during the implementation and delivery of a service/product after‐sales activities six questions about how the company collects precious knowledge for improving services, by exploiting the interactions in after‐sales activities
Questions regarding the relational needs in the market/environment where the company operates complexity of knowledge about environment five questions about the complexity of the competitive environment, by assuming that the more complex is the environment the more knowledge is necessary to manage it complexity of market six questions about the complexity of the markets, by assuming that the more complex is the market the more knowledge has to be collected to establish an appropriate marketing strategy relevance of image in markets four questions about how clients consider the image of a provider as a “substitution” of achieving detailed knowledge of it importance of first contacts with clients six questions about how critical the first contact is for clients
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Ettore Bolisani and Enrico Scarso difficulty in collection of customer needs six questions about the need for provider‐client knowledge exchanges for defining customer needs difficulty in proposal formulation five questions about the capability of clients to acquire useful knowledge from a commercial proposal and how this enables them to decide properly complexity of implementing service/product/solution six questions about the complexity of services/products and the need for provider‐client interactions to manage their delivery relevance of after‐sales relationships six questions about how relevant after‐sales is in the particular market where the company operates
References Aarikka‐Stenroos, A. and Jaakkola, E. (2012) “Value co‐creation in knowledge intensive business services: A dyadic perspective on the joint problem solving process”, Industrial Marketing Management, Vol 41, No. 1, pp 15‐26. Amara, N., Landry, R. and Doloreux, D. (2009) “Patterns of innovations in knowledge‐intensive business services”, The Service Industries Journal, Vol 29, No. 4, pp 407‐430. Bagdoniene, L., Kunigeliene, D. and Jakstaite, R. (2007) “Relationship Marketing as factor for Competitiveness of Knowledge‐Intensive Business Services’ Providers”, XVII International Conference of RESER, Tampere, Finland, 13‐15 September. Ballantyne, D. and Varey, R.J., (2008) “The service‐dominant logic and the future of marketing”, Journal of the Academy of Marketing Science, Vol 36, No.1, pp 11‐14 Berry, L.L., Conant, J.S. and Parasumaran, A. (1991) “A Framework for Conducting a Services Marketing Audit”, Journal of the Academy of Marketing Science, vol. 19, n. 3, pp 255‐268. Bettencourt, L.A., Ostrom, A.L., Brown, S.W. and Roundtree, R.I., (2002), “Client Co‐Production in Knowledge‐Intensive Business Services”, California Management Review, Vol. 44, No. 4, pp. 100‐128. Bolisani, E. and Scarso, E. (2012a) “Knowledge Marketing: Issues and Prospects”, in Cegarra, J.G. (ed.), Proceedings of the 13th European Conference on Knowledge Management, Academic Conferences Limited, Reading, UK, pp 100‐107. Bolisani, E. and Scarso, E. (2012b) “Knowledge‐intensive innovation management: A multiple case‐study of local computer services companies”, African Journal of Business Management, Vol 6, No. 51, pp 12052‐12067. Bolisani, E., Donò, A. and Scarso, E. (2012) “Marketing of Knowledge‐intensive Business Services: Evidence from the ICT sector”, in Schiuma, G., Yigitcanlar, T. and Spender, J. (eds.), Proceedings of IFKAD – KCWS 2012, pp 1256‐1274. Kotler, P., Gregor, W. and Rogers, W. (1977) “The Marketing Audit Comes of Age”, Sloan Management Review, Vol 18, No. 2, pp 25‐43. Landr y, R., Amara, N. and Doloreux, D., (2012) “Knowledge exchange strategies between KIBS firms and their clients”, The Service Industries Journal, Vol 32, No. 2, pp 291‐320. Lusch, R.F., Vargo, S.L. and Wessels, G. (2008), “Toward a conceptual foundation for ser‐vice science: Contribution from service‐dominant logic”, IBM Systems Journal, Vol 47, No. 1, pp 5‐14. Mart inez‐Fernandez, M.C. and Miles, I. (2006) “Inside the software firm: co‐production of knowledge and KISA in the innovation process”, International Journal of Services Technology and Management, Vol 7, No. 2, pp 115‐125. Mulle r, E. and Doloreux, D. (2009) “What we should know about knowledge‐intensive business services”, Technology in Society, Vol 31, No.1, pp 64‐72. Mcdo nald C. (1982) The Marketing Audit Workbook, Institute for Business Planning, Englewood Cliff, NJ. Payne, A.F., Storbacka, K. and Frow, P. (2008) “Managing the co‐creation value”, Journal of the Academy of Marketing Science, Vol 36, No. 1, pp 83‐96. Pimenta da Gama, A. (2011) “A renewed approach to services marketing effectiveness”, Measuring Business Excellence, Vol 15, No. 2, pp 3‐17. Pimenta da Gama, A. (2012)”Marketing audits: The forgotten side of management”, Journal of Targeting, Measurement and Analysis for Marketing, Vol 20, No. 3/4, pp 212‐222. Rothe , J.T., Harvey, M.G. and Jackson, C.E. (1997) “The Marketing Audit: Five Decades Later”, Journal of Marketing Theory and Practice, Vol 5, No. 3, pp 1‐16. Schuc hman, A. (1959) “The Marketing Audit: its Nature, Purposes, and Problems”, in Newgarden, A. and Bailey, E.R (eds.), Analyzing and Improving Marketing Performance: “Marketing Audit” in Theory and Practice, Management Report n. 32, American Management Association, New York, pp 11‐19. Smedlund, A. (2006) “The roles of intermediaries in a regional knowledge systems”, Journal of Intellectual Capital, Vol 7, No. 2, pp 204‐220. Strambach, S. (2008) “Knowledge‐Intensive Business Services (KIBS) as rivers of multilevel knowledge dynamics”, International Journal of Services Technology and Management, Vol 10, No. 2/3/4, pp 152‐174. Vargo , S.L. and Lusch, R.F. (2004) “Evolving to a New Dominant Logic for Marketing”, Journal of Marketing, Vol 68, No. 1, pp 1‐17. Wilso n, A. (2002) The Marketing Audit Handbook – Tools, Techniques and Checklists to Exploit Your Marketing Resources, Kogan Page, London.
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Emotional Knowledge: The Hidden Part of the Knowledge Iceberg Constantin Bratianu and Ivona Orzea Bucharest University of Economic Studies, Bucharest, Romania cbratianu@yahoo.com ivona.orzea@gmail.com Abstract. According to Daniel Kahneman (2011), our thinking process is based on two systems: system 1 operates automatically and quickly, with little awareness of voluntary control, system2 operates slowly and constructs thoughts in a logic order. System 1 processes actually emotional knowledge using our unconscious cognitive capability. Cognitive scientists discovered that we are primarily emotional decision makers, which means that managers and leaders need to rely on their emotional knowledge. The purpose of this paper is to present a qualitative and quantitative research concerning the paradox of emotional knowledge. That means that on one hand most of us ignore emotional knowledge by identifying knowledge with cognitive knowledge, and on the other hand by using emotional knowledge in decision making. The qualitative research has been done by reflecting on knowledge management, strategic management and change management literature concerning emotional knowledge and emotional intelligence, while the quantitative research has been done by conceiving a questionnaire and using it in an academic environment. A total of 1200 questionnaires were distributed to the students of Bucharest University of Economic Studies, and we got a response rate of 37%. Each questionnaire contains 40 questions concerning the awareness, education, transfer, and management of emotional knowledge. The data has been processed with the help of the specialized software SPSS version 19, and AMOS version 18. Statistical analysis includes both exploratory and confirmatory factorial analysis. The results of the statistical analysis reveal the main influence factors affecting our understanding of emotional knowledge, the way we learn through education about emotional knowledge, the way this knowledge is transferred, and the importance of using it by managers and leaders. Keywords: emotional knowledge, emotional intelligence, explicit knowledge, cognitive knowledge, tacit knowledge
1. Introduction It is well known the metaphor of the knowledge iceberg: knowledge may be conceived as an iceberg whose visible part represents explicit knowledge, and the hidden part representing tacit knowledge. The hidden part is much larger than the visible part of the iceberg, fact that reflects the ratio between the tacit knowledge and explicit knowledge. As Polanyi used to say, we may know much more than we can tell. “I shall reconsider human knowledge by starting from the fact that we can know more than we can tell. This fact seems obvious enough; but it is not easy to say exactly what it means. Take an example. We know a person’s face, and can recognize it among a thousand, indeed among a million. Yet we usually cannot tell how we recognize a face we know. So most of this knowledge cannot be put into words” (Polanyi, 1983, p. 4). However, tacit knowledge is a fuzzy concept containing a mixture of experience, subjective insights, intuitions, hunches, ideals, values, and emotions. In order to make a step forward in understanding knowledge nature we may change the old dyad of explicit knowledge‐tacit knowledge (Nonaka, 1994; Nonaka & Takeuchi, 1995) into a new dyad composed of cognitive knowledge‐emotional knowledge (Bratianu & Andriessen, 2008; Bratianu, 2011). The Cartesian dualism of body and mind, expressed so clearly by the famous dictum Cogito, ergo sum !, promoted two ideas about human nature (Kahneman, 2011): (a) people are rational, and (b) emotions measure the departure from rationality. The explanation comes mostly from the Newtonian perspective use by the Western science and culture. By contrast, the Eastern perspective (Kaufman, 1994; Nonaka & Takeuchi, 1995; Nonaka & Zhu, 2012; Ohmae, 1982) emphasizes the oneness of mind and body. Research performed in cognitive science demonstrates that the gap between thoughts and emotions is narrowing, and that they represent two fundamental components of our inner representation of the world we are living in (Damasio, 1994; Damasio, 1999; Fauconnier & Turner, 2002; Frith, 2007; Immordino‐Yang & Damasio, 2007; Kahneman, 2011; LeDoux, 1999). Moreover, as underlined by Hill (2008), in the process of making decisions as consumers, emotions are central and not peripheral. In change management, emotions are dominant in influencing people (Kotter, 1996; Kotter & Cohen, 2002; Kotter, 2008). As a result of all this research, emotional knowledge is emerging as a new and powerful concept with many implications in decision making and knowledge management. The purpose of this paper is to present a qualitative and quantitative research concerning the paradox of emotional knowledge. That means that on one hand most of us ignore emotional knowledge by identifying knowledge with cognitive knowledge, and on the other hand by using emotional knowledge together with
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Constantin Bratianu and Ivona Orzea cognitive knowledge in decision making. The qualitative research has been done by reflecting on knowledge management, strategic management and change management concerning emotional knowledge and emotional intelligence, while the quantitative research has been done by conceiving a questionnaire and using it in an academic environment. This research has been stimulated by the following questions: (a) How much are students aware of the importance played by emotional knowledge in decision making and business? (b) What are the specific ways of transferring emotional knowledge? (c) How much education helped them to understand emotions and emotional knowledge? and (d) How important is to use efficiently emotional knowledge?
2. Emotional knowledge Nonaka and Takeuchi consider tacit knowledge the hidden part of the iceberg, and that emotional knowledge is an important part of it. Subjective insights and intuitions belong to this category of emotional knowledge (Nonaka & Takeuchi, 1995). Emotional knowledge is created by emotions, and integrated together with cognitive knowledge into our mental representation of the world. Emotions can be simply described as being specific reactions to events, agents and their actions, and objects (O’Rorke & Ortony, 1994). Moreover, emotion is fundamental in decision making, being like a spectrum of know‐how that allows people to have adequate reactions to different external forces. Emotions contain emotional knowledge generated by emotional triggers (Immordino‐Yang & Damasio, 2007). Although emotion and cognition have been treated most of the time as two separate fields of research and two separate entities, they “are inextricably intertwined. Feelings influence thoughts and actions, which in turn can give rise to new emotional reactions” (O’Rorke & Ortony, 1994, p. 283). Immordino‐Yang and Damasio (2007) use the concept of emotional thought to describe the overlapping between the emotion and cognition domains. This is extremely important for understanding the real functioning of memory, decision making, and creativity. Thus, reflecting especially on the knowledge management literature we found three main approaches: (1) knowledge is basically cognitive knowledge, and it is generated in the rationality domain; (2) thoughts and ideas are different entities and there is no interaction between them; (c) thoughts and ideas reflect same complex reality and they interact in the decision making. Based on the metaphor of thermodynamics, especially on the transformation between mechanical energy and thermal energy, Bratianu makes a step forward and advances the idea of a continuous dynamics between the cognitive knowledge and emotional knowledge (Bratianu, 2011). That means that cognitive knowledge can be transformed into emotional knowledge, and emotional knowledge can be transformed into cognitive knowledge, respectively. This dynamics represents actually the engine of the decision making, powered by the two systems of thinking, as shown by Kahneman (2011, p. 21): “System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental activities that demand it, including complex computations. The operations of System 2 are often associated with the subjective experience of agency, choice, and concentration”. Knowledge dynamics is important also for the way we are aware of our emotions and we manage them in our personal and professional life (Fenton‐ O’Creevy et al., 2011; Koole, 2009; Lagattuta & Wellman, 2001; Lindquist & Barrett, 2008; Miller et al., 2005; Reus & Liu, 2004). Understanding and using efficiently emotional knowledge is an important capability of managers and leaders (Bass & Riggio, 2006; Daft, 2008; Ekman, 2003; Hess & Bacigalupo, 2010; Jordan et al., 2013; Madden et al., 2012; Miller et al., 2012; Nag & Gioia, 2012). Although Kotter (2012) is discussing the dual management system, his argument for using emotions in decision making may be considered as a generic one. Emotional knowledge is also essential in complex organizational processes like strategies implementation through change management (Kotter, 1996; Mohrman & Lawler, 2012; Rafferty et al., 2013). Our qualitative research leads to a challenging result: the existence of knowledge dynamics, as a continuous transformation process of cognitive knowledge into emotional knowledge, and vice versa. A critical analysis of the emergency of the emotional knowledge as a major player in decision making, with direct implications in management, marketing, leadership and entrepreneurship rises the question of its awareness, and its development through education. Our research is trying to evaluate the degree of such an awareness at students in economics and business, and how much they consider that education in schools and university helped them to master their emotions and emotional intelligence.
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3. Research methodology The instrument used in our research was the questionnaire. The design and elaboration of this questionnaire to collect the quantitative data went through four phases: (1) literature analysis; (2) elaboration of the first draft of the questionnaire; (3) testing the questionnaire, and (4) improving its content, and elaboration of the final version. Literature analysis helped us to understand different perspectives in interpreting emotional knowledge, and the way we learn and use this kind of knowledge. The main ideas of this research we have presented in the first part of this paper. In the second phase we design the basic structure of the questionnaire, considering four main pillars: awareness of emotional knowledge, the specific way of transferring emotional knowledge, education for emotional knowledge and using emotional knowledge. We designed the first draft of the questionnaire with 40 questions able to capture the respondents views concerning emotional knowledge as the hidden part of the knowledge iceberg. This first draft of the questionnaire was tested within a group of experts in knowledge management. The testing phase had as the main purpose the evaluation of the accuracy of the questions used and possible suggestions for improving the questionnaire. Based on the received suggestions we elaborated the final version of the questionnaire. The first part of the questionnaire contains items to describe the general profile of the respondents (age, gender, and level of education). The second part contains 40 assertions aiming at measuring respondent’s agreement level with each of them using a Likert scale with five divisions: 1 (strongly disagree), 2 (disagree), 3 (neither agree nor disagree), 4 (agree), and 5 (strongly agree). For our research we considered the academic environment, and we distributed by mail 1200 questionnaires to undergraduate and graduate students from the Bucharest University of Economic Studies, from all its 11 faculties. The rate of response was of 37%, resulting in 444 valid questionnaires, which means a sufficiently large volume of data to obtain relevant results. The results obtained through the data collection process were analyzed using the specialized statistical software SPSS version 19, and AMOS version 18.
4. Results analysis and discussions The statistical analysis of the collected data had four main directions of thinking: (1) what is the students awareness about the emotional knowledge they have; (2) how much do they know about the specific way of transferring emotional knowledge; (3) how much they learned about emotional knowledge in schools, as a direct result of school’s curriculum, and (4) how much do they know about knowledge dynamics and the importance of emotional knowledge in decision making. We have chosen as methods of analysis exploratory factorial analysis and confirmatory factorial analysis. Exploratory factorial analysis has the role of underlining the factors that could be identified from the sentences under analysis. Furthermore, to validate the exploratory factorial analysis and to obtain an exact measure of the processes of learning and using in business emotional knowledge a confirmatory factorial analysis was undergone. The structure of the statistical population we investigated can be characterized by the followings: 81.56% undergraduate students with ages belonging to the interval of 19‐23 years old, and 18.44% graduate students with ages belonging to the interval of 24‐30 years old. This composition reflects the general structure of the undergraduate and graduate programs offered by our university. Among all the respondents, 63% are young ladies and 37% are young men. Some significant results from the descriptive statistics are presented in Table 1. For all the 40 variables the minimum value is 1, and the maximum value is 5. Table 1: Descriptive statistics No.
Variables
Q01 Q02 Q03 Q04 Q05 Q06 Q07 Q08 Q09 Q10 Q11 Q12
Emotions are important in understanding individuals behavior Emotions are important in decision making We are primarily emotional decision makers Emotions are based on emotional knowledge Emotional intelligence is processing emotional knowledge Thinking is based on both cognitive and emotional knowledge Emotional thinking is faster than rational thinking Leaders influence their followers mostly through emotional knowledge In business one must use his/her emotions Basic emotions result in same facial expressions for everybody Emotional knowledge can be transferred through facial expressions Emotional knowledge can be transferred through body language
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Mean Statistic 4.33 3.36 3.46 3.50 3.77 4.11 4.20 3.76 2.75 3.06 3.76 4.02
Std. Deviation 0.834 1.136 0.997 1.117 0.983 1.007 1.048 1.028 1.084 1.469 1.068 0.890
Constantin Bratianu and Ivona Orzea No.
Variables Emotional knowledge can be transferred through the tone of the voice
Mean Statistic 4.03
Std. Deviation 0.922
Q13 Q14
Emotional knowledge can be transferred through the verbal language
3.80
1.016
Q15
Emotional knowledge can be transferred through images
3.68
0.965
Q16
Emotional knowledge can be transferred through dancing
3.64
1.056
Q17
Emotional knowledge can be transferred through music
3.93
0.972
Q18
Emotional knowledge can be transferred through touching
3.77
1.049
Q19
Most of our communication is done through emotional knowledge
3.50
0.918
Q20
Communicating emotional knowledge depends on the context much more than communicating cognitive knowledge
3.55
0.957
Q21
We learn about emotional knowledge in family
3.86
0.974
Q22
We learn about emotional knowledge in primary and secondary schools
2.95
1.152
Q23
We learn about emotional knowledge in high schools
3.11
1.175
Q24
We learn about emotional knowledge in university
3.00
1.216
Q25
We learn about emotional knowledge directly from our own experience
4.58
0.758
Q26
We learn in schools and university how to understand, and to manage emotional knowledge
2.66
1.215
Q27
We learn in schools and university how to communicate efficiently our emotional knowledge
2.74
1.196
Q28
We had in schools and university special courses about emotions and emotional knowledge
2.38
1.323
Q29
We can understand other people emotions only if we understand our own emotions Education in schools and university should contribute much more to understanding and using efficiently our emotional knowledge
3.91
1.093
4.11
0.980
Using emotional knowledge we can understand much better people we work with We can improve decision making by using our emotional knowledge
4.26
0.837
3.70
1.058
Q33
In negotiations we communicate better by using consciously both cognitive and emotional knowledge
3.98
0.968
Q34
In our mental process cognitive knowledge can be transformed into emotional knowledge and vice versa
3.49
0.951
Q35
Positive thinking is based on positive emotional knowledge
3.92
0.968
Q36
Negative thinking is based on negative emotional knowledge
3.76
1.068
Q37
Leadership involves both emotional knowledge and cognitive knowledge
4.29
0.878
Q38
Emotional knowledge is more important than cognitive knowledge in motivating people
3.82
0.986
Q39
Emotional knowledge is more important than cognitive knowledge in change management
3.24
1.006
Q40
Using emotional knowledge may contribute to generating consumers enthusiasm
4.10
0.877
Q30 Q31 Q32
Analyzing the statistic mean of the first 10 variables we remark a relatively low awareness of the importance of emotional knowledge in decision making (ex. Q02=3.36 and Q03=3.46). Furthermore, respondents are students in economics and business, and most of them cannot understand the practical importance of emotional knowledge in doing business (Q09=2.75). That means that for most of them the cognitive knowledge is the dominant kind of knowledge in decision making and solving business problems. From the next group of 10 variables we learn that most of the students know how emotional knowledge can be transferred (ex. Q12=4.02 and Q13=4.03), but they don’t know the relative high importance of it in our communication (ex. Q19=3.50 and Q20=3.55). This conclusion comes as a logic consequence of the low
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Constantin Bratianu and Ivona Orzea awareness they have about the emotional knowledge. Examining carefully the next group of 10 variables we get the explanation for the above conclusions. Students learn very little about emotions and emotional knowledge in schools and universities (ex. Q22=2.95 and Q26=2.66). There is a lack of such kind of courses in their curriculum (Q28=2.38), and they learn about this emotional knowledge from their direct experience (Q25=4.58). Performing a detailed analysis of all the courses offered in the undergraduate and graduate programs in our university we found only one course in the curriculum of the Business Administration graduate program about Knowledge Management, while such kind of courses are extremely important for educating future specialists in economics and business. This assertion is supported by the respondents perception of the need of using efficiently emotional knowledge, as we see in the last group of 10 variables (ex. Q31=4.26 and Q37=4.29). The method chosen to process in more details the collected data is factorial analysis, that allows identification of the most significant factors able to describe the statistical behavior of the considered population. To verify the accuracy of the method we have applied the Bartlett and Kayser‐Meyer‐Olkin (KMO) tests (Table 2). The KMO test allowed us to determine the efficiency of the application of factorial analysis onto the data collected. A small value of the KMO test (i.e. less than 0.7) underlines an inadequacy in utilizing the method of analysis onto the considered variables, whereas a large value of the test, converging to one, encourages the utilization of the method to sum up the information comprised in the variables. Both the Bartlett test and the KMO test suggested a very good accuracy for using the factorial analysis for the present research. Table 2: KMO and Barlett test Kaiser‐Meyer‐Olkin test Barlett test Approx. Chi‐Square Df. Sig.
0.831 5878.471 780 0.000
The first step in the application of factorial analysis onto the set of data was the principal components extraction, by using the varimax orthogonal rotation. This rotation tries to maximize the variance of the factors components, leading to a smaller loading of variables onto every factor, and making the interpretation of the identified factors more facile. Thus, through the varimax orthogonal rotation we have obtained 11 identifiable factors comprising 60.243% of the information embedded in the original set of data (Table 3). Table 3: Total variance explained for the first extraction Items 1 2 3 4 5 6 7 8 9 10 11
Eigenvalues % of Variance 17.348 7.894 7.701 4.722 4.224 3.993 3.270 3.012 2.816 2.718 2.545
Total 6.939 3.158 3.080 1.889 1.690 1.597 1.308 1.205 1.126 1.087 1.018
% Cumulative 17.348 25.242 32.943 37.665 41.889 45.882 49.152 52.164 54.980 57.698 60.243
By analyzing the composition of each factor in terms of initial variables, and the main four directions of investigation, we performed a second extraction of the main components, focusing on the first four factors. The structure of each factor in terms of the initial variables is presented in Table 4. The first factor contributing to 17.348% of the total variance, contains 16 variables and shows the level of awareness of respondents about emotional knowledge and its importance in management and leadership (Q01, Q05‐Q08, Q31‐Q33, Q37). The second factor is contributing to 7.894% of the total variance and contains 8 variables. It focuses on the specific ways of transferring emotional knowledge (Q11‐Q18). Most of the respondents know the fact that emotional knowledge can be transferred mainly through the body language and the tone of the voice. The third factor contributes to the 7.701% of the total variance, and contains 8 variables. It focuses mainly on the importance of emotional knowledge in our communication, and the ability we have in handling it. The fourth factor contributes only to 4.701% of the total variance, and contains 4 variables. It focuses mainly on
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Constantin Bratianu and Ivona Orzea the way formal education contributes to understanding and development of emotional knowledge. As we have seen from the descriptive statistics, formal education has almost no contribution to our understanding and using efficiently emotional knowledge. Table 4: Rotated component matrix for 4 factors extracted Factor 1 Q01 = 0.592 Q05 = 0.473 Q06 = 0.486 Q07 = 0.448 Q08 = 0.467 Q20 = 0.371 Q25 = 0.490 Q29 = 0.333 Q30 = 0.541 Q31 = 0.664 Q33 = 0.533 Q35 = 0.371 Q36 = 0.355 Q37 = 0.633 Q38 = 0.437 Q40 = 0.606
Factor 2 Q11 = 0.785 Q12 = 0.786 Q13 = 0.768 Q14 = 0.649 Q15 = 0.687 Q16 = 0.700 Q17 = 0.719 Q18 = 0.703
Factor 3 Q02 = 0.418 Q04 = 0.358 Q09 = 0.517 Q19 = 0.410 Q26 = 0.619 Q27 = 0.663 Q28 = 0.589 Q32 = 0.454
Factor 4 Q21 = 0.459 Q22 = 0.838 Q23 = 0.873 Q24 = 0.724
A Cronbach coefficient alpha test was conducted on all four factors to test the reliability of all of the item variables. This was to determine the internal consistency of the scale used. The test results indicate higher values than 0.7 for factors 1, 2 and 4, and less but very close to 0.7 for the third factor. That means a good enough consistency of these factors, and consequently an adequate correctness (Table 5). Table 5: Reliability statistics Factors 1 2 3 4
Cronbach’s Alpha 0.813 0.882 0.663 0.764
No. of items 16 8 8 4
To validate the results obtained we have run a confirmatory factorial analysis. Unlike the exploratory factorial analysis, in a confirmatory factorial analysis the variables are already observed and the aim of the analysis is to refine the influence measurement scale of each sentence comprised in the identified factors (Figure 1). We abbreviate with EKF – Emotional Knowledge Factor. As we can see there are three variables that do not have any direct influence on the four factors. They are: Q03 – We are primarily emotional decision makers, Q10 – Basic emotions result in same facial expression for everybody, and Q34 – In our mental process cognitive knowledge can be transformed into emotional knowledge and vice versa. That means that these variables have a generic value for the whole emotional knowledge management, and not just for one of the main factors identified using the explanatory factorial analysis. From the confirmatory factorial analysis using the software AMOS version 18, we obtained the synthetic data presented in the Table 6 that shows a good concordance with the exploratory factorial analysis.
5. Conclusions Emotional knowledge has been recognized as a distinctive component of the tacit knowledge and the hidden part of the knowledge iceberg only recently, when research in cognitive science revealed the role of emotions in the decision making and mental processes. As that research demonstrates, cognitive knowledge and emotional knowledge are inextricably intertwined. There is a powerful dynamics of thoughts and emotions, that can be understood by using the thermodynamics metaphor. That means that cognitive knowledge may transform into emotional knowledge and vice versa, like energy from one form into another one. This is a challenging hypothesis based on metaphorical analysis that cognitive scientists have yet to prove.
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Figure 1: Confirmatory factorial analysis model Table 6: Confirmatory analysis results with AMOS version 18 Variables Q01 Q05 Q06 Q07 Q08 Q20 Q25 Q29 Q30 Q33 Q35 Q36 Q37 Q38 Q40 Q11 Q12 Q13 Q14 Q15 Q16
Factors EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF1 EKF2 EKF2 EKF2 EKF2 EKF2 EKF2
Estimate 1.359 1.195 1.186 1.001 1.207 0.950 1.007 1.000 1.352 1.429 1.350 1.409 1.459 1.136 1.464 1.457 1.225 1.259 1.000 0.956 1.077
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S.E. 0.235 0.228 0.230 0.214 0.234 0.199 0.186 0.246 0.255 0.245 0.261 0.251 0.222 0.251 0.112 0.093 0.096 0.091 0.101
C.R. 5.782 5.232 5.163 4.671 5.156 4.765 5.415 5.488 5.616 5.510 5.400 5.813 5.113 5.820 13.047 13.112 13.051 10.461 10.694
Constantin Bratianu and Ivona Orzea Variables Q17 Q18 Q02 Q04 Q09 Q19 Q26 Q27 Q28 Q32 Q39 Q21 Q22 Q23 Q24
Factors EKF2 EKF2 EKF3 EKF3 EKF3 EKF3 EKF3 EKF3 EKF3 EKF3 EKF3 EKF4 EKF4 EKF4 EKF4
Estimate 1.010 1.004 1.420 1.751 2.436 1.293 8.862 8.922 6.779 1.786 1.000 1.000 2.707 3.168 2.453
S.E. 0.093 0.099 0.820 0.935 1.199 0.714 4.023 4.050 3.104 0.934 0.393 0.456 0.368
C.R. 10.839 10.184 1.733 1.873 2.031 1.811 0.028 2.203 2.184 1.912 6.885 6.943 6.666
The purpose of our research is to evaluate the degree of awareness of importance of emotional knowledge, and the contribution of education to that awareness at students in economics and business. We used both a qualitative and quantitative research. The qualitative research has been done to get the state‐of‐the‐art in this field of emotional knowledge from literature in the field of knowledge management and leadership. For the quantitative research we developed a questionnaire comprising 40 questions, and distributing to 1200 of students. Finally, we processed 444 valid questionnaires by using the specialized software SPSS and AMOS. We performed an exploratory factorial analysis, and then a confirmatory factorial analysis. Results show that students have a level of awareness about the importance of emotional knowledge just above the statistical average of the analyzed population, and that education contributed very little to it. Education in schools and universities is based heavily on objective and scientific knowledge, as a result of European tradition of the Cartesian dualism of body and mind. Education should consider also the hidden part of the knowledge iceberg, and to introduce into its curriculum disciplines dedicated to emotional knowledge. Many students still consider cognitive knowledge to dominate their decision making and their understanding of life and society. It is time to reconsider these students curriculum, especially to students in economics and business by introduce new courses about behavior economics and complex decision making, with emotional knowledge playing an important part.
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Managerial Factors of Organizational Learning for Sustainable Development Valentina Burksiene1 and Palmira Juceviciene2 1 Department of Public Administration, Faculty of Social Sciences, Klaipeda University, Klaipeda, Lithuania 2 Institute of Educational Studies, Kaunas University of Technology, Kaunas, Lithuania v.burksiene@gmail.com palmira.juceviciene@ktu.lt Abstract: Effective results of organizational learning for sustainable development (OLSD) can be achieved when the process is well organized and managed. However, organizations frequently confront managerial problems of organizational learning. The appropriate learning environment Ba enabling OLSD can be created if using complex of appropriate managerial factors. The aim of this article is to reveal the complex of managerial factors guaranteeing OLSD and present results of empirical research proving the efficiency of those managerial factors. A field experiment was carried out. Its results illustrate the effectiveness of the managerial factors and provide rationale for a discussion whether the conventional SECI model should be supplemented by an introductory stage. Keywords: organizational learning, organizational knowledge creation, sustainable development, managerial factors for sustainable development
1. Introduction In the contemporary world organizations face the challenge of how to adapt successfully to the turbulent environment and to improve the performance. The globally accepted concept of sustainable development (SD) urges to follow the principles of sustainability. Porter (2008), Williams (2008) point out that the most efficient way to adapt the changing environment is learning in an organization, when the organizational knowledge is created and developed. Epstein (2008), Williams (2008) claim that organizational learning (OL) helps embedding SD. Thus, aiming for SD in organizational activities, organizational learning for sustainable development (OLSD) has to take place. It means creation and acquisition of knowledge of SD per se, the development of system thinking which integrates economic, social (including culture) and environmental aspects as well as SD dimensions highlighted for a particular organization (Burksiene 2012). Aiming for effective results of OLSD, the process has to be properly organized and managed. However, organizations often encounter the managerial problems of OL. The managers are mainly result (knowledge)‐ oriented, instead of putting their efforts for developing relevant learning environment important for successful OL. With reference to knowledge creation model proposed by Nonaka, Toyama and Byosiere (2001), we emphasized the significance of Ba (learning environment) and agreed that OLSD takes place in four different Ba where specific SD knowledge is created in each of them and successfully applied in other learning stages (Juceviciene and Burksiene 2009). Success of OLSD mainly depends on arrangement and management of every Ba using appropriate learning methods. A number of authors (Bell and Morse 2003; Epstein 2008; Zink 2008) in their analysis of OLSD suggest using the methods of reflection, discussion, dialogue or other ways of acting that permit sharing the individual knowledge and constructing collective knowledge. These scholars, however, have not provided rationale for a complex of methods relevant for successful creation of organizational knowledge. We argue that successful OLSD requires a complex of methods that may be regarded as managerial factors empowering successful OLSD. According to the theoretical model of OLSD (Juceviciene and Burksiene 2009), organizational learning for sustainable development takes place in different Ba. Thus each Ba calls for different managerial factors. What managerial factors can be used to empower successful OLSD? The aim of the paper is to reveal, what managerial factors should be used in every Ba guaranteeing successful OLSD.
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Valentina Burksiene and Palmira Juceviciene First of all, the managerial factors important for OLSD are revealed drawing on literature analysis. Later, empirical testing of OLSD managerial factors is provided: the methodological background of the empirical research is introduced, field experiment is described, research results are analysed and discussed. Finally, conclusions are drawn.
2. Organizational learning for sustainable development and its managerial factors Organizational learning for sustainable development is a complex process that may be explained by describing the characteristics inherent in OL. Nonaka and Takeuchi (1995) describe OL and view the process as transformations of tacit and explicit knowledge among the individuals and their groups when they interact. It is a never ending and spiral process of socialization, externalization, combination and internalization (SECI). Easterby‐Smith and Lyles (2003) note that OL consists of actions, actors, symbols and processes. Kolb (1984) points out that the learner moves in a spiral way through different learning experience within the iteration of acting, reflecting, conceptualizing and practicing. Thus, these ideas enable to refer to organizational learning as a spiral process characterised by learning of individuals and their groups. DiBella (2003) points out that OL is related to the time and situation in which certain knowledge was created and applied. In other words, learning is contextualized. Nonaka, Toyama and Byosiere (2001) claim that knowledge creation takes place in a particular space referred to as Ba (this is a Japanese concept that might be translated as ‘space’). Ba is described as a context where knowledge resides, is created, shared and embedded. Thus, organizational learning is related to the learning space or environment. Pasteur, Pettit and van Schagen (2006) argue that a successful environment for OL is created with a special focus on learning processes. Aiming to ensure successful OLSD, relevant managerial factors have to be employed that enable to create a comfortable and safe environment for OLSD. Nonaka, Toyama and Byosiere (2001) reveal four Ba as learning environments: Originating Ba; Dialoguing Ba, Systemizing Ba, Exercising Ba applied, accordingly, to the stages of socialization, externalization, combination and internalization in organizational learning (SECI model). A specific issue of OLSD is that it tends to involve people that lack personal (basic) knowledge of SD. This article analyses the situation of employees with knowledge and experience of SD only from environmental perspective who encounter the task of addressing SD as a systemic environmental, economic and sociocultural approach. Here OLSD has to take place by re‐conceptualizing the knowledge on SD. This task should be solved in the very process of OLSD. Thus a new phase of OL starts with the stage of externalization. It embraces the heritage of tacit knowledge from the previous stage of socialization with the conventional approach to SD. What managerial factors should be in place when a group of employees has received a task to draft a new strategic plan based on a new systemic approach to SD rather than the old one (based on exclusively environmental approach) and to convince all the organization to adopt this change? Juceviciene and Burksiene (2009), Burksiene (2012) note that specific managerial factors have to be used for developing Ba that empower OLSD. If the managerial factors are successful, one may expect that successful OLSD will occur in all Ba and SD knowledge that is significant for organization will be created. Originating Ba is necessary for socialization. This means that a common space has to be developed were people are comfortable to create common but tacit knowledge (Nonaka and Takeuchi 1995). In this sense managerial factors are those that help to create a physical (or virtual, which is beyond the scope of the present research) space for being and acting together. But in terms of socialization result in the context of OLSD, we should remember that it contains the tacit knowledge of the conventional SD approach, which has to be re‐ conceptualized before entering the stage of externalization of the new OLSD phase. Here reference should be made to the stage of initiation which is between the processes of the former OLSD socialization phase and the new OLSD phase of externalization (see Figure 1). The following managerial factors are relevant in the initiation stage: 1) interview as a dialogue between expert and informant to identify personal SD knowledge and to discuss the task for shifting to a new approach to SD; 2) organizing Focus group to discuss common understanding on SD in order to prove readiness for the OLSD. These, however, are only
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Valentina Burksiene and Palmira Juceviciene preparatory activities, as it is not likely that group members will acquire collective knowledge based on the new SD approach as a result. The physical and psychological environment for dialoguing Ba has to be created in the externalization stage to make the group members able to reveal their own knowledge and develop explicit collective knowledge (a shared vision on SD, strategy, etc.). In developing this Ba, reflection that is emphasized in Kolb’s (1984) model has to be encouraged. Reflection enables to effectively share the knowledge that is necessary for constructing collective explicit understanding on vision of SD and strategy. The method of concept mapping (both individual and group maps) has to be used for making SD knowledge explicit. It also helps to develop system thinking. Focus group may be applied to make sure that consensus is reached. In these activities, interpretation and integration proposed in Crossan 4 I model (Stevens and Dimitriadis 2004) can be encouraged. Interpretation helps revealing the individual SD knowledge; it is then interpreted by group members in the light of their own understanding. The interpreted knowledge is integrated, since the group seeks for shared attitude to SD in their organization’s strategy. With this knowledge the group is ready for drafting the project of organization’s new SD strategic plan by applying the method of PDCA (plan, do, check, act) cycle (Epstein 2008) (see Figure 1). Systemizing Ba is necessary in the combination stage for transforming the explicit collective SD knowledge into the organization’s formal knowledge (documents). The main methods used are a) presentation of the draft prepared by the workgroup; b) discussion of the workgroup and other groups in an organization; c) application of PDCA. In this stage the interpretation of knowledge on SD of other groups and the workgroup takes place, as well as collective knowledge of higher level is created. The process has to be supported by the allocation of time, organizational and other resources (setting the workgroups meetings, their schedule, facilities, etc.). Organization’s formal knowledge may be expected as a result which is an approval of a new strategic plan based on the new approach to SD. Exercising Ba embraces organizational and educational tools applied in the concrete time period. These tools ensure that the officially approved organization’s documents for SD would take employees’ mind and senses and become their daily knowledge and motivation for sustainable activities. In this phase the learning Ba is created by training and application of PDCA cycle. Initiation stage: 1) Interview in the form of dialogue between expert and informant to identify personal SD knowledge and to discuss the task for shifting to a new approach on SD. 2) Organizing Focus group to discuss common understanding on SD in order to prove readiness for the OLSD.
Dialoguing Ba 1) Construction of individual concept maps to disclose SD strategy essence. 2) Construction of group concept map that reveals the essence of SD strategy. 3) Organization of Focus group in order to confirm the consensus of group decision on SD. 4) Applying PDCA cycle and combining the solutions at each stage for preparation of draft SD strategy.
Originating Ba 1) Physical environment for being and acting together is created. 2)Favourable organizational atmosphere is maintained.
Exercising Ba 1) Organization of training to introduce the employees to the decisions on SD. 2) Applying PDCA cycle for the groups and i\individuals.
Systemizing Ba 1) Applying PDCA cycle for all groups in organization and combining the solutions at each stage of PDCA for preparation of draft SD. 2) Final SD strategy version is formalized.
Figure 1: Managerial factors for Ba enabling OLSD
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Valentina Burksiene and Palmira Juceviciene The four Ba environments of OLSD and the managerial factors applied for their creation are presented in Figure 1. Theoretically validated managerial factors were tested in Neringa Municipality.
3. Empirical testing of OLSD managerial factors In this part we will present the methodology employed for the research. The field experiment will be described introducing its logical structure and methods. The results will be presented and discussed.
3.1 Methodological background The most suitable environment to test the theoretically validated OLSD managerial factors empirically is considered to be a natural organizational environment where OLSD is taking place. Therefore, field experiment was carried out. The possibility to observe OLSD process from inside is considered to be an advantage. The field experiment was carried out at the administration of Neringa Municipality, which is the only municipality in Lithuania located in the territory of the national park. This national part is on the UNESCO world heritage list as an object of cultural landscape. However, for a long period of time SD has been considered from a very narrow perspective and treated as an environmental protection issue. The new understanding that environmental protection has to be related to the solution of economic and social‐cultural problems (and vice versa) influenced the necessity to develop a new document – Neringa strategic plan based on the system approach. A workgroup was formed to draft this document. The municipality administration was aware that the organizational competence in SD area had to be developed. It was useful for us as researchers to join the practitioners’ performance for carrying out the field experiment. The permission from the administration to use their organization’s name while presenting the research results has been received. One of the co‐authors of this paper had worked in the administration of Neringa municipality. The considerable degree of trust between the researcher and the experiment participants helped to carry out the observation of OLSD process from inside and to combine this observation with other research methods. The specific feature of this research is that some OLSD managerial factors served as the methods of empirical research.
3.2 The field experiment The main experiment lasted eleven months. It started when the executives of the municipality administration set up a workgroup (9 employees, all involved in the experiment) for drafting a new strategic plan. Using managerial factors (see Figure 1), two Ba were created: Dialoguing and Systemizing. There was no opportunity to create the other two Ba: 1. Because of the specific circumstances that are beyond the scope of the researchers’ influence, Exercising Ba was not implemented. This was a limitation of the research that was impossible to avoid: the situation in the organization changed after the local governance elections, the implementation of the third phase of SECI cycle – combination – ran over and some of the organization members terminated their employment contracts (because of the changes after the elections). 2. Another environment (Originating Ba), that should take place in a new approach to SD learning and adoption phase, could not be observed either: we could only start the experiment from the introductory stage between the processes of socialization and externalization. Introductory stage. During the experiment the initial SD knowledge was defined by the method of semi– structured interview. Since this interview helped reflecting and making tacit knowledge explicit, the interview may be considered at the same time as research method and as the managerial factor in transition from Originating Ba to Dialoguing Ba. Focus group was also employed for the this stage. Bell and Morse (2003) argue that this method is a relevant managerial factor of learning SD. The same Focus group, simultaneously, served as the method of defining group’s initial collective knowledge. Dialoguing Ba was developed aiming to empower each group member and all together to structure their individual thinking on SD, to construct collective knowledge on SD and to prepare the strategic plan draft based on a new approach to SD. Firstly, an individual reflection takes place and the individual concept maps
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Valentina Burksiene and Palmira Juceviciene are constructed. Later on, group members present their own concept maps for discussions and idea exchange and, as a result, a common understanding on Neringa SD is achieved in the group; collective concept map is created. The application of this method, as Bell and Morse (2003) argue, enables directing the learning process towards the integrated usage of economic, ecological and socio‐cultural means. Concept mapping (as a research method) also enables revealing the structure of existing and obtained knowledge. Tautkeviciene (2005) argues that concept mapping is an excellent diagnostic tool for defining the conceptual changes in understanding and knowledge. This method is also used for revealing system thinking and the problem solving skills in teams. The method of PDCA was used to prepare the draft of a strategic plan based on a new approach to SD. This method also was applied for the Combination and Internalisation stages (the systemic application of PDCA for OLSD is presented in Table 1). Table 1: Systemic application of PDCA: theoretical approach and its implementation at Neringa Municipality PDCA in Epstein’s (2008) theory PDCA in Neringa Municipality field experiment Plan: revise the existing documents from SD perspective, The workgroup drafted (externalization) a new strategic define aims and objectives that integrate SD dimensions, plan (and programmes of its implementation), which create development programmes. was presented to politicians for discussions and corrections indifferent committees and approval in the Council (combination). Do: identify organization’s structures and responsible In the process of developing programmes, there was a people relevant for the implementation of SD strategy; suggestion (after externalization) to revise the initiate training for responsible people and other SD‐related structure of implementation of the plan and responsible members in the organization; carry out programmes. people. A new structure and people were approved after the debates in political committees/ groups (combination) The workgroup was learning in the course of developing the strategic document (externalization), politicians in the committees/ groups were learning in discussions on the drafts of documents (combination) that were approved by the Council. Check: carry out internal audit by monitoring and The workgroup identified the indicators of monitoring measuring the indicators of SD performance (drawing on and evaluation with reference to SD (externalization); the approved system of monitoring and evaluation). they were discussed in committees/ groups (combination) and formalised by the approval of the Council. Act: to carry out management audit and improve the The administration executives and committees process of SD by appointing persons responsible for continuingly interacted with the workgroup to improve continuing performance monitoring and results evaluation. the draft of the strategy, its monitoring system and evaluation indicators (combination).
Aiming for formalization of SD knowledge, Systemizing Ba is initiated and the managerial factor of PDCA (plan, do, check, act) cycle (Epstein 2008) is applied. In this learning environment the workgroup presents the strategic plan to the other groups (departments) in municipality administration. The group discussion is moderated until the final decision on the strategic document of Neringa Municipality based on SD principles is reached. The observation from inside allowed defining the influence of each member on others. As the research strategy focussed on qualitative research, the results were processed by descriptive content analysis.
3.3 Empirical findings: analysis and discussion Introductory stage. Before starting the main experiment, we needed to find out what knowledge the employees bring from the previous stage in the SECI model (socialization). In other words, we were interested if group members have the initial knowledge necessary for drafting a new SD strategic plan.
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Valentina Burksiene and Palmira Juceviciene It was revealed (see Table 2) that the learners of the group had some initial knowledge of SD but this knowledge was inconsistent. The majority of respondents were not able to define explicitly the SD concept based on a new (systemic) approach. However, all of them understood the necessity of the systemic approach to SD as the basic for the strategic plan development and even used it while talking about the strategic actions in Neringa municipality. The interview also resulted in the finding that the members of workgroup had unequal conditions for informal discussions in the socialization stage of the previous phase of OLSD, where SD knowledge of the traditional approach is developed. To paraphrase Nonaka, Toyama and Byosiere (2001), the differences in knowledge largely depend on the extent people are involved into common organizational issues and on the possibility to work together (in the same space: office, workshop room, etc.). The dialogue with the researcher in the interview and the Focus group discussion soon afterwards (both of the methods may be considered as managerial factors helping a very smooth transition from socialization to externalization stage) enabled individuals to expand their understanding of SD significance and to gain new individual knowledge by reflecting. A common understanding was born in Focus discussion: it is necessary to agree on the goal of Neringa Municipality SD and the interrelated development issues. The group also achieved the consensus that the main issues to be integrated are the following: tourism, social development and care, environmental development, education, health, housing and environment, recreation, social infrastructure, economics, business, workplaces and cultural heritage. These issues may be considered as essential dimensions of Neringa Municipality SD. The Focus group started the conceptualization of collective knowledge on SD about the necessary implementation of environment protection requirements for further successful development. Dialoguing Ba was devoted to the researching of individual and collective SD knowledge that was made explicit with the help of individual and group concept maps. This knowledge served as an indicator hat OLSD took place. In their individual concept maps each group member mentioned from 4 to 10 possible dimensions of Neringa SD generated by the Focus group. Six people mentioned three essential SD issues (environmental, social and economic). The collective concept map showed seven dimensions generated by the Focus group. Thus we may note that the group concept map has been created reflecting the collective vision of SD (stimulate, develop and improve the quality in the economy; to guarantee, maintain and organize the social issues; to protect and save the environment) and reveal the suggested strategic directions for SD. In other words, the collective explicit knowledge of the workgroup about sustainable development has been created. This knowledge, however, was not formalized yet. Next Focus group later on highlighted that learners were positive on the concept mapping which enabled to expand their individual knowing, to understand the significance of other SD dimensions and to come to collective understanding. The group members agreed that the increased individual knowing and improved system thinking let them to prepare a more detailed and systematic concept map of the group. Later, the work group prepared the draft of the strategic plan through the PDCA activities. In Systemizing Ba the group was working together with other groups of the municipality on the preparation of planning document on SD. The PDCA and discussions as the managerial factors were used. It is worth noticing that the greatest initiative was exerted by the group which had passed the externalization phase. Having achieved the common agreement, SD knowledge was formalized by approving the prepared planning document on organizational level. Thus, the empirical findings show that the relevant managerial factors in the Ba environment under research helped to initiate and maintain OL; the SD knowledge was constructed, developed and finally integrated into the organization’s strategic document. The relevance of managerial factors is illustrated by the fact that in the process of OLSD, the SD knowledge was created, shared and improved in each Ba empirically researched (see Table 2). Exercising Ba and Originating Ba (in the phase of the OL for shifting on a new approach to SD) were not implemented due objective reasons and this is some limitation of the experiment. Therefore, the managerial factors grounded for these two Ba need to be tested in future research. We have noticed that sometimes the transition from socialization to externalization, especially when knowing has to be re‐conceptualized, requires a supplementary stage. We refer to it as an introductory stage, when
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Valentina Burksiene and Palmira Juceviciene specific managerial factors, involving experts, help employees to see that they need to reconceptualise their knowledge on individual and collective levels. One may question if this is not part of externalization and Dialoging Ba. But Toyama and Nonaka (2000) note that this Ba is associated with dialogues between the participants (our observation: but not the experts and participants). The above may be used to confirm the relevance of the introductory stage in some cases of organizational learning. In our case, this is a need for reconceptualization. Further research is of course necessary to find out if the SECI model may be supplemented with the introductory stage. Another question is if in those cases the introductory stage is relevant only between the stages of socialization and externalization or if other needs may exist; it remains open. Table 2: Knowledge on SD generated by managerial factors during the experiment Ba Introductory stage: shifting from Originating Ba to Dialoguing Ba
Dialoguing Ba
Systemizing Ba
Managerial factor semi‐structured interview between the expert and informant to identify initial individual SD knowledge Focus group in order to reveal what kind of SD knowledge each member of the group has; how it is different or common; to motivate for reaching a new level of knowledge for new SD Construction of individual concept maps (ICM) to reveal the individual knowledge on SD of a new approach. Construction of group concept maps (GCM) while reaching consensus in the group on collective understanding of SD based on a new approach Focus group in order to reveal what kind of SD knowledge has each member of the group; how it is different or common; to motivate for reaching a new level of knowledge for new SD 4) PDCA cycle is used for drafting the strategic plan 1) Conditions created for group‐initiator to present its project to other groups for common discussion 2) Applying the PDCA cycle
Result 1) Individuals were encouraged to externalize their knowledge. It turned out that they had different knowledge, almost sufficient for starting OLSD 2) The group and individual members pointed out that their knowledge is different, it should be presented more precisely to each other for reaching common understanding. This was the preparation for OLSD 1) ICM Each group member pointed out from 4 to 10 possible dimensions of Neringa SD; 6 people out of 9 referred to three essential SD issues 2) GCM The collective concept map shows 7 SD dimensions generated by the Focus group and reflects the group vision of SD 3) Focus group The consensus on SD has been confirmed 4) PDCA cycle A draft of the strategic plan was developed
1) The consensus on SD has been confirmed in all groups A strategic plan on SD prepared and approved: SD new knowledge is formalized on organization’s scale
Further research is necessary to answer the question on OLSD: what level and extent of specific knowledge is sufficient for each group member for a successful process of externalization when reconceptualization takes place in organization?
4. Conclusions Organizational learning for sustainable development is difficult to implement when employees lack relevant experience, especially when a narrower concept of SD is conventional in the stage of socialization. In this case shifting from socialization to externalization stage requires additional managerial factors based on external expert competence. These factors may be a) a semi‐structured interview for identifying the SD knowledge of every member of future externalization group; b) Focus group for approximate identification of collective knowledge, understanding an SD task with a new wider approach and motivating for seeking new SD knowledge. The following challenges and managerial factors for addressing them are characteristic of the externalization stage:
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ability to externalize individual knowledge in a structured way: construction of individual concept maps may be used for this;
ability to present individual knowledge to other group members, find a consensus on common collective knowledge: a group concept map may be developed, drawing on dialogues and discussion, consensus decisions on SD.
In the stages of externalization and combination, an important managerial factor is the method of Focus group which helps workgroups to summarise the results by raising and answering targeted questions. The method of PDCA cycle is a successful managerial factor for bringing together workgroups in the process of externalization, organization’s groups – at the stage of combination, and reaching a new approach to SD in groups and on the level of organization. The PDCA method is also relevant in the stage of internalization. The executives of organizations implementing a systemic SD approach vs a narrow environmental approach should consider the need for additional managerial factors, like inviting experts on a systemic SD approach for diagnosing the employees’ knowledge on SD and encouraging them for understanding the new approach to SD. For OLSD, the following methods may be used successfully as managerial factors: developing individual and group concept maps, Focus groups and PDCA. Thus the first step is to make sure that employees are competent to employ these methods. This research was funded by the European Social Fund under the Global Grant measure
References Bell, S. and Morse, S. (2003) Measuring sustainability: learning by doing, EarthscanPublications Ltd. Burksiene, V. (2012) Darnaus vystymosi organizacinis mokymasis, Doctoral dissertation, Kaunas University of Technology, 2012. DiBella, A.J. (2003) Organizations as Learning Portfolios, In Easterby‐Smith, M. and Lyles, M. A. (Eds.), The blackwell handbook of organizational learning and knowledge management, Malden, MA; Oxford, Blackwell Publishing Ltd., pp. 145–160. Easterby‐Smith, M., Li, S. and Bartunek, J. (2009) „Research Methods for Organizational Learning: The Transatlantic Gap“, Journal of Management Learning, Vol. 40 (4), 439–447, pp. 1350–5076. Epstein, M.J. (2008) Making sustainability work: best practices in managing and measuring corporate social, environmental and economic impacts, Greenleaf publishing. Juceviciene, P. and Burksiene, V. (2009) A model of organizational learning for solution of problems of sustainable development, Changes in Social and Business Environment: proceedings of the 3rd international conference, November 4‐5, 2009, Kaunas University of Technology Panevėžys Institute, Lithuania, pp. 167‐174. Kolb, D. (1984) Experiential Learning: Experience as the Source of Learning and Development, Prenticee – Hall, Englewood Cliffs, NJ, 1984. Nonaka, I. and Takeuchi, H. (1995) The knowledge – creating company, Oxford, University Press. Nonaka, I., Toyama, R. and Byosiere, P. (2001) A theory of organizational knowledge creation: understanding the dynamic process of creating knowledge, In Dierkes, M., Antal‐Berthoin, A., Child, J. and Nonaka, I. (Eds), Handbook of Organizational Learning and Knowledge Creation, Oxford University Press, NY, pp. 491‐517. Pasteur, K., Pettit, J. and Van Schagen, B. (2006) (IDS Sussex). ‚Knowledge management and organizational learning for development‘, KM4Dev workshop. Background paper. Brigiton, [[online], www.ids.ac.uk. Porter, T. and Kordoba, J. (2008) „Three views of systems theories and their implications for sustainability education“, Journal of management onlinefirst, No. 3, [online], http://online.sagepub.com 323. Stevens, E. and Dimitriadis S. (2004) „New service development through the lens of organizational learning: evidence from longitudinal case studies“, Journal of Business Research, No.57 [online], www.sciencedirect.com. Tautkeviciene, G. (2005) Studentų mokymosi aplinkų susiformavimui iš universiteto bibliotekos edukacinės aplinkos įtaką darantys veiksniai, Doctoral dissertation, Kaunas University of Technology, 2005. Toyama, R. and Nonaka, I. (2000) “What is a Good Ba? ‐ The Role of Leadership in Organizational Knowledge Creation”, Hitotsubashi Business Review, No. 48 (1), pp. 4‐ 17. Williams, D. (2008) „Sustainability education’s gift: learning patterns and relationships“, Journal of educatuon for sustainable development, [online] http://jsd.sagepub.com/cgi/content/abstract/2/1/41. Zink, K.J. (2008) „Corporate sustainability as a challenge for comprehensive management“, [online] bwww.amazon.com.
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Capturing Safety Knowledge: Using a Safety‐Specific Exit Survey Christopher Burt, Cassandra Cottle, Katharina Näswall and Skye Williams University of Canterbury, Christchurch, New Zealand Christopher.burt@canterbury.ac.nz Ckc34@student.canterbury.ac.nz Katharina.Naswall@canterbury.ac.nz Sdw69@student.canterbury.ac.nz Abstract: Organizations not only create knowledge, but also have a need to capture knowledge before it is lost with exiting employees. Safety related knowledge is relevant to many organizations, but is particularly hard to capture from employees due to the many variables which constrain employees’ willingness to voice safety issues. Some of these constraining variables, such as management and co‐worker support and trust issues, and fears around a ‘blame culture’, are removed when an employee makes the decision to leave an organization. With these constraints on voicing safety issues removed, organizations may have an opportunity to capture valuable safety knowledge from exiting employees. The use of a safety‐ specific exit survey process was examined. This post employment safety voicing strategy was examined in relation to perceived management and co‐worker support for safety and trust issues. One hundred and one individuals who had recently resigned from a job were questioned about their need to voice safety information at the time they resigned, and their willingness to voice safety issues in an exit survey process. Results show that perceived support and trust for safety are positively associated with on‐the‐job voicing. More importantly, when a participant had left a job where support and trust were perceived as low, they indicated a higher desire to complete a safety‐specific exit survey process. That is when the contextual constraints posed by a lack of support and low trust are removed due to voluntary withdrawal from the job, participants wished to voice their safety concerns. Overall, the results strongly suggest that the introduction of a safety‐ specific exit survey process has the potential to capture valuable safety information, and as a consequence potentially improve workplace safety. Keywords: turnover, safety, exit‐survey, voicing, trust, support
1. Introduction Poor workplace safety can result in employee turnover (Bell & Grushecky, 2006; Cree & Kelloway, 1997; Kincaid, 1996; Ring, 2010; Viscusi, 1979). Workers that leave a job because of safety concerns may leave without voicing their safety concerns. Indeed, they may leave because they feel they are unable to voice their safety concerns, or because they feel that if they do voice safety concerns nothing will be done about them (Cree, & Kelloway, 1997; Hirschman, 1970; Reason, 1997). If employees leave their job due to safety concerns, but these concerns are not voiced, important safety knowledge is being lost. In an attempt to capture safety knowledge from exiting employees, we propose the use of a safety‐specific exit survey. The primary question addressed in this research was whether participants were willing to complete a safety‐specific exit survey. Furthermore, in an attempt to explain why a safety‐specific exit survey might be necessary, the research also examined predictions about relationships between management and co‐worker support and trust (variables which have been found to be associated with employee voicing), and willingness to complete a safety‐specific exit survey. Research suggests that the failure to report safety incidents may result from a lack of management support, sometimes labelled a ‘blame culture’, where voiced safety information is used to assign blame and take disciplinary action against those believed responsible (e.g., Clarke, 1998; Probst & Estrada, 2009; Webb, Redman, Wilkinson, & Sanson‐Fisher, 1989). Withey and Cooper (1989) also suggested that employees weigh up the possible benefits and costs when deciding whether or not to voice their concerns. Reason (1997) argued that to counter this constraint on voicing it is essential to protect informants and colleagues from disciplinary actions taken on the basis of their safety reports. In contrast to the constraining influence that a lack of management support appears to have on employee voicing, research has also found that employees who perceived management as supportive and open to suggestions were more likely to engage in voicing behaviour (Elizabeth & Phelps, 1999). Furthermore, research has found that management openness, and supportive leadership were significant determinants of safety voicing (Neal & Griffin, 2002; Withey & Cooper, 1989). Management support, while important for voicing safety issues, appears to interact with co‐worker support. Research by Tucker, Chmiel, Turner, Hershcovis, and Stride (2008) found that co‐worker support for safety fully
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Christopher Burt et al. mediated the relationship between management support for safety and safety voicing behaviour. This result is consistent with other research which has suggested that supportive group norms are a significant determinant of safety voicing (Neal & Griffin, 2002; Withey & Cooper, 1989). This may reflect the possibility that without co‐ worker support, the worker voicing the safety concern is taking a risk that their co‐worker will respond unfavourably. Management and co‐worker support for safety are clearly associated with trust as an influencing factor in safety voicing. Flin and Burns (2004) applied Mayer, Davis and Schoorman’s (1995) trust model to safety behaviours, observing that the challenging of a peer’s potentially unsafe work practice requires trusting behaviour. Thus trust between all levels of the organisation is paramount to facilitate the voicing of safety issues (Flin & Burns, 2004; Mayer et al, 1995). If an employee has low trust for management, perhaps because they consider that voicing safety concerns would negatively influence their relationship with the organisation or not result in any action (whether justified or not), they may not voice their safety concerns. Research on trust has frequently noted that trust development is associated with positive organisational outcomes (e.g., increased communication and knowledge exchange, Andrews & Delahaye, 2000; enhanced mutual learning, Gubbins & MacCurtain, 2008). Furthermore, safety‐specific trust benefits include increased communication about safety, shared safety perceptions, positive safety attitudes, reduced incident rates and increased personal responsibility for safety (e.g., Hofmann & Stetzer, 1998; Reason, 1997; Watson, Scott, Biship & Turnbeugh, 2005; Zacharatos, Barling & Iverson, 2005). Collectively, the discussion above suggests that the contextual issues of management and co‐worker support, and employee trust in both management and co‐workers, can enhance or place constrains on the voicing of safety concerns. The constraining factors may also reach a point where the employee decides to leave, as to remain is seen as too risky. When an employee makes the decision to leave a workplace, contextual constraints on voicing may be largely removed, as management has little ability to assign blame or take disciplinary action against an employee that has resigned. Similarly, an employee that has resigned has essentially left the social unit or group they worked with, and as such co‐workers responding unfavourably to the employee’s voicing may no longer be a constraining factor. Free of the contextual constraining influences, a safety‐specific exit survey process may provide an employee with an opportunity to voice safety concerns, and data from such a process may provide an organization with valuable safety knowledge. This study addressed the general questions noted above, and tested 2 hypotheses:
Management and co‐worker support and trust measures will be positively correlated with on‐the‐job safety voicing.
Management and co‐worker support and trust measures will be negatively correlated with a need to voice at exit measure.
2. Method 2.1 Sampling, procedure and participants A haphazard sampling approach (Weisberg & Bowen, 1977) was used to locate 101 individuals who had exited, within the last 36 months (mean = 12.3 months, SD = 10.4), a job which they considered had a degree of safety risk. Sampling focused on this population, as obtaining exit related information sometime after the actual job exit has been found to positively influence the amount, specificity, and validity of information obtained (e.g., Lefkowitz & Katz, 1969). From the job title provided by the participant they had worked in the following industries: 22 in construction, 20 in manufacturing, 10 in forestry, 5 in mining, 2 in transportation, 8 in agriculture, 8 in adventure tourism, and 26 in miscellaneous industries (which includes 13 who indicated they worked in a trade). The research survey was distributed via post, email, or by hand. The 101 participants were made up of 79 males (mean age = 26.8 years), and 22 females (mean age = 29.5 years). Responses relating to the job the participant had exited (that for which they completed the exit survey) indicated a mean job tenure of 38.9 months (SD = 62.7), a mean number of co‐workers of 27.0 (SD = 46.4), scores on the Hayes, Perander, Smecko and Trask (1998) Job Safety Risk Scale ranging from 1 to 4.8, mean = 3.0, median = 3.1, SD =.71, and Pearce and Gregersen (1991) Team Member Interaction Scale scores, ranging from 1 to 5, mean and median = 4.0, SD =.77.
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2.2 Materials The front page of the survey provided information regarding informed consent, and participant instructions. Section one contained demographic and background questions, and section two listed 40 workplace safety issues (see Table 3). The remaining sections were presented in a number of different orders to help control for common method variance, and included measures of perceived organizational support for safety, and perceived co‐worker support for safety, management trust, co‐worker trust, team member interaction and job safety risk. Participants responded to items in these measures on five‐point Likert scales (1 = strongly disagree to 5 = strongly agree). Scale scores were obtained by summing ratings across scale items, and dividing the sum by the number of items. It was also necessary to adapt items from the scales into the past tense to correspond with the procedure which required the participant to respond for the last job they had exited: their previous job. In the demographic section participants were asked their age, gender, the date they had left their previous job, the date they filled out the survey, tenure in their previous job, number of co‐workers in their previous job, and job title. Four further questions were asked: Please rate how much ‘safety concerns’ prompted you to leave your previous job? (0 = ‘Not at all’ to 7 = ‘Very much’), and At the time you left your previous job did you feel there were safety issues/concerns which you wanted to tell someone about before you left? (0 = ‘No’ to 7 = ‘Yes there were a lot of issues’). If participants responded with a rating greater than 0 to the latter question they were asked If you now had an opportunity to sit down with management from your previous job and voice your safety concerns how willing would you be to do that? (0 = ‘Not willing at all’ to 7 = ‘Would be very keen to do that’), and If you now had an opportunity to sit down with co‐workers from your previous job and voice your safety concerns how willing would you be to do that? (0 = ‘Not willing at all’ to 7 = ‘Would be very keen to do that’). Section two of the survey was comprised of 40 statements of safety issues (e.g., Work speed pressure from supervisors which reduced safety) designed to measure the extent and type of actual safety voicing on the job, and extent and type of safety issues exited employees might need to voice. For each safety issue, participants were required to tick one or more response options. Response options were defined by four columns placed to the right of the listed safety issues and headed: Not Applicable: The safety issue was not relevant to your previous job; Did: you talked about the issue in your previous job; Yes Management: It is an issue you would have liked to talk to management about but never did; and finally Yes Co‐worker: It is an issue you would have liked to talk to co‐workers about but never did. Three scores were calculated from the section two responses. Firstly, the number of applicable safety issues that could be talked about for each participant was calculated by subtracting the total Not Applicable responses from the 40 described safety issues. Next, an actual voicing score was calculated by dividing the number of did responses by the number of applicable safety issues which could have been talked about. Finally, two need to voice measures were calculated (one for management and one for co‐workers) by dividing the Yes Management and the Yes Co‐worker totals by the number of applicable safety issues which could be talked about. Each of the three variables could range from 1 to 100, and represent the percentage of applicable safety issues participants did talk about, and the percentage of applicable safety issues they would have liked to talk about with management and with co‐workers. Participants perceived job risk was measured using the 10‐item Job Safety Risk scale, developed by Hayes, et al., (1998). This scale was included to ensure that the research had sampled participants who were responding for a job where safety was a real concern in the workplace. Participants were required to indicate the extent to which they agreed that words and phrases (i.e. “dangerous”) described their previous job (alpha = .76). The five item Team Member Interaction scale developed by Pearce and Gregersen (1991) were used to measure job interdependence. The scale was included to ensure the study had sampled individuals whose previous job had provided an opportunity to interact with co‐workers, and thus potentially an opportunity to talk with co‐workers about safety issues (alpha = .86). The three item Perceived Organizational Support for Safety and Perceived co‐worker support for safety scales developed by Tucker et al. (2008) were adopted to measure the degree to which the company and co‐workers encouraged workers to express concerns about safety, and responded to workers safety concerns,
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3. Results 3.1 Safety concerns and voicing at exit The first question addressed was whether safety concerns had prompted participants to resign (exit) their previous job. A mean response of 1.58 (SD = 2.0) was obtained for the question regarding to what extent safety concerns prompted the participant to leave the organization. Given the importance of this question, the distribution of responses was examined: 0 (Not at all) = 50.5%, 1= 8.9%, 2= 10.9%, 3 = 10.9%, 4=5.0%, 5= 10.9%, 6 = 0%, 7 (Very Much) = 3.0%. The response distribution translates into 51 participants who indicated that no concerns about safety had influenced their exit decision, while the remaining 50 participants did have such safety concerns. This split in the sample was used to form two groups which were labelled no safety concerns and safety concerns. Significant differences between these two groups were found for job risk scores, where the group with no safety concerns had a lower job risk mean (2.8, SD = .69) than those in the safety concerns group (mean = 3.3, SD = .63; F[1,99] = 17.647, P <.01), and for responses to the general need to voice question: those in the no safety concerns group had a lower mean (1.3, SD = 1.7) than those in the safety concerns group (mean = 2.8, SD = 2.1; F[1,99] = 13.062, P <.01).
3.2 Feasibility of a safety‐specific exit survey process In order to examine the general feasibility of a safety‐specific exit survey process, the responses of the participants (n=38) in the safety concerns group, who gave a rating greater than 0 to the general voicing question (i.e. At the time you left your previous job did you feel there were safety issues/concerns which you wanted to tell someone about before you left?), to the two questions on willingness to voice their safety concerns after exit to specific targets were examined. The first question pertained to willingness to voice to management. Four participants (10.5%) responded 0 = not willing at all, and the mean response for the remaining 34 participants was 3.82 (SD = 2.05, range 2 to 7). The second question pertained to willingness to voice to co‐workers. Four participants (10.5%) responded 0 = not willing at all, and the mean response for the remaining 34 participants was 4.29 (SD = 1.96, range = 1 to 7). Responses to the latter two questions indicate that 68 percent of the participants that had safety concerns at the time they exited were willing to voice their safety concerns if given an opportunity now. These results may attest to the importance of the safety concerns, and to the feasibility of using a safety‐specific exit survey process.
3.3 Predictors of safety voicing and need to voice at exit Hypotheses 1 and 2 predicted that the measures of management and co‐worker safety support and trust would be positively correlated with actually voicing safety issues, and negatively correlated with wanting to voice at exit. Table 1 shows the correlations addressing these hypotheses. As predicted, safety support and trust were positively correlated with actual safety voicing. Perhaps more importantly, the participants that rated safety support and trust as low in their previous job tended to indicate they wished to talk about more safety issues at exit. Table 1: Correlations between management and co‐worker support and trust measures, and voicing measures
Scale Alpha
Actual voicing Percentage N=34
Management Support Management Trust Co‐worker Support Co‐worker Trust Actual voicing Wanted to voice to co‐workers
.87 .84 .81 .79
.48** .30# .29 .42*
** = P >.01, * = P >.05, # P = .08
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Want to voice to management Percentage N=34 ‐.40* ‐.28 ‐.23 ‐.36* ‐.87** .37*
Want to voice to co‐workers Percentage N=34 ‐.16 .02 ‐.27 ‐.14 ‐.46**
Christopher Burt et al. To further examine hypothesis 2, the participants were divided into 2 groups. The 51 participants in the no safety concerns group (as defined above) formed one group, and the 34 participants in the safety concerns group that indicated they wanted to voice to management and co‐workers at exit formed the ‘wanted to voice group’. Table 2 shows the means and standard deviations for these two groups for the safety support and trust measures. Comparison of the means indicate significant differences for both management safety support and trust. Inspection of the means indicate that the ‘wanted to voice group’ perceived that management support for safety and trust were lower in their previous job compared to the no safety concerns group. Table 2: Means and standard deviations for comparisons of management and co‐worker support and trust measures
No Safety Concerns at Exit N=51
Management Support
3.79 .88 3.52 .79 3.52 .87 3.95 .64
Management Trust Co‐worker Support Co‐worker Trust
Safety Concerns and Wanted to Voice at Exit N=34 3.17 1.30 2.98 1.02 3.39 .95 3.78 .71
ANOVA Comparison F(1,84) = 6.858* 7.539** .298 1.340
** = P >.01, * = P >.05
4. Discussion The results clearly suggest that there is an association between workplace safety and employees’ voluntary turnover decisions. This finding is consistent with previous research (e.g., Bell & Grushecky, 2006; Cree & Kelloway, 1997). The results also support hypothesis 1, showing that perceived support from management and co‐workers, and trust in management and co‐workers were positively associated with voicing safety concerns while in the job. These results are also consistent with previous research findings (e.g., Elizabeth & Phelps, 1999; Tucker, et al., 2008). Of particular importance to this paper are the negative associations found between the support and trust measures, and willing to voice to management after exit. Clearly, employees who had left a job where support and trust were perceived as low had issues they wished to voice, and this sample showed some willingness to voice these concerns in a safety‐specific exit survey. This suggests that the suppressing influence which a lack of safety support and trust might have on voicing within the job may not necessarily extend to the exit context. Overall, the results suggest that once workplace constraints that stem from a lack of support and trust around safety, such as fear of blame or retaliation for voicing, have been removed because the individual has left their job, employees may be willing to voice in a safety‐specific exit survey process. Furthermore, employees’ motivation to complete a safety‐specific exit survey process may stem from a desire to protect the co‐workers that remain. High scores on a safety exit survey (a lot of issues that exiting employees want to talk about) perhaps point to issues with support and trust in the workplace. So while support and trust might not be measured in a safety‐ specific exit survey, the results may form a proxy measure, with extensive post employment voicing perhaps indicating that there could be support and trust issues in the workplace.
4.1 Practical implications: Issues in the use of a safety‐specific exit survey process From an organization’s perspective it may be important that they do not consider a safety‐specific exit survey as a process to find out why an employee is leaving their job. That is, the safety‐specific exit survey should not be thought of in terms of a classic exit interview/survey. The key issue is that traditional exit interviews/surveys conducted at the time the employee exits the job have been criticized for producing bias information, contaminated by impression management, and a desire to distort or hide the employees true reason for leaving (Feinberg & Jeppeson, 2000; Giacalone, Knouse, & Montagliani, 1997; Gordon, 2011). Furthermore, as well as framing the safety‐specific exit survey as a safety initiative, the organization might gain
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Christopher Burt et al. more complex and valid information if the survey is administered sometime after the employee has exited the job (Lefkowitz & Katz, 1969). Separating the safety‐specific exit survey from the actual time an employee leaves the job may also have another benefit. An exiting employee has to make a decision about whether to voice their concerns and potentially benefit their friends and colleagues who remain with the organization, versus the costs to themselves. Costs could include retaliation against the exiting employee by giving them a negative recommendation or reference to a future employer, and/or retaliation against friends and family who may still be working for the organization (Feldman & Klaas, 1999). A simple way to remove these perceived costs would be to allow anonymous completion of the safety‐specific exit survey. However, in practise ensuring complete anonymity may be difficult in roles where the rate of employee turnover is low. A key issue which the safety‐specific exit survey process must address is who conducts the process. That is how can the safety‐specific exit survey process work if employees view management as un‐supportive and not to be trusted? Here it is important to consider the question of whether all management are considered equal in terms of safety support and trust. To address this issue it may be useful to draw the distinction between work related management, such as a supervisor, foreman or line managers, for whom the primary focus may be productivity (to ensure the assigned work is completed), and a safety manager who may have little direct daily contact with employees, but whose role it is to ensure workplace safety. Ideally, it is the safety manager who would be responsible for the safety‐specific exit survey process, as this manager may be seen as in a position to actually respond in a positive way to voiced concerns, whereas the more immediate manager may in fact have already been told of the concerns and not responded due to their focus on productivity. There is, however some research evidence which suggests that attitudes towards both immediate supervisors and authority in general may affect willingness to discuss issues during exit processes (e.g., Knouse, Beard, Pollard & Giacalone, 1996). Each organization needs to consider what safety issues they could, or should, include in their safety‐specific exit survey. Ideally the survey items would be developed to suit the specific workplace or type of work. Arguably, the more idiosyncratic the survey items to a specific organization and the type of work undertaken, the more informative the data it generates will be for safety development. In addition to modifying the safety issues listed in a safety‐specific exit survey, organizations could adopt different response formats. The current focus was on identifying safety issues which employees wished to discuss, what might be termed negative safety issues. By varying the response format, the exit survey could also measure positive safety issues. One alternative or additional response option could be to ask exiting employees to rate how well the organization and their work unit have been managing each safety issue. Adding this response option might help identify both well managed and poorly managed safety aspects. Finally, the study has both strengths and limitations. As a strength, the study advances the use of a knowledge acquisition tool which appears to have previously received no research attention in relation to safety management. Limiting the research is the use of self‐report methodology. However, the variables of interest in the present study would be very difficult to assess with any other method.
5. Conclusion If there is no formal safety‐specific exit survey process, the functional use of any safety related knowledge which exiting employees hold cannot occur. In such circumstances, neither, workplace safety, or the costs associated with employee turnover (assuming the replacement employee may also reach similar safety concerns and subsequently leave), are being addressed. While the relationship between safety and employee turnover identified in the present study suggests that some employees are very likely to have safety issues to voice in a safety‐specific exit survey, such a survey might be usefully applied to all exiting employees from high risk work. Even employees who are not exiting due to specific safety issues may have some useful safety knowledge to contribute to the organization they are leaving. Safety gains from a safety‐specific exit survey process could be considerable, and allow an organization to consistently monitor and improve its safety performance.
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Knowledge Management in Defence Barry Byrne and Frank Bannister Irish Defence Forces and Trinity College Dublin barry.byrne@tcd.ie frank.bannister@tcd.ie
Abstract: Knowledge management in the military has traditionally been carried out by the incorporation of knowledge gained over many years, even centuries, into training and doctrine. Nonetheless, a great deal of knowledge is still learned and transferred in the field, often in quite informal ways, and specialised expertise and insights are frequently lost when experienced personnel leave or are killed in action. This paper examines the emerging trends for knowledge exchange, and explores ways in which technology can be used to facilitate knowledge capture and knowledge transfer in this environment. Emerging technologies have resulted in military forces facing an ever increasing challenge in the race to achieve information and decision superiority. The contemporary operating environments in which peacekeeping forces find themselves require military leaders to process continually increasing amounts of information fed to them by a myriad of sensors in the field. With this vastly increased availability of information comes a corresponding increased risk of information overload and degradation in the ability of commanders to convert information into usable knowledge. While information overload can have serious consequences in the world of business, the implications are even more critical on the battlefield where the quality of decisions can have life and death consequences. Command and control in peacekeeping operations is taking on new dimensions and the role of military personnel is steadily evolving into that of knowledge worker. While intelligence has always been a critical part of military operations, the transition from soldier to knowledge worker may seem an improbable one. However, awareness of the role and importance of knowledge management even at the level of the private soldier and the 'strategic corporal' has grown steadily in recent decades. In the words of a 2010 NATO publication; "knowledge is the new ammunition". This research investigates the potential for Information and Communications Technology (ICT) to aid information and knowledge management in the military in general and on peacekeeping in particular. As part of this research 159 defence personnel from over 15 countries were surveyed to ascertain their opinions and the international trends in this field. Follow up interviews were then conducted with a wide variety of defence experts, civilian and military, across several countries. The findings identify the sharing of information and knowledge as a key enabler in the quest to achieve information and decision superiority both on the battlefield and in the increasingly complex civil-military peacekeeping environment that represents the majority of operations that take place in the world today. A number of recommendations are made to improve the implementation of ICT enabled information and knowledge management initiatives in defence. Keywords: Knowledge management, defence, peacekeeping, decision making
1. Introduction The concept of a transition in the military from traditional soldier to ‘knowledge worker’ is well underway. Information and Knowledge are a military member’s primary resource, regardless of rank. A US Marine Corps General introduced the idea of the ‘strategic corporal’ in 1999, and since then the concept has gained widespread academic and military recognition (Krulack 1999). Militaries have always valued information, but they are increasingly recognising that information, and more specifically, knowledge, is indeed power. (Mace & Thomason 2008). The capture of knowledge, both explicit and tacit, is a challenge for most organisations, but even more so for the military and defence sector. As Goh and Hooper (2009) suggest, that there exists an inherent conflict between allowing information and knowledge to flow freely within the organisation, and the need to keep certain information secure; this is particularly acute in the armed forces where the correct dissemination methods in a closed information environment need careful design. A balance must be found between ease of use and a high level of security and information assurance. Over the last ten years the Irish Defence Forces have embraced the need for continuing change as part of its culture. They have gone through a major evolution and today are a highly professional, modernised, lean organisation with an establishment of 10,000 personnel serving at home and abroad. Ireland has a long and proud tradition of peacekeeping having contributed to 19 international missions in recent years. These engagements have resulted in a large body of knowledge about how to conduct peace keeping operations in what are often extremely volatile and sometimes hostile environments. It is this need to retain corporate knowledge that motivated this research. This research therefore set out to address the question of how Information and Communications Technology (ICT) can support information and knowledge management in defence. The objectives included understanding the current status of information and knowledge management in the Irish Defence Forces, the particular barriers to information and knowledge sharing and the possibilities for using information systems in facilitating the capture and dissemination of information and knowledge. The remainder of this paper is structured as
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Barry Byrne and Frank Bannister follows; first there is a brief literature review on knowledge management (KM) in the military. Next, the research approach is described. In section four the findings and analysis are presented. Section five discusses these findings and section six presents a brief conclusion.
2. Literature review Although some authors use data, information and knowledge interchangeably (Toffler and Butz 1990), it is generally accepted that in any accurate study of the discipline it is important to differentiate between them. This is easy to do with data and information. Knowledge is much more difficult to distinguish and a discussion of this will not be undertaken here as it is assumed that readers will be familiar with this debate. The management of knowledge is also a widely debated topic; protagonists believe it to be the about the management of Drucker’s (1993) “only meaningful resource today”; sceptics describe it as nothing more than the latest management fad (Wilson 2002). Sveiby (1990) was one of the first to write about the measurement of 'intangible assets' and other aspects of 'intellectual capital', but even then the strong ties with information management were evident. Maier (2007) describes knowledge management as a function and states that it is responsible for the resultant selection, implementation and evaluation of goal-orientated knowledge strategies. Rumizen (2002) a KM specialist who has worked with the U.S. Army and National Security Agency, treats knowledge management more as a systematic process and states that it is by this process that knowledge needed for an organisation to succeed is created, captured, shared and leveraged. The US Army states that “knowledge management is a discipline that promotes an integrated approach to identifying, retrieving, evaluating, and sharing an enterprise’s tacit and explicit knowledge assets to meet mission objectives.” (US Army 2010, p2). There is some debate as to whether ’management’ is the correct term to be used in relation to knowledge. Many authors prefer to talk about ’knowledge focus’ or ’knowledge creation’. While NATO has a definition of knowledge management in the Bi-Strategic Command Directive 25-1 that states “NATO knowledge management is a multi-disciplined approach to achieving organisational objectives by making the best use of information, expertise, insights and best practises” it tries to avoid the term ‘management’ and instead refers to the “knowledge centric organization” and “knowledge development” (NATO 2008). Even more dramatically it goes on to state that “Knowledge is the new ammunition. It is a commodity we are constantly collecting, integrating, exploiting and sharing. Regardless of whether you are an operator, staff officer, Subject Matter Expert or General, we are all knowledge managers in the business of transforming information to best serve our needs.” (NATO 2010, p19). Simply put; knowledge management deals with how best to leverage knowledge internally and externally (Liebowitz and Megbolugbe 2003), but perhaps what is needed in the modern environment is recognition that one can never fully manage knowledge, one can only transfer it. The focus should therefore be on managing knowledge transfer frameworks and facilities. In this context there is much debate about the tacit/explicit division and the SECI model which, again for reasons of space, will not be discussed here. Contributors to this debate include not only Nonaka and Takeuchi (1995), but Davenport, (1997) Gourlay (2006a), Stacey, (2001; Tsoukas (2003), Schultze and Stabell (2004), Gourlay and Klien (2008), Niedderer and Imani (2009), Hedlund (1994) and Day 2005). This debate has not deterred many people from pressing ahead with knowledge management models based on SECI and a large body of literature has emerged on each of its components. Liebowitz and Megbolugbe present a useful breakdown of some knowledge management methodologies shown in table 2.1 below. There are many examples of these knowledge management approaches proving highly successful, not only in the introductory phase, but also over extended periods of time. (Rumizen 2002), (Davenport, De Long et al. 1999). The importance of information and knowledge in the modern military environment is well described by McIntyre et al (2003). The exponential growth in the number of sensors and inputs on the battlefield or humanitarian relief environment means that filtering through this Clausewitzian (1976) ‘fog’ of information, to satisfy the Commander’s critical information requirements (CCIR) is fast becoming an almost impossible task. The difficulty lies not in getting the information to the decision-maker, but first in ensuring compatibility and then in the processing of that information, transforming it from data to information and from information to actionable knowledge.
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Barry Byrne and Frank Bannister Table 2.1 – Sample Knowledge Management solutions (Liebowitz and Megbolugbe 2003) IKM Solution
Complexity of Use
Difficulty of Development
Frequent get-togethers to exchange tacit knowledge (i.e. knowledge fairs, brown bag lunches, inter-department seminars)
Low – trying to maximise tacit-tacit knowledge exchanges
Low
Chat rooms, bulletin boards, list servs, online communities, communities of practise, communities of interest, tech clubs, etc. – on the organisation’s intranet Corporate portal for accessing expertise locator systems and used as entry to the organisation’s web site Codifying knowledge and information into knowledge repositories, best practises/lessons learned databases, etc Capturing knowledge and decision making processes via expert systems, intelligent agents, video streaming technologies, etc. Applying data and text mining techniques to look for patterns and inductively create knowledge Using intelligent agents to actively build user profiles and push appropriate lessons learned and material to the respective user
Low – maximising tacit knowledge exchanges in a virtual context
Low
Low
Low to medium
Low to medium
Medium
Low to Medium
Medium to high
Medium
High
Medium
Medium to high
It is important to understand how this information transformed within the military. One means is by staff officers adding their own knowledge, wisdom and insight during the Military Decision Making Process (MDMP) before it reaches the commander (Blodgett 2010). McIntyre, Gauvin et al describe how Choo’s (2002) model of the ‘knowing cycle’ when combined with the Nonaka and Takeuchi model of knowledge creation is reminiscent of the military command and control OODA loop (Observe, Orient, Decide, and Act) in which information and then knowledge are transformed into action. The US Army’s Centre for Army Lessons Learned (CALL) is often cited as one of the pioneering institutions in relation to knowledge management; the NATO Joint Analysis and Lessons Learned Centre (JALLC) is another such institution. Yet despite this head-start on the business world, what in business terms might be called a ‘first mover advantage’, a divide still exists between the effectiveness of civilian KM initiatives and military KM initiatives or programmes. In order to be successful organizations must have robust information and knowledge management strategies, processes, and protocols (Nonaka & Takeuchi, 1995; Davenport & Prusak, 1998; Desouza & Hensgen, 2005), but the challenge arises in reconciling the conflict between encouraging an open, information sharing environment, and maintaining the appropriate security protocols (Desouza and Vanapalli 2005). The problem for Defence organisations as others, is barriers to knowledge sharing. One barrier to adoption is the perception that knowledge is power, and that an individual or sub group that holds onto that knowledge for itself will retain the power associated with it. Another barrier identified by Swan and Scarbrough (1999) and later by Goh and Hooper (2009) is the absence of trust. Hexmoor et al. (2006) recognise the particular need for security, both for the individual and the organisation, but some debate exists over the best ways of overcoming these barriers. Desouza and Vanapilli advocate a strict, controlled approach to information security systems and information assurance while Goh and Hooper recommend a more open, holistic approach to information mechanisms and procedures, leading by example, embracing technical systems and compulsory training. Whichever approach is taken, it is clear that this issue must be addressed as there is a growing interest in applying these technical systems towards the knowledge management of sense-making, threat analysis and decision-making. (McIntyre, Gauvin et al. 2003). This holistic approach, while still leveraging technology to the fullest, ties in closely with the policies of the US Army. In constructing their ‘12 principles of Knowledge Management’ the Army included policies ranging from compulsory training to the “encouraged embedding of knowledge in media such as podcasts, videos and simulations” in the implementation of their knowledge management information system; ‘Army Knowledge Online’. (US Army 2010)
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2.1 Responsibility to Share Balanced with Need to Know The dominance of the traditional concept of “need to know” may in the past have held some military and defence organisations back from exchanging information effectively in recent years. This concept is evolving, and NATO’s new Information Management Policy takes cognisance of this; one of the principles of this document is information sharing. Here NATO states that “Information shall be managed with an emphasis on the ‘responsibility-to-share’ balanced by the security principle of ‘need-to-know’, and managed to facilitate access, optimise information sharing and re-use, and reduce duplication, all in accordance with security, legal and privacy obligations.” (NATO 2007, p3). This is a major paradigm shift in the approach to information exchange within a defence environment. NATO today recognises that the benefits of timely and accurate information exchange far outweigh the risks.
3. Methodology In this study, a mutimethodological approach was taken combining a quantitative survey with structured interviews. This study was conducted on quasi-randomly selected personnel from the Irish Defence Forces representing all ranks, units, corps, arms and brigades. Permission was also sought to interview and survey a wide selection of international militaries. Quantitative and qualitative research was conducted in Little Creek Naval Base, Virgina, NATO headquarters in Brussels, the Swedish Command and Control Training Regiment in Enkoping, and in a number of Irish locations. The large number of international responses obtained made it possible to compare and contrast the opinions of foreign military personnel to those of serving Irish Defence Forces personnel. The survey questionnaire was constructed using mostly closed-ended questions and a (5 point) Likert scale. A literature search for comparable studies revealed one such study conducted on a smaller scale within the New Zealand Defence Forces (Goh and Hooper 2009). Although the latter focused on the barriers to information sharing, some guidance on the construction of suitable questions relating to the potential for information systems to aid information and knowledge management was obtained. Pre-testing was conducted on the questionnaire on a sample group of 30 Irish military personnel. Once these findings had been incorporated into the instrument design, the full survey was undertaken. Due largely to the personal approach taken in the delivery of the surveys and possibly the regimented nature of military organisations, there was a 98% response rate. The data collected from the surveys were analysed using SPSS software. In total 159 surveys were completed, with semi-structured interviews conducted in the USA, Sweden, Ireland and Belgium. Due to the nature of the industry, no identities of personnel interviewed may be disclosed, but the interviewees represented a wide range of nationalities from civilian defence agencies, militaries and military bodies. A senior representative from the CIMIC Fusion Centre based in Norfolk Virginia was also interviewed, giving valuable insight into the difficulties of information sharing in a Civil – Military context. In total 15 interviews were conducted.
4. Findings and analysis The results of the questionnaire and semi-structured interviews showed that all ranks from junior private to senior officer, regardless of their nationality, recognised that there was a definite need for improved information and knowledge management in defence. A considerable amount of analysis was undertaken and there is insufficient space in this paper to report more than a modest faction of the output. The analysis included comparisons between Irish military and international personnel and between difference branches of the Irish military. The following are some of the salient findings. Many military personnel feel they have too little information available to them in their daily work (figure 4.1). Some 61.3% of Irish Defence Forces personnel and 48.8% of international personnel agreeing or strongly agreeing with this statement. The majority of respondents felt that the information that was available to them was inconsistent though almost all respondents regarded information received though information systems as accurate. There is broad agreement that the current information systems are facilitating knowledge and information sharing within defence. While respondents felt that ICT does facilitate information sharing, they also felt they received insufficient training on these systems to fully leverage the possibilities they offer. Information hoarding is regarded as a serious problem (figure 4.1). The threat of possible punitive action for the mistaken sharing of inappropriate or ‘over classified’ information creates a powerful disincentive and prevents some knowledge exchanges existing on any significant level (see next finding).
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Figure 4.1 â&#x20AC;&#x201C; Information hoarding exists between units/formations Information hoarding is also influenced by concerns about confidentiality as can be seen in figure 4.2. During the course of this study confidentiality and the inaccurate of over-classification of documents has frequently been cited as a key inhibitor to information and knowledge exchange in defence. It is clear from Figure 4.2 that regardless of rank, branch or indeed nationality, all respondents felt this was a major inhibitor of information exchange. Confidentiality concerns deter people from sharing information (figure 4.2). This is a major problem and has several dimensions not the least of which is confusion and uncertainty about the requirements for confidentiality in certain types of information and in who is entitled to see what.
Figure 4.2 â&#x20AC;&#x201C; Confidentiality concerns deter people from sharing information
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Barry Byrne and Frank Bannister One international interviewee noted that the situation had become so difficult that even the processing of routine paperwork had been inhibited â&#x20AC;&#x153;I could not even share information with myself...routine unclassified documents that I had created on one PC on my desk were automatically deemed too secure to move to the PC beside itâ&#x20AC;? Absence of motivation to engage in KM related activities is a further contributory factor. (figure 4.3). Staff felt that there were no incentives to engage in sharing of knowledge.
Figure 4.3 â&#x20AC;&#x201C; A suitable reward system exists for positive contribution to knowledge capital As noted by Stevens (2000), though rewards are not essential, they often act as a catalyst to improve sharing (Goh and Hooper 2009). However, the findings of this study show that there are almost no such rewards in place. This runs counter to the advice of Bartol and Srivastava (2002) who emphasized the importance of rewarding knowledge sharing. There is a strong belief that a key factors in information and knowledge hoarding is the belief that information and knowledge are power (figure 4.4). This suggests that there is a degree of cynicism in the military, but if this perception is close to reality, it suggests that operations may be put at risk by individual or group playing territorial games (Bannister 2005).
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Figure 4.4 â&#x20AC;&#x201C; Personnel hoard information because they believe information is power
4.1 Enhancing knowledge management Several ways of enhancing KM in the military were explored in the study. There was agreement on most of the approaches examined, particularly on the need for improved knowledge and information flow between units (figure 4.5)
Figure 4.5 â&#x20AC;&#x201C; Information and Knowledge flow well between units/formations This survey suggests that in general the Irish military is not as advanced in its use of KM as its international counterparts. It must be stressed that, given the small size of the sample, this is only an indicative finding, but it is strongly supported by respondentsâ&#x20AC;&#x2122; comments and observations in the interviews. Table 4.3 is one of
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Barry Byrne and Frank Bannister several examples where international respondents suggested that they were happier with their information and knowledge management than their Irish peers. Table 4.1 - I currently have enough access to information and corporate knowledge I currently have enough access to the information and corporate knowledge of the Defence Forces Stron gly Strong ly Agree Neutral Disagree Disagre e Ag ree Irish Forces
Defence 1.7%
25.6%
2 2.2%
39.3%
11.1%
8.1%
37.8%
2 9.7%
21.6%
2.7%
International
International responses also presented numerous different approaches to addressing information and knowledge management initiatives. The use of portals was a common method, however some used different combinations of functionality within the portal, for example one interviewee commented “We have a wiki for knowledge management and a document management system for information management” The use of awareness campaigns for information management has been particularly effective in Canada where even the most simple of mechanisms was noted to be effective at getting the message across to a large number of personnel. Mouse mats, cups and pens were made up with messages on the importance of data security and information management. What was also apparent from the international responses was that while information management is steadily gaining acceptance as an essential element of any military organisation’s business practises, knowledge management is still a slightly more ‘fuzzy’ concept. Where the responsibility for the direction and leadership of this knowledge management lies is at present not fully understood. This problem was put by one informant thus “The problem is information and knowledge management is being treated as a G2 (intelligence) issue, when really it should be a staff or headquarters issue.” Current information systems do not seem to be providing the level of collaboration facilities required by defence workers. In the current cost-conscious economic climate where defence budgets are being continuously scrutinised for possible savings this situation is less than desirable (table 4.2). Table 4.2 – Information systems encourage collaboration
Irish Defence Forces International Total
Current DF Information Systems encourage collaboration on projects Strongly Strongly Agree Agree Neutral Disagree Disagree .9% 20.9% 34.8% 35.7% 7.8% 5.3% 28.9% 26.3% 34.2% 5.3% 2.0% 22.9% 32.7% 35.3% 7.2%
It is well established in the information systems literature that for systems to be effective and successful, they should, inter alia, be well designed, be built in close consultation with users and have support from top management. However several interviewees were quite critical of the quality of information and knowledge management systems design. The degree of frustration can be seen in figure 4.6.
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Figure 4.6 – Contributing knowledge and information through DF information systems is easy. Finding expertise is a common problem (figure 4.7). In the survey, there was strong disagreement expressed with the statement “I can always locate an individual with a specific skill set”. This was particularly evident in international responses where ‘disagree’ and ‘strongly disagree’ accounted for a large percentage of the responses.
Figure 4.7 – I can always locate an individual with a specific skill set This was one area where the international experience was worse than the Irish one, but this may largely be a matter of scale. It may also be due to the increased emphasis ‘joint’ operations at an international/strategic level in the military world today. This working environment does not lend itself well to the traditional model
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Barry Byrne and Frank Bannister of subject matter experts becoming known to an organisation through socialisation and other informal, contact based means. On a positive note, there is widespread belief that access to information has improved in recent years. The interesting observation here is that despite the majority of international respondents agreeing with this statement, a sizable percentage disagreed completely; again pointing to the complex international operational environment of modern day crisis relief and peacemaking operations coupled the growth in the type and number of information systems trying to address this, not always in a cohesive and structured way.
5. Conclusions and future work Information and knowledge are the most valuable resources to any military while paradoxically also becoming the new ‘fog’ of modern war. The modern operating environments that peacemaking and peacekeeping forces find themselves in require military leaders to process exponentially increasing amounts of information fed to them by a myriad of sensors in the field. Identifying the relevant information and knowledge to enable faster, better informed decisions is a challenge. Despite an apparent ‘first mover advantage’ represented by the early recognition of Lessons Learned dating from Napoleonic times, to the US Army’s Centre for Army Lessons Learned (CALL), through to NATO’s more recent Joint Analysis and Lessons Learned Centre, there still exists a divide between civilian KM adoption and military adoption. This stems from security concerns hindering interoperability, the lack of understanding by military personnel in the appropriate security marking of documents and finally a lack of awareness of the principle of ‘responsibility to share’. One of they key findings of this research noted above, and one which little is currently written about, is the tendency of military personnel to deliberately overclassify documents they are working on so as to err on the side of caution, and for poorly designed information systems to perpetuate this problem. Militaries must ensure that they stay abreast of relevant interoperability considerations and standards when designing/implementing any system. Relevant use of standards such as STANAG (standardisation agreement) and interoperability platforms such as MIP (multilateral interoperability programme) should be leveraged to the fullest. Where possible, use one platform and control access rights accordingly. Another key finding is that there are currently insufficient reward systems in place to motivate personnel to contribute to the knowledge capital of the organisation. This problem is aggravated by the perceived advantages of doing the converse, i.e. hoarding knowledge. In addition to the usual recommendations (more training, top level support for new initiatives, etc.) this research suggests that systems that reward contributions to KM and penalise unnecessary hoarding are important. Greater clarity about confidentiality is also important. At present, military personnel will assume the most restrictive rules apply unless they know otherwise, particularly in a multinational operating environment. Good policies are essential. Fostering communities of practice will enhance cooperation and sharing. In the military these may have different nuances from the civilian sphere, but the basic principles remain the same. New challenges continue to emerge. In any situation information overload is a problem. In a military context, it can literally be fatal. This study suggests an increased awareness and investment in information and knowledge management in defence. With the correct balance of human and technological interaction, information and knowledge transfer frameworks and mechanisms can be facilitated and managed to supply the correct information at the right time, in the right format to the right person to satisfy the military decision maker’s informational needs and objectives. But the effort required is considerable and must be planned and executed with the support of all ranks.
References Bannister, F. (2005) E-government and administrative power: the one-stop-shop meets the turf war, Electronic Government, an International Journal, 2(2), 160-176. Bartol, K. M. and A. Srivastava (2002). Encouraging knowledge sharing: The role of organizational reward systems. Journal of Leadership & Organizational Studies, Summer. Blodgett, C. (2010). December NIMAG Conference 2010. NATO Information and Management Advisory Group, Brussels. Choo, C. W. (1996). The knowing organization: How organizations use information to construct meaning, create knowledge and make decisions* 1. International Journal of Information Management 16(5): 329-340. Choo, C. W. (2002). Information management for the intelligent organization : the art of scanning the environment. Medford, NJ, Information Today. Clausewitz, C., M. E. Howard, et al. (1976). On war, Princeton University Press, Princeton, NJ. Davenport, T. and L. Prusak (1997). Information ecology: Mastering the information and knowledge environment, Oxford University Press, USA.
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Barry Byrne and Frank Bannister Davenport, T. and L. Prusak (1998). Working knowledge: How organizations manage what they know, Harvard Business Press. Davenport, T. H., D. W. De Long, et al. (1999). Successful knowledge management projects. The Knowledge Management Yearbook 1999-2000: 89–107. Desouza, K. (2009). Information and Knowledge Management in Public Sector Networks: The Case of the US Intelligence Community. International Journal of Public Administration 32(14): 1219-1267. Desouza, K. and G. Vanapalli (2005). Securing knowledge in organizations: lessons from the defense and intelligence sectors. International Journal of Information Management 25(1): 85-98. Drucker, P. (1993). Management: Tasks, responsibilities, practices, Harper Paperbacks. Drucker, P. and J. Campanella (1993). Managing for the Future. Oxford, England, Butterworth-Heinemann Goh, C. and V. Hooper (2009). Knowledge and information sharing in a closed information environment. Journal of Knowledge Management 13(2): 21-34. Gourlay, S. (2004). 'Tacit knowledge': the variety of meanings in empirical research. Hexmoor, H., S. Wilson, et al. (2006). A theoretical inter-organizational trust-based security model. The Knowledge Engineering Review 21(02): 127-161. Irish Defence Forces, (2011). www.military.ie. Retrieved 02 Feb 2011, 2011. Krulack, C., Gen USMC (1999). Strategic Corporal: Leadership in the Three Block War. Marine Corp Gazette: pp 18 - 22 Liebowitz, J. (1999). Knowledge management handbook, CRC. Liebowitz, J. (2003). Keynote paper: measuring the value of online communities, leading to innovation and learning. International Journal of Innovation and Learning 1(1): 1-8. Liebowitz, J. and I. Megbolugbe (2003). A set of frameworks to aid the project manager in conceptualizing and implementing knowledge management initiatives. International Journal of Project Management 21(3): 189-198. Likert, R. (1932). A technique for the measurement of attitudes. Mace, B. and G. Thomason (2008). Knowledge Management Is Combat Power. Marine Corps Gazette 92(6): 37. Maier, R. (2007). Knowledge management systems: Information and communication technologies for knowledge management, Springer Verlag. McIntyre, S., M. Gauvin, et al. (2003). Knowledge management in the military context. Canadian Military Journal 4(1): 3540. NATO (2007). The NATO Information Management Policy. N. A. COUNCIL. C-M(2007)0118. NATO (2008a). The Primary Directive on Information Management. N. A. COUNCIL. C-M(2008)0113 (INV): 4. NATO (2008b). Bi-SC Information and Knowledge Management (IKM) DIRECTIVE. B.-S. C. (Bi-SC). 25-1: 1-11. NATO (2010). A lessons learned enabler for NATO transformation. The Three Swords. Stravanger, Norway. 17: 18-22. US NAVY (2005). Navy Knowledge Management Strategy communication U. NAVY. Niedderer, K. and Y. Imani (2009). Developing a framework for managing tacit knowledge in research using knowledge management models. Nonaka, I. and H. Takeuchi (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation, Oxford University Press, USA. Priest, D. a. W. T. A. (2010). The Secrets Next Door (from the series Top Secret America). The Washington Post. Washington. Rumizen, M. (2002). The complete idiot's guide to knowledge management, Alpha Books. Schultze, U. and C. Stabell (2004). Knowing what you don’t know? Discourses and contradictions in knowledge management research. Journal of Management Studies 41(4): 549-573. Stacey, R. D. (2001). Complex responsive processes in organizations: Learning and knowledge creation, Psychology Press. Stevens, L. (2000). Incentives for sharing. Knowledge Management 3(10): 54-60. Sveiby, K. (2001). A knowledge-based theory of the firm to guide in strategy formulation. Journal of Intellectual Capital 2(4): 344-358. Swan, J., H. Scarbrough, et al. (1999). Knowledge management–the next fad to forget people. Toffler, A. and B. Butz (1990). Powershift: Knowledge, wealth, and violence at the edge of the 21st century. New York, Bantam Books. Wilson, T. (2002). The nonsense of knowledge management. Information Research 8(1): 8-1.
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A Framework for Improving an Organizational Memory Information System’s Deployment Architecture Osvaldo Cairo and Oscar Ojeda Galicia Instituto Autónomo de México, México D.F., México cairo@itam.mx oscar.ojeda3@gmail.com Abstract: The demand on Knowledge Management in the organizations, which are out‐performing their peers by above average growth in intellectual capital and wealth creation has lead to a growing community of IT people, who have adopted the idea of building Corporate or Organizational Memory Information Systems (OMIS). This system acknowledges the dynamics of the organizational environments, wherein the traditional design of information systems does not cope adequately with these organizational aspects. The successful development of such a system requires a careful analysis of essential for providing a cost‐effective solution which will be accepted by the employees/users and can be evolved in the future. This paper proposes a nine‐layered framework for improving OMIS’ implementation plan in order to support the effort to captures, shares and preserves the Organizational Memory (OM). The purpose of this framework is to gain a better understanding of how some factors are critical for the successful application of OMIS in order to face how to design suitable OMIS to turn the scattered, diverse knowledge of their people into well‐documented knowledge assets ready for deposit and reuse to benefit the whole organization. Keywords: corporate or organizational memory, information systems, knowledge management
1. Introduction Currently, in most companies, employees' knowledge related to problem solving generally is not documented, and if it is, it is captured in manuals, memos, text files, etc. On the other hand, the transfer of their experiences is traditionally done in work meetings, training courses and by reading manuals, and in a few companies, in electronic form by means of telephone, emails, videoconferences and electronic meeting systems. If a person had a memory like the average company, you would think that this person suffered from a neurological disorder, as companies often forget what they have done in the past and the reasons for what they did. The knowledge of an organization is part of a new capital for businesses and taking advantage of it has become a powerful arm to maximize their potential for adding value and increasing their competitive advantage. The use of the Corporate Memory is a first step in making knowledge part of the corporate culture, due to the fact that it extends and expands knowledge through the capture, organization, dissemination and reuse of the knowledge generated by its employees. The Corporate Memory covers several aspects of the dynamics of an organization; therefore it is necessary to use the information systems to support these kinds of initiatives or projects. The use of the correct resources clearly influences the success of the development and implementation of Corporate Memory Information Systems. This class of systems requires a careful analysis in order to provide a cost effective solution that is accepted by the employees, that meets their objectives, and has the potential to grow in the medium and long term.
2. Theoretical framework Stein and Zwass (1995) define a Corporate Memory or Organizational Information System (OMIS) as "a system that functions to provide a means by which knowledge from the past is brought to bear on present activities, thus resulting in increased levels of effectiveness for the organization." Lehner (1998) defines an OMIS as "a system that integrates the elements that form the basis of knowledge of the organization with the help of information and communications technologies, and/or integrates and supports tasks, functions and procedures that are connected to the use of the organization's base of knowledge". An OMIS has the advantage of storing knowledge electronically; its applications are valuable and useful (if adopted willingly) and favor the achievement of organizational goals at relatively low costs. Among the most important disadvantages of these systems are their difficulty in classifying or indexing the information, costs in the recovery and interpretation of the information, which in some cases depend on the particular type of data, limited by the Information Technologies (TIC) used.
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Osvaldo Cairo and Oscar Ojeda Galicia Stein and Zwass (1995) developed a framework for an OMIS that consists of two layers (see Figure 1). The first layer incorporates four subsystems that are derived from four functions of effectiveness: integration, adaptation, achievement of goals and pattern maintenance. Integration is the coordination and management of information across the organization, while adaptation is the ability of the organization to adapt to the changes in its environment. The third subsystem is the attainment of objectives that depend on the ability of the organization to establish goals and assess the degree of compliance. Lastly, the reproduction of a social system through time (Pattern Maintenance) refers to the ability of the organization to maintain the cohesion and morale of the work force. The second layer consists of mnemonic functions, including the acquisition of knowledge, conservation, maintenance, search and retrieval of information. These two layers may or may not be based on Information Technologies (TIC).
Figure 1: Framework for an OMIS (adapted by Stein and Zwass, 1995) Stein and Zwass (1995) argue that certain situations could limit the deployment and use of an OMIS. They point out that although an OMIS can demonstrate its effectiveness in an organization, the project to develop it may not actually start. Even if the project is initiated, it may not be concluded. If the project is completed, the system may not be used. If the system is used, it may not be used properly. And even, if it is used correctly, it may not reach its full potential. A model of success for an OMIS should allow the assessment of the extent to which the implementation of an OMIS will reach its full potential in relation to the improvement in the effectiveness of the organization.
2.1 Success model for an OMIS Jennex, Olfman, Pituma and Tong‐Tae Park (1998) created a successful model adapted to the context of the OMIS based on the model of DeLone and McLean's (1992) known as I/S Success Model (see Figure 2). The model consists of five recursive blocks. This model has different, independent blocks in relation to the quality of the system and quality of the information.
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Figure 2: Model of success for an OMIS The model can justify the factors for success in the implementation of an OMIS within an organization. It begins with the quality system block to determine the terms of its operative characteristics. Subsequently, the information quality is measured in terms of the results or generated outputs. The third block measures the components of the OMIS in terms of use. The individual impact consists in identifying the change in staff performance associated with productivity. Finally, the organizational impact is associated with the effectiveness throughout the company, which is measured in relationship to the internal organizational performance (costs, work environment, trained personnel, quality of products and services, etc.) and the external organizational performance (level of customer satisfaction, sales, market position, value added, social responsibility, perception of consumers and investors, etc.).
3. Methodology A proposal for the architecture of the elements that must be included in the Organizational Memory Information System (OMIS) is presented in this section. It is different from other already existing architectures that integrate the planning phase and measuring of results. To elaborate it, elements from various projects of OMIS ‐‐ of the architecture proposed by Stein and Zwass (1995), the model by Jennex, Olfman, Pituma and Tong‐Tae Park (1998), among other research about the Corporate Memory ‐‐ were taken into account. The functional elements of this architecture are looking for the collection, preservation, recovery and distribution of the knowledge of the employees of an organization. The objective is to propose an architecture of nine layers (see Figure 3) to improve the implementation plan in order to support the Corporate Memory to increase its chances of success.
Figure 3: Structure for an organizational memory information system Each of the layers that make up the architecture works as a service, so that the architecture is scalable, flexible and robust. In this way, each organization can adapt the architecture according to its needs, including having
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Osvaldo Cairo and Oscar Ojeda Galicia the possibility of omitting certain elements of the layers (always when it accepts the risks or the reduction in the quality of the results delivered to the upper layers), in order to achieve the objectives established for this type of project. The main objectives of each of the layers are:
Layer of culture of knowledge. The goal is to establish an environment that promotes the sharing of knowledge among the members of an organization. It lays down the foundations for the support, collaboration and participation, with the purpose of registering the knowledge of the employees and using it for the benefit of the organization. It is not necessary to have a mature or deeply rooted culture of knowledge in order to establish these systems. However, the employees need a culture that will enable them to be facilitators for the construction and operation of an OMIS.
Layer of planning. It establishes the levels of the Corporative Memory, with the intention of having a clearer picture of the objectives and activities to carry out. In addition, it serves to identify the areas of opportunity of the project and to determine if the organization is ready to continue with the following stages of the project. This layer has seven modules, which are: a) align the objectives of the OMIS with the objectives of the organization; b) prepare for the change; c) create a work team for the project; d) audit the current situation; e) define the important functions; f) relationship with the employees and g) analysis of the return on investment (ROI).
Layer of knowledge. This layer establishes a methodology on how the knowledge of the people is going to be sorted, stored and used. It has a strong impact on the way in which knowledge will be processed and consists of four modules: a) select the elements of knowledge that will be stored in the OMIS; b) contextualize the knowledge stored in the OMIS; c) agents monitor the life cycle of the knowledge stored and d) quality of knowledge.
Storage Layer. It provides for the physical means of storage, establishes the location of the storage systems, the dimensioning of the storage space, design of the database or metadata, and categories for grouping the information (databases, metadata, documents, etc.).
Layer of Elements and Quality of the System. The system handles a wide variety of functions and supports certain activities. Therefore, this layer establishes the elements that support the system in the effective and efficient management of the employees' knowledge. The main elements are: the business process model (BPM), the organizational model, roles, profiles and ontologies (tasks, domains and information). Ludger van Elst, Andreas Abecker and Heiko Maus (2001) developed a model that represents the interaction of these elements. In addition, it is necessary to have agents who know how to handle or manage the different scenarios that may be present in the system.
In relation to the quality of the system, the objective of this module is to define its quality in terms of its operative characteristics, i.e., it describes how good the system is. The quality is divided into three groups: a) technical quality; 2) quality in the use of the system; and c) quality in the information provided.
Security Layer. It establishes the processes, mechanisms and strategies to protect the information contained in the system. The knowledge contained in the system is a valuable asset to the organization, and therefore it is recommended that the best safety practices be applied. Some basics that should be considered when applying security in these systems are: to facilitate the supply of the OMIS, and to improve the recovery processes of knowledge and automatic privacy mechanisms.
Communication Layer. Within the organization, the aim of the communication of knowledge is to take the isolated knowledge (tacit and explicit) that the members of the organization have and transmit it to all of the employees at the moment they need it. It sets out the strategies and mechanisms for communicating knowledge registered in the system, as well as that which doesn't exist, but that can be found through directories of experts or though other means.
User Interface Layer. It allows the identification of points to consider in designing a user interface in order that the one‐to‐one interaction with the system is pleasant, thus increasing the chances of acceptance of the system. In the case of an OMIS, it establishes an interface similar to a virtual desktop in which work and knowledge can be merged, increasing the possibilities of use. In the design of the user interface, usability should be considered. Jakob Nielsen (1993) establishes 10 basic heuristic usabilities: a) simple and natural dialogues; b) speak the user's language; c) minimize the memory usage; d) consistency; e) feedback; f) clearly marked exits; g) shortcuts for the experts; h) good error messages; i) prevent errors; and j) in case all else fails, there must be assistance and documentation.
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Layer of measurement and evaluation. It establishes the planning of measurement indicators that reflect the reality of the Corporate Memory in order to fully know the benefits of the OMIS, and identify areas of opportunities in a precise manner. On some occasions, it is difficult to measure when the expectations are not easily quantifiable (economic, productivity, comparison in relation to its competitors, etc.). However, certain indicators are proposed that can help measure the impact that an OMIS has (at both the individual and organizational level), which are: learn and improve, effectiveness and efficiency, usability, socialization, preservation and reuse of knowledge, generate new knowledge (tacit and explicit), quality, ease in managing knowledge, return on investment (ROI), security of knowledge, increase of knowledge without human intervention, and innovation and achievement of objectives.
There is a tenth layer that could be applied as part of a process of continual improvement of the system and only under certain circumstances. These are: a) having an OMIS working at its maximum potential; b) the system offers tangible benefits and fulfills its objectives; c) investment for its deployment and d) consolidation of the culture of knowledge.
Extract, Transform and Load (ETL). The purpose of this layer is to automatically enrich the recorded knowledge in the system to see information from external sources. To the extent possible, it seeks to eliminate human intervention in the search and selection of information from different sources (customers, providers, internal/external systems, competitors, news, statements of results, etc.) This layer requires a rigorous analysis to select and/or design a solution that allows it to choose the correct information to supplement the knowledge within the proper context.
4. Benefits A study by Gartner Group estimates that more than half of the companies that are classified in the Fortune 1000 will depend on KM and KMS by the year 2003 (Johne, 2001) to extend the gap between them and their competitors. Drucker points out that knowledge is productive only if it is applied to establish a difference. He suggests that this productivity should be the determining factor of any company or industry – apply knowledge to products and /or services. The life cycle of products and services can accelerate in an unprecedented manner, through knowledge. Some examples of this is the market value (values to March 25, 2011) of some companies, such as Apple, Microsoft, IBM, Google and Pfizer. Even conventional retailers like Walmart consider its competence in the management of logistics a knowledge‐intensive activity, in order to turn it into its primary driver in business successes. In addition, the ability of companies to exploit their intangible assets has become a more decisive factor than their ability to manage and invest in their physical assets. When the markets change, uncertainty prevails, technologies proliferate and competitors multiply, and the products and /or services can quickly become obsolete. In order to be successful, companies should focus on obtaining the following skills:
Generate new knowledge.
Distribute it rapidly.
Incorporate it into their products and / or services.
An organization that learns sees the differences that exist between its actual and expected results, and tries to correct the errors that have caused these differences. This type of company seeks to improve its actions through the acquisition of knowledge and understanding. It does not only capture the knowledge, but it uses its ability to respond and adapt to changes in the organizational environment (Hashim and Othman, 2003).
5. Conclusions This article discussed the proposal of a new architecture that allows for the improvement in the implementation of the Corporate Memory Information System, and which consists of nine layers. These layers are designed to establish the levels of the system and knowledge as well as the layout of the elements that must integrate an information system. They ultimately define the indicators that measure the reality of the Corporate Memory in order to know how it achieves organizational efficiency and the competitive advantage. The contribution of this proposal is to have an architecture that integrates both aspects of information systems, such as aspects that are not associated with Information Technologies (IT), with the intent that the architecture can be applied to any Corporate Memory project without limiting its scope. The architecture is
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Osvaldo Cairo and Oscar Ojeda Galicia designed in layers that function as services and that are independent of each other, with the purpose of easy and flexible implementation, and additionally provides modularity, adaptation to the changes and scalability. Finally, the implementation of an OMIS covers a variety of factors (tangible and intangible) that can influence the achievement of the goals for which it was conceived. Having an architecture or framework that serves as a guide to learn about the elements that influence the success of those projects facilitates its implementation and its future growth. The Information Technologies (IT) can contribute as a central component of knowledge management and subsequently toward organizational learning.
Acknowledgements This work has been founded by Asociación Mexicana de Cultura A.C.
References Abecker, A., Bernardi, A., Hinkelmann, K., Kuhn, O. and Sintek, M. (1998) Towards a Technology for Organizational Memories, IEEE Intelligent Systems, Vol. 13, No. 3, pp. 30‐34. Ackerman, M. S. (1994) Definitional and Contextual Issues in Organizational and Group Memories, in: Proceedings of the 27rh Hawaii International Conference of System Sciences (HICSS), Organizational Memory minitrack Annie Brooking (1999), Corporate Memory: Strategies for Knowledge Management. International Thomson Business Press. Ackerman, M. S. and McDonald, D. W. (1996) Answer Garden 2: Merging Organizational Memory with Collaborative Help, in M. S.Ackerman (Ed.) Proceedings of ACM CSCW'96 Conference on Computer‐Supported Cooperative Work, ACM Press, New York Computer and Information Science February, 2009. Aguilar, M.C. (1996) Modelo para el Desarrollo de una Memoria Organizacional Utilizando en Concepto de Core Competence, Tesis de Maestría en Administración de tecnologías de información, ITESM, México. Baird, L. and Cross, R. (2000) Technology is Not Enough: Improving Performance by Building Organizational Memory, Sloan Management Review, Cambridge. Brown, J. S. and Duguid, P. (2000) Balancing Act: How to Capture Knowledge Without Killing It, Harvard Business Review, Boston. Choo, C.W. and Bontis, N. (2002) The Strategic Management of Intellectual Capital and Organizational Knowledge, Oxford University Press, New York. Conklin, E.J. (1993) Capturing Organizational Memory, in Proceedings of GroupWare ‘92, D. Coleman (Ed.), Morgan Kaufmann, San Mateo, CA, 133‐137, 1992. Also in Groupware and Computer‐Supported Cooperative Work, R. M. Baecher (Ed.), Morgan Kaufmann, pp 561‐565. Davenport, T.H. and Prusak, L. (1998) Working Knowledge, Harvard Business School Press, Boston. De Geus, A. P. (1988) Planning as learning, Harvard Business Review, Boston, pp 70‐74. DeLone, W.H., and McLean, E.R (1992) Information Systems Success: The Quest for the Dependent Variable, Information Systems Research, pp 60‐95. Dieng R., Corby O., Giboin A. and Ribiere M., (1998) Methods and Tools for Corporate Knowledge Management, Project ACACIA and INRIA, Proceedings of KAW'98, Eleventh Workshop on Knowledge Acquisition, Modeling and Management, Canada. Dodgson, M. (1993) Organizational learning: A Review of Some Literatures, Organization Studies, Vol. 14, No. 3, pp 375‐ 394. Drucker, P. F. (1994) The Age of Social Transformation, The Atlantic Monthly, The Age of Social Transformation, November, Vol. 274, No. 5, pp 53‐80. Drucker, P. F. (1999) Knowledge‐Worker productivity: The biggest Challenge, California Management Review, Vol. 41, No. 2, Winter 1999, pp 79‐94. Duncan, R. and Weiss, A. (1979) Organizational Learning: Implications for Organizational Design, in Straw, B. (Eds), Research in Organizational Behavior, JAI Press, Greenwich, CN, pp 75‐124. Dzbor, M., Paralic, J. and Paralic, M. (2000) Knowledge Management in a Distributed Organization, Kmi‐TR‐94 technical report, Knowledge Media Institute, Open University. Easterby‐Smith, M. and Lyles, M.A. (2011) Handbook of Organizational Learning & Knowledge Management, Wiley, United Kingdom. Grant, R.M. (1997) The Knowledge‐based View of the Firm: Implications for Management Practice, Long Range Planning. Vol. 30. No. 3, pp 450‐454. Gray, P. and Tehrani, S. (2004) Technologies for Disseminating Knowledge, In C. W Holsapple (Hrsg.), Handbook on Knowledge Management 2, Knowledge Directions, Springer, Germany. Hashim, N.A. and Othman, R. (2003) Organizational Amnesia: The Barrier to Organizational Learning, [online],Proceedings of the 3rd Annual Conference on Organizational Knowledge, Learning and Capabilities, Athens, Greece, Universiti Kabangsaa Malaysia, http://apollon1.alba.edu.gr/OKLC2002/Proceedings/pdf_files/ID308.pdf. Heijst, G. (1998), The Lessons Learned Cycle. Information technology for Knowledge Management, U. Borgoff and R. Pareschi, Springer, Germany, pp 17‐34.
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The KAMET II Methodology: A Real Process for Knowledge Generation Osvaldo Cairó and Silvia Guardati Department of Computer Science, ITAM, México DF, México, Río Hondo 1, Mexico cairo@itam.mx guardati@itam.mx Abstract: Knowledge acquisition (KA) is considered today a cognitive process that involves both dynamic modeling and knowledge generation activities. We understand KA should be seen as a spiral of epistemological and ontological content that grows upward by transforming tacit knowledge into explicit knowledge, which in turn becomes the basis for a new spiral of knowledge generation. This paper presents some of our attempts to develop a knowledge acquisition methodology that mainly build a bridge between two important fields: knowledge acquisition and knowledge management. KAMET II (Cairó and Guardati, 2012), the evolution of KAMET, represents a modern approach to creating diagnosis‐specialized knowledge models and knowledge‐based systems (KBS) that are more efficient. Keywords: knowledge acquisition, knowledge management, knowledge modeling, knowledge generation
1. Introduction Although technologies have been improved and in general, much work has been done in recent years, knowledge acquisition remains the main factor that hampers a well‐controlled KBS life cycle. The problem still exists. Because the acquisition of knowledge involves predominantly a social process and a cognitive process, we think that efforts to acquire and model the know‐how, know‐why and the care‐why of an expert (or group of experts) must undoubtedly involve knowledge and ideas from different areas, such as psychology, sociology, philosophy and computer science. Knowledge undoubtedly represents the main competitive advantage of an organization ‐‐ we assumed the ability of the firm to recognize and assess the value of knowledge. The competitive advantage derives from difficult‐to‐imitate capabilities that lives in the mind of individuals, tacit knowledge, and that are embedded in dyadic and network relationships (Yli‐renko et al., 2001; Dyer and Singh, 1998). It is the knowledge, the ability to create, to use, and to transfer it, which may allow the creation or improvement of new products or services. But knowledge is often tacit. Therefore, it is difficult to transfer knowledge to another person by means of the written word or verbal expression. This is precisely one the main obstacles. This paper addresses this important problem. We conceive the process of knowledge acquisition as a cognitive process that involves both dynamic modeling and knowledge generation activities. These processes are integrated in a spiral of epistemological and ontological content that grows upward by transforming tacit knowledge into explicit knowledge, which becomes the basis for a new spiral of knowledge generation. KAMET II is a methodology based on models designed to manage knowledge acquisition from multiple knowledge sources (KS). The method provides a strong mechanism to achieve KA in an incremental fashion, in a cooperative environment, and in a shared context for knowledge generation. It must be said that KAMET II seeks to be general, although it is primarily aimed at solving diagnosis problems.
2. KAMET II: The life‐cycle model as a knowledge generation process The KAMET II life‐cycle model (LCM) provides a graphical framework for managing the knowledge acquisition process. Besides providing structure to set up and facilitate ways to organize knowledge acquired from multiple knowledge sources, to share knowledge, monitor project progress, and check quality control, much of the motivation behind utilizing a LCM as a knowledge generation process is based on the search for the efficient transformation of tacit knowledge into explicit knowledge. Knowledge lives in the minds of individuals and we are trying to make it explicit. We are much more interested in the dynamic process of knowledge generation than the stockpiling of knowledge. This is one of the main differences with the previous version of the methodology (Cairó, 1998). The KAMET II life cycle consists of four stages: the strategic planning of the project, initial model building, feedback model building, and final model building. Each stage involves a process of knowledge transformation.
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Osvaldo Cairó and Silvia Guardati This was inspired by the concept of Ba. For those unfamiliar with the concept, ba can be thought of as a shared space for emerging relationships, a shared space that serves as a foundation for knowledge creation (Nonaka et al., 2000). The following sections briefly describe each stage.
2.1 The strategic planning of the project This is the socialization stage in which ideas, views, emotion, feelings, experiences and knowledge should be shared through face‐to‐face interactions. It involves the sharing of tacit knowledge between individuals. This is where the knowledge‐creation process begins. This process is necessarily context‐specific in terms of who participates and how they participate. Social, cultural and historical contexts are important for human beings (Vygotsky, 1986), as such contexts provide the basis for interpreting information to create meaning (Nonaka et al., 2000). The strategic planning of the project is essential to the development of the project. The Project Manager (PM) and the four groups involved in the project ‐‐Knowledge Engineers (KE), Human Experts (HE), representatives of potential users (PU), and fund sponsors (FS)‐‐ must interact and be in total agreement with the definition of the project to ensure its success. In this process, teamwork is definitely the fundamental key. The steps comprised in the first stage (Cairó, 1998) are: a) define project goals, b) identify potential users, c) specify potential benefits, d) divide the knowledge domain into sub‐domains, e) identify the knowledge sources that will be involved in the project, f) define mechanisms of model verification and validation, g) build the project’s dictionary, h) specify other necessary resources to obtain KA, i) define techniques to attain knowledge acquisition, j) estimate time to complete the knowledge acquisition stage, k) estimate project costs, and l) specify project documentation.
2.2 Initial model building The externalization process takes place in the second stage. It is the time for transforming tacit knowledge into comprehensible forms that can be understood for others. When tacit knowledge is made explicit, knowledge is crystallized. This means that now knowledge can be shared by others, and therefore, become the basis for a new process of knowledge generation. The externalization process is also essential because it transcends the limits of what we are accustomed to. It is what allows us to move from the invisible, tacit, to the visible, explicit. This is the model ultimately that will allow us to interact with other agents and the environment for the knowledge generation cycle to take place. In the second stage, Knowledge Engineers elicit knowledge from different knowledge sources and proceed to build the initial model, which is constituted by one or more models, as we will explain later. This stage involves the largest number of risks, which mainly arise because interviews involve introspection and verbal expression of knowledge, resulting in a difficult task for humans, and especially for experts. The success of the initial model is also heavily dependent on the skills of knowledge engineers to socialize with the experts and to formalize tacit knowledge. The steps comprised in the second stage are: a) attain knowledge elicitation from multiple knowledge sources, b) reassess project time, c) develop a library of cases, d) develop the initial model, e) verify and validate the initial model, and f) revise and document the initial model.
2.3 Feedback model building It is the time for combination ‐‐ the process of converting explicit knowledge into more complex and systematic sets of explicit knowledge (Nonaka et al., 2000). The KE distributes the initial model among the different knowledge sources to be analyzed. Ideas, experiences or perspectives are exchanged in relation to the model. Because individuals typically have different views, training, ideas, knowledge and experience, it is logical that differences are common and inevitable at this time. This should not be a cause for concern. The synthesis of these differences should be used to generate new knowledge and bring forth diverse views in reference to the created artifacts. Finally, the PM and KE, together with the experts, review and analyze the changes introduced in the initial model and construct the feedback model. This involves collecting externalized knowledge and then combining such knowledge. At the end of this stage, fewer inaccuracies will be found in the model because now it has
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Osvaldo Cairó and Silvia Guardati been enriched and reflects the knowledge and experience of several specialists in the knowledge domain of the application. It must be remembered that the feedback model is only a refined and better initial model. The steps that constitute the third stage are: a) distribute the initial model among experts who then analyze it and generate feedback, b) develop the feedback model incorporating the different views of experts, c) verify and validate the feedback model, and d) revise and document the feedback model.
2.4 Final model building In the last stage, the multiple knowledge sources participate in a series of meetings, under the coordination of the PM, to develop the final model. The stage is considered to be complete when the model satisfies the proposed objectives with a high degree of plausibility and/or there are no experts capable of further transforming it. Inaccuracy at the end of the stage must be minimal, since the model now expresses the knowledge acquired from multiple knowledge sources, which collaborated in different degrees and ways to solve the problem. The final model shows that explicit knowledge can be re‐distributed among team members and converted into tacit knowledge again. The steps to be followed in the fourth stage are: a) re‐distribute the feedback model among experts who then analyze it, c) develop the final model incorporating new and more specific opinions from the experts, d) verify and validate the final model, and e) revise and document the final model.
3. The KAMET II conceptual modeling language (CML) We must always keep in mind that we are looking for a dynamic process in which tacit and explicit knowledge are exchanged and transformed.
3.1 The KAMET II CML assumptions The KAMET II CML has three levels of abstraction. The first one corresponds to structural constructors and structural components. The structural constructors are used mainly to highlight the problem itself. We distinguish between problem, classification and subdivision (Figure 1).
Figure 1: Structural constructors The structural components (Figure 2), on the other hand, are used to establish the characteristics and possible solutions to the problem. We distinguish among symptoms, antecedents, time, value, inaccuracies, process, formula, solution and examination. The second level of abstraction corresponds to nodes (N) and composition rules (CR). Nodes are built using structural constructors and structural components. We distinguish between three different types of nodes: initial, intermediate and terminal. Composition rules (Figure 3), for their part, are the ones that permit the appropriate combination of nodes. The third level of abstraction corresponds to the global model. It consists of at least one initial node, any number of intermediate nodes, and one or more terminal nodes. A global model should represent the knowledge acquired from multiple knowledge sources in a specific knowledge domain.
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Figure 2: Structural components
Subdivision: Shows a subdivision.
Implication: It represents a connection from a source to a complication.
Action: Expresses that something must be completed: a formula, an examination, etc.
Union: The line shows a a connection between subdividions.
Figure 3: Composition rules
3.2 The KAMET II CML formalization The formalization of KAMET II CML (Cairó and Guardati, 2012) is based more on a metalanguage, than on a strict group of theorems and mathematical proofs. The characterization of the method through diagrammatic conventions and postulates can be summarized as follows. 3.2.1 Diagrammatic conventions A diagrammatic convention is mainly a chart, graph, drawing or outline designed to demonstrate or explain how something works or to clarify the relationship between the parts of a whole. Following are the diagrammatic conventions:
DG1. The structural constructors and structural components can be named using a numerical or linguistic label. The use of names accelerates and facilitates the construction of models.
DG2. The indicator is used to set up the number of elements that must be present in either a structural component or group. It is represented with a square and is located in the upper right‐hand corner of the group or the structural component. An indicator is named in three different ways: an n is used to express the exact number of elements that must be present, an n+ is used to indicate that at least n elements must be present, and an n,m is used to show the minimum and maximum number of elements that must be present, where n and m are integer values, and m>n.
DG3. A chain is defined as the link of two or more symptoms, antecedents, and/or groups (DG4). The order of the link is irrelevant.
DG4. A group is defined as a special chain. The linked elements have times and/or values in common, or are related among each other through an indicator. The group concept is recursive.
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DG5. Assignment is defined as the process of labeling a node. The objective of the assignment is to be able to reuse the node in any other part of the model without having to redefine it. It allows reusing a complete node not only in form but also in content. Reusing is a universal principle of coping with complexity and to avoid redesigning or redeveloping parts of a product, which already exist. The assignment provides greater flexibility in modeling.
3.2.2 Postulates The postulate or axiom is a proposition in logic that is not proved or demonstrated but is considered to be either self‐evident or assumed to be true as a basis for reasoning. Its truth is taken for granted, and serves as a starting point for deducing and inferring other propositions. Following are the postulates of the method:
P1. The structural component time should always be placed to the right of a group, problem, subdivision, antecedent, symptom, etc.
P2. The structural component value is always placed above a symptom, antecedent or group. The value component can make use of an indicator.
P3. The solution component is only related to structural constructors.
P4. There are three types of nodes: initial (I), intermediate (M) and terminal (T).
P5. The nodes are related using composition rules. The following relationships are possible: initial with terminal, initial with intermediate, intermediate with intermediate, and intermediate with terminal.
P6. An initial node represents a symptom, antecedent, group, or chain. It is used to describe a part of the problem. It does not have input flow and can have more than one output flow.
P7. The intermediate node is used to describe an intermediate part of the problem. It may have one or more further inflows and one or more output flows.
P8. A terminal node represents a structural constructor. It has one or more input flows. The output flow is only used to show possible solutions.
P9. The initial and intermediate nodes can be grouped together, without losing their properties or functions, into molecular nodes. These nodes, in turn, will act as a node in their own right. The molecular nodes are formed through conjunctions or disjunctions.
P10. The composition rules are used mainly to relate the different nodes and the structural components with the solution component.
3.2.3 A simple example of modeling In this section, we will provide a simple example of modeling in order to illustrate the method sketched in the previous section. The example involves diagnosing faults in electricity (Figure 4).
Figure 4: Simple electrical diagnosis The model shows that problem P1 can occur as a result of two different situations. In the first one, the model shows that if symptoms 1 and 5 are known to be true then we can deduce problem P1 is true with a probability of 0.6. In the second one, the model shows that if symptoms 1 and 2 are observed then we can conclude that the problem is P1 with a probability of 0.70. On the other hand, we can deduce that the problem is P3 with a probability of 0.40 if symptoms 3 and 4 are known to be true. Finally, we can reach a conclusion that the problem is P2 with a probability of 0.90 if problems P1 and P3 and symptom 7 are observed.
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Osvaldo Cairó and Silvia Guardati Finally, we add a real example of retinal migraine (Figure 5). The examples were extracted from the knowledge models of a knowledge‐based system for the diagnosis of headache disorders, cranial neuralgia, and facial pain.
Figure 5: Retinal migraine
4. KAMET II: A typical four component architecture The conceptual framework is a typical four component architecture (Fensel, 2000) that defines different elements to solve diagnosis problems: a task that defines the problem that should be solved by the knowledge‐based systems, a problem‐solving method that defines the reasoning process of the knowledge‐ based systems, and a domain model that describes the domain knowledge of the KBS. Each of these elements is described independently to enable the reuse of each of them. Additionally, a fourth element, known as adapter, is introduced to adjust the three other independent and reusable parts.
5. KAMET II methodology: Applications and results The KAMET II Methodology (Cairó and Guardati, 2012) has been successfully used in different applications and knowledge domains. We have developed tens of KBSs applying KAMET mainly in medicine – cranial neuralgia and uveitis ‐, telecommunications, recruiting, concrete design, scheduling, human resources management system, and customer services, among others. A great deal of literature has also appeared on KAMET in recent years (Hwang et al, 2011; Tseng and Lin, 2009; Lin et al., 2008; Calvo‐Manzano et al., 2008; Chu and Kwang, 2008; Elfadil, 2008; Beydoun et al., 2006; Hwang et al., 2006; Abdullah, 2006; Wagner and Subey, 2005; Chen et al., 2005). We think KAMET II, which involves a new dynamic modeling process and a revolutionary and fresh knowledge generation process, provides the necessary elements so that KE can continue building KBSs. The methodology also focuses naturally on risk‐reduction, which is a fundamental part in software and knowledge engineering.
6. Conclusions In this paper, we presented a renewed and fresh knowledge acquisition methodology from multiple knowledge sources. There are two main goals in developing KAMET II. The first is to improve the phase of knowledge acquisition by making it more efficient. The second, and more important, is to introduce knowledge acquisition as a cognitive process, as a spiral of epistemological and ontological content that grows upward by transforming tacit knowledge into explicit knowledge, which becomes the basis for a new spiral of knowledge generation. This is one of the first attempts at incorporating both a dynamic modeling process and a knowledge generation process in a knowledge acquisition methodology.
Acknowledgements This work has been founded by Asociación Mexicana de Cultura A.C.
References Cairó, O., and Guardati, S. (2012) “The KAMET II methodology: Knowledge acquisition, knowledge modeling and knowledge generation”, Expert Systems with Applications, Vol 39, No. 9, pp 8108‐8114. Cairó, O. (1998) “KAMET: A Comprehensive Methodology for Knowledge Acquisition from Multiple Knowledge Sources”, Expert Systems with Applications, Vol 14, pp 1‐16. Chu, H., and Hwang, G. (2008) “A Delphi‐based approach to developing expert systems with the cooperation of multiple experts”, Expert System with Applications, Vol 34, No. 4, pp 2826‐2840.
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Osvaldo Cairó and Silvia Guardati Dyer, J., and Singh, H. (1998) “The relational view: cooperative strategy and sources of interorganizational competitive advantage”, Academic of Management Review, Vol 23, pp 660‐679. Fensel, D. (2000) Problem‐Solving Methods: Understanding, Description, Development, and Reuse, Lecture Notes in Artificial Intelligence, Vol 1791, Springer‐Verlag Berlin, Heidelberg. Hwang, G., Chen, C., Tsai, P., and Tsai, C. (2011) “An Expert System for Improving Web‐based Problem‐Solving Ability of Students”, Expert System with Applications (Article in Press). Nonaka, I., Toyama, R., and Konno, N. (2000) “SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation”, Long Range Planning, 33, pp 5‐34. Tseng, S., and Lin, S. (2009) “VODKA: Variant objects discovering knowledge acquisition”, Expert System with Applications, Vol 36, No. 2, pp 2433‐2450. Wagner, P., and Zubey, M. (2005) “Knowledge acquisition for marketing expert systems based upon marketing problem domain characteristics”, Marketing Intelligence & Planning, Vol 23, No. 4, pp 403‐416. Yli‐renko, H., Autio, E., and Sapienza, H. (2001) “Social Capital, Knowledge Acquisition, and Knowledge Explotation in Young Technologies‐Based firms”, Strategic Management Journal, Vol 22, pp 587‐613.
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Knowledge management capabilities in family firms Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Department of Management and Finance, University of Murcia antonioc@um.es danieljj@um.es
Abstract: Family firms face increasing global competition, changing customer demands and rapid technical change. In this context, the profitability of firms and even their survival depend on their ability of responds rapidly and flexibly. That is the main reason why innovation is frequently considered a key element for achieving a competitive advantage. Numerous studies have suggested that knowledge management capabilities, such as organizational memory and absorptive capacity are important in generating innovations. Furthermore, family involvement in the firm distinguishes the family firms from others. Several studies have focused on the capacity of the family to generate innovations and knowledge management in family firms. The results of an investigation with 249 Spanish firms show that both absorptive capacity and organizational memory have a positive relationship with innovation, as well as with family involvement in the management, where the second and subsequent generations are involved. Also, we found evidence that family involvement in management over generations fosters knowledge management capabilities (absorptive capacity and organizational memory). The relationship between family ownership and innovation was indirect. In general, the results show that family firms promote innovation through knowledge management strategies. Keywords: Absorptive capacity, organizational memory, innovation and family firms
1. Introduction The importance of knowledge as a determinant of innovation has received much theoretical attention over the last few years. The Resource-Based View (RBV) emphasizes the role of knowledge management in growth, generation, maintenance and development of innovation. In this work, two important knowledge management capabilities are analyzed. First, absorptive capacity, or the firm’s ability to identify, assimilate and exploit knowledge from the environment (Cohen and Levinthal, 1990). Second, organizational memory (OM) or the accumulated body of data, information and knowledge created during the organization’s course of action (Jackson, 2012). OM reflects the sum of know-how acquired through the company’s life, and plays an important role in future decisions (Walsh and Ungson, 1991). Numerous studies have suggested that there is a link between OM, absorptive capacity and a firm’s ability to generate innovations. In recent decades, there is an increasing interest in studying family firms because they are the prevailing form of enterprise worldwide (Littunen and Hyrsky, 2000) and because they are an important engine of economic growth and job creation in European economies, and the product innovations generated by family firms are a key source of growth. Sirmon and Hitt (2003) use the Resource-Based View (RBV) of firms to argue that family businesses assess, select, discard and revitalize their resources differently from non-family businesses. Family involvement in the firm distinguishes family firms from others (Chrisman et al., 2003). This paper suggests that these resources introduced to the family business by the family create capabilities that foster innovation. However, empirical research is scarce, not only regarding this proposition, but also with regard to innovation and knowledge management in family firms.
2. Literature framework 2.1 Innovation According to the RBV, resources are at the heart of competitive advantage and, therefore, business success. The RBV remains one of the most prominent theoretical foundations of management research (Newbert, 2007). The RBV describes how resources can contribute to the competitive advantage of organizations. In general, the literature considers innovation to be critical for firm success. The rationale behind this idea is that innovation often serves to deal with the turbulence of the external environment. In this context, companies with the capacity to innovate will be able to respond to challenges faster and to exploit new products and market opportunities better than non-innovative companies (Brown and Eisenhard 1995). From
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez this perspective, innovation allows the development of valuable and scarce resources in the company. Moreover, the capacity to innovate is difficult to imitate. Innovation has been conceptualized in a variety of ways. The definition given by Damanpour et al. (1989) broaches these different issues. They understand innovation as “the adoption of an idea or behavior, whether a system, policy, program, device, process, product or service, that is new to the adopting organization”.
2.2 Family firms Scholars have also applied the RBV to the field of family firms (Zellweger et al., 2010). Through this theoretical lens, Habbershon and Williams (1999) first introduced the term “familiness”, describing it as the idiosyncratic bundle of resources and capabilities resulting from the interaction of the family and business systems. In order to understand the family's role in supporting the competitiveness of the family firm, it is important to understand different family-based attributes of family firms that can create familiness.Within familiness there are three dimensions that distinguish the influence of the family in the business (Astrachan et al., 2002): power or family involvement in ownership and management; experience of the generation in control; and, finally, culture. This paper focuses on the influence of family in ownership and management, and experience of the generation in control. A family firm is defined as one in which there is majority family ownership. Family businesses tend to be disadvantaged in the development of innovation capabilities, and family firms are ill-equipped to build these capabilities; financial resources are more limited, and/or the family is concerned with the preservation of wealth, as the majority of its assets are invested in the business, and so they limit their investment and risk (Carney, 2005). Creating innovative capabilities requires a large investment in R&D and technological diversification, and usually forces the family to establish associations, or lease property to third parties outside the company, such as venture capital or institutional investors. Establishing external partnerships requires control mechanisms to review the actions of the non-family owners, reducing the opportunities associated with innovation. The concern of the family that owns the business to control partner opportunism reduces the company's ability to respond effectively to environmental changes or to take advantage of market opportunities that arise (Zahra et al., 2004).The tendency not to adopt innovative capacity increases with the extent that family presence increases in the ownership structures of the company, since it increases the interest to preserve family wealth, and reduces risk in the firm. It is therefore expected that: H1A. There is a negative relationship between the percentage of family ownership and innovation. The competitive advantages of family businesses improve when owner-managers involve other family members in the business (Eddleston and Kellermanns 2007). When only one person is in charge of decisions about innovation, other family members may not understand the decisions taken in the company and not participate (Kellermanns et al., 2012). However, when family members are included in the decision making process, they are more likely to critically evaluate the benefits of innovative behavior from many points of view, improving the quality of decisions and risk management in the business (March and Shapira 1987). High levels of family involvement in management may benefit innovative behavior (Kellermanns et al., 2012).Therefore, we expect: H1B. There is a positive relationship between family involvement in management and innovation. The family experience, understood as the information knowledge, judgment and intuition that comes through successive generations, affects the company's innovative capacity (Beck et al., 2011). Family firms in different generational stages differ in their innovation-oriented culture. The empirical study of Zahra (2005) emphasizes that family firms have a more innovation-oriented culture when later generations are involved in the management of the firm. An innovation oriented culture has an emphasis on creativity (Hurley and Hult, 1998), and creativity facilitates innovation (Amabile et al., 1996, Prajogo and Ahmed, 2006). This consequently has a positive influence on the family firm’s innovation. Therefore, we propose the following hypothesis: H1C. Innovation is higher among second- and subsequent- generation family firms than in firstgeneration family firms.
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2.3 Absorptive capacity and organizational memory Absorptive capacity is the ability of a firm to recognize the value of new, external information, assimilate it and apply it to commercial ends (Cohen and Levinthal, 1990). The contribution of Zahra and George (2002) was an ongoing attempt to analyze the dimensions of this construct. Following Cohen and Levinthal (1990), they claim that absorptive capacity is a bi-dimensional dynamic capability and its dimensions can be developed distinctly. Potential absorptive capacity (PAC) reflects the capability to acquire and assimilate external knowledge, while transformation and exploitation of the acquired knowledge constitutes absorptive capacity (RAC). As a result, PAC enhances receptiveness to knowledge of a company, while RAC represents a set of organizational routines related to transformation and use of the acquired awareness. Thus, PAC fosters RAC and the latter promotes the exploitation of this knowledge through the development of innovations. In consequence: H2A. There is a positive relationship between the potential absorptive capacity and the realized absorptive capacity. H2B. There is a positive relationship between the realized absorptive capacity and innovation. The work of Walsh and Ungson (1991) offers a deeper insight into how former experiences of a company can affect its present in terms of decision making. Being on the cutting edge is usually a result of consistent learning throughout the company’s history. Moreover, experience and success co-evolve; retrieving and manipulating past experiences is important, not only for avoiding new mistakes, but also to exploit old and valuable knowledge. Their viewpoint coincides with the idea of path dependency, which explains the continual use of products or services based on prior commitment and reference points of the company. In other words, a firm’s history influences its subsequent behavior (Teece et al., 1997). This indicates the importance of the firm’s old knowledge in the creation of new knowledge. Thus, PAC will increase the OM, since a company acquires new knowledge that could be stored in organizational databases or in the employees’ minds. Also, companies will exploit the acquired knowledge. However, the exploitation of this knowledge for innovations, i.e. RAC, will depend not only of the PAC but also on the current knowledge that is stored in the company. Thus, H2C. Organizational memory mediates the relationship between potential absorptive capacity and realized absorptive capacity. Based on the arguments above, and given the positive relationship suggested between innovation, OM and absorptive capacity, it seems reasonable that the scenarios that favor innovation in family business also favor the development of OM and absorptive capacity. So we expect that: H2D1. There is a negative relationship between the percentage of family ownership and potential absorptive capacity and organizational memory. H2D2. There is a positive relationship between the family involvement and potential absorptive capacity and organizational memory. H2D3. Potential absorptive capacity and organizational memory is higher among second- and subsequent-generation family businesses.
3. Methodology 3.1 Data collection and sample The present study investigates 475 Spanish manufacturing firms with more than 40 employees. A pre-test was conducted with five CEOs to check the intelligibility of the questionnaire used. Based on their feedback, a number of items were reworded. This pre-test also involved five academics from different universities and improved the clarity of the questionnaire and ensured effective, accurate and unambiguous communication with the respondents. The data was collected using a structured questionnaire via a webpage designed specifically for this purpose. The process was managed by a specialized market research company. First, we contacted the CEO or innovation executive of each organization. We explained the purpose of the survey, provided a username and password and gave the webpage address, following the practice used in similar studies in the field (Li and Atuahene-Gima, 2001; Atuahene-Gima et al., 2006). The market research company then tracked completion of the questionnaire and helped organizations to complete it. All the processes were supervised and the quality
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez of this activity was tested by contacting a randomly selected sample of firms that had answered the questionnaire. The questionnaire was designed based on the review of the literature described above. Finally, a total of 249 usable questionnaires were received (a response rate of 52.42%). These responding companies belong to different sectors of the economy, which ensures a good representation of companies in general. The food and beverage industry, the furniture industry and metal production have the highest representation in the sample. There are no significant differences in the mean responses on any construct across firms from different industries. In addition, Chi-square distribution analysis revealed no significant differences between the sample and the population, in terms of industry distribution, number of employees and sales volume. The rate of investment in R&D was measured. We found that 34.1% of the companies do not spend anything on R&D and that 53% of the companies dedicate less than 10% of their budgets to R&D. 22.9% of the firms spend more than 10% of their budgets on R&D activities. The percentage of income from sales of new products to total sales was also measured, and it was found that 31.7% of the companies did not generate any income from their product innovations in the previous year, 36.2% of the companies generated less than 10% from new product sales, and 22.1% of the companies generated more than 10% of their income from new product sales.
3.2 Measures and measurement properties Organizational innovation measure includes four items, each referring to one of the four types of innovation SRE (OCDE, 2005): innovations in products, processes, commercialization and management (ρc =0,95, AVE ρc =0,81). Organizational Memory: In the present context, OM refers to the old know-how and experience acquired by the company with regard to a category of products or services. In other words it is the old knowledge that a company has already acquired about a given product category. In this contribution, we adopt the scale offered by Chang and Cho (2008). This scale considers OM to be measured by the degree of knowledge, experience, SRE AVE familiarity and R&D investment in a specific kind of production (ρc =0,94, ρc =0,81). Absorptive Capacity: In this study we adopt and adapt the two-subcomponents of absorptive capacity offered by Zahra and George (2002). Thus, PAC and RAC were measured using the scale developed by Jansen el al. SRE AVE SRE AVE (2005) (PAC: ρc =0,96, ρc =0,85; RAC: ρc =0,98, ρc =0,92).. Family involvement: This is measured by the percentage of family managers and by the percentage of family ownership as in other works (Chrisman et al., 2005). Family generation. To distinguish between consolidated firms and second generation firms, for family firms, we set the age limit at 30 years. This decision is congruent with other works, e.g. Fernández and Nieto (2002). To assess the unidimensionality of each construct, a confirmatory factor analysis of the four constructs was conducted (Anderson and Gerbing, 1988). The measurement model provides a reasonable fit to the data 2 [χ (98)=206.37 (p=0.00), NFI=0.96, TLI=0,97, CFI=0,98, IFI=0,98, RMSEA=0,06]. The traditionally reported fit indexes are within the acceptable range. Reliability of those measures was calculated with Bagozzi and Yi’s (1998) composite reliability index and with Fornell and Larcker’s (1981) average variance extracted index. For all the measures both indices are higher than the evaluation criteria of 0.6 for the composite reliability and 0.5 for the average variance extracted (Bagozzi and Yi, 1998). Furthermore, discriminant validity is indicated since the average for every construct is higher than the square estimated correlation parameter between each two constructs (Fornell and Larcker, 1981). Table 1: provides an overview of construct means, standard deviations and correlations among the variables measured to test our hypotheses.
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Table 1: Construct correlation matrix Construct
Mean
Correlation Matrix
Standard deviation
1
2
3
4
5
6
1 Family generation
0,21
0,41
1
2 % Family ownership
62,57
38,94
0,46**
1
3 % Family managers
28,84
22,05
0,24**
0,39**
1
4 Potential Absorptive Capacity (PAC)
3,47
1,05
0,15*
-0,03
0,14*
1
5 Organizational Memory (OM)
2,45
0,8
0,19**
0,10
0,29**
0,60**
1
6 Realized Absorptive Capacity (RAC)
3,7
1,53
0,06
0,01
0,11
0,82**
0,68**
1
7 Innovation
3,34
1,12
0,23**
0,11
0,24**
0,75**
0,62**
0,7 6* *
*** p<0,01; ** p<0,05; * p<0,1
4. Analysis and results A structural equation modeling (SEM) methodology was employed to test the hypotheses. The proposed structural model is shown in Figure 1. Conventional maximum likelihood estimation techniques were used to 2 test the model (Jöreskog and Sörbom 1996). The fit of the model is satisfactory [χ (139)=293.93 (p=0.00), NFI=0.95, TLI=0,97, CFI=0,98, IFI=0,98, RMSEA=0,06] (see Table 2), thereby suggesting that the nomological network of relationships fits our data.
Figure 1: A model of the relationship between family involvement, family generation, PAC, RAC, OM and innovation. Table 2: Construct structural model Hypotheses Linkages in the model
Standardized parameter estimates
Number
Sign
Parameter
Estimate
t-value
% Family Ownership -> Innovation
H1A
-
γ14
-0.03
0.73
% Family Managers -> Innovation
H1B
+
γ24
0.13
3.07***
Direct Effects
Family generation -> Innovation
H1C
+
γ34
0.15
3.42***
PAC -> RAC
H2A
+
β31
0.68
13,65***
RAC -> Innovation
H2B
+
β43
0.77
16.77***
OM -> RAC
H2C
+
β32
0.28
6.12***
PAC -> OM
H2C
+
β21
0.59
9.92***
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez
% Family Ownership -> PAC
H2D1
-
γ11
-0.17
2.21**
% Family Managers -> PAC
H2D2
+
γ21
0.15
2.17**
Family generation -> PAC
H2D3
+
γ31
0.18
2.47**
% Family Ownership -> OM
H2D1
-
γ12
0.04
0.62
% Family Managers -> OM
H2D2
+
γ22
0.19
3.34***
Family generation -> OM
H2D3
+
γ32
0.04
0.60
PAC -> Innovation
κ14
0.65
12.97***
OM -> Innovation
κ24
0.21
5.82***
% Family Ownership -> Innovation
κ41
-0.10
1.98**
% Family Managers -> Innovation
κ42
0.14
2.91***
Family generation -> Innovation
κ43
0.12
2.54**
PAC -> RAC
κ13
0.16
5.51***
% Family Ownership -> RAC
κ31
-0.13
2.00**
% Family Managers -> RAC
κ32
0.18
2.95***
Family generation -> RAC
κ33
0.16
2.57***
% Family Ownership -> OM
κ21
-0.10
2.17**
% Family Managers -> OM
κ22
0.09
9.92**
Family generation -> OM * p<0,1; **p<0,05; ***p<0,01; Fit statistics for measurement model: 2 χ (139)=293,93 (p=0.000), NFI=0.95, TLI=0,96, CFI=0,97, IFI=0,97, SRMR=0,04, RMSEA=0,06
κ23
0.11
2.41**
Indirect effects
In term of our hypotheses (Table 2), the findings for H1B (% Family managers -> Innovation;γ24 = 0.13, p<0.01) and H1C (Family generation -> Innovation;γ34 = 0.15, p<0.01) suggest that, as predicted, innovation is positively associated with family involvement in management and family firms in the second generation or more. We accept, therefore, Hypotheses H1B and H1C. Family ownership does not have a direct effect on innovation, even if it produces an indirect effect as can be seen in Table 2 (% Family ownership -> Innovation; κ41=-0.10, p<0,05). We reject Hypothesis 1A because the effects on innovation are caused indirectly rather than directly. The family-run and family generation to run the business also have indirect positive effects on innovation (% Family managers -> Innovation, κ42=0.14, p<0.01; Family generation -> Innovation, κ43=0.12, p<0,05). This finding support the thesis argued in the literature that familiness can be a source of competitive advantage. So, in spite of the risks and costs of innovation, companies which have a more family commitment to the business will have more innovative behavior. Companies with higher PAC increase the OM (PAC ->OM, β 21=0.59, p<0.01) and RAC (PAC ->RAC, β 21=0.59, p<0.01). We found that companies with higher level of PAC (PAC ->RAC, β31=0.68, p<0.01) and OM (OM ->RAC, β32=0.28, p<0.01) will be more innovative, since RAC affects innovation (RAC -> Innovation; β43=0.77, p<0.01). Thus, OM mediates the relationship between PAC and RAC. We accept, therefore, Hypotheses H2A, H2B and H2C. On the other hand, we find that companies with greater family involvement in the management of the family business, and family businesses in the second generation onward, have a greater PAC (%Family managers -> PAC, γ21=0.15, p<0.05; Family generation -> PAC, γ31=0.18, p<0.05). There is less PAC in the most family-owned businesses (%Family ownership -> PAC, γ11=-0.17, p<0.05). Contrary to our prediction, we did not find any direct relationship between family ownership and OM, although for firms that were in their second generation or later there was a direct impact on increasing OM, suggesting there are indirect relationships between family ownership, family generation and OM (%Family ownership -> OM, κ21=-0.10, p<0.05; Family generation -> OM, κ23=0.11, p<0.05). Last, we find in companies with a greater family involvement in management a greater OM (%Family managers -> OM, γ22=0.19, p<0.01).
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez We reject Hypotheses H2D1 and H2D3 as there are no direct effects between family ownership, family generation and OM, and we accept Hypothesis H2D2 that proposes a positive relationship between family involvement and PAC and OM. These results suggest that PAC and OM plays an intermediate role in the link between family involvement, family generation and innovation.
5. Conclusions Family involvement in ownership and management sets the minimum threshold for considering a firm a family firm and to enable the family to exercise its influence over the company (Zellwegeret al., 2010). But the most interesting characteristic is that these companies try to survive and transmit their business to their own family descendants. This requires that the company should adapt to organizational changes and consequently innovate. In family firms, innovation is important since it enables them to be passed on to later generations (Beck et al., 2011). A review of the literature shows that innovation requires a learning process that allows companies to generate new knowledge and provide fresh ideas for generating innovations. However, this process requires the participation of internal stakeholders (employees, family owners-managers) and external stakeholders (customers, suppliers, other organizations). Since, individual learning, though valuable, is not enough to guarantee success throughout the process of new product development, the company must share and manage knowledge resources to develop innovation. Our results show, on the one hand, how the knowledge-based (Wernerfelt, 1984) and dynamic capabilities approaches (Teece et al., 1997) emphasize the role of knowledge in growth, generation, maintenance and development of innovations. Specifically, we have examined two knowledge management capabilities and we have found a positive influence between organizational memory, absorptive capacity and product innovations. This relationship is further enhanced as OM increases, since OM mediates the relationship between PAC and RAC, since there is a positive relationship between the PAC and the RAC, and between the RAC and innovation. This evidence is similar to other studies (Lavie and Rosenkopf, 2006) and demonstrates that these capabilities are determinants of the development of successful innovations. On the other hand, we have analyzed the influence of the family on the relationships between knowledge capabilities and innovation. We have found evidence that family involvement in management fosters knowledge management capabilities (absorptive capacity and OM), and also that as the business passes to the next generation it promotes the absorption of knowledge. There is a positive direct relationship between family involvement in management and generation and innovation. However, we did not find a negative direct relationship, but only an indirect one, between family involvement in ownership and innovation. This result is similar to other studies that have failed to find a relationship between family ownership and innovations (Wu, 2008, Gudmundson et al., 2003). Furthermore, the analysis of the mediator effects of family involvement in ownership and management and the family generation on the relationship between knowledge management capabilities and innovation reveals that family support can foster this relationship. A possible explanation for this result is that the avoidance of risk-taking behavior in first-generation family firms leads to them having a high concentration of ownership in one or a few people involved in managing the business (Kellermanns et al., 2008). In addition, because of the changed environmental conditions during the internal orientation and riskaverse behavior of the first-generation family firms, later-generation family firms need to reinvent themselves and go beyond the legacy they know. In subsequent generations the property is spread over a larger number of family owners who participate and engage in management of the business. The results suggest that there are benefits of incorporating the family in the management of the business as a means to develop knowledge and promote innovation. However, this study has some limitations. First, the survey used single informants as the source of information. Although the use of single informant remains the primary research design in most studies in this area, multiple informants would enhance the validity of the research findings. In order to get round this limitation, analyses have tested for the absence of potential common method variance caused by collecting data from a single informant in each firm. The tests showed that there is no single factor with eigenvalue greater than one (Jöreskog and Sörbom 1996). A second limitation is the cross-sectional design of this research. Thus, researchers should interpret with caution the causality between the constructs (Jöreskog and Sörbom 1996).
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Future research should use longitudinal studies and the inclusion of others individual characteristics of the family business founders. Acknowledgements We acknowledge the funding received from the Spanish Ministry of Science and Innovation (Research Project CSO2010-17761) to undertake this research. References Amabile, T., Conti, R., Coon, H., J, L. and Heron, M. (1996) Assessing the work environment for creativity. Academy of Management Journal, 39, 1154-1184. Anderson, J. C. and Gerbing, D. W. (1988) Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423. Astrachan, J. H., Klein, S. B. and Smyrnios, K. X. (2002) The F-PEC Scale of Family Influence: A Proposal for Solving the Family Business Definition Problem1. Family Business Review, 15, 45-58. Atuahene-Gima, K., Li, H. and De Luca, L. M. (2006) The contingent value of marketing strategy innovativeness for product development performance in Chinese new technology ventures. Industrial Marketing Management, 35, 359-372. Bagozzi, R. P. and Yi, Y. (1998) On the evaluation of structural equation model. Journal of the Academy of Marketing Science, 16, 74-94. Beck, L., Janssens, W., Debruyne, M. and Lommelen, T. (2011) A study of the relationships between generation, market orientation, and innovation in family firms. Family Business Review, 24, 193-196. Brown S.L. andEisenhard KM. (1995) Product development: past research, present findings, and future directions. Academy of Management Review, 20(2), 343–78. Carney, M. (2005) Corporate governance and competitive advantage in family-controlled firms. Entrepreneurship Theory and Practice, 29(3), 249–266. Chang, D. R. and Cho, H. (2008) Organizational memory influences new product success. Journal of Business Research, 61 13-23. Chrisman, J. J., Chua, J. H., and Zahra, S. A. (2003) Creating wealth in family firms through managing resources: Comments and extensions. Entrepreneurship Theory and Practice, 27, 359–365. Chrisman, J. J., McMullan, E., and Hall, J. (2005) The influence of guided preparation on the long-term performance of new ventures. Journal of Business Venturing, 20, 769–791. Cohen, W. M. and Levinthal, D. A. (1990) Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128-154. Damanpour, F., Szabat, K. A. and Evan, W. M. (1989) The relationship between types of innovation and organizational performance. Journal of Management Studies, 26, 587-601. Eddleston, K. andKellermanns, F. W. (2007) Destructive and productive family relationships: A stewardship theory perspective. Journal of Business Venturing, 22(4), 545–565. Fernandez, Z. and Nieto, M.J. (2005) Internationalization Strategy of Small and Medium-Sized Family Businesses: Some Influential Factors. Family Business Review, 18, 77-89. Fornell, C. and Larcker, D. F. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, XXVII, 39-50. Gudmundson, D., Tower, C. and Hartman, E. 2003. Innovation In Small Businesses: Culture And Ownership Structure Do Matter. Journal Of Developmental Entrepreneurship, 8, 1-18. Habbershon, T. G. and Williams, M. (1999) A resource-based framework for assessing the strategic advantage of family firms.Family Business Review, 12, 1–25. Hurley, R. E. and Hult, G. T. M. (1998) Innovation, market orientation and organizational learning: An integration and empirical examination. Journal of Marketing, 62, 42-54. Jackson, P. (2012) Transactive directories of organizational memory: Towards a working data model. Information and Management, 49, 118–125 Jöreskog, K.G. andSörbom, D. (1996) LISREL 8 user's reference guide. Chicago: Scientific Software International. Kellermanns, F. W., Eddleston, K. A., Barnett, T. and Pearson, A. 2008. An Exploratory Study Of Family Member Characteristics And Involvement: Effects On Entrepreneurial Behavior In The Family Firm. Family Business Review, 21, 1-14. Kellermanns, F., Eddleston, K.A., Sarathy, R., and Murphy, F. (2012) Innovativeness in family firms: a family influence perspective. Small Business Economic, 38, 85–101 Li, H. and Atuahene-Gima, K. (2001) Product innovation strategy and performance of new technology ventures in China. Academy of Management Journal, 44, 1123−1134. Littunen, H. and Hyrsky, K. (2000) The early entrepreneurial stage in Finnish family and nonfamily firms. Family Business Review, XIII, 41-54. March, J. G. andShapira, Z. (1987) Managerial perspectives on risk and risk taking.Management Science, 33(11), 1404– 1418. Newbert, S. L. (2007) Empirical research on the resource-based view of the firm: An assessment and suggestions for future research. Strategic Management Journal, 28, 121–146.
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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez OCDE (2005) Oslo Manual, The measurement of scientific and technological activities. Proposed guidelines for collecting and interpreting technological innovation data, European Commission. Retrieved August, 2005, from World Wide Web: http://www.oecd.org. Prajogo, D. I. and Ahmed, P. K. (2006) Relationships between innovation stimulus, innovation capacity, and innovation performance. RandD Management, 36, 499-515. Sirmon, D. G. andHitt, M. A. (2003) Managing resources: Linking unique resources, management and wealth creation in family firms. Entrepreneurship Theory and Practice, 27, 339–358. Teece, D. J., Pisano, G. and Shuen, A. (1997) Dynamic capabilities and strategic management. Strategic Management Journal, 18, 509-533. Walsh, J. P. and Ungson, G. R. (1991) Organizational memory. Academy of Management Review, 16, 57-91. Wu, H. 2008. When Does Internal Governance Make Firms Innovative? Journal Of Business Research, 61, 141-153. Zahra, S. A. and George, G. (2002) Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27, 158-203. Zahra, S. A. and Sharma, P. (2004) Family business research: A strategic reflection. Family Business Review, 17(4), 331–346. Zahra, S. A. (2005) Entrepreneurial risk taking in family firms. Family Business Review, 18, 23-40. Zellweger, T.M., Eddleston, K.A. andKellermanns, F.W. (2010) Exploring the concept of familiness: Introducing family firm identity.Journal of Family Business Strategy, 1, 54–63.
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Relationship Between Perceived Organizational Support, Self‐ Efficacy, Subjective Norms and Knowledge Sharing Delio Ignacio Castaneda and Manuel Fernández Ríos Pontificia Universidad Javeriana, Colombia, Universidad Autónoma de Madrid, Spain delio.castaneda@javeriana.edu.co mf.rios@uam.es Abstract: Despite the growing interest in knowledge sharing, there are few studies that contribute to its explanation. The research was framed on the behavioral perspective of knowledge management, interested in the identification and study of the human factors associated to knowledge management. In this direction, the paper presents the results of a research in which it was studied the relationship between perceived organizational support, self‐efficacy and subjective norms on the knowledge sharing intention and behavior. The research was conducted with 188 knowledge workers of a public organization at the national level in Colombia. According to results, there is a positive relationship between perceived organizational support, subjective norms, self‐efficacy and knowledge sharing intention with the knowledge sharing behavior. At the same time, a positive relationship was found between subjective norms and knowledge sharing intention. There was not found relationship between perceived organizational support and the knowledge sharing intention. Results are consistent with the conceptual framework. A model of the relationship between variables was validated using chi‐ square. There are some lessons to practitioners about the role of psychosocial variables in the facilitation of knowledge sharing. Keywords: perceived organizational support, self‐efficacy, subjective norms, knowledge sharing
1. Introduction Knowledge management is an organizational field related to creation, organization, distribution and use of knowledge (Ju, Lin, Lin & Kuo, 2006). A behavior to make it possible is knowledge sharing. Storey and Barnett (2002) emphasized the need to understand human factors which are related to the knowledge sharing behavior, as a way of contributing to the development of knowledge management. The paper presents results of a research in which it was evaluated the relationship between three psychosocial variables: perceived organizational support, self‐efficacy and subjective norms, and the knowledge sharing intention and behavior. Additionally, a model of the studied variables is presented using Structural Equation Modeling (SEM). There is a growing interest in studying knowledge sharing in organizations. As it was expressed by Kogut & Zander (1995), firm´s survival depends in part of having and sharing knowledge; this behavior is also associated to organizational competitiveness. Despite the awareness of the relevance of knowledge sharing, there are few studies that contribute to its explanation (Steward, 2008). This is confirmed by Wang & Noe (2010) who based on a review concluded that the issue is still incipient. Helmstadter (2003) defined knowledge sharing as voluntary interactions between human actors where raw material is knowledge. Knowledge sharing is not an automatic action, but a behavior highly dependent on human will (Dougherty, 1999; Scarbrough & Carter, 2000). Knowledge sharing requires motivation to act (Wah, Menkhoff, Low & Evers, 2005). What an individual share is: know‐what, know‐how, know why, know‐what for, experiences, contextual information, values, ideas, believes and insights. There are different frameworks for the explanation of human behavior. One of the most powerful theories is the social cognitive theory formulated by Bandura (1986, 1999), who stated that people are not autonomous agents acting without influence of context, or entities who respond mechanically to environmental conditions. In this theory, personal factors, environment and behavior operate as determinants of reciprocal influence (Bandura, 1989). Therefore, human behavior is partly self‐generated and partly determined by environmental conditions. For social cognitive theory, people are agents, self‐evaluators of their motivations and actions, who are in constant interaction with environment (Bandura, 2001). A central concept in Bandura´s social cognitive theory is self‐efficacy, which states that individual beliefs about his/her capacity to achieve a particular behavior influence performance (1977). Self‐efficacy is not associated to the number of skills a person has, but to beliefs the individual has about his/her capacity to act in a variety of circumstances (Cisneros & Munduate, 2000). Self‐efficacy contributes to predict whether or not a person faces a task. In this sense a person with high self‐efficacy to share knowledge is expected to share it.
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Delio Ignacio Castaneda and Manuel Fernández Ríos There is some research linking self‐efficacy and knowledge sharing behavior (Endres, Endres, Chowdhury & Alam, 2007; Lu & Leung, 2004; Lu, Leung & Koch, 2006). Bock & Kim (2002) found a positive relationship between these two variables; however, self‐efficacy was understood as expectations of contributions, which moves away from the original concept of Bandura (1977). Cabrera, Collins & Salgado (2006), in an exploratory study in a multinational company found relationship between breadth role self‐efficacy and knowledge sharing. Hsu, Ju, Yen & Chang (2007) found that knowledge sharing has direct and indirect effects on knowledge sharing behavior. Some authors have also found a positive relationship between self‐efficacy and knowledge sharing behavior in virtual communities (Chen, Chuang & Chen, 2012; Tseng, 2007). From above the following hypothesis is formulated: H1. Knowledge sharing self‐efficacy influences the knowledge sharing behavior. Another variable associated to the explanation of a behavior is perceived organizational support (POS), which is defined as the global interpretation of a worker about how much the organization values his contributions and takes care of his welfare (Eisenberger, Huntington, Hutchinson & Sowa, 1986). POS generates a feeling of reciprocity in the person to contribute to organizational objectives (Eisenberger, Armeli, Rexwinkel, Lynch & Rhoades, 2001). This concept correlates to organizational commitment, better performance and less rotation (Rhoades & Eisenberger, 2002; Uchenna & Tolupe, 2013). Allen & Shanock (2013) stated that POS is a relational mechanism that binds employees to the organization. If POS produces a feeling of reciprocity, then it is expected, that a worker shares his knowledge. There are few studies on the relationship between POS and knowledge sharing. King & Marks (2008) found a positive correlation between POS and the effort individuals do to share knowledge. Bartol, Liu, Zeng & Wu (2009) found that the correlation between POS and knowledge sharing was strong only to workers with a high perception of work security. Lu, Leung & Koch (2006) did not find relation between POS and knowledge sharing. Hsin, Shian & Sung (2011) found that POS mediated the relationship between high commitment to human resources management and knowledge sharing behavior. In the present investigation, unlike King & Mark (2008), it was not measured the effort to share knowledge, but the intention to share it and the knowledge sharing behavior. Additionally, unlike the study of Lu, Leung & Koch (2006), it was used the POS instrument designed by the authors of the construct (Eisenberger, Huntington, Hutchinson & Sowa, 1986). The following hypotheses are formulated: H2: Perceived organizational support influences the intention to share knowledge. H3: Perceived organizational support influences the knowledge sharing behavior. In this research it was also investigated the relationship between self‐efficacy and POS. Stadkovic & Luthans (1998) stated that self‐efficacy changes when the person obtains new information and experience performing a task. Having feedback on performance or watching a model doing an action increases self‐efficacy (Saks, 1995). Maurer, Pierce & Shore (2002) held that POS increases self‐efficacy. Meanwhile, Lu, Leung & Koch (2006) did not found relationship between the two variables. However, in that study POS was measure by a scale developed by the authors and not by the instrument designed by the owners of the construct (Eisenberger, Huntington, Hutchinson & Sowa, 1986). In this research the relationship between POS and self‐ efficacy was studied using the original POS scale. The following hypothesis is formulated: H4. Perceived organizational support influences self‐efficacy to share knowledge. Subjective norms is the person`s perception that people who are important to him/her think he/she should or should not perform the behavior in question (Carpi & Breva, 2001; Fishbein & Ajzen, 1975). Subjective norm is the perceived social pressure to do or not an action. A normative belief is related to the approval or not of a behavior by who are important referents to the individual (Ajzen, 1991). If subjective norm is high, so is the intention. Unlike POS, subjective norm is not a perception of support but an individual`s belief about what is expected to do in a context, and the motivation to act. In organizational contexts, if an employee believes his boss considers he should share knowledge and the person is motivated to do what his boss wants, this is called a subjective norm to share knowledge. Unlike POS, subjective norm is not an overall perception of backing, but a belief about what it is expected to do in a context and the motivation for action. In the absence of strong social norms people tend to share knowledge based on personal benefits and costs (Constant, Kiesler & Sproull, 1994).
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Delio Ignacio Castaneda and Manuel Fernández Ríos There are some studies about the influence of subjective norms on the knowledge sharing intention (Bock & Kim, 2002; Bock, Zmud, Kim & Lee, 2005; Castaneda & Fernández, 2010; Lin & Lee, 2004; Ryu, Ho & Han, 2003), and some on the influence of subjective norms on knowledge sharing (Bock & Kim, 2002; Castaneda & Fernández, 2010; Lin & Lee, 2004; Müller, Spiliopoulou & Lenz, 2005). There is also evidence of the importance of perceived social pressure from bosses on knowledge sharing behavior (Chatzoglou & Vraimaki, 2009). Based on these studies the following two hypotheses are stated: H5. Subjective norms influence the intention to share knowledge H6. Subjective norms influence the knowledge sharing behavior. Finally, according to the reasoned action theory (Fishbein & Ajzen, 1975), the closest determinant of behavior is the intention. Intention is the cognitive representation of the disposition of an individual to perform a behavior (Ajzen, 1991). Intention is the degree in which a person has a conscious plan to do a behavior (Warshaw & Davis, 1985). According to a prospective study, intention has explained between the 19% and 38% of the variance of behavior (Sheeran, Trafimow & Armitage, 2003). Therefore, the following hypothesis is stated: H7. Knowledge sharing intention influences knowledge sharing behavior. Figure 1 shows the research model. Self-efficacy H4 H1
H1 Perceived Organizational Support
H2
Knowledge Sharing
H1
I
i
H7
H3 H4
H5
H4
H1
H1
Subjective Norms
H4 H4
H1
Knowledge Sharing Behavior H6
H4
Figure 1: Research model
2. Research methodology This is a correlational study that utilized self‐report responses using an online survey within an organization. There is large evidence of the relevance of the constructs: perceived organizational support, self‐efficacy and subjective norms in relation to some behaviors, but few studies in relation to knowledge sharing. This is the reason why it is stated a correlational study, but with some explanatory scope. To validate the research model it is used Structural Equation Modeling (SEM), a statistical technique to evaluate how the proposed model is fitted to data.
2.1 Participants and procedure A survey was conducted with 188 knowledge workers of a public organization at the national level in Colombia. 114 of respondents were women and 74 men. With the support of the human resources and organizational development offices of the public organization, 392 workers who occupied jobs at the professional, advisory and management levels were invited to answer the online questionnaire. 48% of them answered the request. An email was sent to the workers who fulfilled the research requirements. The email provided a link that conducted the participants to a web page that contained a short description of the survey as well as a confidentially statement.
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2.2 Instruments Perceived Organizational Support (POS): It was used the 8 items version of the instrument developed by Eisenberger, Huntington, Hutchinson & Sowa (1986). The tool was translated into Spanish using the procedure translation back translation. The questionnaire uses a likert scale of 7 levels of answer. For the variables: subjective norms, self‐efficacy, intention to share knowledge and the knowledge sharing behavior it was used the instrument validated by Castaneda & Fernandez (2010). Each variable includes 4 items with the exception of subjective norms which utilizes 8 items. The variables use a likert scale of 7 levels of answer. The reliability of the instrument was of 93% using alpha of Crombach.
3. Data analysis and results In this study some psychosocial variables which have showed theoretical consistency were tested in relation to the knowledge sharing intention and behavior. In order to test the hypotheses, the correlations between the variables were calculated and their degree of significance. Figure 1 shows the research model and table 1 the correlations between the variables. Five of seven hypotheses found support from data. There was not found significant correlation between perceived organizational support and knowledge intention and between perceived organizational support and self‐efficacy. Next step was to assess the validity of the model. H1 examines the link between knowledge sharing self‐efficacy and the knowledge sharing behavior. The correlation was 0,435, significant at the 0,01 level. The results are in the expected direction according to the self‐efficacy theory (Bandura, 1977). In this sense, as it was found with other behaviors, there is a relationship between self‐efficacy and the knowledge sharing behavior. This is, individual`s beliefs of his or her capacity to share knowledge is directly related to his or her knowledge sharing behavior. The results contribute to document the importance of this construct in relation to knowledge sharing. Although there are some previous studies that investigated the relationship between these two variables, one of them conceptualized self‐efficacy as expectations of contribution (Bock & Kim, 2002), far from the original concept created by Bandura (1977) and the other focused the attention on the role breadth self‐efficacy (Cabrera, Collins & Salgado). Further studies may investigate the relationship between self‐efficacy and different types and levels of knowledge sharing. Table 1: Pearson Correlations between the variables of the hypotheses Correlation
Hypothesis
Self- Efficacy
Variables Knowledge Sharing
0,435 **
H1
Perceived Organizational Support
Knowledge Intention
0,026
H2
Perceived Organizational Support
Knowledge Sharing
0,213**
H3
Perceived Organizational Support
Self- Efficacy
0,7
H4
Subjective Norms
Knowledge Intention
0,476**
H5
Subjective Norms
Knowledge Sharing
0,729**
H6
Knowledge Intention
Knowledge Sharing
0,510**
H7
** correlation is significant at 0,01 level
H2 and H3 inquired on the association between POS and Knowledge sharing intention and behavior respectively. It was not found a significant correlation between POS and Knowledge sharing intention. Although there are no studies published linking POS and knowledge sharing intention, there is a related study in which it was found a liaison between POS and the effort to share knowledge (King & Mark, 2008). In our research it was stated that if POS generates a feeling of reciprocity (Eisenberger, Armeli, Rexwinkel, Lynch & Rhoades, 2001), then there was a connection between POS and knowledge sharing intention. The results do not support this hypothesis. In our study, the correlation between POS and knowledge sharing behavior was 0,213, significant at the 0,01 level. There are some contradictory findings in the literature. White Lu, Leung & Koch (2006) did not find
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Delio Ignacio Castaneda and Manuel Fernández Ríos relation between POS and Knowledge sharing; Bartol, Liu, Zeng & Wu (2009) reported relationship only with workers with a high perception of work security. According to the conceptual framework, POS generates a feeling of reciprocity in workers, which is expected to be manifested in behaviors such as sharing knowledge. It is suggested additional research to understand when POS has a direct association to knowledge sharing and when it does not. H4 evaluated the linkage between POS and self‐efficacy. It was not found support from data to this hypothesis. This fact contradicts the assertion of Maurer, Pierce & Shore (2002) and support the finding of Lu, Leung & Kock (2006) of no connection between these two variables. Additional research is suggested in the topic, particularly because according to Stadkovic & Luthans (1998) self‐efficacy changes when the person obtains information from performance. Receiving information from the organization may impact self‐efficacy. H5 and H6 declared that subjective norms are related to knowledge sharing intention and behavior. The correlation between subjective norms and knowledge sharing intention was 0,476, significant at the 0,01 level. According to the reasoned action theory the two closest determinants of intention are: subjective norms and attitude (Fishbein & Ajzen, 1975). As expected from this theory and the results from previous studies (Bock & Kim, 2002; Bock, Zmud, Kim & Lee, 2005; Castaneda & Fernández, 2010; Lin & Lee, 2004; Ryu, Ho & Han, 2003), the perception that an individual has from referents in an organization about knowledge sharing impact his intention to perform this behavior. In the same direction, it was found a correlation of 0,729, significant at the 0,01 level, between subjective norms and knowledge sharing behavior. The results contribute to add empirical evidence on the relation of these two concepts. Workers in organizations need to know from their leaders that sharing their knowledge is desirable. When it happens, this behavior has social pressure to occur in the organization and the probability that it takes place increases. H7 asserted that knowledge sharing intention influences knowledge sharing behavior. According to results there was found a positive correlation between the two variables, 0,510, significant at 0,01. Findings support the reasoned action theory which asserts that the closest determinant of behavior is the intention. This theory has been taken as a framework in few knowledge sharing studies and it was found a positive relationship between the knowledge sharing intention and the knowledge sharing behavior (Bock & Kim, 2002; Castaneda & Fernández, 2010; Reychav & Weisberg, 2010). The closest predictor of knowledge sharing is its intention. To validate the research model it was used Structural Equation Modeling (SEM). To evaluate the fitness of the model it was used the chi square value, which represents the differences between the observed covariance matrix and the predicted covariance matrix. According to data, chi square was 87,739, with 2 degrees of freedom and a probability level of 0,000, which let us affirm that the considered variables in this research model are good predictors of knowledge sharing intention and behavior. Figure 2 shows the model. A purpose of proposing a model is to identify few variables that explain largely a behavior. In this research some constructs that have been strong explaining human behavior, but incipient explaining knowledge sharing were studied together. From this research, if an organization focuses its attention in facilitating in employees perceptions of support, clear messages from leaders on the importance of knowledge sharing, and positive beliefs about their capacities to share knowledge, then the intention to share knowledge and the knowledge sharing behavior may occur. The research focused on psychosocial variables associated to knowledge sharing. There were not considered organizational conditions which also impact knowledge sharing, for example, the availability of resources and a knowledge oriented culture. Further studies are suggested to research psychosocial variables and organizational conditions together. In addition, there are few publications that present results on the relationship between perceived organizational support and subjective norms. Phattanacheewapul & Ussahawanitchakit (2009) in Thailand found that perceived organizational support mediates the link between subjective norms and task perseverance. In the future may be investigated the role of perceived organizational support as a mediator variable between subjective norms and knowledge sharing behavior.
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Delio Ignacio Castaneda and Manuel Fernández Ríos 0.76
E3
H4
H4
H1
1 0.62
Self-efficacy
H4
E1
H4
H1
0.7
0.80
1
-0.20
H4
H1
H4
Perceived Organizational Support
H1
-
Knowledge Sharing Intention
H1
0.14 H4
H4
0.47
H1
H1
H4
-
H4 H4
0.88
H4
H1
1
H1
Subjective Norms
Knowledge Sharing Behavior 1.00 H4
1
H4
H1
E2
0.78 H4
Figure 2: SEM analysis research model
4. Conclusions The purpose of this research was to contribute to the understanding of the role of some psychosocial variables in the explanation of the knowledge sharing behavior. All the studied variables have strong theoretical frameworks: Self‐efficacy from the social cognitive theory, subjective norms from the theory of reasoned action, and POS is a widely studied construct in organizations. Although these variables have been highly studied in psychology, they have been used recently in the understanding of the knowledge sharing behavior. In our research, it was found empirical support on the relationship between POS, self‐efficacy, subjective norms, intention to share knowledge and the knowledge sharing behavior. There are some implications from findings to practitioners in knowledge management. First, to strengthen human resources practices that may increase the perception of organizational support as a form to facilitate the knowledge sharing behavior. Second, the design of organizational interventions oriented to increase the knowledge sharing self‐efficacy in workers. Sometimes low performance in sharing knowledge may be explained not because of a lack of competence to share knowledge but due to low self‐efficacy associated to knowledge sharing. Third, leaders have a strong role orienting workers to specific actions. They must send the message of knowledge sharing as a must. If workers assume knowledge sharing as a subjective norm, they may be more willing to share knowledge and do so in practice. There are some limitations in the research. The first is that participants were knowledge workers of a public organization, then, it is not possible to generalize these results to public organizations in general or to private companies. However, results went in the direction of other studies. Second, POS was not unidimensional as expected from the theory (Eisenberger, Huntington, Hutchinson & Sowa, 1986). When it was run a factorial analysis of data, some items of the POS scale shared factorial loads in the intention to share knowledge scale. Additional research it is suggested on the communalities between POS and the intention to share knowledge.
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The Value of Extended Framework of TAM in the Electronic Government Services1 Juan‐Gabriel Cegarra‐Navarro1, Stephen Eldridge2, Eva Martinez‐Caro1 and Maria Teresa Sanchez Polo 1 1 Universidad Politécnica de Cartagena, Spain 2 Lancaster University Management School, UK juan.cegarra@upct.es s.eldridge@lancaster.ac.uk meugenia.sanchez@upct.es juan.cegarra@upct.es Abstract: Spanish City Halls are making a great effort to develop citizen‐targeted online services in an attempt to enhance their effectiveness and reduce expenses. Hence, citizens’ engagement is essential for the adoption of e‐Government services. In this research, an extended Technology Acceptance Model (TAM) is developed to test citizen engagement towards online e‐Government services from a sample of 307 citizens who used the benefits adviser tool within a Spanish City Hall. To achieve this goal, a structuring equation model is developed and tested to confirm the explanatory power of citizen satisfaction on citizen engagement. The results obtained suggest that the core constructs of TAM (perceived usefulness, ease of use and attitude) significantly affect users’ citizen engagement. This study also reveals a general support for citizen satisfaction as a determinant of citizen engagement in e‐Government services. The implications of the findings are discussed and useful insights are provided on what policy to follow to establish the appropriate conditions to build citizens’ engagement intent. Keywords: citizen engagement, satisfaction, technology acceptance model, end users
1. Introduction In general terms, local government institutions can be considered repositories of knowledge in the form of laws, regulations or specific cases. These institutions provide and deliver public services that are of key importance to citizens and business. In countries like Spain, the factors that influence the nature and structure of the Spanish Public Administration (e.g. demand, costs, regulations, organisation, etc) are undergoing rapid change. Recent reforms have regionalised the Spanish Public Administration in order to improve response times and increase the participation of communities in the development and management of electronic online services at regional and local levels (Cohen & Nijkamp, 2004). According to a report recently released by the Press Office of the Spanish Ministry for Public Administrations (MAP in Spanish, 2011), in September 2011 Spain found itself among the ten most advanced countries in this area and ranked fifth in Europe in terms of both availability and sophistication of on‐line public services (SIPA, 2011). The progress of e‐Government in Spain has undoubtedly been favoured not only by the greater awareness and predisposition to engagement shown by potential service users but also by the planning and legislative efforts made by Spain’s public sector in the last few years (MAP in Spanish, 2011). In Spain, most if not all municipalities (called “municipios” in Spain) are engaged in the development and delivery of efficient services to the public. Heichlinger (2004) defines e‐Government simply as a set of activities supported by information systems with the aim of improving the relationships between government institutions and citizens. These include collecting and paying money according to the laws and bylaws of Spain as well as resolutions of city councils. A key component of local services is that of official town websites (OTW). These are highly visible manifestations of city developments and are used for service delivery and information. They enable local governments to provide citizens, business and other organisations with convenient access to local services and opportunities to collaborate via information communication technologies (ICT) (Lean et al., 2009). Despite the fact that the majority of municipal governments have their own ICT and websites to provide public information to citizens (Moon & Norris, 2005), there has been no emphasis on offering online financial and 1
The dates of this research were taken from a research program supported by the Spanish Ministry of Education (REF: ECO2011‐28641‐ C02‐02), the R&D Project for Excellence. Andalusian Ministry of Education (REF: SEJ‐6081), and the research program supported by the Agencia de Ciencia y Tecnología Región de Murcia (f SéNeCa 18709/EE/12).
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Juan‐Gabriel Cegarra‐Navarro et al. service transactions nor on providing opportunities for electronic and interactive political and policy participation (Criado & Ramilo, 2003; Norris & Moon, 2005). As Criado and Ramilo noted in a previous study of Spanish local government websites (2003), a low level of two‐way interaction between local governments and citizens could be characteristic. To address this, the Law on Citizens' Electronic Access to Public Services published in June 2007 2 in Spain sought to strengthen the commitment towards e‐Government implementation and use by autonomous communities and local authorities through the improvement of coordination mechanisms between various levels of government in providing e‐Government services (eServices) to citizens. The initial stages of the implementation of ICT‐based services in the local government environment can be difficult, but considering that most technical obstacles are gradually being overcome, the question that arises is whether people are willing to use these new technological advancements (Suki & Ramayah, 2011). Acceptance of information technology by users is deemed a necessary condition for its success (Davis, 1989). Regarding this, while customer engagement has been widely studied in the information technology area, research has largely concentrated on customer responses to online retailers (e.g. Reichheld & Schefter, 2000), few, if any, studies have considered the ways in which the use of municipal‐portals can be accepted through a municipal’s ICT infrastructure (operationalised in this paper as citizen engagement). There is a considerable volume of work related to technology acceptance. What we employ in this paper is an application of the Technology Acceptance Model (TAM) (Davis 1989). Despite the amount of academic research dedicated to examining the determinants of information technology acceptance, and to TAM in particular, very little research has been conducted on City Halls to help identify how technologies may be accepted by citizens. Hence, the primary aim of this research is to use the core concepts of TAM to test the citizen’s engagement towards e‐Government services offered by City Halls. To achieve this goal, a modified TAM is developed and tested by using the Structural Equation Modelling (SEM) approach. These relationships are examined through an empirical investigation of 307 citizens who used the benefits adviser tool within a Spanish City Hall. The concept of citizen engagement is discussed in detail in the following section. Section 3 investigates the development of hypotheses as to how the TAM contributes to citizen’s engagement in e‐ Government. Details of the survey which was used to collect appropriate data to test the models is presented in section 4, whilst the results of testing the models are presented in section 5, followed by a discussion in section 6.
2. Conceptual framework Abramson and Means, (2001) define e‐Government as digital governmental information or a way of engaging in digital transactions with the public (citizens and businesses) and employees. Fraga (2002) suggests that e‐ Government is the transformation of internal and external relationships in the public sector through net‐ enabled operations. Durrant (2002) defines e‐Government as “a permanent commitment by government to improve the relationship between the private citizen and the public sector through enhanced, cost‐effective and efficient delivery of services, information and knowledge”. For Jaeger and Fleischmann (2013), e‐ Government is about developing a citizen‐centred government environment which serves citizens (customers) at any time, regardless of their physical location. The above definitions suggest a variety of processes and services that can be supported by the use of ICT in government affairs, as well as the diversity of perspectives that can be adopted to assess their impacts in both governments and citizens (). These perspectives also provide us with an illustration that e‐Government is a way for public administration to become more open and transparent, to enable democratic participation, to become more service‐oriented, providing personalised and inclusive services to each citizen, to become more productive and to deliver maximum value for taxpayers' money as well as for any ICT investment. Researchers agree that e‐Government has considerable potential to contribute to learning efficiency, gains and cost reductions for local government (e.g. Criado & Ramilo, 2003; Carter & Belanger, 2005; Badri & Alshare, 2008; Lean et al., 2009). The opportunity to access new knowledge, learn about government and conduct online transactions can reduce red tape and simplify regulatory processes, therefore helping citizens to engage more in issues that are important to local communities (e.g. public transport or street design issues). 2
http://www.boe.es/boe/dias/2007/06/23/pdfs/A27150‐27166.pdf
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Juan‐Gabriel Cegarra‐Navarro et al. Just recently, in countries like the USA a number of e‐Government projects have been developed to help communities address their local problems with the use of websites (Bertot et al., 2011). In this way, a form of civic engagement is promoted which focuses on public concerns and which includes both political involvement in political institutions as well as community involvement in associational or voluntary activities or institutions (Putnam 2000; Jennings & Zeitner 2003; Bennett 2008). Despite these trends and premises, there are only a few cities around the world that continuously engage with citizens in policy dialogues or work with community organisations to strengthen citizen engagement and participation at the neighbourhood level (Ho, 2002). What seems to be dominating research in the use of e‐Government websites is the study of the dynamics of networks of communication that emerge in political campaigns, most of which are dominated by incumbent groups (Hindman, 2009: Araya et al., 2010). Civic engagement in general may be defined as individual and collective courses of action that are designed to identify and address matters of public concern (Hays, 2007). Another way of describing this concept is the sense of personal responsibility individuals should feel to uphold their obligations as part of any community (Putnam, 2000). This means that civic engagement can take many forms, from organisational involvement to electoral participation, individual volunteerism or engagement with new activities of the government. This paper is particularly concerned with the latter. That is, it focuses on those aspects of civic engagement that are mediated through local government websites, rather than formal political institutions or voluntary activities. It should be noted here that in this paper the civic engagement that we refer to is “citizen engagement”. More specifically, it is concerned with citizen engagement facilitated by local governments to deal with local affairs concerning pollution issues, school affairs and street design issues (Zukin et al. 2006; Lim, 2007). From this perspective, citizen engagement includes efforts to directly address an issue, work with others in a community to solve a problem or interact with the local institutions. Nowadays, e‐Government in Spain encompasses any type of mutual communication or interaction between citizens, business and public organisations and because of this, e‐Government is perceived as the use of ICT for controlling electronically public administration’s processes from both internal and external perspectives 3 (Criado & Ramilo, 2003; Claver et al., 2008). Although initiatives like the Avanza2 and Avanza Local Plans give testimony of how local and regional governments in Spain have been continuous adopters of ICT in recent years (Torres et al., 2005; De‐Miguel‐Molina, 2010; SIPA, 2011), the digital informative transparency of Spanish city councils is very poor (De‐Miguel‐Molina, 2010). As Gandía and Archidona (2008) noted, Spanish city councils often use their web sites to diffuse information of a general nature and with promotional or political purposes that do not contribute directly to relevant informative content. Neither do they allow users to take advantage of the relational and interactive capacity of the internet. A possible explanation for the low disclosure levels among Spanish city council web sites may relate to the website strategy and implementation adopted by Spanish city councils, and how such strategies have been associated with low (or non existent) citizen engagement (Gandía & Archidona, 2008).
3. Hypotheses As noted above, there are different definitions of citizen engagement but common elements include knowledge of and discussion of public affairs (Rose & Grant, 2010; Jennings & Zeitner 2003; Mossberger et al., 2008). E‐Government may provide new venues for information, enhancing citizen knowledge of government policies, processes, programs, and performance, as well as community issues (Norris 2001). This knowledge, in turn, may also encourage discussion or participation in community issues, including joining a group online and face‐to‐face interaction with neighbours (Norris, 2001). Information about community affairs available on local government websites might promote discussion and mobilization around these issues with neighbours, both online and offline (Norris, 2001), this points to the information capacity of e‐Government as being a potential resource for acquiring knowledge for citizen engagement (Norris 2001; Jennings & Zeitner 2003; Mossberger et al., 2008). However, the knowledge learned through a public service website is likely to be dependent on the gratifications individuals seek from media and their resultant media choices. Uses and gratification theory predicts that people use the Internet or other media in a variety of ways for a range of ends to satisfy different goals (Althaus & Tewksbury, 2000). Put it another way, the achievement of user satisfaction with public service websites requires attention to several earlier levels of user interaction. In this study, the Technology 3
http://www.planavanza.es/avanzalocal/Paginas/Index.aspx
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Juan‐Gabriel Cegarra‐Navarro et al. Acceptance Model (TAM) was used to analyze the processes of creating satisfaction with public service websites. The Technology Acceptance Model (TAM), first introduced by Davis (1989), is one of the most frequently employed models for research into new information technology acceptance. This model applies Fishbein and Ajzen’s Theory of Reasoned Action (TRA) to explain the pattern of voluntary information system usage at an individual level (Kim & Chang, 2007). TAM has been the subject of a lot of research in the area of information systems over nearly two decades and has been supported by a number of studies. TAM suggests that when users are presented with a new technology, their decision about how and when they will use it is determined by assessing their beliefs, attitudes and intentions (Davis, 1989). There is a considerable volume of work relating to technology acceptance. What we employ in this paper is an application of the Technology Acceptance Model (TAM) (Davis, 1989). Attitude toward using a technology (A) was defined by Davis (1989) as “the degree of evaluative affect that an individual associates with using a system in his or her job”. Attitude is determined by a function of two beliefs: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). PU was defined as “the degree to which a person believes that using a particular system would enhance his or her job performance”. PEOU is “the degree to which a person believes that using a particular system would be free from effort” (Davis 1989). PU and PEOU create belief among potential users and subsequently form their attitude. A user that believes the new technology will be useful and relatively easier to implement may be expected to have a more positive attitude towards that particular technology. On the other hand, perceived ease of use has a direct effect on perceived usefulness. Between two systems that perform an identical set of functions, users find the one that is easier to use more useful. However, perceived usefulness has no impact on perceived ease of use. As Davis (1993) explained, perceived usefulness concerns the expected overall impact of system use on job performance, whereas ease of use pertains only to those performance impacts related to the process of using the systems per se. Moreover, TAM postulates that Behavioural Intention (BI) is viewed as being jointly determined by the person’s attitude towards using system (AT) and PU (Davis et al., 2009). Finally, actual system use is determined by BI. The technology acceptance model specifies the causal relationships between perceived ease of use (PEOU), perceived usefulness (PU) and attitude toward using (A). Overall, the TAM provides an informative representation of the mechanisms by which design choices influence user acceptance, and should therefore be helpful in applied contexts for forecasting and evaluating user acceptance of ICT. Therefore, based on Davis (1989), traditional TAM hypotheses were tested as part of their work, and we propose: H1: Perceived ease of use is positively associated with perceived usefulness H2: Perceived usefulness is positively associated with attitude H3: Perceived ease of use is positively associated with attitude Although, the research model built was based on TAM, several modifications were made to improve use of e‐ Government services such as satisfaction and citizen engagement. On the one hand, satisfaction construct was introduced in the model. Although user satisfaction and technology acceptance have evolved largely as parallel research streams, the two approaches can be integrated. Such integration can help build a conceptual bridge from design and implementation decisions to system characteristics to the prediction of usage. Ultimately, this would improve the predictive value of user satisfaction and augment the practical utility of technology acceptance (Wixom & Todd, 2005). According to Bitner et al. (2002), effective and successful self‐service technologies are those that have been designed and implemented especially to ensure customer satisfaction and to keep customers’ motivations and expectations in mind. Satisfaction in a given situation is a person‘s feelings or attitudes toward a variety of factors affecting that situation (Wixom & Todd, 2005). From an ICT point of view, satisfaction construct represents the degree to which a user’s perceived personal needs and the need to perform specific tasks satisfactorily are met by an information system (Goodhue & Straub 1991). Within the literature on user satisfaction, satisfaction is typically viewed as the attitude that a user has toward an information system. Therefore, user satisfaction is conceptualized as affective reactions of individuals and it can be defined as an attitudinal construct. Several authors (e.g. Guimaraes & Igbaria, 1997; Chris et al., 2006; Eastman et al., 2011), point out that users with a
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Juan‐Gabriel Cegarra‐Navarro et al. more positive attitude towards a technology are likely to be more satisfied with it. Hence, attitude was considered here as an antecedent of satisfaction and the hypothesis we propose under this framework is: H4: A positive attitude towards a technology is positively associated with satisfaction The above considerations also lead us to argue that satisfaction achieved through local government websites, could be expected to facilitate citizen engagement as well. If citizen engagement includes knowledge, interest, discussion, and participation, then satisfaction with public service websites is one of the resources supporting these different aspects of engagement (Norris, 2001). Regarding this, some prior research shows that online news is a better predictor of citizen engagement than use of traditional media (Mossberger et al., 2008), and e‐Government also has many features that lower the costs of information acquisition. Thus, satisfaction with public service websites has a positive influence on citizen engagement, likelihood of recommending, word of mouth and reuse/loyalty intentions (Van Riel et al., 2001; Taylor & Hunter, 2002; Yoon, 2002). User satisfaction associated with ICT usage can influence subsequent use of information (Yen & Gwinner, 2003; Yang & Peterson, 2004). Regarding this, user satisfaction involves making the citizen aware of the e‐Government services and generating some positive feelings through the local government website. If online services meet citizen’s expectation, satisfaction occurs. In addition, satisfaction can result in successive use of the online services, which in turn facilitates citizen engagement. Here satisfaction is created first leading to citizen engagement. Therefore, we propose: H5: Satisfaction is positively associated to citizen’s engagement in e‐Government
4. Method Using the records of the Cartagena City Council, we considered 1995 users, who were contacted and asked by the City Council to participate in the study. Of these users, only 307 agreed. Then, on April and May 2012 we conducted 307 telephone interviews with users, using a simple structured questionnaire. Therefore, the data analysis was based on 307 valid responses (a response rate of 15.38%) with a factor of error of 5.15% for p=q=50% and a reliability level of 95% percent. The great majority of respondents were male (73 percent) and had university studious (37 percent). Additionally, this study conducts two statistical analyses to ensure the absence of non‐response bias (Armstrong & Overton, 1977). Firstly, this study compares the responding and non‐responding users in terms of level of education (1= secondary school; 2 = Bachelor’s Degree; and 3 = Master’s Degree). In this regard, the independent sample t‐test revealed no significant difference between the two groups (p= .93). Secondly, the respondents are then divided into two groups based on telephone interview dates (i.e. 1 = April; and 2 = May). Comparison of the two groups in terms of e‐Government use again revealed no significant differences based on the independent sample t‐test (p = .71). Therefore, non‐response bias should not be a problem in this study.
4.1 Measures In order to assure the research can be generalized, it is important to add control variables to the regression model in order to assure that the effects of technology on our population sample achievement are independent of the user’s focus on their achievement. With respect to this issue, the findings of traditional sociological studies point to more positive attitudes towards computer technology among males (e.g. Arch & Cummins, 1989). Specifically, some empirical evidence suggests perceived usefulness more salient for men than for women (e.g. Venkatesh & Morris, 2000) while other researchers find that technologies are perceived as more useful by women than by men (e.g. Gefen & Straub, 1997). Thus, the responder’s gender may be related to the Perceived Usefulness. In this paper, the variable “gender” has been treated as a control variable and was measured with a single variable classified into two categories (1=male and 2= female). Before undertaking the survey, a series of telephone interviews with five users of a pilot sample was undertaken to learn about their understanding about the benefit adviser tools. As shown in Figure 1, these users stated that the benefit adviser tool basically allows them to apply for a census certificate and pays local taxes such as the motor vehicle tax and the property tax. They also stated that the benefit adviser tool helped them to see how payment is being processed, and is also useful for generating more variations of existing scenarios by providing scenario generation hints for each comparison feature. A questionnaire was developed to be the instrument for data collection. All items were measured using a seven‐point Likert‐type scale with anchors from “Strongly disagree” to “Strongly agree”. We combined scales
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Juan‐Gabriel Cegarra‐Navarro et al. from several other relevant empirical studies with new items to make an initial list of 15 items (3 measuring the range of PEOU; 3 measuring the existence of PU, 3 measuring attitude, 3 measuring satisfaction and 3 relating to citizen engagement). Several items were modified through interviews with colleagues. Table 1 provides an overview of the final 15 questions used in the questionnaire. From an examination of the results shown in Table 1, we can state that all of the constructs are reliable.
Figure 1: The benefit adviser tools Table 1: Construct summary: Confirmatory factor analysis and scale reliability y
Items Services enhance effectiveness in doing things. Services make it easier to do things. Services enable me to accomplish thongs more quickly. In my opinion, it is desirable to use the city council’s website. I think it is good for me to use the city council’s website. Overall, my attitude toward the city council’s website is favourable. These services have met my expectations. I am pleased with the experience of using these services. My decision to use these services was a wise one. Public meeting in which there is a discussion of town affairs. Public meeting in which there is a discussion of school affairs. Citizen consensus conferences on critical street design issues Interacting with the city council’s website does not require a lot of my mental effort. I find the city council’s website to be easy to use. I find it easy to get the services to do what I want to do.
y
Standardized loading .76 .84 .81 .82 .78 .80 .73 .80 .77 .81 .75 .70 .73 .88 .77
y
T-value 13.81 14.12
y Reliability (SCRa., AVEb) SCR= .84 AVE=.63
14.39 14.96
SCR=.84
12.42
AVE=.64
13.96 13.21
SCR= .85
14.88
AVE=.65
12.88 13.41
SCR= .85
13.64
AVE=.66
10.85 16.63
SCR=.84
20.87
AVE=.64
16.59
Notes: The fit statistics for the measurement model were: Satorra-Bentler χ2(79)=176.40; χ2/d.f= 2.23; GFI=.90; CFI=.93; IFI=.94; RMSEA= .063; a SCR= Scale Composite Reliability (SCR) of pc= (Σλi)2 var (ξ) / [(Σλi)2 var (ξ) +Σ θii] b Average variance extracted (AVE) of pc= (∑λi2 var (ξ))/[∑λi2 var (ξ) + ∑θii] The asymptotic covariance matrices were generated to obtain the scaled chi-square (Satorra and Bentler, 1988) and robus estimation of standard errors.
Discriminant validity was determined by comparing the square root of the AVE (i.e., the diagonals in Table 2) with the correlations among constructs (i.e. the lower triangle of the matrix in Table 2). On average, each construct related more strongly to its own measures than to others (Fornell & Larcker, 1981).
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Juan‐Gabriel Cegarra‐Navarro et al. Table 2: Construct correlation matrix
1. Perceived usefulness (range 1–7) 2. Attitude (range 1–7) 3. Satisfaction (range 1–7) 4. Citizen engagement (range 1–7) 5. Perceived ease of use (range 1–7) 6. Gender (range 1–2)
Mean 5.03 5.32 4.77 5.26 4.72 1.27
S.D 1.09 1.14 1.04 1.10 1.22 0.44
CA .84 .84 .81 .80 .83 n.a
1 .79 .71*** .66*** .52*** .46*** -.04
Correlation matrix 2 3 .80 .66*** .62*** .56*** -.06
.83 .67*** .54*** -.02
4
.81 .34*** .02
5
.80 -.07
6
n.a
Notes: *** <.01; n.a. = not applicable Mean = the average score for all of the items included in this measure; S.D. = Standard Deviation; CA = Cronbach’s Alpha; Intercorrelations are presented in the lower and shady triangle of the matrix. The bold numbers on the diagonal are the square root of the Average Variance Extracted.
5. Results Following the recommendations of Anderson and Gerbing (1988), we tested our theoretical model (TM), with ‘satisfaction’ as intermediate variables between ‘attitude’ and ‘citizen engagement’, against an alternative model (AL), considering that ‘satisfaction’ does not need to be done first. Figure 1 provides a synopsis of these models. While in the first model (Theoretical Model) the impacts of ‘attitude’ on ‘citizen engagement’ is potentially mitigated by the extent to which satisfaction exists, in the case of the Alternative Model, the impact of the ‘attitude’ is not mediated through the extent to which satisfaction exists. The goodness of fit indices show that the theoretical model has more adequate fit indices: RMSEA, CFI, IFI and PNFI (see Figure 1), than the alternative model. It is interesting to note that the difference of PNFI between the two models is above 0.01, a critical value recommended by Hair et al. (1998) as indicating that one model represents a significant gain of parsimony over another. In the Alternative Model we have also found an insignificant effect of ‘attitude’ on ‘citizen engagement’, with a standardized coefficient of 0.09. Furthermore, the theoretical model explains more variance in citizen engagement than the alternative model. Therefore, the data we obtained provides support for the theoretical model where the extent to which satisfaction exists is considered as a mediating variable between ‘attitude’ and ‘citizen engagement’. Together, these results provide full support for H1, H2, H3, H4 and H5. In addition, responder sex was insignificant with a standardized coefficient of (β 21=0.08) and therefore gender does not affect the Perceived Usefulness (see Figure 1). Therefore, our results did not indicate any significant effects of gender on Perceived Usefulness and although there was a positive correlation in Figure 1 it was not significant. It would appear that neither females nor males favour or appreciate the benefits of technology. Gender
.08ns
.53***
R2= .28 Perceived usefulness
.28***
Perceived ease of use
R2= .74 Satisfaction
.71***
.86***
.86*** R2= .74
R2 =.81 Attitude
Citizen engagement
Theoretical Model (TM): χ2/d.f= 2.09; CFI=.93; IFI=.93; PNPI= .79; and RMSEA=.060
Gender
.09ns
.53*** Perceived ease of use
R2 =.28 Perceived usefulness
.28***
R2 =.73 Satisfaction
.71*** R2 =.81 Attitude
.85***
0.76*** .09ns
Alternative Model (AM): χ2/d.f= 2.47; CFI=.92; IFI=.92; PNPI=.78; and RMSEA=.069 Notes: *** p < 0.01 ns=not significant
Figure 2: Structural models
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R2=.72 Citizen engagement
Juan‐Gabriel Cegarra‐Navarro et al.
6. Discussion Relevant e‐Government literature has emphasised the fact that citizens who use e‐Government will benefit from the services and consequently be encouraged to adopt e‐Government as a regular method of accessing and interacting with public services. Therefore, the first contribution of this research is to question the existing models which relate to technology and citizen engagement in online e‐Government services. This paper supports or goes in the same direction of previous studies in identifying the value of TAM in the implementation of e‐Government services (e.g. Davis, 1989; Kim & Chang, 2007; Suki & Ramayah, 2011). The data indicates that TAM (perceived usefulness, ease of use and attitude) significantly affect user behavioural intention, in our study operationalised as citizen engagement, which implies that the main aspects of TAM apply to this context as well. In addition, perceived usefulness was found to be the most significant effect on attitude, which suggests that a citizen’s belief in usefulness is a decisive antecedent of affective variables (i.e. attitude and satisfaction), and consequently, of citizen engagement. This is consistent with previous research which found that perceived usefulness plays a more significant and stronger role than perceived ease of use on the affective variables (Roca et al., 2006). The second contribution is to extend the basic TAM towards the postcedents by adding the variables satisfaction and citizen engagement. While many researchers have extended the basic TAM by introducing additional variables as antecedents, surprisingly there are few studies that deal with the post‐acceptance process beyond the TAM framework (Kim & Chang, 2007). In this regard, modelling local government websites acceptance is very useful to local institutions but understanding why citizens build citizen engagement towards them is crucial. The research model tested provides deeper insights into the process of citizens’ engagement build‐up. Satisfaction was included in the model acting as a link between TAM variables and citizen engagement and results indicate that a positive attitude towards e‐Government services leads to users’ satisfaction. Hence, it is very important to work to get the highest positive attitude in users by enhancing easiness of use and, mainly, perceives usefulness. The results also support the position that through satisfaction of citizens, City Halls will enlarge citizen engagement. Thus, City Halls must continuously work at obtain satisfied users to encourage their continuing using the local government websites. This insight corroborates the notions of Suki and Ramayah (2011), that the acceptance of e‐Government services can be explained in terms of attitude towards e‐Government services. What this means for e‐Government is that when vaguely formed beliefs and attitudes concerning the system to be implemented have already been developed, these vaguely formed attitudes should be taken into account if a local government wishes to give a new system fair consideration (Hartwick & Barki, 1994). These findings support the view of Carter and Belanger (2005), that perceived usefulness has positive and significant effects on citizens’ continual usage intentions towards e‐Government services. If the utility of e‐Government websites is understood, then mechanisms can be developed for allowing electronic transactions to occur in a controlled and constructive way. The third contribution of this research is to test the TAM in a citizen context. Previous research on the TAM has mainly been conducted in workplace settings and, in particular, within regional and national contexts (Criado & Ramilo, 2003; Carter & Belanger, 2005; Badri & Alshare, 2008; Lean et al., 2009). In this type of environment, people’s attitudes, intentions, and behaviours, as well as their interrelationships are likely to be shaped by formal authority and directives (Lanseng & Andreassen 2007). This research has empirically supported the core concepts of TAM in a citizen context, where respondents are free to form their own beliefs, attitudes, and intentions, as the theoretical foundation of the TAM assumes. Thus, the results contribute to the general validity of the model. We think that this is an important finding, as potential for any City Hall to implement e‐ Government services will depend substantially on its ability to support these dimensions, thus, public administrators may be over‐investing in the implementation of e‐Government services, and under‐investing in (or underestimating) mechanisms and aspects to coordinate them. Put another way, since the population has different levels of technology readiness, reliable, user‐friendly services, with good user interface consistency, should be designed. In addition, services should be pre‐tested thoroughly and sufficiently across a wide range of users to see if they actually have been designed to be easy to use by the average user. By failing to do so, implementation may prove unsuccessful and more resources may be spent than saved (Lanseng & Andreassen, 2007).
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Juan‐Gabriel Cegarra‐Navarro et al. This study has some limitations. Firstly, although the constructs have been defined as precisely as possible by reference to the literature and validated by practitioners, they can realistically only be regarded as proxies for an underlying phenomena that in themselves not fully measurable. Secondly, only a single research methodology was employed and further research through interviews and observational case studies could be undertaken for triangulation. Thirdly, any extrapolation of the conclusions might not be generalisable beyond the sample frame, which could be addressed by cross‐sector and cross‐cultural studies. Finally, we assumed that use of e‐Government was similar for different actors and participants, and that therefore their assessment could be done in the same way as evaluating electronic online services. In other words we do not include the possibility of actors and participants being able to consider alternative uses of services available to them. Therefore, this assumption should be reviewed and explored further and might involve actors and participants whose concerns and interests might differ from ours. Taking into account this limitation, it would also be interesting to extend the survey to different actors and participants, since they might have a different level of knowledge concerning computers and technology tools, and finally, despite most City Halls in Spain having internet access, there is a lack of awareness of the existence and/or value of e‐Government services to citizens’ engagement, and this provides an opportunity for further research. In order to ensure that future research is more accurate and reliable, studies should be based on more than the four variables used here as citizen engagement is affected by many factors. This is because these four variables cannot fully explain the factors influencing citizens’ acceptance of e‐Government services. Consequently, future findings might be inconclusive. E‐Government will continue to be an important topic to monitor, as it will dramatically affect the life of the individual citizen and their governments on a global scale.
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A Context‐Aware Architecture for the Management of Laundry Business Processes Ufuk Celikkan and Kaan Kurtel Department of Software Engineering, Izmir University of Economics, Izmir, Turkey ufuk.celikkan@ieu.edu.tr kaan.kurtel@ieu.edu.tr Abstract: Business processes capture the experiences, insights and the knowledge of how a company conducts its business. Because this knowledge is embodied in business processes, it is important that this knowledge is managed effectively and efficiently by the business to reach its goals. While, business processes are essential in understanding how businesses operate, they also play a major role in how information technology is used in the implementation of information systems. Therefore, Business Process Management Systems have been developed to identify, understand, manage and coordinate business processes. The need for management software have had an effect on the role of software architects, who are becoming more involved in developing business process, in addition to their traditional role of describing the software. In this paper, the authors propose a conceptual Laundry Management System solution and architectural framework to monitor and autonomously manage the laundry process. The washing of laundry on an industrial scale has become highly automated, carried out by machines using sensors generating very detailed data. Data from these sensors allow the precise control of the laundry operation, often remotely. The combination of new machines with information technology has created a more efficient and cost effective process which requires software based on extensible architecture. Our proposal for such a system incorporates the features of a context aware architecture since the operations of a laundry exhibit the properties of a typical context‐aware system. The laundry context data is classified and categorized as being primary and secondary. Primary context types are further categorized as location (where), identity (who), time (when) and activity (what). The context modeling is based on ontology, as this is the most expressive model. The system defines clear boundaries among data acquisition, data management and the business logic which are encapsulated in their respective layers. The system employs an inference and a workflow engine which conveys the overall status of the system to the user through a convenient user interface. The proposed architecture is based on Service Oriented Architecture. The business oriented functionality and business rules are captured as a service for to be used by the system components internally and by the customers externally. Moreover, the use of web services eliminates the tight coupling between subsystem components. Weak coupling supports flexibility and reusability. Using service‐oriented architectures to integrate and unify various departments within a laundry business is also very straightforward. For instance, the logistics department can easily discover whether an item is ready to be shipped or the finance department can have very detailed report on the cost of the resources used to clean a particular garment. Keywords: business process management, context‐aware systems, laundry management system, service oriented architecture, web services
1. Introduction Information technology is becoming an integral part of every business. As a result, software architects no longer only describe what the software does, but also all the processes connected with the business (Weske, 2007). Business processes and rules together describe the business and they continuously change to adapt the business to meet the demands of today’s challenges. Business Process Management (BPM) identifies understands and manages the business processes and aligns customer needs with the business goals while business rules formally specifies ways of connecting policies and constraints of an enterprise to information systems (Debevoise, 2007). Linkage of business processes to business rules is instrumental in implementing business intentions in business processes and information systems (Fedlkamp et al., 2007). The IT that supports a business must work seamlessly with the business objectives and, therefore must be cognizant of the changes happening in the environment, and deal appropriately with changes in the processes and rules. A context aware architecture applied to Business Process Management provides the agility needed. The operation of a laundry service is similar to any other business in the sense that it consists of many different processes. The management of these processes is crucial to the efficient and effective operation of a business. A Laundry Management System (LMS) has the primary task of monitoring and optimizing laundry processes in order to increase customer satisfaction and business productivity, and to ensure that operational, tactical and strategic management decisions are accurate, consistent and timely at every level. Information Technology plays an important role in achieving this goal. A laundry business that aligns its processes
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Ufuk Celikkan and Kaan Kurtel seamlessly using information technology can implement a sustainable profit model, ensure customer satisfaction, and create and maintain its competitive advantage. This paper presents a conceptual software solution and proposes an architectural framework for the features and services of an industrial laundry service, based on the notion of context‐awareness. Unlike the traditional application areas of context aware computing such as human computer interaction and mobile computing, the methodology used in this study will be a process oriented approach applied to the domain of laundry. One objective of the system is to manage context according to the relationships among processes (Rosemann and Receker, 2006), in this case laundry processes, instead of managing context according to the individual user or system. The context aware system will oversee the progress of the whole transaction as it moves through each process. The system is based on the features suggested by Dey and Abowd (2000) and can be summarized as such: information and services are presented to a user, a service is executed and context is linked to information for later retrieval. Therefore, another objective of the proposed context aware system is to provide services taking into account the needs of users or other entities in the system by exploiting information provided in the context. This objective can be most effectively provided by a Service Oriented Architecture based on web services augmented with context awareness. This combines the advantages of flexibility and robustness of web services and context aware systems (Gu et al., 2004). The rest of the paper is organized as follows. Section 2 includes an overview of the systems based on context‐ aware features and other Laundry Management System. In Section 3, the authors describe laundry operations from a process point of view. Section 4 presents the technical architecture and our design of a proposed laundry management system based on context‐aware service‐oriented architecture. The authors also suggest in this section some open source tools that could potentially be used in the implementation of the system. Finally, Section 5 draws some conclusions about the proposed system.
2. Literature review Context‐aware systems are highly adaptive systems that react to the ever‐changing context by adjusting their operations without needing an explicit intervention from the user. Several architectures and design principles are proposed for the implementation of context‐aware applications. One common underlying principle that governs a good context‐aware architecture is the separation of context acquisition and context use. This is mostly achieved by employing a layered approach that uses encapsulation to hide the details of lower layers from higher layers. With this layered approach, it is possible to separate the functions of business logic from user interface and data acquisition. Rehman et al. (2007) has proposed a system based on Model‐View‐ Controller paradigm while the conceptual architecture for context‐aware systems proposed by Ailisto et al. (2002) and shared by others consisted of five different layers: physical, data acquisition, inference, storage/management and application. Even though such architecture is robust enough, it must be complemented by a flexible and extensible context model for representing and storing context data so as to facilitate the processing and exchange of the widest possible spectrum of context by intra and inter applications. Therefore, choosing the right context model is paramount to the effective development and maintenance of the context‐aware application. Several context modeling approaches have been proposed and discussed in (Strang and Linnhoff‐Popien, 2004) and (Perttunen et al., 2009). Among these, ontology based models are the most expressive in terms of simplicity, flexibility, and extensibility, while being generic. Context‐aware Architectures (CA) have a wide area of application domains. There have been implementations using CA in a diverse range of other domains. The majority of these are in the mobile computing segment which involves mobile computing agents, in particular, handheld devices. Baldauf et al. (2007) and Hong et al. (2009) reviewed of context‐aware systems literature in detail. These studies pointed out many types of context‐aware applications, including the creation of smart environments such as home, hospital (Munõz et al., 2003), class room and tourism (Abowd et al., 1997). The Hong et al. (2009) study also lists context‐aware applications in the areas of information systems, decision support systems, communication systems and web service. Truong and Dustdar (2009) surveyed several systems from the web services arena and Miraoui et al. (2008) surveyed context aware architectures in pervasive computing environments. As far as the authors are aware, there are no laundry management system implementation proposals based on the principles of context‐aware architectures in the literature. The existing laundry system implementations do not address the entire process in a complete way but focus on specific aspects. Lu and Yu (2010) and Lu et al. (2010) proposed software design that uses Radio Frequency Identification (RFID) technology to track to‐be‐cleaned items
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Ufuk Celikkan and Kaan Kurtel between the laundry shop and the factory but does not account for the processes that take place within the factory itself. Tajima et al. (2011) and Van et al. (2012) proposed tracking laundry items using clothes hangers. The study by Noor et al., (2012) proposed a “smart basket” system as an alternative solution in order to optimize the management of electrical and water consumption in domestic laundry activities.
3. Laundry processes This section describes the operations of a laundry from a business processes perspective in order to reveal the fundamental business functions and services. Business processes are supported by technical operations which are carried out by the technical architectural framework based on information technology. The Laundry Management System technical architecture is presented in Section 4. The core laundry business processes typically contains four major activities and shown in Figure 1:
Collection and Transportation
Administration/Back Office operations
Scheduling
Cleaning
Figure 1: The workflow of laundry management system (authors’ work, 2013) Collection and Transportation: This sequence includes the collection of laundry to be washed, transportation to factory and returned to customer to an agreed schedule. Collection requires some attention as certain items need to be treated separately due to having different conditions (i.e. soil type). It is important that linens and bedding used in surgical operations are processed separately from other laundry at every stage. Administrative: Administrative process mostly involves managerial and administrative activities pertaining to taking orders, controlling cost, packaging, billing and other kinds of customer services. Controlling costs therefore increasing profits is the primary goal of a company’s financial affairs. Correct pricing of the laundry services, minimizing personnel and material costs is vital to maintaining a healthy financial position. An effective cost control is achieved when cooperation among the aforementioned four processes is enhanced. For example, the amount and type of detergent used in the cleaning process and delivery routes used during transportation process both directly affect the costs. Scheduling: Scheduling operations include the scheduling of collection, delivery, and cleaning. Cleaning: The cleaning process stands at the core of a laundry business; therefore, it needs a high degree of control and monitoring. An efficient cleaning process is a highly complex operation, with different rules and parameters used depending on the industry. For instance, for the health industry the World Health
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Ufuk Celikkan and Kaan Kurtel Organization strictly defines in their web site (2013) laundry disinfection rules for severe acute respiratory syndrome (SARS) since contamination by blood, body fluids, secretions and excretions are primarily responsible for its spread. Another complicating factor is the use of different commercial laundry equipment and industrial machines in this process. Activities in the cleaning process are carried out either by these sophisticated machines or by humans, or in some cases, a combination of both. The overall success of operation depends on accurate and timely functioning of the whole operation, which can be enhanced by innovative and well designed information technology services such as RFID and rule‐based workflow management.
4. Technical architecture A layered architectural model is used in the realization of the Laundry Management System. One of the key advantages of a layered architecture is that it partitions the system into functionally disjoint layers, each of which provides a set of cohesive services through a public interface. Our layered model is shown in Figure 2 and explained below. Physical layer consists of virtual and physical sensors which generate aggregate data that is more accurate and relevant than information obtained from a single source. Physical sensors capture the state of the cleaning process and report machine status in the form of raw data via some communication mechanism (PLC, IP‐based). Virtual sensors (the external data sources) use Application Programming Interfaces or web services to obtain data such as GPS position or real‐time camera stream. The next layer‐ data acquisition layer is responsible for storing application and context data, user profile and the rules in a database. The application data represent business oriented operational data. This layer retrieves context data from external sources using web services, combines data from different atomic data sources into higher level information and stores it in the database. Context data is represented in Resource Description Framework (RDF) (RDF, 2013) and processed using Jena (Apache Jena, 2013). The inference layer provides the central coordination of the processes through its workflow engine and makes deductions and inferences via its rule engine using the information stored in the database. The open source jBoss technologies, Drools (Drools, 2013) and jBoss business process management workflow engine, jBPM (JBPM, 2013) are two promising candidates in the implementation due to their availability at no cost, their programming support and editorial tools for non‐technical users. The top layer ‐ presentation layer‐ represents the user interface and the navigational elements of the system. The users interact with the system using services of this layer.
Figure 2: Context‐aware architecture for the laundry management system (authors’ work, 2013)
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4.1 Context model Based on the definition by Dey (2001), the content included in the context can vary. In the case of laundry domain, context could include information such as collection time, identification tags, the location and weight of the items, washer temperature, the type and amount of detergent used, the wash duration, and the cost. The accurate specification of the contents of the laundry domain context requires a flexible, extensible, generic and rich enough model that allows the easy definition and manipulation of context data. The authors shall follow the two‐tier taxonomy introduced by Dey et al. (2000) in our context classification. The context types will be classified as primary or secondary. The primary context types, those that are marked as being more important, are location (where), identity (who), time (when) and activity (what).The other piece of context information, i.e. secondary type, are attributes of the primary types, and therefore each secondary type can be indexed to a primary type. Table 1 provides a list of attributes that are included in context information for a washing machine and the sources of these attribute values. Ontology will be used to model contextual data of LMS. Ontology based context models possess several desired properties such as formality and extensibility (Strang and Linnhoff‐Popien, 2004), (Perttunen et al., 2009), (Gruber, 1993), (Studer et al., 1998). The formality of ontology based modeling makes it suitable for formal reasoning techniques and extensibility is of particular importance for a domain such as the Laundry Management System, because the addition of new context elements must be simple. Although designed for the semantic web, Web Ontology Language (OWL) can be used to represent information which cannot be retrieved from the web, so has been chosen to represent our context (2013). Web Ontology Language is intended to be used when information is processed by the applications rather than presented to the humans. Table 1: Laundry context data and types Primary Context Types Identity Identity
Secondary Context Type (Attributes) Type of laundry Material
Identity Activity Activity
Color Temperature pH value
Activity
Water Hardness
Location Identity
Location Number of times washed Time
Time
Description
Data source
Medical, hospitality, community Represents the type of the laundry’s material, such as fiber, cotton, and silk Color of the article. i.e. white/non‐white Water temperature Monitoring pH value that withstands the acids and caustic solutions Amount of Calcium and Magnesium cations (Ca2+ and Mg2+) Represents the location of garments Total number of times an article was washed
Manuel, Barcode, RFID Manual
The amount of time spent on the different phases of the cleaning process
Clock
Color Sensor Thermometer pH Sensor Hardness Sensor RFID & Barcode RFID
4.2 Service based context interpretation and inference A laundry management system is composed of several processes which can be categorized as information and business processes. Business processes are driven by business rules which create a set of guidelines for the business process and are expressed in some formal or informal notation. On the other hand information processes manage the information flow. Both information and business processes are driven by a workflow engine, which oversees the progress of a complete laundry transaction as it progress from one process to another. The business rules are interpreted by a rules engine which in turn guides the workflow engine. All these components exchange information using web services. The rules engine which itself a web service, uses the data obtained from context sources through web services and while the workflow engine is able to accesses services of the rules engine through a web service. The context data is represented in RDF which can easily be processed by applications. The use of web services decouples the laundry business logic from information and business processes. As business rules are loosely connected to the architecture through web services, it is possible to completely change the business rules and the rules engine without affecting the business processes. In the web service model, the rule engine acts like web service server, with the business process as the client. The business process will interact with the rules engine using solicit‐response port type. Figure 3 shows the interaction between the business process and the rule engine.
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Figure 3: Web service interaction (authors’ work, 2013) The business rule engine consumes the data and performs the computations, comparisons and controls, and finally returns a value. The advantage of using such a model is that it allows the modification of the computer program, the port and the operation calls without requiring any changes to the client‐business process. Workflow will invoke a rule on the rules engine using a web service and change the flow based on the response. When a business rule changes or an addition is needed, only the rule engine and web service needs to be modified. In addition, the workflow engine can invoke a web service to request a piece of context data such as the pH value of the water in order to choose the most appropriate path in the flow. Workflow engine orchestrates the processes of the LMS by creating tasks and dividing them into subtasks. The workflow engine then sequences, schedules routes and monitors these tasks. The data acquired from context sources asynchronously generates events which are processed by the workflow engine. The workflow engine could also trigger data collection synchronously, for example by requesting the location of a garment or pH value of the water using a web service. The workflow specifies how the available tasks are utilized in response to events. The graphical user interface interacts with the workflow engine to query the state of a process, and if necessary, to alter the flow. In order to change path in its flow, to start or terminate a task, the workflow engine relies on the rules engine, which creates a deductive connection between the business rules and the workflow engine. Figure 4 demonstrates how the workflow and rules engine act as a controller coordinating various subsystems using web services.
Figure 4: System‐wide process view of the laundry management system (authors’ work, 2013)
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5. Discussion The proposal in this paper concentrates more on the relationships and interactions among processes. Laundry management system can be partitioned into two major processes: business and information processes. The former are driven by the business rules and the latter are driven by the information technology. These are further decomposed into sub processes. Web services allow two aspects to be decoupled, first business processes using workflows from business rules, and secondly, context data providers from the rules engine. A context‐aware laundry system can monitor and alter the cleaning process using the context information and the use of service‐oriented architecture makes the integration and unification of various departments within a laundry business very straightforward. In order to illustrate the functioning and practical benefits of the system, we present a context‐aware scenario below. This scenario demonstrates how the proposed system would be beneficial to a preferred hotel customer, who wants his laundry done at the hotel. “Mr. Jones is a very special, cost conscious customer with some allergic reactions to pathogens in fabric. A five star hotel does not want to lose the business of Mr. Jones. Therefore, the hotel does everything within their capacity to fulfill the laundry requirement to his satisfaction. When the hotel picks up Mr. Jones’ laundry or when they replace the bedding and towels in his room, they ensure that the laundry process is based on strict guidelines. Moreover, they want to make sure that his laundry is delivered to him exactly on time and within the agreed cost requirements.” This scenario shows the kind of context information that must be taken into account by the Laundry Management System. The context information in the scenario is given in italics below. The system attaches an RFID tag to Mr. Jones’ laundry items to inform LMS that items in the laundry process belong to Mr. Jones, and sets the parameters for the cleaning process. The system uses a special kind of cleaning agent that requires a particular temperature range. The drying process is done using outside air instead of the dryer. When the process is finished the items are specially sealed and delivered to Mr. Jones at the exact time requested. As a special customer, he is charged a special discounted price. A context‐aware laundry system can monitor and alter the cleaning process using the context information for Mr. Jones, which, in this scenario consists of item ids (RFID tag), detergent type, temperature, drying conditions (circulating air at room temperature), time, and cost. The flexibility of the system allows other context information to be added. For instance, if Mr. Jones does not want to use bedding and towels that are washed more than three times, this requirement can easily be incorporated by adding another piece of attribute into the context, namely the number of times an item washed. Using a service‐oriented architecture based on web services, the operator can constantly and remotely monitor the process, obtain the status of items associated with Mr. Jones and intervene to the process if necessary. The proposed layered architecture is modular, extensible, and cohesive. The use of web services provide the highest degree of decoupling of system components and the agility needed in the current IT environment.
6. Conclusion This research paper is a conceptual paper that proposes a laundry management system solution based on the principles of context‐aware and service‐oriented architectures in which context acquisition is done through web services and context modeling is ontology‐based, as this is the most expressive model. The advantage of using a service‐oriented context‐aware architecture is that the integration of the Laundry Management System with the partners is seamless. The proposed system allows the convenient integration of information technology infrastructure of hotels, hospitals or other businesses using cleaning services with an industrial cleaning system. Using service‐oriented architectures to integrate and unify various departments within a laundry business is also very straightforward. The logistics department, for instance, can easily discover whether an item is ready to be shipped or the finance department can have very detailed report on the cost of the resources used to clean a particular garment. Controlling costs therefore increasing profits is the primary goal of a company’s financial affairs. Correct pricing of the laundry services, minimizing personnel and material costs is vital to maintaining a healthy financial position. As a further stage, the authors are planning to implement this infrastructure using open source software and deploy it in a real environment.
References Abowd, G.D., Atkeson, C.G., Hong, J., Long, S., Kooper, R. and Pinkerton, M. (1997) “Cyberguide: A mobile context‐aware tour guide”, Wireless Networks, Vol. 3, No. 5. pp 421‐433.
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Ufuk Celikkan and Kaan Kurtel Ailisto, H., Alahuhta, P., Haataja, V. Kylloenen, V. and Lindholm, M. (2002) “Structuring context aware applications: Five‐ layer model and example case”, Proceedings of the Workshop on Concepts and Models for Ubiquitous Computing. Goteborg, Sweden. Apache Jena, [Online], Available: http://jena.apache.org/index.html [21March 2013]. Baldauf, M., Dustdar, S. and Rosenberg, F. (2007) “A survey on context‐aware system” International Journal of Ad Hoc and Ubiquitous Computing, Vol.2, No. 4, pp 263‐277. Debevoise, T. (2007) Business Process Management with a Business Rules Approach. Surge Publishing. Dey, A.K., (2001) “Understanding and using context”, Personal Ubiquitous Computing, Vol. 5, No.1, pp 4‐7. Dey, A.K. and Abowd, G. D. (2000) “Towards a Better Understanding of Context and Context‐Awareness”, Proceedings of the Workshop on the What, Who, Where, When and How of Context‐Awareness. New York: ACM Press. Drools: JBoss Business Logic integration Platform, [Online], Available: http://www.jboss.org/drools/ [21 March 2013]. Feldkamp, D., Hinkelmann, K., Thönssen, B. (2007) “KISS – Knowledge‐Intensive Service Support: An approach for agile process management”, Advances in Rule Interchange and Applications, LNCS 4824, pp. 25‐38, Springer. Gruber, T.R. (1993) “A translation approach to portable ontology specifications” Knowledge Acquisition, Vol. 5, No. 2, pp 199‐221. Gu, T., Pung, H.K. and Zhang D.Q. (2004) “A service‐oriented middleware for building context‐aware services”, Journal of Network and Computer Applications, Vol. 28, No. 1, pp 1‐18. Hong, J.Y., Suh, E.H. and Kim, S.J. (2009) “Context‐aware systems: A literature review and classification”, Expert Systems with Applications, Vol. 36, No. 4, pp 8509‐8522. JBoss Business Process Management (BPM) Suite, [Online], Available: http://www.jboss.org/jbpm/ [21 March 2013]. Lu, Y. and Yu, H. (2010) “A Flexible Architecture for RFID Based Laundry Management Systems”, 6th International Conference on Wireless Communications Networking and Mobile Computing, pp 1‐4. Lu, Y., Zhang, W. Qin, Z. Meng, Y. and Yu, H. (2010) “DeftRFID: A lightweight and distributed RFID middleware”, Intelligent Sensors, Sensor Networks and Information Processing, Sixth International Conference, pp 181‐186. Miraoui, M., Tadj, C. and Amar, B.C. (2008) “Architectural Survey of Context‐Aware Systems in Pervasive Computing Environment”, Ubiquitous Computing and Communication Journal, Vol. 3, No. 3, pp 68‐76. Munõz, M.A., Gonzalez, V.M., Rodriguez, M. and Fa vela, J. (2003) “Supporting context‐aware collaboration in a hospital: an ethnographic informed design”, Proceedings of Workshop on Artificial Intelligence, Information Access, and Mobile Computing 9th International Workshop on Groupware, CRIWG, Grenoble, France, pp 330–334. Noor, M. Z. H., Razak, M. H. A., Saaid, M. F., Ali, M. S. A. M., and Zolkapli, M. (2012) “Design and development of ‘smart basket’ system for resource optimization”, Control and System Graduate Research Colloquium (ICSGRC), pp 338‐342. OWL, [Online], Available: http://www.w3.org/TR/owl‐features/ [21 March 2013]. Perttunen, M., Riekki, J. and Lassila, O. (2009) “Context representation and reasoning in pervasive computing: a review”, International Journal of Multimedia and Ubiquitous Engineering, Vol. 4, No.4, pp 1–28. Rehman, K., Stajano, F. and Coulouris, G. (2007) “An Architecture for interactive context‐aware applications”, Pervasive Computing, Vol.6, No.1, pp 73‐80. Resource Description Framework (RDF), [Online], Available: http://www.w3.org/TR/rdf‐primer/ [21 March 2013]. Rosemann, M. and Receker, J. (2006) “Context‐aware Process Design: Exploring Extrinsic Drivers for Process Flexibility”, 18th International Conference on Advanced Information Systems Engineering. Proceedings of Workshops and Doctoral Consortium, Namur University Press Luxembourg, pp 149‐158. Strang, T. and Linnhoff‐Popien, C. (2004) “A Context Modeling Survey”, First International Workshop on Advanced Context Modeling, Reasoning and Management at UbiComp. Studer, R., Benjamins, V.R. and Fensel, D. (1998) “Knowledge engineering: Principles and methods”, Data Knowledge Engineering, Vol. 25, No. 1‐2, pp 161‐197. Tajima, N., Tsukada, K. and Siio, I. (2011) “AwareHanger: Context‐aware hanger for detecting the status of laundry”, Pervasive 2011, San Francisco, CA, USA. Truong, H‐L., and Dustdar, S. (2009) “A survey on context‐aware web service systems”, International Journal of Web Information Systems, Vol. 5, pp 5–31. Van, N.T., Lee, S.J., Lee, C.W., Eom, K. H. and Jung, K.K. (2012) “An implementation of Laundry Management System based on RFID hanger and wireless sensor network”, Ubiquitous and Future Networks (ICUFN), 2012 Fourth International Conference, pp 490‐493. Weske, M. (2007) Business Process Management, Springer. World Health Organization (WHO) “Practical Guidelines for Infection Control in Health Care Facilities”, SEARO Regional Publication No. 41, [Online], Available: http://www.searo.who.int/LinkFiles/Publications_PracticalguidelinSEAROpub‐ 41.pdf [21 January 2013].
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Modeling Organizational Intelligence Based on Knowledge Management in the Technical and Vocational Training Organization of Tehran Hossein Chenari, Fattah Nazem and Mahmood Safari Department of Education, Roudehen Branch, Islamic Azad University, Roudehen, Iran hossein_chenari@yahoo.com safari@damavand.riau.ac.ir
Abstract: The dire necessity of organizational intelligence is undeniable with regard to the importance of organizational intelligence in the Technical and Vocational Training Organization. In the other hand the effective factor leading to the organizations’ success does not only include capital, human force and raw material, whereas, it critically depends on the organization’s potential in producing the knowledge among the staff (Tanghoo, 2008). The research purpose is to construct a structural model to assess the organizational intelligence in the Technical and Vocational Training Organization of Tehran based on knowledge management. The population comprised all the employees of the Technical and Vocational Training Organization, out of which a sample of 226 employees was randomly chosen. The research instruments were two questionnaires which were administered in the Technical and Vocational Training Organization: Albrecht (2003) organizational intelligence questionnaire which consisted of 49 items with three underlying constructs of srategic vision, shared fate, appetite for change, heart, alignment and congruence, knowledge deployment and performance pressure with Cronbach’s Alpha of 0.88, and Sallis & Jones’ (2002) knowledge management questionnaire which consisted of 42 items with ten underlying constructs of vsion and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication for the organization with Cronbach’s Alpha of 0.83. The results of path analysis using LISREL software indicated that dimensions of knowledge management had a direct effect on organizational intelligence with the indices of 0.93. The model also showed that the factor of intellectual capital, leadership and management in knowledge management had the highest direct effect on organizational intelligence. It was also concluded that the proposed model appeared to be fully workable. Keywords: Knowledge management, organizational intelligence, Technical and Vocational Training Organization
1. Introduction One of roles of present era for the management and employees in an organization is intelligence. Also, the management and employees try to apply human capital and organizational capital for developed efficiency and effectiveness in their organization. Therefore, these goals will not be available unless all of them in the organization use intellectual capital as optimum. Most chief executive officers feel that knowledge is the most critical asset of their organization. In today’s movement, towards knowledge management, organizations try to leverage their knowledge internally in the organization and externally to their customers and shareholders. They try to capitalize on their organizational intelligence to maintain in the edge (Liebowitz, 1999). As a fascinating concept and intriguing research area, “intelligence” finds strong appeal in many disciplines outside of individuals and cognitive psychology (Sternberg & Kaufman, 1998). One of the disciplines that provoked increased interest in the importance of intelligence is the management and organization development literature (Glynn, 1996; March, 1999; Stalinski, 2004). Even if we disregard the entire literature in which organizational intelligence was supposedly aggregated (Kurzman & Owens, 2002), the term is still ambiguous in the context of organizational development scholarship. This is true because there is a lack of a unified theory of intelligence in organizational settings as noted by the numerous and fragmented perspectives and ideas of researchers in the field (Glynn, 1996). Albrecht (2003) designed a modal that Includes Seven Key dimensions of organizational intelligence (OI):
Strategic Vision: strategic vision refers to the capacity to create evolve, and express the purpose of the enterprise and not to any particular vision, strategy, or mission concept in and of itself .
Shared Fate: a sense as “We're all in the same boat” creates a powerful sense of community and esprit de corps. Without a sense of shared fate, the psychological tone of the culture degenerates into a "Look out for number one" spirit.
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Appetite for Change: Some organizational cultures, usually led by their executive teams, have become so firmly set in their ways of operating, thinking, and reacting to the environment that change represents a form of psychological discomfort or even distress.
Heart: Separate from the element of shared fate, the element of heart involves the willingness to give more than the standard.
Alignment and Congruence: In the intelligent organization the system, broadly defined, all come together to enable the people to achieve the mission .
Knowledge Deployment: Knowledge deployment deals with the capacity of the culture to make use of its valuable intellectual and informational resources.
Performance Pressure: It's not enough for executives and managers to be preoccupied with the performance of the enterprise, i.e. its achievement of identified strategic objectives and tactical outcomes. In the intelligent organization, everyone owns the performance proposition, i.e. the sense of what has to be achieved and the belief in the validity of its aims (Albrecht, 2003).
Having an efficient and thriving educational organization triggering appropriate opportunity to develop and flourish students is an important issue which occupied the mind of planners and scholars (Mac Gilchrist, 2004). Notably, nowadays organizations encounter rapid and astonishing changes and their survival depends on the ability to adapt to changes. Flexibility, ability to adapt, and enjoyment of individuals and organizational ability to utilize the experiences are most important in strategies of organizations. As changes are rapidly occurring, survival and function of an organization depends on accelerating learning and developing knowledge management (Stonehouse & Pemberton, 1999). Although efficient application of the knowledge leads to formation of intelligent organizations, it rests on creative application of knowledge. Thus, educational organizations should simultaneously instruct knowledge, efficiency, and utilizing knowledge to the students to strengthen their potential talents. Organizational intelligence, therefore, is the most important ability to realize it. The necessity of organizational intelligence is undeniable with regard to the importance of organizational intelligence in the Technical and Vocational Training Organization. Hence, knowledge management takes on a pivotal role as an important resource in creating the competitive advantage. The effective factor leading to the organizations’ success does not only include capital, human force and raw material, whereas, it critically depends on the organization’s potential in producing the knowledge among the staff (Tsang ho, 2008). Organizations are bound to create an environment in which requiring, transferring and advancing the knowledge is facilitated among the staff members through enhancing the pattern of meaningful interactions (Nonaka, &Takeuchi, 1995). Sallis & Jones (2002) offer a useful knowledge management self-assessment checklist with scoring elements such as:
Vision and mission: It refers to having vision as a knowledge-based organization and sharing it with the stakeholders and the mission as the knowledge creator and translating it into practical strategies.
Strategy: It refers to developing modeled scenarios and applying them in the management.
Organizational culture: It refers to the different dimensions of culture including the creating, centralizing, sharing, and recognizing organizational culture as a key competence.
Intellectual capital: It includes recognizing the value of intellectual assets and codifying its tacit knowledge.
Learning organization: Under learning organization, organization should create continuous learning, define skills to create new knowledge, recognize EQ and its influences encourage creative thinking, and promote action learning both for individuals and teams.
Leadership and management: In leadership and management, organizations are required to have seniormanagement support, have knowledge leaders and managers with appropriate leadership styles, and develop strategies for promoting middle-managers.
Teamwork and learning communities: Under teamwork and learning communities, organization should encourage learning communities and knowledge teams, establish trust, and recognize the need for intellectual autonomy.
Sharing knowledge: It signifies that organizations ought to collect, record major organization events, and share new information, and understand competitors’ knowledge management system.
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Knowledge creation: It requires the organizations to recognize new knowledge, those known as experts, and turn it into service.
Digital sophistication for the organization: In terms of digital sophistication, organizations are to develop technologies among its employees by clear technological architecture, enhancing its knowledge, and devising virtual collaborative systems and/or communities. (p.125-129 )
Aliei and Bahrololoum (2011), in a research entitled “Analysis of Knowledge Management and Organizational Intelligence Relationships in Science and Technology Parks” show that organizational intelligence involves emotional, behavioral, and cognitive dimensions. The results suggest that it is not necessary for organizations to focus on the all dimensions, but the main concern should be based on the importance and performance of the knowledge management factors. Therefore, considering the efficiency of information systems and the senior manager’s commitment to the principles of knowledge management, achievement is provided in the short run for organizations. Competitive advantage has been shown increasingly to rely on the effective management of knowledge (Bukowitz & Petrash, 1997; Stewart, 1997). This is particularly relevant for multinational firms, which may adapt not only the organizational structure of the subsidiary to the host country, but also its knowledge management practices in expanding abroad. Indeed, Drucker et al. (1997) have identified ‘‘harnessing the intelligence and spirit of people at all levels of an organization to continually build and share knowledge’’ as a top priority for firms wishing to succeed in today’s competitive environment (Chow et al., 2000). A prevailing perspective of knowledge management is the knowledge management value-chain common to many knowledge management descriptions (Shin et al., 2001; Dalkir, 2005; Chen & Chen, 2006). The four stages of knowledge acquisition, storage/sharing, diffusion, and application, although not necessarily sequential, are required to achieve the efficiency function of knowledge management within the organization (Alavi & Leidner, 1999; Drucker, 2001). As such, the two goals of knowledge management are productivity gains through efficient decision making and problem solving, and innovation by way of bringing a new idea to market (Hollsopple & Joshi, 2000). A previous thorough literature review of the history of knowledge management evolution from 1995 to 2004 (Chen & Chen, 2006) has showed that indeed the knowledge management process is similar to that of a value-chain. According to Chen and Chen (2006), ‘‘the basic underlying assumption is that knowledge may be viewed from a unified perspective as it circulates in the organization creating knowledge assets and influences the performance of the organization’’ (p. 18). Organizational intelligence is a new and important topic in organizational behavior and development scholarship. However, researchers should also investigate organizational intelligence empirically. The multidimensional and multifaceted nature of organizational intelligence can be tested by operationalizing information-processing capabilities, emotional capabilities and adaptive capabilities (Keskin et al, 2006). Mendolson et al, (2007), in their study, showed that organizational intelligence has a strong impact on the financial performance of organizations. Organizations with high organizational intelligence have gained more profit and progress. And also, they have captured external information, and ensured that the right decisions are made in these organizations. Mendolson (1999) mentions that “Organizational intelligence has a strong effect on a company’s performance.” The study of Sattari Ghahfarrokhi (2008) is consistent with the present research, demonstrating that there are positive and significant relationship between knowledge management and organizational intelligence. The results of the research demonstrate how the types of customer knowledge available to an organization can be categorized by the perceived quality and the perceived accessibility of the knowledge. These findings contribute to the field of knowledge management by moving towards a theory of how customer knowledge is used by an organization, and how internal and external factors affect this utilization. Furthermore, this study raises awareness of the importance of a KMS in managing customer knowledge, including key aspects of its design and implementation (Paquette, 2008).
2. Purpose of the study The duty of the Technical and Vocational Training Organization of Tehran is to provide the technical workers with necessary training they need in order to work in industrial factories . Because these training centers cover many areas in the whole country, the results of the present study can yield fruitful outcomes.
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Hossein Chenari, Fattah Nazem and Mahmood Safari The purpose of the research is to construct a structural model to assess organizational intelligence in the Technical and Vocational Training Organization of Tehran based on the knowledge management. Regarding the purpose of the research, the researcher tries to answer the following questions:
3. Research questions
What is the structural model of organizational intelligence based on the knowledge management in the Technical and Vocational Training Organization?
Which variable has the highest effectiveness on organizational intelligence?
How is organizational intelligence knowledge management effective on promoting organizational intelligence?
How much is the goodness of fit in this study?
4. Method of the study The research methods of the study are: library research to access the theoretical framework and the related literature; and the survey method to collect, classify, describe, and analyze the data. The population under investigation in this study consist of official staff working in 12 administrative districts of the Technical and Vocational Training Organization in Tehran. Regarding the minimum research sample required for the staff’s group, 226 individuals were randomly selected, using simple random sampling method, and the same number of questionnaires were distributed among them. The research instruments were as follows: organizational intelligence which was designed and developed based on the theory of Albrecht (2003). The organizational intelligence questionnaire consisted of 49 items with seven underlying constructs of strategic vsion, shared fate, appetite for change, heart, alignment and congruence, knowledge deployment and performance pressure with Cronbach’s Alpha of 0.88, and Sallis & Jones (2002) knowledge management questionnaire which consisted of 42 items with ten underlying constructs of vision and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication for the organization with Cronbach’s Alpha of 0.83.The results of the study were obtained through applying path analysis using LISREL software (See Fig. 1 for more details).
5. Findings of the study The data collected from the administration of the instruments were analyzed. These data included the different indexes of central tendency, variability and the distribution of staff’s groups, the staff members’ scores obtained from knowledge management and organizational intelligence questionnaires and their related components. The distribution of the staff members’ scores in the given variables had tendency toward normality. As shown in Figure 1, the Lambda rate of external latent variable of knowledge management components was 0.38 for leadership and management, 0.23 for teamwork, 0.12 for sharing knowledge, 0.23 for knowledge creation, 0.29 for digital sophistication, 0.11 for vision and mission, and 0.01 for strategy, 0.08 for organizational culture, 0.39 for intellectual capital, and 0.17 for learning organization whose accumulation form the knowledge management variable with the effectiveness rate of 0.93. It means that 93% of the variation in the dependant variable of intellectual capital, Leadership and management is explained by a collection of these indexes. The variable of collective action indicates the highest amount of internal consistency in the external latent variable. The Lambda rate of internal latent variable of organizational intelligence components was 0.35 for strategic vision, 0.04 for shared fate, 0.27 for appetite for change, 0.41 for heart, 0.22 for alignment and congruence, 0.54 for knowledge deployment , and - 0.03 for Performance Pressure. Their accumulation form the organizational intelligence variable. The validity of variable indicates the highest amount of internal consistency in the internal latent variable. Since the model’s goodness of fit index is 0.92, it can be stated that it has an acceptable fit. The calculated index indicates the direct effect of knowledge management components on employees' organizational intelligence. Moreover, the model shows that the highest direct effect is related to intellectual capital, and Leadership and management. Table1 presents the indexes related to the model’s fit:
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Figure 1: Path analysis model for components of knowledge management and organizational intelligence Table 1: Model’s fit indexes Index Lewis-Tucker (Non-normed fit index) Bentler-Bonett’s (Normed fit index) Hoelter Root Mean Square Error (RMSEA) GFI
Rate 0.92 0.91 0.73 0.042 0.92
Interpretation High fit (more than 0.90) High fit (more than 0.90) High fit (more than 0.70) High fit (equal to or less than 0.05) High fit (more than 0.90)
The goodness of five fit indexes presented model’s fit and empirical data. Therefore, desirability adaptation is provided for the designed model and empirical data and can approve it as an appropriate model for the organizational intelligence. On the whole, it can be proposed that this proposed model has full fit since LewisTucker’s non-normed fit index (0.92) and Bentler-Bonett’s normed fit index (0.91) were both higher than 0.90. Besides, Hoelter’s index (0.73) was higher than 0.70 and shows high fit. The root mean square error (RMSE) (0.042) was lower than 0.05 and goodness of fit (GFI )( 0.92) was higher than 0.90 and indicate the new model’s fit.
6. Discussion and conclusions The results of path analysis method revealed that dimensions of knowledge management have positive impact on organizational intelligence. The findings of the present study, furthermore, indicated the influential role of knowledge management on organizational intelligence. The results of this study are in line with the studies done by (Ordones de Pablos, 2002; Keskin et al., 2006; Choi & Jong, 2010; Yaghoubi et al., 2010). Aliei & Bahrololoum (2011) show that knowledge management involves social, emotional, behavioral, and cognitive dimensions which invest on the two factors contributing to the efficiency of information systems, and the senior manager’s commitment can earn the most achievements in the short run for organizations. An important work of organizations should be to invest on intelligent personnel, so that the organizational operations become more efficient and effective than before. In general, it is inferred that intelligence is an undeniable factor for organization's intellectual capital, because the first condition to each organization to be successful is having intelligence (Yaghoubi et al., 2010). A common thrend in this body of work is that knowledge management processes are positively related to performance. These results have been shown to hold for many performance variables including long term measures such as firm market value (Choi & Jong,
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Hossein Chenari, Fattah Nazem and Mahmood Safari 2010), and other non-financial indicators of performance such as new product launch success and increasing rate of sales (Ordones de Pablos, 2002). As it was mentioned earlier, the unique outcomes of the present study indicate the direct effect of knowledge management components on organizational intelligence in the Technical and Vocational Training Organization of Tehran . Moreover, the model shows that the highest direct effect is related to intellectual capital, and Leadership and management. Moreover, through offering, guaranteeing and expanding the most efficient and superior services to Technical and Vocational Training Organization located in Tehran, and also identifying and fulfilling their needs, their satisfaction can be fulfilled and their loyalty can be engendered. Furthermore, considering the fact that intellectual capital exerts the most principal effect on the organizational intelligence, it can be suggested that in the Technical and Vocational Training Organization:
Intellectual capitals should be appreciated and used appropriately by organizations;
Organizations should seek tacit knowledge (individual’s aggregate behaviors, experiences, aspirations, values, and feelings);
Existing challenges to the practice of knowledge management should be resolved by people in charge;
Leaders of organizations had better be knowledge leaders who choose appropriate leadership styles to apply, and distribute knowledge;
Some employees of the Technical and Vocational Training Organization should be trained to develop knowledge creation process.
In conclusion, the newly-proposed results in this research that show the direct effect of knowledge management components on organizational intelligence, can be effectively employed to enhance the organizational intelligence in similar organizations. It can be done through strengthening the knowledge management indexes, that is, vsion and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication.
Acknowledgements The researchers want to extend a heart-felt thanks to the members of Technical and Vocational Training Organization for their commitment and efficient research assistance. They are truly appreciated as their partnership was absolutely vital to carry out this research.
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An Introduction to STRIKE: STRuctured Interpretation of the Knowledge Environment Sally Eaves and John Walton Faculty of Arts, Computing, Engineering, and Sciences (ACES), Sheffield Hallam University, UK research@sallyeaves.co.uk J.R.Walton@shu.ac.uk Abstract: Knowledge forms a critical part of the income generation of the system and the complex environment in which actors participate in the creation of knowledge assets merits robust, eclectic consideration. STRIKE ‐ STRuctured Interpretation of the Knowledge Environment affords an unobtrusive and systematic framework to observe, record, evaluate and articulate concrete and abstract elements of a setting, across internal and external dimensions. Inter‐ relationships between actor and environment are preserved. STRIKE is supported by underlying techniques to enrich data and enhance the authenticity of its representation. Adoption of photography and videography tools provides illustrative and interpretive benefits and facilitates researcher reflexivity. This structured approach to data analysis and evaluation mitigates criticisms of methodological rigour in observational research and affords standardisation potential, germane for application in a verification or longitudinal capacity. Advancing exploratory validation studies, the method is employed to evaluate the knowledge environments of two enterprises in the UK creative sector. These occupy a critical role in fostering entrepreneurial innovation alongside participant self‐efficacy. Access Space in Sheffield and the Bristol Hackspace are committed to open software, open knowledge and open participation; sharing peer learning, creativity and socio‐technical aims to address broadly similar community needs. Drawing on Wittgenstein’s Picture Theory of Meaning, the knowledge management perspective is abstracted from the STRIKE assessment. It is argued that the tiered analytical approach which considers a breadth of dimensions enhances representation and interpretation of the knowledge environment and presents a diagnostic and prescriptive capability to actualise change. The paper concludes by evaluating framework effectiveness, findings application and future direction. Keywords: knowledge environment; knowledge management; observational framework; workplace design; innovation
1. Introduction: Knowledge management in praxis Knowledge management is diverse in nature, difficult to demarcate and subject to multiple attempts at definition. It is broadly considered as formal and informal exploratory, evaluative and synthesising knowledge interventions (Wiig 1993), undertaken at the level of individual and collective intellectual assets. Approaches centre on harnessing the organisational knowledge base to support optimal performance through innovation, reutilisation and learning (Du Plessis 2007). Drawing on Freitas, Morais and Lopes’ (2012) literature analysis presented at ECKM 2012, knowledge management practices cover nine core areas ranging from innovation management to lessons‐learned, supported by technological tools. Mechanisms to facilitate these practices are equally broad, spanning fifteen dimensions from learning‐by‐doing to mentoring. Additionally, workplace design is increasingly recognised as a “strategic instrument” (Bakke 2007, p6) that can support knowledge management, particularly collaborative norms and creativity (Walter 2012). Monitoring and evaluating a diversity of knowledge management components presents a critical challenge (Hulsebosch, Turpin and Wagenaar 2009). An array of macro and micro techniques to appraise value are available (Perkmann 2002) but can be difficult to align with organisational realities, especially in highly original settings. The rapidly evolving and cross‐disciplinary creative sector is representative of this problem. It lies incongruent with the information‐processing or object‐centred perspective associated with quantitative measurement approaches and further, would benefit from new qualitative means to elucidate and appraise its socio‐technical and place‐centric dimensions. The development of an innovative, flexible and lightweight tool to surface, monitor and evaluate the knowledge environment from a holistic perspective, illuminating the learning and sharing behaviours therein, is therefore considered timely and germane.
1.1 The creative sector The definition of a creative industry is nebulous but in this study it reflects the intersection of manufacturing and digital technologies with The Arts, underpinned by a socially meaningful purpose. The growth of open‐ access workshops, hacklabs, hackerspaces and makerspaces embody this approach, benefiting from the pool of knowledge afforded by an open source production model. Although terms are often used interchangeably,
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Sally Eaves and John Walton different groups afford their own specialisation, ideology and historical roots (Maxigas 2012). All provide opportunities for idea incubation and contagion, technical and social engagement, collaboration and skill support. This presents an underexplored context within knowledge management research despite increasing recognition between the provision of such environments and advances in entrepreneurial local and global innovation (Mota 2013). Certain groups afford social action outcomes: nurturing individual empowerment, self‐efficacy and the development of intellectual and social capital through practical learning which can foster wider population benefits (Walton 2010). Reflecting on The Medici Effect, this fusion of cross‐disciplinary skills and shared purpose has the potent to create an inter‐sectional space for “remarkable, surprising and groundbreaking ideas” (Johansson 2004, p6) to flourish.
2. Explication of STRIKE technique Observation can be employed to describe or represent a setting and is frequently unstructured in nature. STROBE – STRuctured OBservation of the Business Environment (Kendall and Kendall 1984) was conceived from film theory to provide a reliability and validity assessed framework to aid system analysts unobtrusively observe, classify and interpret the physical business environment of decision‐makers and their interaction with it. This can advance understanding of human information requirements and the alignment between technology solutions and end‐user needs. The authors opine a capacity and underlying need to develop the system and business requirement analysis focus of STROBE to one affording a knowledge perspective, capable of application across multiple domains. A level of granularity is required to provide insight into increasingly complex and dynamic post‐industrial contexts and the environment in which organisational actors participate in the creation of knowledge assets (Boisot 1998). This can illuminate the nuances of cultural norms which form the core driving dynamics for knowledge transfer to be supported (Ipe 2003). STRIKE affords originality in terms of scope, breadth and flexibility of design, and the qualitative data acquisition and evaluation methods incorporated. The framework systematically evaluates dimensions across the internal and external knowledge environment and supports identification of any dissonance between them. Internal observations comprise Design/Layout; Aesthetics: Placement and Decoration of Workspaces; Knowledge Sources and Branding whilst external evaluation considers both Physical and Digital Presentation. This approach is congruent with the multiple, influential roles afforded by workspace design (Elsbach and Bechky 2007) and the need to enhance understanding of its relationship with creativity (Walter 2012). Place‐ centric creative enterprises therefore present a novel, rich and emergent context for STRIKE evaluation.
2.1 Technique validation, development and theoretical lens Drawing on the Design Science Research Method (Heje, Baskerville and Venable 2012), STRIKE has been subject to descriptive ex‐ante evaluation by iteration in a naturalistic setting. Face validity analysis was undertaken by Dr Gordon Rugg from Keele University, a knowledge elicitation expert. Successful ex‐post evaluation within two verification studies in hi‐technology private sector environments (Eaves 2013; Eaves and Walton 2013) has demonstrated a particular capacity to allow the semantic layer to become more transparent. This study explores and develops tool utilisation in a different contextual setting and is proposed to surface novel, interpretative insight into knowledge transfer, its management and any boundaries that hinder optimisation. STRIKE aligns with the increasingly acknowledged yet underexplored perspective of sociomateriality (Leonardi, Nardi and Kallinikos 2012). This recognises organisations, individual actors and technologies as continually linked and re‐linked with meanings, properties and respective boundaries entangled, temporal and subject to constant reproduction (Orlikowski and Scott 2008). It is also congruent with the material‐semiotic perspective of Actor Network Theory (Latour 2005).
2.2 Supporting techniques Photography and videography were utilised to support researcher observation. Ethical concerns and image confidentiality were duly considered.
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Sally Eaves and John Walton Photography offers both an illustrative capability that reflects its “quasi‐representational” nature (Warren 2005, p861) and an interpretive capacity to develop a multi‐layered narrative, providing a highly accessible frame of reference for reflection. It is employed to enrich, complement and augment observation and support researcher neutrality. Video technology enables a multidimensional perspective on context and can facilitate focus on, and analysis of, actor behaviours (Coiro 2009) and their interactions with the knowledge environment. Although usage and analysis of videography lacks the comprehensive methodological guidance and case history of more traditional methods, its introduction within STRIKE is based on the purposeful intent to bring something extra, building on the non‐digital methods employed within the validation studies. A time‐lapse technique was used to record workshop/exhibition sessions and create stills.
3. Research methodology A dual organisation case‐study approach was adopted with an inductive and qualitative perspective. The STRIKE method was enacted through researcher walk‐through observation sessions, supplemented by photography and videography.
3.1 Access Space Access Space (2013) in Sheffield was established in 2000 by CEO James Wallbank and remains the UK’s longest running open access media lab. In contrast to most hackerspaces, it operates under registered charity status with the aim to advance public education in IT and visual arts alongside supporting unemployment relief: a tripartite focus on The Arts, Education and Urban Regeneration. It therefore bridges the creative and third sectors. There are no preconditions or entry requirements ‐ anyone can take part. This is particularly important in communities such as those served by the enterprise, where many individuals have traditionally felt “digitally excluded” (Walton 2010, p11). In 2012, Access Space was recognised as one of 50 “New Radicals”: organisations making Britain a better place to live and work (Nesta 2012). Despite these achievements, funding from Arts Council England was withdrawn in 2011 presenting a profound threat to its financial sustainability. Within the physical space, there are two principal areas supported by a core of 6 staff. The media lab provides free internet access and facilities to develop expertise in open source software, web development and a range of audio and visual digital skills. The adjacent but separate Refab Lab was opened in 2009 and is based on the FabLab concept developed at MIT. This space houses fabrication equipment such as a 3D printer and laser cutter, supports materials recycling, and is used by artists‐in‐residence to develop exhibition projects.
3.2 Bristol Hackspace The second creative context is Bristol Hackspace (2013), founded in November 2009 as a social enterprise with the goal to “open up technology to anybody who takes an interest in it”. It is similarly committed to the principals of open source and open knowledge. The hackspace is based in the Windmill Hill ward which experiences deprivation levels above average for the city. It is run entirely by volunteers at BV Studios, an artist‐led shared project and art space arranged into units within a warehouse of 30,000 square‐feet. Activities are practical and hands‐on, ranging from projects in computing, robotics, electronics and metalwork to craft based creative skills. Open evenings are held each Thursday with a Hackkids session for under‐16’s taking place once per month. Strong links are maintained with local technology groups and across the wider hackerspace network. A minimum monthly subscription of £10 is requested from the 39 full members, with a small income obtained through public workshops, exhibitions and occasional externally funded projects. Membership levels are increasing with discussions ongoing regarding enterprise future direction and its accommodation within the physical space.
4. STRIKE findings and integrated discussion The environmental elements across each case setting are now fully elucidated. Images of workshop events are stills created from video recordings.
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4.1 STRIKE assessment of Access Space Core dimensions from the STRIKE evaluation are presented in Table 2, supported by photography to enrich observation, support transparency and enhance audience capacity to actualise place. Table 2: STRIKE evaluation of Access Space Environmental Element
Description and Supporting Photography
Design/Layout
Open‐plan main media lab with circular seating to enable socialisation. There is a separate Refab Space with secured access which houses heavy equipment alongside materials for recycling. A dedicated area created and used principally by one staff member is located above its floor plate.
Aesthetics; Placement and Decoration of Workspaces
Dissonance is observed between cluttered areas and carpet in need of replacement in the open main area and the highly organised, tidy Refab Space which affords more staff and artist‐in‐ residence privacy.
Further contrast identified between the personal, creative output of participants (not staff) displayed in the media space and strong evidence of Industrial Art and personalisation attributed primarily to one staff member found in Refab. Across both zones, work is evolving, practical and amorphous in orientation.
Knowledge Sources
Hands‐on practical peer learning leading to self‐experimentation. Literature embracing community interests alongside technical themes is available to take away. One revelatory example of explicit knowledge is observed, a sign which emphasises the tacit, problem‐solving emphasis of the space: 'please help me with my problem but do not solve it for me'.
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Description and Supporting Photography
Branding
Distinct branding for Access Space and the Refab Space. Local community focus exemplified by the urban fabric project exhibited. This uses rapid prototyping equipment to promote dialogue on the “new” Sheffield.
Physical External Presentation
Digital External Presentation
Accessible city centre location within a IT/Creative Industries district. Physical space lacks visibility and aesthetic evidence of the creativity within.
Facebook, Twitter and Vimeo (video) conduits preferred to Flickr (photo). Distinction between Access Space (media lab focus) and the Refab space. No significant evidence of online discussions regarding decision‐making.
STRIKE evaluation is not indicative of deep knowledge management dysfunction but both strengths and opportunities for enhancement are inferred. Reflecting on Gensler’s (2008) modes of working, the media lab is particularly well suited to the elements of collaborate, learn and socialise, whilst the Refab area allows more opportunities for individual focus. Access Space has a strong creative identity but this is not reflected in its physical external presentation which is understated – you could easily walk past. The digital presentation is more representative, supported by dual branding and a social network presence but still does not provide full visibility of the rich diversity observed. Recording of day‐to‐day behaviour is revelatory of the actual breadth of knowledge activities in praxis which correspond to the pragmatic theory of truth. These demonstrate practical relevance and usefulness to an individual or group, with a strong problem‐solving emphasis. This is verified and legitimised by prominent display of knowledge artefacts which allow idea expression (Walter 2012) and support a positive psychology. This aligns with symbolic functionality (Elsbach and Bechky 2007). These artefacts demonstrate the individuality of participant works: their interests, creativity and priorities, congruent with the do‐ocracy ethos described by Chen (2009, p55). It also illuminates a lack of personalised décor or visibility in respect to staff projects. One exception is identified with reference to the Industrial Art prominent in the Refab area which reflects the craftsmanship and discipline skills of an individual staff member critical in its construction. It is noted that in combination with the additional privacy and increased order observed in this separate zone, this physical arrangement has the potential to develop into dissonance impacting knowledge boundaries, even within a collegiate‐style setting. Any design that enables significant separation between actors, and allows differences in the features afforded (Walter 2012) can experience such problems (Elsbach and Bechky 2007).
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Sally Eaves and John Walton Further, it is argued that the knowledge artefacts observed afford a lens into organisational identity, the potential future direction of Access Space and its evolving superordinate goal: aspects that staff had found difficult to elucidate during individual reviews (Walton 2013). By demonstrating the material structure of ideas (Bieler 2001), STRIKE affords a means to demonstrate underlying interests and points of intersection expressed in artefacts. This can support the understanding of intersubjective meaning in action; it is revelatory of the knowledge that is most valued as a collective. This perspective is supported by the work of Gramsci (1971), who asserts that a level of philosophy is implicit in all forms of practical action. In terms of knowledge management evaluation, the hands‐on transfer, experiential development and dialogic norms identified in the space are difficult to express within SMART objectives: outcomes are not typically amenable to standard measurement approaches. Although the learning processes and knowledge sharing behaviours are clearly valued by beneficiaries including the committed staff, these are not easy to measure and are difficult to plan against. This problem maps against the knowledge exploration‐exploitation dilemma and is a critical issue for creative enterprises with a charitable status, where articulating knowledge value is core to securing funding and sustainability.
4.2 STRIKE assessment within Bristol Hackspace The core elements emergent from the STRIKE evaluation are presented in Table 3. Table 3: STRIKE evaluation of Bristol Hackspace Environmental Element Design/Layout
Aesthetics; Placement and Decoration of Workspaces
Knowledge Sources
Description
Supporting Photography
Clearly identifiable work zones for different activities. Connecting “corridors” allow flow between areas. Informal seating supports socialisation.
Whitewashed walls, clean lines, tidy and organised equipment. Provision of individual storage space. Limited evidence of personalised décor.
Emphasis on practical demonstration and self‐learning by experimentation. External flow into space encouraged by attracting speakers. The touchscreen table is a focal point for web access and dialogic discussion.
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Sally Eaves and John Walton Environmental Element Branding
Description
Supporting Photography
Supported by consistent use of social media (Twitter and Flickr in particular) and attendance at Maker‐Faire events. Publicity material promotes activities, affording a distinctive logo and providing a QR website code to create an integrated approach.
Physical External Presentation
Digital External Presentation
External aesthetics are consistent with internal observations. Accessible location near transport links, clearly signposted online.
Narrative emphasis on the association of hacking with creativity and building. Website design including wiki and blog are congruent in design and branding. A GoogleGroup account demonstrates strong collegiate style decision‐making.
On evaluating and comparing the STRIKE data sets, the Bristol Hackspace displays greater symbiosis between the knowledge environment as a synchronous physical locale and as an asynchronous digital web presence: one which also affords increasingly synchronous communication opportunities through Web 2.0 tools that enable immediacy of response. This can positively impact the intensity of experience perceived by members (Mitchell 2003). Social media channels are used extensively and illuminate the projects and knowledge activities undertaken. Within the physical space, there is less demonstration of artefacts or personalisation in comparison to the exhibition of participant creativity within Access Space, reflecting differentiating nuances in group goals. The physical environment is particularly suited to the dimensions of collaborate, learn and socialise Gensler (2008). There are some opportunities for focussed individual working but privacy to afford concentration can be limited. The setting design presents a calm, consistent and pleasing aesthetic which can support a positive sensory experience for participants (Elsbach and Bechky 2007). This is particularly utile to provide an appropriate setting for the under‐16’s supervised Hackkids workshops. Should future resources permit, attention to aesthetics within Access Space’s media lab would similarly enable development of a knowledge environment that supports a younger audience. Thematic analysis of the Bristol Hackspace GoogleGroup (2013) is revelatory of knowledge environment tensions congruent with the lifecycle development of an expanding enterprise. There is a high level of virtual organisation of ideas which was equally reflected within the zoned areas and order observed in the physical space. Underlying discussion concerns how to balance membership growth, collaborations and space management, alongside securing funding and long‐term sustainability. In common with Access Space, identity is a persistent theme but here this is more explicitly acknowledged with members articulating their respective
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Sally Eaves and John Walton and sometimes divergent interests, and engaged in dialogic discussion regarding how best to accommodate them. Supported by a strong capacity to act, this collective approach may aid the dissipation of potential knowledge boundaries, particularly pragmatic forms (Carlile 2004).
5. STRIKE evaluation STRIKE affords a systematic, unobtrusive framework which supports consistency of approach alongside flexibility of application and high communicability of findings. The tool demonstrates capability to perform in a variety of circumstances, moving from the hi‐technology private sector organisations considered within validation studies, to the highly original creative sector enterprises appraised in this research. An authentic, panoptic lens to connect to the actor lifeworld is made available, providing structured and in situ capture, expression and evaluation of their knowledge environment. The approach conforms to Wittgenstein’s (2001) picture theory of meaning affording a pictorial, representational and logical level which aids interpretation and articulation. The method elucidates the importance of human interaction across the physical, technological and social environment to create and evolve meaning and value. The socio‐technical and internal‐external dimensions benefit holistic appreciation of knowledge practices and mechanisms, affording identification of presentational dissonance. It also enhances understanding of emergent and planned space design in creative settings, developing empirical support for the conceptual workspace creativity framework developed by Walter (2012). It is opined that the multidimensional orientation of STRIKE provides a novel means to enable the verbalisation of tacit knowledge transfer practices (Seidler‐de Alwis and Hartmann 2008) which is difficult to achieve through traditional interactive methods. It presents an unobtrusive language (Wittgenstein 2001) to express meaning and surface underlying issues, as exemplified by the materiality of ideas achieved through their physical demonstration and evaluation. This may be described as the reification from tacit to explicit knowledge which affords benefits for reviews and processes of organisational translation (Walton 2013) ‐ aspects that impact both settings in distinct means, aligned to their respective lifecycle stages and goals. STRIKE supports articulation of the value of the knowledge activities undertaken; this is pertinent to Access Space where it can aid demonstration of the “Reach and engagement” funding criteria explicated by Arts Council England (2011, p3). Its diagnostic‐prescriptive capability is also considered germane for utilisation by practitioners across a range of settings. As an example, implementation of a high‐level knowledge management initiative would equally benefit from an approach that can illuminate cultural nuances such as resistance versus acceptance behaviours and additionally, enable a form of transactional analysis of actor perspectives. Further, as the method provides a lens into a context at a particular juncture and across specific dimensions, it affords standardisation benefits. It can be employed in a verification or longitudinal capacity to validate or revisit research findings, or equally to evaluate the success of a knowledge management intervention over time. STRIKE would also be suitable for application in mixed methods research to support data triangulation. Enactment of this framework is enhanced by visual tools which enable a multiplicity of perspectives and reduce reliance on direct researcher observation. Whilst a single image can present “very particular information”, a cumulative group can begin to afford “signifiers” revelatory of the cultural context (Prosser 2012, p1). Videography proved effective for researcher reflection and to support the creation of additional stills but its full dimensionality is inherently difficult to articulate within a textual piece. It does however offer additional potent for presenting findings directly: as a familiar, rich, engaging and distinctive visual medium, video can convey a deep sense of “direct experience with the primary phenomena” (Pea 1999, p353). This supports the call to incorporate digital methods into the mainstream (NCRM 2013). In future studies, the application of social media evaluation tools such as Google Analytics will be considered to extend assessment of the digital external environment.
6. Knowledge environment conclusions Access Space and Bristol Hackspace are exemplar enterprises which support, and are catalysts for, rapid technological innovation. From different perspectives, they are also considered drivers in a critical new social‐ economic model in which social economic change is regarded the embodiment of innovation: supporting the development of intellectual and social capital and affording the potential for sustainable entrepreneurship
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Sally Eaves and John Walton (Mota 2013). This is facilitated by an open knowledge production model which co‐exists with more traditional forms, alongside an enabling, almost cosmopolitical (Latour 2004) knowledge environment that bridges socio‐ technical dimensions to support curiosity, self‐efficacy, idea incubation and artefact production. In congruence with the nature of the sector, knowledge management practices may be described as emergent. It is argued that the diagnostic‐prescriptive tool STRIKE focuses attention to, and evaluation of, knowledge in action to benefit the overarching mechanisms that support them, including workspace design. Technological developments and production model changes have indeed removed many of the barriers of time, space and restricted knowledge that have previously inhibited wider levels of collaboration and innovation. This study elucidates that despite this evolution, the physical environment and actor interaction with it plays a critical role in supporting the practices and mechanisms of knowledge management. It is important that this is integrated with its digital presence. Specifically, the Refab environment within Access Space is demonstrative of the relationship between technology and architecture (Silver and McLean 2008): it affords a physical design solution that is creative as well as functional, fit for purpose but adaptable to future needs, elegant but also practical. In the Bristol Hackspace, the organised activity zones and easy flow between them is notably supportive of task organisation alongside exposure to multidisciplinary techniques and creative collaboration (Walter 2012). The effectiveness of Access Space and the Bristol Hackspace may be attributed to the development of pragmatic, eclectic knowledge communities which balance individual and group goals, utilising dynamic, integrative and “participatory technology‐development techniques” (Grenier 1998, p.vii). Place, tools, research and development, social structure and innovation are therefore increasingly merged and aligned. Drawing on the MOA framework (Gan, Kosonen and Blomqvist 2012), these enterprises exemplify a tripartite of staff/attendee motivation and developed abilities, alongside the opportunity afforded by place: providing both cognitive and physical space to those who work, volunteer or participate within them.
References Access Space (2013). Access Space: About Us [online]. Last accessed 20 March 2013 at URL: http://www.access‐ space.org/doku.php?id=about:ethos Arts Council England (2011). Information Sheet – Digital activity. Arts Council England. Bakke, J. (2007). A Nordic guide to workplace design. Nordic Innovation Centre. Bieler, A. (2001). Questioning Cognitivism and Constructivism in IR Theory: Reflections on the Material Structure of Ideas. Politics, 21 (2), pp. 93–100. Boisot, M. (1998). Knowledge Assets – Securing Competitive Advantage in the Information Economy. Oxford University Press. Bristol Hackspace (2013). Who we are and what we do [online]. Last accessed 20 March 2013 at URL: http://bristol.hackspace.org.uk/ Bristol Hackspace Googlegroup (2013). Bristol Hackspace Members [online]. Last accessed 20 March 2013 at URL: https://groups.google.com/forum/?fromgroups#!forum/bristolhackspace Carlile, P. (2004). Transferring, Translating and Transforming: an Integrative Framework for Managing Knowledge across Boundaries. Organization Science, 15, pp. 555‐568. Chen, K. (2009). Enabling creative chaos : the organization behind the burning man event. University of Chicago Press. Coiro, J. (2009). Rethinking reading assessment in a digital age: How is reading comprehension different and where do we turn now? Educational Leadership, 66 (6), pp. 59‐63. Du Plessis, M. (2007). Knowledge management: what makes complex implementations successful? Journal of Knowledge Management, 11 (2), pp. 91‐101. Eaves, S. (2013). Mixed Methods Research: Creating Fusion from the QUAL and QUAN Data Mosaic. Paper presented at the 12th European Conference on Research Methodology for Business and Management Studies (ECRM), University of Minho, Guimaraes, Portugal, 4‐5 July 2013. Eaves, S. And Walton, J. (2013). A Multi‐Layered Approach to Surfacing and Analysing Organisational Narratives: Increasing Representational Authenticity. Paper presented at the 12th European Conference on Research Methodology for Business and Management Studies (ECRM), University of Minho, Guimaraes, Portugal, 4‐5 July 2013. Elsbach, K. And Bechky, B. (2007). It’s More than a Desk: Working Smarter Through Leveraged Office Design. California Management Review, 49 (2), pp. 80‐101. Freitas, R., Morais, P. And Lopes, F. (2012). Knowledge Management Practices: A Framework Proposal. Paper presented at the 13th European Conference on Knowledge Management, Universidad Politécnica de Cartagena, Spain, 6‐7 September 2012.
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Sally Eaves and John Walton Gan, C., Kosonen, M. And Blomqvist, K. (2012). Knowledge Sharing in Crowdsourcing – it is More Than Motivation. Paper presented at the 13th European Conference on Knowledge Management, Universidad Politécnica de Cartagena, Spain, 6‐7 September 2012. Gensler (2008). 2008 Workplace Survey United States. [online]. Last accessed 20 March 2013 at URL: www.gensler.com Gramsci, A. (1971). Selections from the Prison Notebooks. London: Lawrence and Wishart. Grenier, L. (1998). Working With Indigenous Knowledge ‐ A Guide for Researchers. IDRC. Hulsebosch, J., Turpin, M. And Wagenaar, S. (2009). Monitoring and evaluating knowledge management strategies. IKM Emergent. Ipe, M. (2003). Knowledge Sharing in Organizations: A Conceptual Framework. Human Resource Development Review, 2 (4), pp. 337‐359. Johansson, F. (2004). The Medici Effect – Breakthrough Insights at the Intersection of Ideas, Concepts and Cultures. Harvard Business School Press. Kendall, K. And Kendall, J. (1984). Structured Observation of the Decision Making Environment: A Reliability and Validity Assessment. Decision Sciences, 15 (1), pp. 107‐118. Latour, B. (2004). Politics of Nature: How to Bring the Sciences into Democracy. Harvard University Press. Latour, B. (2005). Reassembling the Social ‐ An Introduction to Actor‐Network‐Theory. Oxford University Press. Leonardi, P., Nardi, B. And Kallinikos, J. (2012). Materiality and Organizing: Social Interaction in a Technological World. Oxford University Press. Maxigas (2012). Hacklabs and hackerspaces – tracing two genealogies. Journal of Peer Production. [online] Last accessed 20 March 2013 at URL: http://peerproduction.net Mitchell, W. (2003). Places for Learning: New Functions and New Forms. Presented as part of the MIT World ‐‐ special events and lectures series. MIT Media Lab, Cambridge, Massachusetts, July 3rd 2003. Mota, C. (2013). What we can learn from hackerspaces. Presentation at TEDxStockholm [online]. Last accessed 20 March 2013 at URL: http://tedxtalks.ted.com/video/What‐we‐can‐learn‐from‐hackersp NCRM (2013). Digital methods as mainstream methodologies [online]. Last accessed 20 March 2013 at URL: http://www.ncrm.ac.uk/research/NMI/2012/digitalmethods.php Orlikowski, W. And Scott, S. (2008). Sociomateriality: challenging the separation of technology, work and organization. The Academy of Management Annals, 2 (1), pp. 433‐474. Pea, R. (1999). New Media Communications Forums for Improving Education Research and Practice. In: E. LAGEMANN And L. Shulman (Eds.), Issues In Education Research: Problems And Possibilities, Jossey‐Bass Education Series, pp. 336– 370. Perkmann, M. (2002). Measuring Knowledge Value? Evaluating the Impact of Knowledge Projects. KIN brief. Prosser, J. (2012). Image‐based Research: A Sourcebook for Qualitative Researchers. Routledge. Seidler‐De Alwis, R. And Hartmann, E. (2008). The use of tacit knowledge within innovative companies: knowledge management in innovative enterprises. Journal of Knowledge Management, 12 (1), pp. 133‐147. Silver, P. And Mclean, W. (2008). Introduction to Architectural Technology. London: Laurence King. Walter, C. (2012). A Framework for Creating Creative Workspaces. Paper presented at the 13th European Conference on Knowledge Management, Universidad Politécnica de Cartagena, Spain, 6‐7 September 2012. Walton, J. (2010). Education and Skill Development through the Reconfiguration of Discarded Hardware: Turning Base Metal into intellectual Capital. In: International Conference on Challenges to Inclusive Growth in the Emerging Economies, Ahmedabad, India, 15‐17 December 2010. Indian Institute of Management. Walton, J. (2013). The Obligatory Passage Point: Abstracting The Meaning In Tacit Knowledge. Paper accepted for presentation at the 14th European Conference on Knowledge Management, Kaunas University of Technology, Kaunas, Lithuania, 5‐6 September 2013. Warren, S. (2005). Photography and Voice in Critical Qualitative Management Research. Accounting, Auditing & Accountability Journal, 18 (6), pp. 861‐882. Wiig, K. (1993). Knowledge Management Foundations Vol 1, 2 and 3. Schema Press. nd Wittgenstein, L. (2001). Tractatus Logico‐Philosophicus. 2 ed., Routledge.
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Ipe Revisited: Validating a Multidimensional Model of Individual Knowledge Sharing Influences Sally Eaves Faculty of Arts, Computing, Engineering, and Sciences (ACES), Sheffield Hallam University, UK research@sallyeaves.co.uk Abstract: This paper elucidates the spectra of influences that impact the intra‐organisational tacit and explicit knowledge sharing behaviour of the middle line. It addresses a deficiency in research that affords an eclectic approach across both knowledge types simultaneously and at an individual level of analysis. Ipe (2003) develops a conceptual model of knowledge sharing between individuals, opining that behaviour is influenced by Motivation to Share, the Nature of Knowledge, Opportunity to Share and most significantly, Culture. A critical analysis is presented to surface limitations and concludes the framework to be overly reductionist. This provides the catalyst for revision: a pluralistic consideration of the elements which impact volition and capacity to share. Adopting a multi‐disciplinary perspective, significant augmentations to the original factors are proposed and the Nature of the Individual and Organisational Velocity are introduced as key impacting elements on knowledge sharing, the latter in a moderating capacity. The Nature of the Individual embraces the influence of human characteristics such as personality traits and demographics. Organisation Velocity is an original conceptualisation of the continual, episodic and ambiguous change which reflects the reality of many post‐industrial settings. It is expressed as the tension between centrifugal and centripetal forces acting on the five other influence factors. Exploratory validation of the resultant Multidimensional Model of Individual Knowledge Sharing Influences is achieved through a robust, empirical study elucidating the sharing behaviour of middle management in four leading UK Communication Sector operators. All six factors are shown to impact individual knowledge sharing practice, with Organisational Velocity acting in a moderating and primarily centrifugal capacity on Motivation to Share, Opportunities to Share and the Nature of the Individual. It is demonstrated that a panoptic, interdisciplinary perspective combining human, social, technological and contextual factors must be considered to understand behaviour and optimise knowledge management interventions. A particular element may not be evaluated in isolation. Keywords: knowledge sharing, individual knowledge sharing influences model, nature of the individual, organisational velocity, middle managers
1. Introduction: Individual knowledge sharing behaviours and challenges Knowledge exists across multiple organisational levels and may be transferred in different forms and directions (Ipe 2003) but is typically controlled at the level of the individual (Gupta and Govindarajan 2000). Knowledge sharing is considered the critical, determining factor in knowledge management success (Boisot and Cox 1999) with intra‐organisational exchange emergent from individual motivations (Bock et al. 2005) and consequent actions and interactions (Foss 2007). The capacity to leverage knowledge assets is therefore dependent on human capital: the individuals, who create, use and critically, can elect to share what they know. Middle management affords a vital influence combining boundary spanning position (Lin 2007) with the strategic sense‐making capacity to perform analytic, intuitive and pragmatic roles to create, integrate and share knowledge (Janczak 2004). Exchange remains a complex and often unnatural process with diverse challenges identified across individual, organisational and technological dimensions. These include dynamic contexts, free‐riding, conflicting values, lack of time or tools, and socio‐cultural issues (Riege 2005). Transferability problems also relate to its very nature with tacit knowledge difficult to express and share due to its sticky, experiential, intuitive and sense‐ making properties (Chon 2011). There remains a lack of holistic understanding of the factors influencing sharing behaviour with many studies wholly conceptual (Ipe 2003), focussed on one knowledge type (Lin 2007) or on a limited number of influences (Bartol and Srivastava 2002). Drawing on Lincoln and Guba’s (1985, p226) definition of the characteristics of a research problem, this is ‘‘a state of affairs that begs for additional understanding”.
2. Ipe’s theoretical drivers of knowledge sharing behaviour Ipe (2003) opines that individual knowledge sharing is influenced by Motivation to Share, the Nature of Knowledge, Opportunity to Share and Culture. Although soundly based on a significant literature review, it is argued that the relative importance and interaction of these factors is not adequately explored, nor the underlying constructs fully substantiated. The resultant conceptual model does not consider a breadth of
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Sally Eaves influencing factors and is perceived to be overly reductionist and insufficient to reflect the range of potential contributory issues and a holistic treatment of individuals. Specifically, Ipe assumes that individuals are homogenous. The author asserts that this view negates the potential for differences in response to context and stimuli to be appropriately addressed. It is argued that individuals are not homogeneous in respect to their motivations (McGregor and Cutcher‐Gershenfeld 2006) or emotions (Pfister and Böhm (2008) but a dominant force may be determinative.
2.1 A multidimensional model of individual knowledge sharing influences Reflecting on the critical analysis of Ipe’s framework, an expansive, multidisciplinary literature review was undertaken drawing on the evaluation guidance of Boote and Beile (2005). Studies were selected the basis of foci (outcomes, methodological approach, underlying theory); contribution to goals (issue identification, criticism, integration/synthesis); and coverage (multi‐disciplinary, emergent nature, authority). The approach may be described as a narrative but incorporating systematic review practices. Development was supported by the mixed methods case study findings of primary research (Eaves 2013), alongside peer and expert‐based discussions until a saturation point was achieved. Explication of all factors and constructs identified for the new model is now provided. 2.1.1 Opportunities to share factor In order to share knowledge, opportunities must be available for organisational actors to do so. These may be formal or informal in nature and span individual, social, organisational and technological dimensions. The constructs aligned to this factor are elucidated in Table 1. Table 1: Opportunities to share constructs Constructs Knowledge Sharing Tools/Techniques Knowledge Management Team Knowledge Management Strategy (Individual/Organisational) Social Network Structure and Hierarchy Perceived Behavioural Control Managerial Role HRM Practices Time ICT
Primary Reference Bartholomew (2005) Bartholomew (2005) Wei, Choy and Yew (2009) Chow and Chan (2008) Wei, Choy and Yew (2009) Ajzen (2002) Refaiy and Labib (2009) Lepak and Snell (2002) Kankanhalli, Tan and Wei (2005) Teerajetgul, Chareonngam and Wethyavivorn (2009)
2.1.2 Motivation to share factor Motivation facilitates knowledge sharing behaviour through the complex processes of socialization, externalization and/or combination. It comprises internal, intrinsic aspects that impel individual action alongside external aspects which may be action inducing. Bock et al. (2005) stress the importance of improving understanding of individual‐level motivations. Aligned constructs are presented in Table 2. Table 2: Motivation to share constructs Construct (Intrinsic Motivators) Intention to Share Emotion Eagerness to Share Image Sense of Self‐Worth Commitment Power Knowledge Ownership (Individual/Department/Organisation) Construct (Extrinsic Motivators) Willingness to Share
Primary Reference Bock et al. (2005) Van den Hooff, Schouten and Simonovksi (2011) De Vries, Van den Hooff and De Ridder (2006) Kankanhalli, Tan and Wei (2005) Bock et al. (2005) De Vries, Van den Hooff and De Ridder (2006) Kankanhalli, Tan and Wei (2005) Constant, Kiesler and Sproull (1994)
De Vries, Van den Hooff and De Ridder (2006)
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Sally Eaves Construct (Intrinsic Motivators) Sharer‐Receiver Relationship Trust Distributive Justice Procedural Justice Pay Satisfaction
Primary Reference Lichtenstein and Hunter (2005) Teerajetgul, Chareonngam and Wethyavivorn (2009) Reychav and Weisberg (2009) Moorman (1991)
Sweeney and McFarlin (2005)
2.1.3 Nature of knowledge factor This moves beyond the consideration of a tacit/explicit distinction to reflect knowledge type based on an operational, procedural, process or product perspective. Task characteristics are explored via the dimensions of equivocality, uniqueness and interdependence. Knowledge auditing is incorporated as its use can facilitate understanding of how well internal activities are meeting organisational goals, whilst identifying potential knowledge stores. Aligned constructs are detailed in Table 3. Table 3: Nature of knowledge constructs Construct Knowledge Type Task Equivocality
Primary Reference Huysman and de Wit (2010) Van Den Hooff and Huysman (2009)
Task Uniqueness Task Interdependence Knowledge Auditing
Lepak and Snell (2002) Jarvenpaa and Staples (2001) Bartholomew (2005)
2.1.4 Culture factor Ipe (2003) presents culture as the primary factor in knowledge sharing behaviour, influencing all others. Every actor possesses personal values, beliefs and experiences which influence their perceptions and actions. These combine with the norms, practices, values and history which intimate organisational culture, creating a powerful dynamic. Culture is a distinct factor in this model. 2.1.5 Nature of the individual factor This original factor considers the direct impact of specific personality traits and demography on individual knowledge sharing behaviour, areas which are underexplored. These characteristics are typically either static or evolve over an extended period of time. It is argued therefore that they should be considered as distinct from the more contextually influenced and variable aspects aligned with (intrinsic) Motivation to Share. Constructs associated with this factor are elucidated in Table 4. Table 4: Nature of the individual constructs Construct Allocentric Personality Ideocentric Personality Gender Function Education Level Certification Type Role Experience Organisation Tenure Sectoral Tenure
Primary Reference Matzler et al. (2008) Matzler et al. (2008) Harrison and Mason (2007) Riege (2005) Keyes (2008) Eaves (2013) Bakker et al. (2006) Ojha (2005) Eaves (2013)
2.1.6 Organisational velocity This potential moderating influence advances the environmental velocity and knowledge intensity model of Jarzabkowski and Wilson (2006). It is opined that velocity can also be an organisational characteristic as within an industry similar size market players are far from homogeneous in their internal environments. The following definition is offered:
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Sally Eaves “Accelerated rates of discontinuous change: complex, dynamic, multi‐dimensional and multi‐ faceted in nature, these can puncture the organisational equilibrium and are considered continually episodic”. Adopting a pragmatic perspective, this original conceptualisation builds on elements of existent theories of change, specifically advancing Weick and Quinn’s (1999) work on two distinct types. Continuous change is described as "constant, evolving, cumulative" (p366) whilst episodic change is “infrequent, discontinuous, and intentional" (p365). It is argued that this polarity, although considered more representative than the static, linear and rational orientation of authors such as Lewin (1951), still does not reflect the reality of increasingly uncertain environments. In such cases, the tempo of change may almost be described as continually episodic. It is constant yet not cumulative, with strategic direction ambiguous and moving; it is discontinuous in terms of type and scale but not in frequency, suggesting that effective adaptation is not attained (Eaves 2013). Synthesising the factor review, Figure 1 introduces the resultant conceptual framework.
Figure 1: Conceptual multidimensional model of individual knowledge sharing influences
3. Methodology 3.1 Research setting The high‐technology UK communications sector is continually evolving and knowledge intensive with diverse challenges including complex consumer behaviours, strong competition and converging data architecture. Four leading operators by market share are considered ‐ one of which (Firm A), has been established to be representative of high Organisational Velocity (Eaves 2013). This affords a rich opportunity for individual knowledge sharing practice to be compared against the grouping of the other three operators which demonstrate relatively stable conditions.
3.2 Model validation strategy A quantitative survey was developed based on the extensive literature review and the findings of a mixed‐ methods case study which facilitated nuanced understanding within a specific setting (Eaves 2013). This method enabled model testing across leading organisations in the same sector to provide an exploratory assessment and comparison of how the factors and aligned constructs apply. Additional case or ethnographic research could be pursued at a later stage dependant on findings. Construct measurement utilised or augmented existing scales where appropriate, selected on the basis of scope, relevance and demonstration of dimensionality, reliability and validity. The dependent variables of tacit and explicit knowledge sharing were measured across questions employed or adapted from the established behaviour scales of Yi (2009) and Reychav and Weisberg (2009). Independent variables were aligned across the
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Sally Eaves five core influence factors in the model as previously detailed. A five point Likert scale was adopted throughout for attitudinal measurement. Dr Gordon Rugg from Keele University, a knowledge elicitation expert, conducted content validity analysis on construct design and survey wording, with focus directed at reducing self‐reporting bias. A pre‐test was performed to evaluate specification, framing, ordering, usability and phrasing to reduce ambiguity and the potential of non‐response. Purposeful sampling was adopted to identify middle manager respondents (N=78) with research undertaken in Q3 2012 via web‐based survey distribution.
4. Findings and integrated discussion The data set comprised a majority of males (N=60) aged 50‐59 (N=30) and with sectoral experience of 15+ years (N=48), aligning with the employment profile of this industry in the UK. Reliability analyses were conducted in order to determine internal consistency reliability, achieving acceptable Cronbach Alpha coefficients above .70 for all scales. A synopsis of correlation results is provided alongside full presentation of regression findings for the four organisations as one group.
4.1 Correlation and regression analysis: Demographics Pearson or Spearman's rho correlations were performed as appropriate to data type. Two backward stepwise linear regression analyses were conducted as detailed in Tables 5 and 6. Predictors having a probability level above .15 were removed. Results are highlighted in respect to having probability levels lower than .05 (95%+ confidence), lower than .01 (99%+), and lower than .001 (99.9%+). Table 5: Regression Analysis on Tacit Knowledge: Demographics Scale B Std. Error t Education Level ‐.088 .095 ‐.92 Function .889*** .191 4.65 Certifications Held ‐.131* .049 ‐2.70 Sectoral Tenure .063 .062 1.01 Organisation Tenure ‐.494*** .068 ‐7.23 KM Team Presence 1.122*** .225 4.99 Knowledge Auditing ‐.212 .165 ‐1.29 K Type: Operational .263 .212 1.24 K Type: Procedural .621** .198 3.13 K Type: Process .207 .214 .97 K Type: Product .430* .177 2.43 Constant 4.048*** .301 13.45 Notes: *p<.05, **p<.01, ***p<.001; N = 47; F(12, 34) = 10.20, p<.0001; R2 = .7826, Adj R2 = .7058.
Based on the predictors included, 70.58% of the variance in tacit sharing is explained. Function, Knowledge Management Team Presence and Knowledge Type (Procedural, Product) are positively significant, with number of Certifications Held and Organisation Tenure negatively significant. Table 6: Regression analysis on explicit knowledge: demographics Scale B Std. Error t Gender (Female) ‐.487* 189 ‐2.57 Function .232 .206 1.13 Role Experience .073 .100 .73 Sectoral Tenure ‐.054 .082 ‐.66 Organisation Tenure ‐.230** .082 ‐2.81 Knowledge Auditing .326** .120 2.72 K Type: Operational ‐.788** .233 ‐3.38 K Type: Procedural ‐.016 .267 ‐.06 K Type: Process ‐.483 .256 ‐1.89 K Type: Product ‐.318 .226 ‐1.41 Constant 3.843*** .364 10.55 Notes: *p<.05, **p<.01, ***p<.001; N = 61; F(11, 49) = 4.58, p<.001; R2 = .5067, Adj R2 = .3960.
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Sally Eaves The model collectively explains 39.60% of the variation in explicit knowledge with only Knowledge Auditing found positively significant. Gender (Female), Knowledge Type (Operational) and congruent with tacit findings, extended Organisation Tenure afford a negative, significant association.
4.2 Correlation and regression analysis: Scales Pearson correlations revealed a large number of scales demonstrated a strong positive or negative relationship with tacit and/or explicit knowledge sharing behaviour. A negative correlation identified between the Time (Opportunities to Share) and Power (Motivation to Share) scales and both types of knowledge sharing was particularly significant. Based on question design, the inference that time availability is negatively associated with sharing necessitates additional insight. Table 7 presents the results of backward stepwise regression analysis. This indicates that 77.02% of the variation in tacit knowledge is explained on the basis of the predictors included. Table 7: Scales regression analysis on tacit knowledge Scale B Std. Error t r2 Ideocentric Personality ‐.160 .057 ‐2.83** .022 Allocentric Personality ‐.419 .130 ‐3.23** .247 Eagerness to Share .136 .066 2.05* .268 Sharer‐Receiver Relationship .190 .059 3.20** .475 Time ‐.161 .051 ‐3.18** .296 Structure and Hierarchy ‐.091 .054 ‐1.67 .170 Power ‐.128 .053 ‐2.40* .108 Intention to Share ‐.271 .074 ‐3.65** .258 Emotion .077 .052 1.48 .320 Perceived Behavioural Control .121 .057 2.13* .452 Social Network .145 .056 2.59* .257 Task Eqivocality .184 .062 2.97** .372 Task Uniqueness .093 .041 2.25* .062 Distributive Justice .101 .050 2.02* .154 Ownership: Department .071 .036 1.99 .027 Ownership: Organisation ‐.082 .049 ‐1.65 .052 Ownership: Individual ‐.075 .048 ‐1.54 .001 Commitment .128 .054 2.35* .233 Constant 6.613 .560 11.81*** 2 2 Notes: *p<.05, **p<.01, ***p<.001; N = 72; F(18, 53) = 14.22, p<.001; R = .8285, Adj R = .7702.
A positive and significant association was found between tacit knowledge sharing behaviour and the following scales: Eagerness to Share, Sharer‐Receiver Relationship, Perceived Behavioural Control, Social Network, Task Eqivocality, Task Uniqueness, Distributive Justice and Commitment. A negative significant relationship was found with regard to the scales for: Ideocentric Personality, Allocentric Personality, Time, Power and Intention to Share. Table 8 summarises explicit knowledge findings, indicating 65.23% of the variation is explained. Significant and positive associations with explicit knowledge were found for the following scales: Eagerness to Share, Knowledge Ownership (Department), Sharer‐Receiver Relationship, Structure and Hierarchy, Task Uniqueness, Pay Satisfaction and Culture. Additionally, significant negative associations were identified with regard to: Knowledge Ownership (Individual), Sense of Self‐Worth, KM Strategy (Organisation), KM Strategy (Individual), Social Network, Procedural Justice and Image. All factors are significantly involved in sharing practice, justifying the multidimensional approach. With respect to correlation, where a significant relationship is identified, this is primarily positive and impacts tacit and explicit knowledge simultaneously. This is congruent with the dynamically‐linked emphasis opined by Polanyi (1966) and the mutual facilitation discussed by Cook and Brown (1999). Only Sectoral Tenure has a significant
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Sally Eaves relationship with explicit knowledge in isolation. At regression, more negative relationships are identified and there is greater differentiation on the significance and direction of relationships based on knowledge type. This justifies the decision to split the knowledge sharing dependent variable by a tacit/explicit distinction. Results such as the negative impact of Time (availability), Allocentric Personality and Intention to Share on tacit sharing require further exploration. Table 8: Scales regression analysis on explicit knowledge Scale B Std. Error t r2 Knowledge Tools Used ‐.086 .059 ‐1.47 .004 Eagerness to Share .262 .114 2.30* .049 Ownership: Individual ‐.171 .068 ‐2.53* .006 Ownership: Department .148 .057 2.61* .007 Sharer‐Receiver Relationship .271 .083 3.27** .222 Structure and Hierarchy .650 .098 6.60*** .218 Task Uniqueness .255 .073 3.51** Willingness to Share .183 .100 1.82 .065 Sense of Self‐Worth ‐.608 .130 ‐4.67*** .108 KM Strategy: Organisation ‐.298 .094 ‐3.16** .016 KM Strategy: Individual ‐.307 .108 ‐2.86** .016 Social Network ‐.197 .087 ‐2.28* .042 Pay Satisfaction .410 .070 5.85*** .162 Procedural Justice ‐.216 .077 ‐2.82** .007 Image ‐.218 .090 ‐2.42* .032 Culture .289 .118 2.45* .178 Constant 5.058 .510 9.92*** Notes: *p<.05, **p<.01, ***p<.001; N = 72; F(16, 55) = 9.32, p<.001; R2 = .7306, Adj R2 = .6523.
5. Assessing the impact of organisational velocity With origins in physics, centrifugal or centripetal forces can also be applied to conceptual behaviours to represent an effect (LaLiberte 2009). Organisational Velocity as a centrifugal force moderates the significance of a construct with the outcome of decreasing sharing behaviour, moving away from the knowledge sharing core inter‐sectional point as illustrated in Figure 1. By contrast, Organisational Velocity as a centripetal force moderates the significance of a construct increasing knowledge sharing behaviour, pulling towards the centre of the model. To determine impact, data for Firm A with its established high Organisational Velocity context was removed, analyses repeated and compared. From a correlation perspective, Motivation to Share has a significant relationship with Organisational Velocity in terms of the Power construct which affects tacit and explicit knowledge sharing as a centrifugal force. A significant relationship is also observed within Opportunities to Share, impacting the Time construct for both knowledge types centrifugally. The same factor is influenced with the Social Network construct for tacit knowledge sharing only and as a centripetal force. At regression, the Nature of Knowledge and Culture reveal no significant relationship. Constructs within Motivation to Share and Opportunities to Share are primarily impacted centrifugally, alongside the centripetal affect of Knowledge Ownership: Department (Motivation to Share) on explicit knowledge and Social Network influence on tacit knowledge (Opportunities to Share). The Nature of the Individual is only impacted centrifugally. High Organisational Velocity affords a greater range of impact by factor for tacit knowledge sharing but a greater number of constructs are moderated for explicit sharing. The centrifugal affect is notably strong for Allocentric Personality, Time and Intention to Share. Synthesising overall findings, the conceptual framework is revisited in Figure 2. These findings surface issues of knowledge ownership and personal versus organisational knowledge management strategies. It is inferred that in uncertain and dynamic circumstances, dimensions which would be expected to benefit knowledge sharing practice are militated or indeed, reversed. It is opined that actor focus orientates towards knowledge protection rather than its transfer. Aligning with the “accelerated growth” of personal knowledge management (Cheong 2011, iii) and increasing middle line influence (Janczak 2004),
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Sally Eaves opportunities such as time availability or the benefits of social network membership may be utilised for individual rather than organisational gain.
Figure 2: Revised multidimensional model of individual knowledge sharing influences
6. Conclusions and benefits of study The Multidimensional Model of Individual Knowledge Sharing Influences advances Ipe’s (2003) framework by affording breadth and cross‐disciplinary coverage. A plethora of constructs related to Motivation to Share, the Nature of Knowledge, Opportunity to Share, Culture and Nature of the Individual are significantly associated with sharing behaviour across all operators. The model progresses from conceptual explication to exploratory empirical assessment with the variance explained by the regression models notably strong, particularly for tacit knowledge. Differences in practice are identified based on knowledge type, supporting the tacit and explicit distinction utilised. Consideration of the impact of context is afforded through development and exploratory validation of the original conceptualisation of Organisational Velocity. Differences in sharing norms were observed in the high velocity context of Firm A as opposed to the other operators, with reduced sharing identified through constructs within the Motivation to Share, Opportunities to Share and the Nature of the Individual factors. This demonstrates its moderating capability, primarily as a centrifugal force. The study findings affirm its justification: knowledge sharing is too complex a process to be explained by one or a few factors in isolation or by a specific, narrow focus on tacit or explicit knowledge. Further, continual episodic change, central to the definition of Organisational Velocity, is interpreted to exert a notable impact at the individual level with expansive consequences for intra‐organisational knowledge sharing. This increased understanding of the driving and restricting influences affecting individual sharing behaviour can support provision of enabling conditions. It can also benefit the design and facilitation of knowledge management and strategic change management interventions.
7. Limitations and future direction This study captures the individual influences impacting knowledge sharing at a particular point of time. Repeating the research process at staged intervals would provide an opportunity to develop longitudinal enquiry, fully examining the orientation and strength of causal relationships and changes in Organisational Velocity over time. Research could then be developed to operationalise the direction and magnitude of Organisational Velocity changes as vectors. Further, it would be utile to explore the impact of this dimension in contexts of varying levels of knowledge intensity and to examine Functional and Role Velocity as potential sub‐ components. Case study and ethnography could be employed to support this process. The exploratory findings
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Sally Eaves from this work therefore provide a catalyst for the direction of future research and the management of intense organisational conditions in praxis.
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Simulation of Space Operation ‐ A Study on Learning in Control Rooms Anandasivakumar Ekambaram1, Brit‐Eli Danielsen2, Liz Helena Froes Coelho2 and Trine Marie Stene2 1 SINTEF, Trondheim, Norway 2 NTNU Samfunnsforskning AS/CIRiS, Trondheim, Norway siva@sintef.no brit‐eli.danielsen@ciris.no Liz.coelho@ciris.no Trine.stene@ciris.no Abstract: Simulation is one of the ways to promote learning in organizations. Learning constitutes several aspects, and one such aspect is reflection. This paper looks at the role of reflection in and around the simulation process. In other words, this paper looks at the role of reflection and learning in simulation. This paper is based on a study that is a part of a research project called the N‐USOC project. The Norwegian User Support and Operations Centre (N‐USOC) is one of nine European control centres for European Space Agency's (ESA's) payload and science operations on‐board the International Space Station (ISS). These USOCs (User Support and Operations Centres) are located in Belgium, Denmark, France, Italy, Germany, Netherlands, Norway, Spain and Switzerland. In order to work on console the operator has to go through a certification process. Simulation is applied as an important part of the training, when the new employees are to be certified. Experienced employees also participate in simulation sessions in order to prepare themselves for a specific experiment. ESA and NASA arrange the simulation sessions. One simulation is studied, where the major participants of the simulation‐session are: (1) N‐USOC: User Support and Operations Centre in Norway (2) MUSC: This is an USOC in Germany (3) COL‐CC: Columbus Control Centre (Col‐CC) is ESA's control centre that has responsibility for the European module Columbus on ISS (4) POIC: Payload Operations Integration Centre (POIC) is NASAs control centre responsible for payload operation on ISS. This paper uses qualitative and quantitative methods to study the simulation sessions with the focus on the topics of reflection and learning. Reflection ‐ when it is considered in connection with a professional action that an organizational member participates ‐ can be viewed as reflection‐on‐action and reflection‐in‐action. It is interesting and important to look at these two processes with respect to learning through simulation, because these two processes would lead to understand more on how participants of simulation make sense of the learning process, and how they learn and create knowledge. This understanding is useful in order to make possible improvement in the simulation sessions in the future. Keywords: learning, simulation, space operation, reflection, sense making
1. Introduction Learning is considered as a means for organisations to obtain sustainable competitive advantage. In this regard, it is relevant to mention learning related theories, such as learning organizations (Senge, 1990) and resource‐based theories (Prahalad & Hamel, 1990). Learning can manifest in various forms, for example, creating new knowledge and sharing existing good practices. Learning can happen in individual, group and organizational levels (Crossan et al., 1999). Different kinds of mechanisms are used to promote and facilitate learning in organizations. In this paper, we shall look at simulation as a learning mechanism: How a group of people, some of them are geographically scattered and located in different control rooms, learn space operations through simulation. This learning process constitutes several aspects. We shall look at this learning process primarily from the stand point of reflection. The purpose is to study the participant’s reflection and learning with respect to a simulation session. In other words, we study the role of reflection and learning in a simulated learning situation. This paper has the following structure:
The context: Contextual information connected to the study on which this paper is based.
Theoretical framework
Research methods
Results and discussion
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Concluding remarks
2. The context 2.1 Space operations The International Space Station (ISS) is a habitable space station in low Earth orbit (between 330 and 435 km above the Earth surface). The station has been continuously occupied by humans since November 2000. The ISS programme is a joint project among five participating space agencies: the American National Aeronautics and Space Administration (NASA), the Russian Federal Space Agency (Roscosmos), the Japan Aerospace Exploration Agency (JAXA), the European Space Agency (ESA), and the Canadian Space Agency (CSA). The ownership and use of the space station is established by intergovernmental treaties and agreements. The ISS serves as a unique microgravity and space environment research laboratory in which crew members conduct experiments in biology, human biology, physics, astronomy, meteorology and other fields. The station is also suited for the testing of spacecraft systems and equipment required for missions to the Moon and Mars. ESA’s laboratory on‐board the ISS is a module called Columbus. ESA has chosen a decentralized Ground Segment for its payload and science operations on‐board the ISS, by the use of User Support and Operations Centres (USOCs). Under the overall management of ESA, the European User Support and Operations Centres (USOCs) act as the link between the scientific user communities and ESA's Columbus Control Centre (Col‐CC) in Oberpfaffenhofen, Germany, NASA's Payload Operations Integration Center (POIC) in Huntsville, Alabama, and the Russian Mission Control Centre in Moscow. These USOCs are located in Belgium, Denmark, France, Italy, Germany, Netherlands, Norway, Spain and Switzerland. The Norwegian User Support and Operations Centre (N‐USOC) is one of these nine European control centres. The mission of N‐USOC is to provide qualified support to the ISS microgravity research activities in general. Specifically, N‐USOC is responsible for two payloads in the Columbus module; the European Modular Cultivation System (EMCS) and the Vessel ID System (VIS). During operations N‐USOC personnel is on console to monitor and control the payloads and associated crew operations 24/7. The operations require close cooperation with other control centres, as well as engineering support and science teams. In order to have the necessary qualifications, the console personnel have to go through specialized training and certification (Danielsen & Stene, 2013).
2.2 Simulations in space operations Simulation is an important part of the training and certification process of console operators that monitor and control equipment on‐board the ISS. The simulations are “live”, which means the actual players use genuine systems in a real environment (Classification of simulations as it is used by the American Department of Defence Modelling and Simulation Coordination Office (M&S CO)). For N‐USOC operators, “live” simulations imply that simulation sessions are performed in the N‐USOC control centre, using the same tools and interacting with control centres internationally just as is done for real‐time operations. In this environment the trainees will spend time learning valuable lessons in a "safe" virtual environment yet living a lifelike experience. In addition to the mandatory training provided in the N‐USOC training program, the trainees are responsible for their own preparation before the simulations. After the simulation there will be a debrief and an evaluation of the trainees performance is given. Evaluation gives important feedback for the trainee to improve performance, and is also the basis for the formal certification.
2.3 A specific simulation of an experiment to be executed on‐board the International Space Station (ISS) The simulation being focused in this study is a Joint Multi‐Segment Training (JMST). The JMSTs are defined as simulations under the responsibility of NASA, where in addition to the NASA Payload Operation and
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Anandasivakumar Ekambaram et al. Integration Center (POIC) all other relevant payload control centres and training facilities are involved. JMSTs are high‐fidelity, flight‐specific simulations across various station segments to practice communications and coordination among the different centres, sometimes including the Mission Control Center in Houston (MCC‐ H) and crew (or surrogate). The simulation was held on February 21 2013, and in addition to POIC, ESA and JAXA control centres participated. For this study we focused on the participants from the control centers involved in the future execution of the ESA experiment Gravi2. The Gravi2 is a biology experiment that will use several facilities on the ISS, and therefore will need the interaction of several centres responsible for the different facilities. Figure 1 shows the control centres participating in the simulation. In addition to the crew, the following centres were involved in Gravi2 operations during this JMST: NASA POIC (Payload Operation and Integration Center), ESA Col‐CC (Columbus Control Centre), N‐USOC and MUSC (Microgravity User Support Centre). N‐USOC is the overall responsible for the Gravi2 operations, being responsible for the science, operations planning and one of the facilities involved. The N‐USOC control centre are manned with two operators during the experiment execution: one is responsible for the EMCS facility (EMCS Ops working towards POIC) and the other is responsible for the science, planning and all operations outside the EMCS facility (N‐USOC Ops working towards Col‐CC). Before the actual simulation session, a chart with the responsibility sharing between the teams was distributed to all centres involved to make sure they were all on the same page.
Figure 1: Gravi2 Joint Multi‐Segment Training operations interface. The boxes represent different ground operators. The black boxes represent the operators from the NASA POIC. The white boxes represent the operators from the ESA Col‐CC. The light grey boxes represent the operators from the USOCs involved (N‐USOC and MUSC). The astronaut assigned to this operation is represented by the grey box on the top. The communication between the centres is outlined by the arrows
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Anandasivakumar Ekambaram et al. The trainees participating from N‐USOC were certified console personnel. The goal for the simulation session was to prepare and train with all centres involved in the Gravi2 operations as well as generic training for the operators. The preparation for the simulation started with classroom lessons about the Gravi2 science and operations. The N‐USOC participants went through the timeline with the specific activities being simulated. In addition, the following topics were covered: anomaly reports, lessons learned from past operations, and “What‐If” scenarios for Gravi2. Just after the simulation, debrief with all the participants were held by the NASA simulation director. The participants got feedback about their performance and the major issues were discussed. The N‐USOC training manager also performed an internal debrief the day after the simulation, where the focus was on the N‐USOC performance, challenges and improvements.
3. Theoretical framework Theories related to learning in organizations have cognitive and behavioural dimensions (Fiol & Lyles, 1985). When it comes to looking at learning in simulation or in simulation related mechanisms, such as serious games, the focus has been primarily on individual learning: How the individual's cognitive framework changes in order to carry out new pattern of behaviour that corresponds to the expected effect of the learning process. Though the learning has both cognitive and behavioural aspects attached to it, we shall consider mainly the cognitive aspect of learning. In this regard, it is important to look at the concept of reflection. Boud et al. (1996) suggest that reflective skills are needed in order to turn an experience into learning. When reflection is considered in connection with a professional action that an organizational member participates, then it can be viewed as reflection‐on‐action and reflection‐in‐action (Schön, 1998). Reflection‐on‐action is a process in which the individual reflects on his or her past experience or on a future act deliberately or unintentionally. Reflection‐in‐action is a process in which the individual reflects on what he or she is experiencing while he or she is engaging in the activity. It is interesting and important to look at these two processes (reflection‐on‐action and reflection‐in‐action) with respect to learning through simulation – How do the participants of simulation make sense of the learning process? Argyris and Schön discuss about learning as understanding and eliminating the gap between the expected result and the actual result of an action (Argyris & Schön, 1996). When an unexpected result of an action occurs, it will create surprise for the person who has taken that action. In a learning situation, this surprise tends to create reflection on what has happened with respect to the expectation. This is a way of making sense of the experience. Hence, the person thinks retrospectively and finds cues to make sense of his / her experience. This sense‐making can lead to actions that can eliminate the gap between the expected result and the actual result. Weick (1995, page 45) mentions that in order to understand sense‐making, one has to understand how people cope with interruptions. He says: "The reality of flow becomes most apparent when that flow is interrupted. An interruption to a flow typically induces an emotional response, which then paves the way for emotion to influence sensemaking. It is precisely because ongoing flows are subject to interruption that sensemaking is infused with feeling." He also points out the joint influence of expectation and interruption with respect to sense‐making processes. The gap between the expected results and actual results that Argyris and Schön (1996) describe can be eliminated by making changes (taking corrective measures) within the existing values and norms, or changing the existing values and norms. The former is called as single‐loop learning and the latter is called as double‐ loop learning. Single‐loop learning is connected to maintaining efficiency – doing things right according to the existing values and norms. But, double‐loop learning is about doing the right things, by questioning the existing values and norms. This is important especially in a dynamic work environment; because, in order to be effective in such an environment, one probably has to think out‐of‐box at least now and then. Asking fundamental / critical questions can be seen in connection with what Schön (1998, page 61) calls the reflective practitioner:
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Anandasivakumar Ekambaram et al. A practitioner’s reflection can serve as a corrective to over‐learning. Through reflection, he can surface and criticize the tacit understanding that have grown up around the repetitive experiences of specialized practice, and can make new sense of the situation of uncertainty or uniqueness which he may allow himself to experience. The description mentioned above points out the possibility of new ways to approach and tackle the situation at hand. Single and double loop learning can be compared to the learning experiences that a learner could gain from participating in simulation. Simulation provides choices that can lead to single or double loop learning. Various choices of actions, which can be tested in simulation, allow the learners to explore new associations of alternative decision paths to make sense of the situation and of the dynamics of the intended learning. It is interesting to look at mental models in this regard. According to (Senge, 2006, page 8): "Mental models are deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action. Very often, we are not consciously aware of our mental models or the effects they have on our behaviour." The definition shows the strong connection between mental model and behaviour. Simulation can stimulate, strengthen and / or challenge existing mental models and engage the learners to shape their mental models. When simulation takes place, mental models of the learners contribute, among other things, to develop understanding of the situation (to make sense of the situation), to make choices and to create expectations of their choices / actions. And, at the same time, results of their actions can also shape their mental models. By presenting graphical illustrations, etc., simulation makes an attempt to connect the learner's mental models to the context, content and form of the learning material. Hence, simulation tends to establish some kind of a common ground of understanding quickly. As the learning processes progresses in an interactive manner, the intended learning is expected to materialize through shaping the mental models and developing intended behavioural patterns.
4. Research method Although the simulation only involves two staff members from N‐USOC, the project includes both quantitative and qualitative methods. Before the simulated scenario, all involved control centres in the simulation got a structured questionnaire. In addition, the two participants at N‐USOC were interviewed. The interview was conducted as a semi‐structured interview after the simulation session. The participants gave their permission to use a tape recorder. A guide was outlined in order to be a basis for the interviews and to ensure that important topics were covered. During the interview, the two N‐USOC trainees were asked to reflect about the simulation process. The participants were asked to reflect on topics related to the simulated training session; preparation, accomplishment, and feedback afterwards.
5. Results and discussion 5.1 Results from the questionnaire The first part of the questionnaire study focuses on pre‐simulation situation – how the participants view the simulation before their participation. This study shows that the respondents had a clear understanding of objectives for their participation. They presented their objectives and expectations related to the simulation. This presentation points out that the respondents had reflected on their current knowledge and on the knowledge that they wanted to acquire. They were also interested in participating in the simulation. When the respondents were asked how easy / difficult they expected it would be for them to perform their part in the simulation, they answered they expected it to be difficult. This perception led the respondents to make special efforts to prepare for the simulation. Fifty per cent of the respondents said that it was easy to find relevant information to make the preparation. Though the respondents saw possible difficulties, it seems
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Anandasivakumar Ekambaram et al. that they acknowledged the importance of the learning process. Seventy five per cent of the respondents said that the simulation would improve their ability to work better or significantly better than before. This description suggests that the respondents' mental models were attuned to gain benefits from the oncoming learning process. The second part of the questionnaire study looks at how the participants experienced the simulation. Seventy five per cent of the respondents said that the simulation was interesting or very interesting. The respondents said that what they learned during simulation was valuable. This valuable learning is, according to the respondents, either something new or a good repetition. From this statement, it can be assumed that the simulation provided possibilities for both single‐loop learning (repetition of good practices and minor adjustments within the existed norms and values) and double‐loop learning (learning something new by questioning the existing norms and values). Our understanding is that the learning during the simulation was single‐loop learning, since we could not find a clear episode that can suggest the occurrence of double‐loop learning in the simulation. Seventy five per cent of the respondents said that the knowledge that they had gained from the simulation would improve their ability to work better or significantly better than before. One respondent mentioned that his or her performance would not change and it would be business as usual. It is interesting to note that this respondent mentioned that the simulation experience was boring and disappointing, because a toxic spill event that had been expected did not occur. This respondent's response points out how much preparation (for instance, looking at various scenarios) was made with respect to participating in the simulation. The respondent's disappointment can also be looked at in connection with expectations and interruptions that are associated with a sense‐making process; the respondent is disappointed when his / her expectations for the flow of events were interrupted (the expected toxic event did not occur). It is also to be noted that this particular respondent however perceived the learning process as a valuable repetition. Occurrence of the good preparation was emphasized by seventy five per cent of the respondents who said that they had not had any question or doubts before or during the simulation.
5.2 Results from the interviews In this part we focus on the two N‐USOC participants and the results from the interviews. The results were conducted after the actual simulation, and therefore the results concern reflections afterwards. During simulations, there is usually an anomaly or unexpected event occurring. These anomalies are meant to be realistic and are based on incidents or events that previously have occurred real‐time. During the interview both participants reported that no unexpected situation had happened. They recognized the anomalies that occurred and immediately knew how to handle them. They both found this to be a result of spending time on preparation for the simulation. Hence, the decisions they had to make during the session, was expected in some respect. They had read about all anomalies that had occurred earlier. This implied that they did not feel stressed during the anomaly resolution; they felt that they could manage the challenge and they felt confident when making decisions. The focus on preparation that the interviewees mentioned reflects the results from the questionnaire study that describes the issue of preparation. Both trainees reported one common and major challenge during the simulation; a lot of traffic on the voice loops. At some points it was a lot of action at the same time at several of the control centres. This affected the situational awareness, which in turn is very important for understanding the whole situation (making sense of the situation), for communication, collaboration and planning of the upcoming events. The trainees still felt they managed to solve these situations and communicate the most important issues with their counterparts. These episodes seem to highlight a single‐loop learning process, in which the participants made efforts to accomplish the desired results within known norms and values. Furthermore, this episode also points out reflection‐in‐action through which the participants learned to deal with the situation. Immediately after the simulation ended, a debrief was held on the voice loops with all participants from all the control centres. The N‐USOC trainees received a general positive feedback. An internal debrief was held the
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Anandasivakumar Ekambaram et al. following day. Participants in the internal debrief was: the two N‐USOC trainees, the person running the simulator as well as the N‐USOC Training Manager. During this latter debrief the whole simulation was talked through and very specific feedback was given to each of the two trainees. In the interview, they expressed that the specific feedback was valuable for their learning progress. In our understanding, the debriefing session seems to emphasize the importance of applying and adhering to existing norms and values. In other words, the debriefing session seems to highlight single‐loop learning. From both the trainees view, simulations are an important and valuable learning tool for the control room job. The simulation gave an opportunity to rehearse skills, to achieve a better understanding of the communication flow and learning valuable lessons in a "safe" virtual environment.
5.3 Characteristics that make the simulation process an effective learning tool From this study, it is believed the three key elements enhancing the learning from simulations are (1) the preparation phase, (2) the very realistic simulation itself and (3) the following reflection and lessons learned. The participants’ attitude towards the upcoming learning experience as well as the effort they spend on preparation will greatly influence the learning outcome. Teamwork, communication, multitasking and stress handling are all important skills for performing well as a console operator. These are skills that are not possible to achieve through classroom lessons, they need to be practised and adjusted in the actual situation. The simulation environment used in the ISS program is very close to the real‐time experience. The trainees are seated in the actual control centre, using the actual tools used for real‐time operations. All the roles and the whole scenario is very close to a “live” situation, the only difference is the actual activities not being performed on‐board the ISS, but this part is also simulated by a crew surrogate. Bellini et al. (2008, page 45) say, "It is important to recognize that the creation, diffusion and application of knowledge is situated and thus heavily influenced by the context of practice." Simulation environments provide an appropriate context (close to a "live" situation) to learn and develop knowledge, so that the knowledge can be applied and utilised effectively when a "live" situation emerges. Performing a debrief where lessons learned are discussed and the opportunity where the trainee can reflect on what he/she learned make the learning process complete. A debrief will reveal the understanding of all parties of the situations they have worked through. To understand the situation from the other interacting parties is important for future cooperation. This also gives the opportunity to correct any wrong assumptions. Debriefs, in this regard, can be seen as a kind of dialogues; dialogues that can bridge the gap between individual learning and organisational learning (Oswick et al., 2000) and contribute to the externalisation of knowledge (Nonaka & Takeuchi, 1995). The trainee will receive evaluation of their performance from the training manager or other participants. If the trainee is able to reflect on his/her own performance, as well as reflect on the evaluation provided by others, this will enhance learning and in the end improve performance. Senge (2006, page 288 – 289) describes an industrial example (Intel) that illustrates the importance of reflection as an important part of learning that enhances work performance.
6. Concluding remarks We have presented learning aspects that are associated with a simulation session. This simulation session was aimed to provide the participants, who are located at various control rooms, more knowledge on space operations. We have chosen to look primarily at one learning aspect, namely reflection. Considering the notion of reflection as a central point of focus, we have discussed relevant aspects, such as sense‐making, mental models single‐loop learning and double‐loop learning. Based on our study presents, we have found that there was a notable amount of effort that the participants of the simulation made in order to prepare themselves for the simulation. In this regard, they tried to find relevant information. In addition, it seems that the participants reflected on their relevant, previous experiences as a part of their preparation. Their previous experiences might be limited. But, it would not necessarily limit the reflection process or their preparation for the simulation. The participants would derive more information and more understanding by reflecting on their (limited) experiences. Individuals may give different emphases on different components of their experiences. Their personal characteristics and external factors can lead them to
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Anandasivakumar Ekambaram et al. make the different emphases. These emphases and the way of perceiving the experiences can create a version of the events (perhaps a kind of a personal history) that is related to their experience. March et al. say that people draw more information from their limited experience, by considering the unique incidents that they experience as detailed stories rather than single data points. In this regard, they elaborate their experience by discovering more aspects of experience, more interpretations of experience and more preferences by which to evaluate experience (March, Sproull and Tamuz, 1996) – a sort of a process of making sense and adding context to the information. Weick (2001, page 462) says, If sense making is about nothing else, it is about the resourcefulness with which people elaborate tiny indicators into full‐blown stories, typically in ways that selectively shore up an initial hunch. The above description points out a pre‐simulation learning process that incorporates reflection‐on‐action – that is, participants reflecting on relevant, previous experiences in order to gain more understanding and thus prepare themselves better for the simulation. Even though many of the participants (respondents) had originally expected that the simulation would be difficult, the results showed they did not find it difficult afterwards. This highlights the high degree of preparation that the participants did. Our study also tends to suggest that the learning associated with the simulation was single‐loop learning. Verified and well‐established norms and values can be necessary for space operations that are cost‐sensitive. Hence, there may not be any encouragement for trying something new by disregarding existing norms and values. This could explain the occurrence of single‐loop learning in the simulation. In this paper, we have described that simulations are an important and valuable learning tool for the control room job. We describe this by presenting important aspects that characterize the learning process. We believe that looking at these aspects provide insights that can help to modify future simulation sessions. There can be other implications with respect to simulation sessions; for instance, these sessions can (1) enhance team‐ building, and thus contribute to better cooperation (2) require each unit, which participates in the sessions, to gain adequate contextual understanding of the work done by other units prior to the sessions. There are limitations in our study. For instance, the number of respondents was not many. Our study would have been much richer, if we had had more respondents. We also find possibilities for further research. For example, the effect of debriefing session can be followed up in future simulation‐sessions. This study will be important, since learning and knowledge related research studies point out pitfalls associated with debriefing processes (Schindler & Eppler, 2003).
References Argyris, Chris, and Schön, Donald A. (1996). Organizational learning II : theory, method, and practice. Reading, Mass.: Addison‐Wesley. Bellini, Emilio and Canonico, Paolo (2008): Knowing communities in project driven organizations: Analysing the strategic impact of socially constructed HRM practices, International Journal of project Management, 26. Boud, D.; Keogh, R.; and Walker D. (1996): Reflection: Turning Experience into Learning, Kogan Page, London. Crossan, M. M., Lane, H. W. & White, R. E. (1999): An organizational learning framework: from intuition to institution. Academy of Management Review, vol.24, no. 3, 522‐537. Fiol, C. Marlene and Lyles, Marjorie (1985): Organizational learning, Academy of Management Review, Vol. 10, No. 4. March, James G.; Sproull, Lee S.; and Tamuz, Michal (1996): Learning From Samples of One or Fewer, Printed in Michael D. Cohen, Lee S. Sproull: Organizational Learning, Sage Publications, Inc. Oswick, Cliff; Anthony, Peter; Keenoy, Tom; Mangham, Iain L. (2000): A dialog analysis of organizational learning, Journal of Management Studies, September. Nonaka, Ikujiro and Takeuchi, Hirotaka (1995): The knowledge creating company – How Japanese companies create the dynamics of innovation, Oxford University Press. Prahalad C.K., Hamel G., (1990), ‘The core competence of the corporation’, Harvard Business Review, 68, 79‐91. Schindler, Martin and Eppler, J:Martin (2003): Harvesting project knowledge: A review of project learning methods and success factors, International Journal of project Management, 21, 3. Schön, Donald A. (1998). The Reflective Practitioner, How Proffessionals Think in Action: Ashgate. Senge, Peter M. (2006): The Fifth Discipline – The art and practice of the learning organization. Random House Business Books. Weick, Karl E. (1995): Sensemaking in Organizations, SAGE Publications, Inc. Weick, Karl E. (2001) Making sense of the organization, Blackwell Publishing.
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The Role of Knowledge Management and Innovation in Challenging Times – A View on the Leisure Boat Industry Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen 1 SINTEF, Trondheim, Norway siva@sintef.no Carl.C.Rostad@sintef.no Bjornar.Henriksen@sintef.no Abstract: The leisure boat industry in Norway has faced with several challenges in recent years. In 2007, there was much optimism. And, there was a common understanding that year 2007 would be a record‐breaking year in terms of boat sales. What happened next was an unexpected turn of events. In 2008 the market collapsed and workers were laid of, companies discontinued or changed their focus from production to service and off‐season‐storage (which is often the case with small companies). The same trend was seen on a global scale in the period of 2009 to 2011 that started optimistic, but yet another financial crisis hit the market. One important explanation for the abyssal development with the leisure boat industry is that leisure boats are the first thing that people stops buying in financial challenging periods, and is the last thing they start to buy when an economic upturn manifests itself. Year 2012 has also been a very difficult year for the world wide leisure boat industry. This paper will look at the relevance of innovative approaches and concepts, which incorporate elements of knowledge management, in dealing with the challenges that the leisure boat industry has been facing with. The study related to this paper is a part of a research project called Eco‐Boat MOL. The project has four industrial partners and three R&D partners. It started in 2011. This is a conceptual paper that reflects on the studies conducted in the research project so far. Methods that were used in these studies were of qualitative nature. Based on the reflection of these studies and on the conduct of a literature study, this paper presents the following: (1) different aspects of innovation and knowledge management, (2) interrelation between the aspects of innovation and the aspects of knowledge management, and (3) conceptual models that can be used to look at the improvement possibilities for the leisure boat industry. Concepts such as business process reengineering (BPR) and lean thinking are taken into account to describe the importance of understanding customer needs and of delivering the expected results effectively and efficiently. Relevant industrial examples are given in order to illustrate the description. Considering this description as a starting point / background, discussion on the aspects of knowledge management and innovation is presented. Finally, conclusion winds up the whole discussion. Keywords: innovation, knowledge, leisure boat industry, learning
1. Introduction This paper will look at the relevance of innovative approaches and concepts, which incorporate elements of knowledge management, in dealing with the challenges that the leisure boat industry has been facing with. The study related to this paper is a part of a research project called Eco‐Boat MOL. The project has four industrial partners and three R&D partners. It started in 2011. In connection with this paper, we consider the following definitions of innovation and knowledge: O'Sullivan and Dooley (2009, page 5) define innovation "as the process of making change, large and small, radical and incremental, to products, processes, and services that results in the introduction of something new for the organization that adds value to customers and contributes to the knowledge store of the organization". Davenport and Prusak (1998, page 5) say: "Knowledge is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information. It originates and is applied in the minds of knowers. In organizations, it often becomes embedded not only in documents or repositories but also in organizational routines, processes, practices and norms". This paper first presents the current business situation of the leisure boat industry and some concepts that are related to process innovation and improvement, as well as product innovation. Then, the concepts are looked at in connection with the leisure boat industry. Finally, the concluding remarks winds up the whole discussion.
2. The current business situation – the leisure boat industry This section presents some of the important market characteristics the industrial partners are operating in and is an analysis focusing on the business market the industrial partners are operating in.
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen The leisure boat market has taken sever blows in the last years. In 2007 the optimism was present and there was a common consensus that this would be a record‐breaking year in terms of boat sales. What happened next, no one expected. In 2008 the market collapsed and workers were laid of, companies discontinued or changed their focus from production to service and off‐season‐storage (which is often the case with small companies). Figure 1 illustrates US industry retail powerboat sales. This is also illustrative for what also happened in Europe as illustrated in Figure 2 where the Finnish domestic boat‐production is shown with a blue graph.
Figure 1: US Industry Retail Powerboat sales (1965‐2010) (Craig, 2012)
Figure 2: Trends as reported by ICOMIA (ICOMIA, 2010). Legend: Blue=Finnish boat‐production, Yellow=Japanese boat‐production, Light blue = New Zealand boat production The same trend was seen on a global scale in the period of 2009 to 2011 which started optimistic, but yet another financial crisis hit the market. One important explanation for the abyssal development with the leisure boat industry is that leisure boats are the first thing that people stops buying in financial challenging periods, and is the last thing they start to buy when an economic upturn manifests itself. Based on the experience of the authors, 2013 will also be a very difficult year for the leisure boat industry.
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen Another important aspect of the boat‐industry is that there are many customer‐segments. Disregarding the obvious segments like fishing, inshore/offshore segments etc, the customers are divided between the rich and very rich to the customers who borrows everything to buy a boat. And, it is important to remember that the buying cost is just one part of the picture, in addition there are service and maintenance costs, fuel costs, mooring/marina costs, off‐season storage costs and more. What has happened in the market is that the customers with money are using longer time to decide, while the customer who might think of buying a boat (but needs a loan), goes for the second‐hand market. Another challenge business‐wise for the BOMA‐boat‐producers and generally for all producers, is that material costs are increasing. This is illustrated by Haynes (2012) "Builders and accessory makers find themselves squeezed while trying to keep prices low for consumers. Builders are struggling to keep boat prices stable in the face of a bruised economy and past increases that some believe have outpaced inflation. But fluctuating raw material and commodity prices are making that challenge a tough one." Internal processes in design/production/sales and also service are not developed to a level that one would expect from company's designing and producing high‐cost products. The statements of Lazzara (2008) still rings true: "For the most part boats are built the same way today as they were in the 50′s. I realize materials have changed as have techniques, but our industry is still very labour intensive". Even though there are some examples of mass production approaches (like Bavaria), lean manufacturing techniques (like Hydrolift) and modularization initiatives (like Windy Boats in Norway), design/production/sales still have a lot of potential in order to improve. This has been among one of the highest priorities of for example the Norwegian leisure boat industry through the cluster‐project Arena Leisure Boat which has initiated R&D projects of more than 110 million NOK (AFB, 2012). The situation described regarding very low or no sales of new boats, very challenging market conditions, probably shifts in consumer demands, all requires an innovative focus towards the boating industry. As such, all industrial partners in the BOMA project have the same drive towards innovation. Here it is relevant to note what Jens Ludmann, CEO of Bavaria Yachtbau, said in his keynote address at Marine Equipment Trade Show: "Innovation and strong suppliers are the key ingredients needed for boat‐builders to succeed in today’s market." His words reflect the need to look at the connection between business and innovation (not looking them as separate entities) with the aim of identifying what is required and what is possible. The following sections present concepts and approaches that can be considered with respect to carrying out improvement and innovation in organizations that strive to stay in and compete in the business.
3. Process innovation and improvement When facing challenging conditions, business organizations would try to cut down unnecessary cost and time. One of the ways that organizations adopt in this regard is improving or renewing their business processes by focusing on the customer in order to eliminate non‐value added activities. There are several concepts that are connected to process improvement and management. Here, we shall look at 2 concepts:
Business process reengineering
Lean thinking
3.1 Business process reengineering (BPR) Hammer and Champy (1990) defined BPR as The fundamental rethinking and radical redesign of business processes to achieve dramatic improvements in critical, contemporary measures of performance, such as cost, quality, service, and speed.
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen The authors describe 4 key words of this definition:
Fundamental: Here, it is about asking fundamental questions; questions such as:
Why do we do what we do? Why do we do it the way we do? These fundamental questions can make awareness of assumptions behind activities that are performed. These assumptions may be inappropriate or hidden. The focus here is not what is already there, rather what it should be.
Radical: BPR, as it is suggested in the beginning by Hammer and Champy (1995), takes into consideration radical changes, not small improvement. As the authors say, it is about business reinvention not business improvement. But, the focus on this radical aspect was somehow changed in such a way to include continuous improvement (Hammer, 1996)
Dramatic: The fundamental questioning of existing current work practices and radical rethinking can lead to dramatic improvement. The authors emphasize that BPR should be applied in companies where there is a need for a big change.
Processes: The authors say that many companies do not focus on processes, but they focus on tasks and structures. They define processes as "a collection of activities that takes one or more kinds of input and creates an output that is of value to the customer" (Hammer & Champy, 1995, page 35).
This definition points out an importance of focusing on creating value for the customer. This customer focus can be seen as the very basic construct on which the four pillars of BPR stand; based on the customer focus the fundamental questions are asked in order to radically rethink how the work should be done and thus develop processes that can create dramatic improvement.
The following example describe how reengineering business processes could lead to Improvement: IBM Credit gives financial assistance to the potential customers. The process that we are looking at here is "The credit issuance process". The credit issuance process initially included 5 stages. After the radical change, the whole process took only 4 hours – the original time span had been 6 days on average, sometimes 2 weeks. Hammer and Champy (1995) say "The old process had been overdesigned to handle the most difficult applications that management could imagine."
3.2 Lean thinking Lean concept is a managerial approach that was developed from the Toyota Production Systems. The main aim of the lean concept is to eliminate waste and non‐value activities. Waste and non‐value‐added activities are to be identified by having a customer perspective. Waste and activities that do not add value to the customer needs will hence be eliminated. Waste can be described in several ways. Referring to the Toyota Production System, Cullen et al. (2005) presents the following types of waste:
Over production
Waiting
Transportation
Inventory
Motion
Over‐processing
Defectives
Shingo (1992) points out rework as on of the waste types. Womack et al. (1996) describe lean thinking as follows: "In short, lean thinking is lean because it provides a way to do more and more and with less and less – less human effort, less equipment, less time and less space – while coming closer and closer to providing customers with exactly what they want."
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3.3 BPR and lean thinking Lean thinking and the BPR‐philosophy to certain extent overlap each other, especially when it comes to eliminating non‐value‐added activities. At the same time, these two concepts can be viewed separately, but complementary to each other. BPR‐philosophy can be seen as a means to identify the right thing – doing the right thing – by asking the fundamental question that can lead to dramatic change. Once the right thing is identified, how it can be done efficiently – doing (the right) thing right – can be described by the help of lean thinking, which is a continuous improvement. In this regard, BPR‐philosophy and lean thinking can be seen as complementary to make improvement in business processes. The aspect of learning (from the experiences connected to the improvement efforts) can be viewed in addition to BPR and lean thinking, when it comes to making improvement in processes. Figure 3 illustrates it.
Figure 3: Process improvement through a combination of BPR, Lean thinking and the aspect of learning Boud et al, (1996) suggest that reflective skills are needed in order to turn an experience into learning. Hence, reflection is a significant aspect in learning and knowledge creation. Asking the fundamental questions that characterizes BPR can lead the project / organisation to identify and utilize new opportunities to work better. This can be seen as a reflective process. Asking these fundamental questions can be seen in connection with what Schön calls the reflective practitioner. He (Schön, 1998, page 61) says, "A practitioner’s reflection can serve as a corrective to over‐learning. Through reflection, he can surface and criticize the tacit understanding that have grown up around the repetitive experiences of specialized practice, and can make new sense of the situation of uncertainty or uniqueness which he may allow himself to experience." The description mentioned above points out the possibility of new ways to approach and tackle the situation at hand. Another way to look at reflection with respect to innovation is the process depicted in Figure 3: "Reflecting on the experiences and learning from them". Reflection that results from this process can be of two nature, namely single‐loop learning and double‐loop learning. Argyris and Schön discuss about learning and knowledge creation as understanding and eliminating the gap between the expected result and the actual result of an action (Argyris & Schön, 1996). When an unexpected result of an action occurs, it will create surprise for the person who has taken that action. In a learning situation, this surprise tends to create reflection on what has happened with respect to the expectation. This is a way of making sense of the experience. Hence, the person thinks retrospectively and finds cues to make sense of his / her experience. This sense‐making can lead to actions that can eliminate the gap between the expected result and the actual result.
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen The gap between the expected results and actual results that Argyris and Schön (1996) describe can be eliminated by making changes (taking corrective measures) within the existing values and norms, or changing the existing values and norms. The former is called as single‐loop learning and the latter is called as double‐ loop learning. Single‐loop learning is connected to maintaining efficiency – doing things right according to the existing values and norms. But, double‐loop learning is about doing the right things, by questioning the existing values and norms. This is important especially in a dynamic work environment; because, in order to be effective in such an environment, one probably has to think out‐of‐box at least now and then.
4. Product innovation 4.1 Customer focus – crowd sourcing Obtaining ideas, opinions, feedback and information from the customers about their needs is very useful to embark on product innovation. An act of obtaining such information is called crowd sourcing. In this regard, it can be interesting to look at this topic in some organizations. Starbucks: Starbucks focused on using digital media to build up customer relationships. This was the initiative taken by the founder and CEO of Starbucks during 2008 when there was a significant decline in sale. After 2 years, they found that 4% increase in sales, and the net quarterly (the last quarter) profits in 2009 up to $241 million. Compare to the same period in the previous year, this amount represents an increase of 375% (Godson, 2010). Though there can be several reasons for this success, there was no doubt on the role that the focus on digital media played in this regard. Facebook, Twitter and youtube are some of the digital media that Starbucks utilizes. "My Starbucks Idea" is an initiative that Starbucks has taken to gather ideas from their customers in order to improve the product and the coffee‐drinking‐experience that their customer have. Starbucks applies the idea of Crowdsourcing. There can be possible challenges in involving customers in the improvement effort:
Too much information: There can be too much information from too many customers / consumers. This information overloading can affect the improvement effort. One way to solve this problem is to establish private communities, where an acceptable number of loyal customers are selected to participate in the improvement effort by providing their suggestions. Establishing such communities would create a sense of belongingness as well as responsibility among the selected customers. This feeling and involvement could lead the customers to become an advocate or ambassador for the improved product, when it is made.
How all ideas from the customers can be integrated with the product: This is a problem of operationalization. One way to deal with the challenge is to establish an open dialog between customers and the product developers, so that customers can understand the limitation of developing the improved product based on their suggestions.
Lego: Lego has also involved customers to find innovative ways to improve their product. Lego In one occasion, Lego arranged a contest in order to obtain a better understanding of Lego created Lego factory that to give their customers a richer experience to enhance and build relevance for its classic toy offering. Lego factory is powered by Lego digital designer (LDD). Lego factory set comes in custom packaging that includes all Lego elements that are required to construct the virtual design physically. During one occasion, Lego arranged a contest in order to obtain a better understanding of the types of models that the consumers would design using LDD. The contest lasted for 11 weeks and 8000 models were custom designed. Ten models were voted consumers and Lego master Model Builders to become real Lego sets available exclusively through the company's Shop‐at‐home division. Contest winners, whose age ranged from 9 to 38, will receive royalties based on sales of their winning designs (Tidd and Bessant, 2009). To improve relations and dialogue with its customers, the Lego group has implemented the program "Lego ambassador" consisting in selecting around 40 ambassadors in over 20 countries around the world among the community of fans that had naturally developed on the internet. These ambassadors, representing these communities, are responsible for transmitting information in one way or another and are completely integrated into the design of new products (http://open‐your‐innovation.com/2010/04/01/open‐innovation‐ crowdsourcing‐and‐the‐rebirth‐of‐lego).
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen In a recent interview to the BBC, the CEO of LEGO mention about the important of experimenting and innovation. He said: "The ultimate survival technique is experimentation. When you experiment, you have also said that you are willing to fail. Failure is best way to learn." (CEO of Lego, a Danish toy company, Knudstorp (2012)) His view, in a way summarizes the company's attitude towards innovation in order to survive and succeed.
4.2 Crowd sourcing and Learning / knowledge creation Experimentation that Knudstorp mentions points out the need to apply existing knowledge in new ways and / or create new knowledge in order to produce the desired product. Experimentation can be seen in connection with double‐loop learning. Creating product ambassadors has a close relation with communities of practice that is one of the central aspects of learning in organizations. Communities of practice can be seen as one of the manifestations of social networks. The term / concept was introduced by Lave and Wenger (1991). Referring to Seufert et al. (1999) and Adams et al. (2000), Dalkir (2005, page 112) describes community of practice as "a group of people, along with their shared resources and dynamic relationships, who assemble to make use of shared knowledge, in order to enhance learning, and create a shared value for the group." Crowd sourcing has become an effective source of innovation. In the recent issue of Harvard Business Review, Boudreau and Lakhani (2013) say: "If you exclude crowdsourcing from the corporate innovation tool kit, you are loosing an opportunity" (page 63). Based on the description of the above examples, we shall present a model that illustrates increment of customer‐base by involving customers (Figure 4).
Figure 4: Involving customer to increase the customer base
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen The examples mentioned here involve the concept of open innovation. One definition of open innovation is: "The use of purposive inflows and outflows of knowledge to accelerate internal innovation, and to expand the markets for external use of innovation, respectively" (Chesbrough etal.,2006: 1). When it comes to open innovation, knowledge management systems can be used to capture and structure information from the customers to facilitate innovation efforts. The purpose of crowd sourcing can be seen in connection with an approach called outcome‐driven innovation. This approach was presented by Anthony W. Ulwick (2009) as an effort to provide an effective approach to the innovation process. Ulwick consider that existing approaches are broken or ineffective. He says, "Most of today’s innovation processes and practices date back more than 20 years – and they contribute to the 70–90 percent new product failure rates that companies currently experience" (Ulwick, 2009; page 2). The cornerstone of Ulwick's approach is "to get jobs done". He says: "A job is defined as the fundamental goals customers are trying to accomplish or problems they are trying to solve in a given situation. Current products and services are merely point‐in‐time solutions that enable customers to execute jobs. They should not be the focal point for value creation. A vinyl record, a CD, and an MP3 storage unit, for example, all help customers accomplish the job of storing music. Focusing on creating a better record doesn’t help in the creation of the CD or the MP3 device, but focusing on improving the job of storing music supports the discovery and creation of new ways to help customers get the job done better." In other words, organizations should understand the customer's true definition of value. When it comes to knowing the customer's needs, we would like to present the following matrix (Figure 5). This matrix can be seen as a means to structure the need identification efforts, as well as to find relevant methods and strategies for the need identification efforts.
Figure 5: Customers and companies with respect to identification of customer‐needs
5. The concepts and the leisure boat industry The concepts presented earlier can be looked at with respect to making improvement in the leisure boat production and in the industry general. Customer needs can be identified, analyzed and structured by applying concepts such as crowd sourcing, open innovation and outcome‐driven innovation. Reflecting on and learning from relevant experiences that other industries have are very useful in applying these concepts in the leisure boat industry. Experiences from other industries cannot be used directly as such. Differences in contexts are to be taken into account, and the relevant knowledge is to be "extracted" from those experiences. Once the
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Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen needs are identified and concretized, then processes that transform the needs into the corresponding products can be developed based on concepts such as BPR and lean thinking. In addition, understanding and monitoring technological development that are relevant for leisure boat industry is important; for example, how sensors can be utilized to capture information in order to know how the boats are actually used by the customers (without infringing on the customers' privacy) is highly beneficial to make appropriate changes in the production of (new) leisure boats. Efforts are to be made in the organizations (leisure boat companies) so that organizations learn continuously in order to ensure that the customer needs are satisfied and that the work processes, which create the products, are effective and efficient. The learning that happens at the individual level in the organizations should be shared with other organizational members. Knowledge management systems can support knowledge sharing and cooperation. O'Sullivan and Dooley (2009) say two of the primary causes of failure in the innovation process relate to the poor sharing of results and poor communication and sense of community.
6. Concluding remarks This paper is a conceptual paper. In this paper, we have presented theories as well as industrial examples related to innovation and knowledge management. We have also presented conceptual models connected to our discussion. These presentations can be taken into consideration, when it comes to study the leisure boat industry to find out possibilities of improving the industry. This paper provides a basis for a framework that can be used to find the improvement opportunities and strategies. Further research can be done to look at future innovative efforts that the industry would take. In addition, further studies can be conducted to develop more understanding on the connection between communities of practice, innovation and crowd sourcing.
Reference Adams, E. and Freeman, C. (2000): Communities of practice: Bridging technology and knowledge assessment, Journal of Knowledge Management, 4(1). AFB (2012), Arena Leisure Boat ‐ Norwegian cluster project, http://www.arenafritidsbaat.no/prosjekter.htm, accessed 28.06.2012 Argyris, Chris, and Schön, Donald A. (1996). Organizational learning II : theory, method, and practice. Reading, Mass.: Addison‐Wesley. Boud, D.; Keogh, R.; and Walker D. (1996): Reflection: Turning Experience into Learning, Kogan Page, London. Boudreau, Kevin J. and Lakhani, Karim R. (2013): Using the crowd as an innovation partner, Harvard Business Review, April. Chesbrough, Henry (2006): Open business models – How to thrive in the new innovation landscape, Harvard Business School Press, Boston, Massachusetts Craig, J. (2012), Searching for new buyers, http://www.boatingindustry.com/top‐stories/2012/02/01/searching‐for‐new‐ buyers/, accessed 28.06.2012. Dalkir, Kimiz (2005): Knowledge management in theory and practice, Elsevier Inc. Davenport, T. H. & Prusak, L. (1998) Working Knowledge ‐ How organizations manage what they know. Harvard Business School Press. Godson, Mark (2010): Relationship Marketing, Oxford University Press. Hammer, Michael and Champy, James (1995): Reengineering the corporation – A manifesto for business revolution, Nicholas Brealey Publishing Limited. Haynes, R. (2012), Raw facts: Material costs drive up prices, http://www.tradeonlytoday.com/component/content/article/4‐features/518228‐raw‐facts‐material‐costs‐drive‐up‐ prices, accessed 28.06.2012 ICOMIA (2010), Annual ICOMIA Boating Industry Statistics Book, http://www.icomia.com/library/Default.aspx?LibraryDocumentId=1492, Published by ICOMIA Knudstorp, J. V. (2012): BBB website: http://www.bbc.co.uk/news/business‐19343014 (Referred 30th August 2012) Lazzara, R. Government bailouts and the future of boating, http://richlazzara.wordpress.com/category/lazzara‐ yachts/page/4/, accessed 28.06.2012 O'Sullivan, David and Dooley, Lawrence (2009): Applying innovation, SAGE Publications Inc. Schön, Donald A. (1998). The Reflective Practitioner, How Proffessionals Think in Action: Ashgate. Seufert, A.; von Krogh, G. and Bach, A. (1999): Towards knowledge networking, Journal of Knowledge Management, 3(3). Shingo, S. (1992): The Shingo prize production management systems: Improving process functions, Cambridge: Productivity. Tidd, Joe and Bessant, John (2009): Managing Innovation – LEGO case study (www.willeyeurope.com/college/tidd) Ulwick, Anthony W. (2009): What is outcome‐driven innovation (ODI)?, STRATEGYN, Inc. Womack, James and Jones, Daniel T. (1996): Lean thinking, Simon & Schuster, New York.
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Knowledge Sharing Challenges in Developing Early‐stage Entrepreneurship Tiit Elenurm1 and Anne Reino2 1 Estonian Business School, Tallinn, Estonia 2 University of Tartu, Tartu, Estonia tiit.elenurm@ebs.ee anne.reino@ut.ee Abstract: The paper reflects networking patterns and knowledge sharing challenges of potential and early‐stage entrepreneurs using the first Global Entrepreneurship Monitor survey in Estonia as the departure point. The role of different advisors in the personal knowledge management of entrepreneurs is analysed taking into consideration high early‐stage entrepreneurship level in Estonia that so far does not lead to high number of sustainable and growth‐oriented established businesses. Findings of the GEM survey highlighted different patterns of advice seeking among new entrepreneurs expressing innovative business development ambitions and entrepreneurs that did not express such vision. Innovative entrepreneurs used more often knowledge sharing with researchers and on cross‐border networking while other entrepreneurs mainly received advice from family members and friends. Knowing personally some entrepreneur who had started business activities during last two years appears to be an essential facilitator for moving from the role of a potential entrepreneur to early‐stage entrepreneurial activities. Compared to such country of improvement‐driven opportunity seeking entrepreneurs as Denmark, Estonian early‐stage entrepreneurs more often receive advice from majority of stakeholders, except banks. Friends, people with much business experience, customers and spouses or life companions have been the main advisors for nascent entrepreneurs both in Estonia and Denmark although Estonia belongs to the group of efficiency‐driven economies and Denmark is an innovation‐driven economy. The role of friends has diminished both for Danish and Estonian entrepreneurs when they moved from the stage of nascent entrepreneurs to the stage of being new entrepreneurs. Estonian entrepreneurs focus more on networking with experienced entrepreneurs and with enterprises as cooperation partners after the nascent entrepreneurship stage. Cross‐border knowledge sharing between early‐stage entrepreneurs in efficiency‐driven and in innovation‐driven economies can benefit both sides. Personal knowledge management practices of early‐stage entrepreneurs can be enhanced by entrepreneurship education and training that takes into consideration imitative, innovative and co‐creative entrepreneurial orientations of potential entrepreneurs. Developers of the national entrepreneurship and innovation support system have to apply customized approach in providing mentoring services to opportunity‐driven and necessity‐driven entrepreneurs and to enhancing networking efforts of early‐stage entrepreneurs depending on their innovation and internationalization priorities. Keywords: knowledge sharing, global entrepreneurship monitor, business opportunities, entrepreneurial orientations, personal knowledge management
1. Introduction Personal knowledge management and knowledge sharing, networking and early stage entrepreneurship are all among the topical issues that have been studied widely in recent years. It has been stressed that knowledge management, knowledge acquisition and learning through networks are important for successful entrepreneurial initiatives (Chunyan 2005; Ruiz‐Arroyo et al. 2012). Organisational learning and knowledge management should be based on diversity of sources (McEvily and Marcus 2006) and on networks both inside and outside the entrepreneurial organisation (Owen‐Smith and Powell 2004). Cope (2005) has called to study entrepreneurial networking with potential customers, suppliers, competitors and support service providers, including banks and accountants. However, the gap exists between the entrepreneurial networking discourse and the knowledge management research in the field of early‐stage entrepreneurial activities. The present paper studies networking practices and knowledge management challenges faced by early‐stage entrepreneurs. The research uses data from the Global Entrepreneurship Monitor (GEM) survey, where Estonia was involved for the first time in 2012. The research question is: what are the knowledge sharing patterns of potential and early‐stage entrepreneurs that have to be addressed by knowledge management in the national entrepreneurship and innovation support system and in cross‐border knowledge sharing? The paper is structured as follows. Firstly it gives an overview of literature on the role of knowledge management and networking in the entrepreneurship context. Knowledge sharing in the early‐stage entrepreneurship is related to entrepreneurial orientations and to the GEM research framework. After that data from the GEM survey in Estonia and in some other countries that reflects the context for networking and
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knowledge sharing is presented. Findings from the special GEM section about networking are then used for comparing advisors of Estonian and Danish early‐stage entrepreneurs. The final section discusses implications of GEM results for developing the support system for co‐creative, innovative and internationally oriented entrepreneurs and the role of knowledge management in such support system.
2. Knowledge management and entrepreneurship Knowledge management in small firms and in networks of such firms has in recent years become a topical research issue (Valkokari and Helander 2007) but in order to understand knowledge management challenges of established firms, the research should focus already on the stage, where entrepreneurs enter the process of setting up a new venture and monitor knowledge sources that could support their entrepreneurial initiative. Davenport and Prusak (1998) have described knowledge as a fluid mix of framed experience, contextual information and expert insight that provides a framework for evaluating and incorporating new experience and information. This description is especially relevant in situations, where potential and early‐stage entrepreneurs have to screen new business opportunities and overcome fear of failure. Potential entrepreneurs are more likely to have inspiration for their entrepreneurially oriented careers if they have contacts with other entrepreneurs, including entrepreneurs in their family or among their friends (Davidsson and Honig 2003; Arenius and Minniti 2006; Özdemir and Karadeniz 2011). Demand for knowledge can vary during the early stages of entrepreneurial activities. For example some entrepreneurs need experience‐based knowledge about practicalities of start‐up activities; others need contacts for accessing new markets or personal emotional support. Research that has been conducted by Klyer and Grant (2010) using Global Entrepreneurship Monitor (GEM) 2002‐2004 data from 35 countries has revealed that individuals who personally know an entrepreneur that has recently started a venture, are more likely to participate in entrepreneurial activities. Though, one should be careful when generalising these findings. The study revealed that social networks of female entrepreneurs are less likely to include entrepreneurs than networks of male entrepreneurs. The social capital concept also helps to explain networking practices. For example Kwon and Arenius (2010) have found that residents from countries with high generalized trust were more ready to invest in an entrepreneur with whom only weak personal ties existed. Nonaka and Takeuchi (1995) developed the model of four modes of knowledge conversion, which explains conversions between tacit and explicit knowledge domains. This classical knowledge spiral model allows differentiating explicit knowledge of nascent entrepreneurs that is more reflected in their formal education and tacit knowledge that is gained from previous work and start‐up experience (Davidsson and Honig 2003). Understanding the sources of tacit knowledge assumes information about types of stakeholders that are relevant and trusted by entrepreneurs to give them advice. Hall et al. (2008) stress the need to differentiate between hard and soft knowledge. In the entrepreneurship field hard knowledge can be linked to financing entrepreneurial activities and complying with legal regulations in the enterprise setup process. Soft knowledge can be related to success factors that are not easy to formalize, for instance the influence of human capital and innovative business opportunities or mistakes to avoid in the business start‐up process. Both types of knowledge are important ones for entrepreneurs. The sources of gaining that knowledge may however differ to great extent. McMullen et al. (2007) explain that an entrepreneurial opportunity can be either an objective construct visible to an entrepreneur or a new construct created by a knowledgeable entrepreneur. Hayne et al. (2009) stress the central role of knowledge resources and social capital for nascent entrepreneurs and linkage between new and earlier knowledge in the process of opportunity identification. Entrepreneurial opportunity recognition can initiate learning processes on the level of an individual but also knowledge sharing with stakeholders that can participate in knowledge creation for understanding the opportunity or contribute to conditions needed for the entrepreneurial initiative based on this opportunity. Lindsay and Craig (2002) specify three stages of opportunity identification: opportunity search, opportunity recognition and opportunity evaluation. Social networks can serve as instruments for identifying new business opportunities (Ardichvili et al. 2003). Innovative nature of business opportunity creation will however depend on the composition of the network because networking can also lead to following stereotypes and imitating old business ideas that are not competitive in the changing business environment. Mostert (2007) suggests getting out of your comfort zone as a way to creative ideas. In this context interpersonal networking actions aimed at network‐broadening (Vissa 2012) deserve attention. Different networking partners are needed for sharing experience of end users,
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for accessing research‐based knowledge and for obtaining financial capital for rapid growth. Stages of the entrepreneurial process also lead to changes in networking priorities (Casson and Giusta 2007). Self‐ confidence in own knowledge and skills enhances entrepreneurial initiative (Markman et al. 2002). Knowledge sharing in networks can broaden the knowledge base that reflects mistakes made earlier by other network members and will make self‐confidence of an early‐stage entrepreneur more grounded and the new venture more sustainable. Entrepreneurial opportunities are important for all early‐stage entrepreneurship activities, but the GEM concept differentiates necessity‐driven and opportunity‐driven entrepreneurs. Necessity‐driven entrepreneurs are forced to become entrepreneurs because they do not find a job as salary‐earners and necessity to get some income drives to use available opportunities. They usually have neither time and finances nor knowledge to create a new business opportunity. Opportunity‐driven entrepreneurs choose to become entrepreneurs when they discover or create new entrepreneurial opportunities that they perceive to be a better choice for increasing their income and/or self‐actualization than the role of salary earner. GEM applies the concept of the World Economic Forum that has divided economies into factor‐driven, efficiency‐driven and innovation‐driven in its Global Competitiveness Report (Schwab 2012). In factor‐driven economies international competitiveness of enterprises is mainly based on cheap labour and low cost of other production factors. In efficiency‐driven economies success of new entrepreneurs depends heavily on their access to investments. Innovation‐driven economies are by their nature knowledge‐based and access to new knowledge and networking for knowledge creation become crucial success factors for entrepreneurs. There is evidence, that opportunity‐driven entrepreneurship is more spread in advanced innovation‐based market economies than in factor‐driven or efficiency‐driven economies (Xavier 2013). Knowledge management focuses on accessing the right type of knowledge at the right time and in the right format that is essential for understanding changes in the business environment and for identifying new business opportunities by entrepreneurs. Peter Drucker (1985) expressed his view that innovation and risk‐ taking are more entrepreneurial than managerial challenges. Peter Drucker (1999) has been among the first management and entrepreneurship thinkers to highlight the importance of managing oneself as a knowledge worker in the emerging knowledge economy. He stressed that knowledge workers have to understand not only their own strengths and the value of their knowledge but the value of knowledge offered by their mentors. Personal knowledge management skills enable not only the personal growth and advancement of individuals, but also support external information awareness, internal knowledge dissemination, organisational focus on the core business and continuous innovation in organisations (Cheong and Tsui 2010). Davenport (2010) explained the core of personal knowledge management by describing capabilities that are essential for creating, sharing and applying knowledge. These capabilities include searching and capturing knowledge in such a way that others can easily benefit from this. Examples here range from tagging personal documents that can be then accessed by others to searching for innovative ideas in global online networks. In order to promote a start‐up enterprise with globalization ambitions, online externalization of the advantages of their technologies and services and participation in social networks has become an essential skill. Snowden (2005) stated that while traditional knowledge management in organizations tries to force people to share knowledge with colleagues they do not necessarily want to work with, social knowledge networking is more about mutually directed relationships and much more communitarian. Researchers have developed the entrepreneurial orientation construct that integrates five dimensions: innovation, pro‐activeness, risk‐taking, autonomy and competitive aggressiveness (Lumpkin and Dess 1996). The construct of the single entrepreneurial orientation however does not address some crucial choices that influence knowledge search and sharing by entrepreneurs. The construct of a single entrepreneurial orientation has been further developed by differentiating three entrepreneurial orientations: imitative entrepreneurship, individual innovative entrepreneurship and co‐creative entrepreneurship (Elenurm et al. 2007). Followers of the imitative orientation could benefit from following experienced entrepreneurs in their neighbourhood but also from scanning and filtering such business practices in more advanced market economies that can easily be transferred to a less advanced business environment. The co‐creative entrepreneurial orientations utilize knowledge sharing in networks and open innovation for developing new business ideas. Open innovation assumes the use of purposive inflows and outflows of knowledge to accelerate internal innovation and simultaneously to expand markets for external use of innovation
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(Chesbrough et al. 2006). Consistent individual innovators have to focus on protecting their innovative ideas and as a result, their opportunities to rely on open innovation and networking practices may be more limited.
3. Using GEM data for understanding networking and knowledge sharing 3.1 Methodology GEM survey from 2012 involved 198 000 respondents in 69 countries At least 2000 respondents were involved in each country. GEM sampling rules enable representative and comparable samples of adult population (18‐ 64 years) in all involved countries. In addition GEM also collected data through national expert surveys. The main focus of GEM surveys is on measuring participation levels of individuals at different stages of the entrepreneurship process to enable comparisons within and across individual economies and economic development levels. GEM methodology uses as the primary measure of entrepreneurship the Total Early‐stage Entrepreneurial Activity (TEA) index in the adult population. It includes the share of start‐up nascent entrepreneurs currently setting up their business and new entrepreneurs that have been running their business more than 3 months but less than 3.5 years. Potential entrepreneurs expressing intention to start a news business in the foreseeable future are also identified (Bosma 2012). GEM aims to identify factors that encourage or hinder entrepreneurial activities (Xavier et al. 2013). From the knowledge sharing and networking point of view are important these factors of the GEM model that reflect education and training, cultural and social norms, fears and perceived opportunities, innovation and international orientation. In the GEM study an essential question for investigating entrepreneurs’ social network in the context of experience‐based knowledge sharing is: “Do you personally know someone who has started a business in the past two years”. GEM survey includes questions about co‐operation with other enterprises and an optional section about networking as receiving advice from different stakeholders, including family and friends, current boss and work colleagues, people from other countries, researchers and investors, lawyers, investors, banks, accountants, public advising services, suppliers and customers, firms that collaborate or compete with the entrepreneur. These questions will be the main focus of present study.
3.2 Estonian GEM survey results in 2012 Estonian first GEM survey gave evidence of high early‐stage entrepreneurial activity. In Estonia TEA index was 14%, the highest in Europe. It was also high in Latvia (13%), the southern neighbouring country of Estonia but much lower in Finland (6%), the northern overseas neighbouring country of Estonia. TEA index was 5% in Denmark that we use as the comparison base for the optional section about networking as this section was missing in surveys of Estonian neighbouring countries. It should be however taken into consideration that in addition to Finland and Denmark the majority of innovation‐driven economies in Europe have TEA index between 4‐6%. Exceptions of high TEA indexes are Austria (10%), the Netherlands (10%) and the United Kingdom (9%). In Estonia the share of respondents that had discontinued their business is 4% which is higher than EU average 3% (Xavier et al. 2013). Bosma (2009) points out that high TEA index can in some economies reflect dominance of the necessity‐driven entrepreneurship. However in Estonia the share of necessity‐driven entrepreneurship is 18%, lower than the EU average 21%. The share of improvement‐driven opportunity seekers among Estonian early‐stage entrepreneurs is 49% (EU average 47%). That is a bit higher than in Latvia (46%) but much lower than in Finland (60%) and in Denmark, where 71% of entrepreneurs start their business in order to pursue independence or to increase their income (Xavier et al. 2013). The share of improvement‐driven entrepreneurs in Denmark is the highest among all countries involved in the GEM 2012 survey. Improvement‐driven opportunity seekers have more time and resources to seek new knowledge and monitor new trends that can lead to innovative business ideas compared to such necessity‐driven entrepreneurs that are forced to start‐up a business in the situation where they lost their job and their family urgently needs income. At the same time, when applying confidence level 0.05, there is no significant difference between perceiving business opportunities in Estonia and in Denmark. In Estonia 45% and in Denmark 44% of all respondents see opportunities to start a business in the next 6 months. In Estonia 45% of respondents perceive that they have knowledge, skills and experience to start a business and this indicator is a bit higher than the EU average (42%), but similar to Denmark (45%).
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Early‐stage entrepreneurs have more chances for experience‐based knowledge sharing if in their network some individual has started a business during recent two years. 37.5% of Estonian and 33.5% of Danish respondents knew such person. Estonian share of such respondents is the highest among efficiency‐driven economies in the EU, followed by Lithuania (32.9%) and Latvia (32.3%), Estonian and Latvian results can be explained by high TEA indexes of these two countries but in Lithuania the share of respondents personally knowing start‐up entrepreneurs was high despite 7% TEA index that is substantially lower than in other two Baltic countries. Among innovation‐driven EU economies the highest share of respondents that knew a recent start‐up entrepreneur were in Slovakia (42.5%), followed closely by Finland (41.8%), Sweden (41%) and Slovenia (40%). The lowest share of such respondents was in Belgium, 22.1%. In this group of countries Estonian overseas neighbours Finland and Sweden have TEA index 6% and Slovenia even lower 5% while Slovakia has relatively high 10%. It can be concluded that networking opportunities with early‐stage entrepreneurs are influenced also by other factors in addition to the share of early‐stage entrepreneurs in a country.
3.3 Comparing Estonian results of the networking section with an advanced market economy At this stage results of the optional networking section of the GEM survey were available only for comparing Estonian results with Danish results but authors considered this comparison relevant for two reasons. Firstly, Denmark represents an advanced market economy in the region around the Baltic Sea and secondly, there is a potential for knowledge sharing between Estonian and Danish entrepreneurs. Altogether 570 respondents from Estonia and 387 from Denmark answered the questions about the sources of information and advice used by them as potential and early‐stage entrepreneurs. Figure 1 gives overview of nascent entrepreneurs’ networking patterns based on receiving advice in the start‐up process. Figure 2 presents the same information about new entrepreneurs that have been in business more than 3 months but less than 3.5 years. Differences between Estonia and Denmark that have confidence level 0.05 are marked with *. 55.0
Friends * Somebody with much business experience A customer Your spouse or life‐companion * An accountant * Somebody who is starting a business * A firm that you collaborate with Current work colleagues Other family or relatives Somebody in another country * A supplier A possible investor Somebody who has come from abroad A lawyer A public advising services for business Your parents * A current boss A researcher or inventor A firm that you compete with A bank EST
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Figure 1: Share (%) of nascent entrepreneurs in Denmark (DK) and Estonia (EST) receiving advice from different stakeholders Figure 1 indicates that friends, people with much business experience, customers and spouses or life companions have been the main advisors for nascent entrepreneurs both in Estonia and Denmark. Figure 1 demonstrates that compared to Danish nascent entrepreneurs, Estonians have in this start‐up phase more often asked advice from friends, accountants, and people from other countries but also from parents. Comparison of nascent entrepreneurs with potential entrepreneurs who have not started start‐up activities
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yet, shows that potential entrepreneurs have less business‐related networking with friends (69.4% in Estonia and 49.5% in Denmark). 51.6% of potential entrepreneurs in Estonia and 38.2% in Denmark know somebody with extensive business experience. The role of friends has diminished both for Danish and Estonian entrepreneurs when they moved from the stage of nascent entrepreneurs to the stage of being new entrepreneurs (Figure 2). Estonian new entrepreneurs have focused at this later stage their networking more on people with business experience than Danish entrepreneurs. Estonian new entrepreneurs have also intensified knowledge sharing with firms that collaborate with them while the share of Danish entrepreneurs taking advice from their collaboration partners has diminished when moving further from the nascent entrepreneurship stage. Both, Estonian and Danish new entrepreneurs have received advice from customers less often than nascent entrepreneurs in these countries. Although Estonian entrepreneurs in general have received more often advice from different stakeholders than Danish entrepreneurs, there is one exception: receiving advice from a bank. 37.0 45.9 41.0
Friends Somebody with much business experience * A customer Your spouse or life‐companion An accountant Somebody who is starting a business A firm that you collaborate with* Current work colleagues Other family or relatives Somebody in another country A supplier * A possible investor * Somebody who has come from abroad A lawyer A public advising services for business Your parents A current boss A researcher or inventor A firm that you compete with A bank EST
DK
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11.3 20.2 13.2 22.2 9.5 15.5 21.5 28.0 12.9 14.5 7.0 18.0 8.4 12.9 19.7 7.1 0
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Figure 2: Share (%) of new entrepreneurs in Denmark (DK) and Estonia (EST) receiving advice from different stakeholders. Estonian GEM Survey included additional questions about ambitions of entrepreneurs to offer innovative products to domestic or foreign customers. Among innovative nascent entrepreneurs whose intention was offering new products or services to international markets, 66.1% had received advice from a potential investor and 27.9% of such entrepreneurs had received advice from a researcher or inventor. Only 23.8% of foreign market focused innovative entrepreneurs had received advice from their spouses of life‐companions (Eesti Arengufond 2013). It is different from the general pattern of nascent entrepreneurs on Figure 1. Comparison of advisors of female and male entrepreneurs involved in the Estonian GEM survey highlights that in the case of female entrepreneurs the role of friends as advisors is less important than in the case of male entrepreneurs. Such statistically significant difference was not established when comparing Danish male and female entrepreneurs. Despite high employment level of Estonian women, their empowerment as entrepreneurs and related networking activities still need to be developed.
4. Discussion and conclusions Comparing Estonian GEM results with other countries revealed high early‐stage entrepreneurship participation in Estonia compared to other EU countries but also higher discontinuation rate than the EU average. Estonian early‐stage entrepreneurs often lack growth ambitions. It is crucial for the innovative entrepreneurship to expand and to access international markets in order to enable Estonia to move from an efficiency‐driven to an
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innovation‐driven economy. Monitoring new business opportunities and knowledge sharing with the right mix of stakeholders can lead to more sustainable and growth‐oriented entrepreneurship in whole country. Knowing personally some entrepreneur who had started with business activities during last two years appears to be an essential facilitator for moving from the role of a potential entrepreneur to early‐stage entrepreneurial activities. It is however not clear if such experience‐based knowledge source will enable creating new business opportunities for innovative entrepreneurship Comparison of advisors of Estonian and Danish early‐stage entrepreneurs revealed that Estonian entrepreneurs have used the advice from the larger number of different stakeholders than Danish entrepreneurs. Knowledge sharing between entrepreneurs and banks seems however to be more advanced in Denmark. In both countries potential investors, public advising services, researchers and inventors should become more active networking partners for potential and early‐stage entrepreneurs. Limitation of the present study that used GEM survey answers is however lack of more specific information about the content of advice given by different stakeholders and revealing potential contradictions of their recommendations. In order to overcome this limitation, combination of quantitative and qualitative research is needed. There are opportunities to apply personal knowledge management and knowledge sharing logic in developing support systems for early‐stage entrepreneurship and especially for innovative entrepreneurship. The role of public advising services should be increased and it could be done by following the logic of knowledge management in order to facilitate conversions between tacit and explicit knowledge domains of entrepreneurs. It is important to link early‐stage entrepreneurs who are mainly influenced by tacit knowledge of their family and close friends to the networks that enable access to explicit knowledge about new technology and market trends for discovering new business opportunities and for participating in open innovation activities. However, we should remind that not all potential entrepreneurs are ready for co‐creative entrepreneurship and open innovation and therefore the same support mechanism does not suit for everybody. For some potential and nascent entrepreneurs mentoring or coaching relation with an experienced entrepreneur will be more useful, especially if they follow imitative entrepreneurial orientation and are afraid of personal failure. As we mentioned before, Estonia is still an efficiency‐driven economy and its entrepreneurship and innovation support system would certainly benefit from cross‐border knowledge sharing with entrepreneurs in Denmark and with other innovation‐driven economies, where knowledge about international marketing of innovative goods and services is more widespread. Such international knowledge sharing and co‐creative entrepreneurship may at the same time increase early‐stage entrepreneurship in advanced market economies. Focus of the entrepreneurship education should not be limited to procedures of setting up a business and writing a business plan but it should help participants to understand priorities and tools of their personal knowledge management and networking and knowledge sharing opportunities for potential and early‐stage entrepreneurs.
Acknowledgements The authors acknowledge the key role of the Estonian Development Fund in conducting the first GEM survey in Estonia and cooperation with other members of the Estonian GEM national team in analysing survey result. Assistance and advice of Professor Thomas Schøtt was crucial for using the Danish GEM networking section data. Assistance of Kadri Paes was operational for statistical data analysis.
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A Systematic Review and Comparison of Knowledge Management‐ Frameworks Nora Fteimi and Franz Lehner University of Passau, Passau, Germany nora.fteimi@uni‐passau.de franz.lehner@uni‐passau.de Abstract: In recent years, knowledge management (KM) became an increasingly important discipline. The literature considering KM offers a fast‐growing collection of content consisting of various theories, concepts or topics. Depending on the relevant context and the underlying reference discipline this content might be quite heterogeneous or would even conflict with each other. Furthermore, numerous different orientations as well as reference disciplines, design possibilities and schools are proposed for KM. In conclusion, it seems that a common unified understanding of the discipline KM is lacking. Based on a systematic literature review, this paper aims to present a first contribution to consolidate and order this research field by providing an overview of KM‐frameworks already existing in the literature. The research objectives lie in a systematic analysis and comparison of existing KM‐frameworks, the categorization and review of the frameworks with respect to their applicability in research and praxis. We classify the studies according to four categories: “Meta‐analysis for KM”, “Classification proposals of models and frameworks in KM”, “Classification proposals for knowledge management systems” and “classification proposals for KM in general”. To observe is the lack of a common understanding of definitions as in the case of describing models for KM or in defining terms as “knowledge” or “knowledge management systems”. Moreover the variety and huge amount of different existing classification proposals could hinder the process of selecting the right classification proposal e. g. in enterprises which implement KM. We contribute to research by presenting a first step towards consolidation and obtaining a single common understanding of the KM discipline. The systematic comparison and the proposed categorization of the frameworks can be used as a starting point for further research in order to get an overview of the state of the art and to classify new research projects. Practitioners receive a guide that offers help and direction in introducing and implementing KM within the company. Keywords: knowledge management, knowledge management‐frameworks, literature‐review
1. Introduction In recent years knowledge management (KM) became an increasingly important discipline (Vorakulpipat and Rezgui 2008). The literature considering KM offers a fast‐growing collection of content consisting of various theories, concepts or topics. Depending on the relevant context and the underlying reference discipline this content might be quite heterogeneous or would even conflict with each other. Furthermore, different orientations are proposed for KM. In addition to the different reference disciplines and design possibilities, various concepts, attitudes and schools exist, which justify and explain KM. Moreover, it can be noticed that research and practice discuss and handle KM‐related problems and topics differently. In conclusion, it seems that a common unified understanding of the discipline KM is lacking (cf. (Heisig 2009; Serenko et al. 2010)). The preceding overview illustrates how heterogonous KM is, both as a research discipline as well as from a practical perspective. In the future, a main topic of research will be to consolidate and order the various content and trends of this discipline and to try to achieve a common understanding about KM. Research will thereby be able to gain a base for the systematic comparison and classification of research results. Practitioners can rely on consistent methods and approaches when implementing KM‐related activities and will be able to make the right decisions at the right time in the right place. The remainder of this paper is structured as follow: In Section 2 we give an overview of the research objectives followed by this paper. In Section 3 we present a state‐of‐the‐art of already existing KM‐frameworks by means of a structured literature review. In Section 4 we point out future work and contribution of our research.
2. Research objectives and methodology This paper aims to present a first contribution to consolidate and order this research field by providing an overview of KM‐frameworks already existing in literature. To set up the state of the art this study addresses the following research objectives:
A systematic analysis and comparison of existing KM‐frameworks
Categorization and classification of identified frameworks
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Review of these frameworks with respect to their applicability in research and praxis
We conducted a structured literature review. On the one hand this ensures that the methodic procedure copes with a scientific approach of the study’s problem and on the other hand that all relevant sources can be gathered and analyzed (Fettke 2006). We followed a taxonomy presented by Cooper (Vom Brocke et al. 2009; Cooper 1998). In his taxonomy (cf. Table 1) Cooper proposed six characteristics, each consisting of several categories that can be adapted for the literature review. All fields in this table shaded in grey color were adapted for this paper. Table 1: Taxonomy for literature reviews (cf. (Vom Brocke et al. 2009; Cooper 1998)) Characteristic Focus Goal Structure Perspective Audience Coverage
Categories Research outcomes Research methods Theories Applications Integration Criticism Central Issues Historical Conceptual Methodological Neutral Representation Espousal of Position General Public Specialized Scholars General Scholars Practitioners/ Politicians Exhaustive Selective Representative Central/Pivotal
The focus of our literature review lies on research outcomes, as well as on adapted research methods and applied theories in the analyzed studies. Moreover, we aim to integrate central issues discussed by other researchers in their frameworks. Concerning the structure of this review we classified the studies according to the conceptual category seeking to look up for frameworks and classifications suggested in literature. As far as possible we tried to espouse a neutral perspective in reflecting the studies. This review addresses scholars as well as practitioners who are interested in KM. Finally we distinguish a selective level of coverage based on high ranking journals with regard to the scope of this paper. Besides papers in different high ranking scientific journals related to KM (e.g. “Knowledge Management Research and Practice” or “Journal of Knowledge Management”), also topical relevant conference papers were included in the research process. Forward and backward searches were performed, too. The literature was searched based on different, for analysis relevant keywords such as “Knowledge Management” or “Knowledge Management Systems” in conjunction with “Meta‐Analysis”, “State of the Art”, “Review” and “Framework”. These appropriate keywords were used for literature searches of electronic databases e. g. AiSEL, ScienceDirect and journal websites. Initial hits were reduced by analyzing their titles as a first step. In a second synthesizing step, abstracts of the initial hits were analyzed in‐depth depending on their relevance to the objectives of this paper. The resulting hit list yielded the source basis for this study and consists altogether of 25 papers. It is shown in Table 2. Table 2: Summary of reviewed papers
(Nie et al. 2007) (Heisig 2009) (Nie et al. 2009) (Serenko et al. 2010) (Lee and Chen 2012)
(Holsapple and Joshi 1999) (Mcadam and Mccreedy 1999)
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Category
Meta‐analysis in KM
(Serenko and Bontis 2004)
Title The future of knowledge management: An international Delphi study Meta‐Review of Knowledge management and intellectual capital literature: Citation impact and research productivity rankings Building a taxonomy for understanding knowledge management Harmonisation of knowledge management ‐ comparing 160 KM frameworks around the globe An approach to aid understanding emerging research fields‐ the case of knowledge management A scientometric analysis of knowledge management and intellectual capital academic literature (1994‐2008) Revealing research themes and trends in knowledge management: from 1995 to 2010 Description and analysis of existing knowledge management frameworks A critical review of knowledge management models
Classificatio ns proposals for models and frameworks in KM
Authors (Scholl et al. 2004)
Nora Fteimi and Franz Lehner
(Liao 2003) (Jennex 2006) (Saito et al. 2007) (Becerra‐Fernandez and Sabherwal 2011) (De Carvalho and Ferreira 2011) (Alavi and Leidner 2001) (Binney 2001) (Azmi and Zairi 2005) (Moteleb and Woodman 2007) (Asl and Rahmanseresht 2007) (Jafari et al. 2009)
Title Reviewing the knowledge management literature: towards a taxonomy A review of the main approaches to knowledge management An evolutionary and interpretive perspective to knowledge management Knowledge management and knowledge management systems: conceptual foundations and research Issues The Knowledge management spectrum ‐ understanding the KM landscape Knowledge management technologies and applications ‐ literature review from 1995 to 2002 Classifying Knowledge Management Systems based on Context Content A strategy‐based ontology of knowledge management The Role of Information and Communication Technologies in Knowledge Management Knowledge Management Software Knowledge management and knowledge management systems: conceptual foundations and research Issues The Knowledge management spectrum ‐ understanding the KM landscape Knowledge management: A proposed taxonomy Notions of knowledge management systems: A gap analysis Knowledge management approaches and knowledge gaps in organizations A review on knowledge management discipline
Category
Classification proposals for Classification proposals for knowledge KM in general management systems
Authors (Kakabadse et al. 2003) (Lloria 2008) (Vorakulpipat and Rezgui 2008) (Alavi and Leidner 2001) (Binney 2001)
In a first step, we classify the identified studies according to four categories: “Meta‐analysis in KM”, “Classification proposals for models and frameworks in KM”, “Classification proposals for knowledge management systems” and “Classification proposals for KM in general”. Choosing these categories was motivated by the most frequently followed objectives and the methodology used in the reviewed papers. Some of the studies conduct a Meta‐Analysis of a huge number of KM‐papers, whereas others outline specific frameworks and models used in KM and classify these. Within the third category we classify all studies that examine and propose frameworks for knowledge management systems (KMS). Papers that handle and discuss KM‐related themes and frameworks in general were assigned to the category “KM in general”. The following sections present and compare the identified frameworks.
3. Research results According to the above mentioned categorization the following subsections present a summary of the reviewed papers. Our focus lies on the first three categories (cf. table 2). This limitation has been made since these categories handle special and concrete frameworks in KM, whereas the last category “KM in general” still discusses frameworks with a more general character. For each category we subsume the analyzed frameworks by revealing core research aims and classification attempts in terms of the proposed frameworks. Each subsection concludes with a comparison of the frameworks and discusses their applicability in research and praxis.
3.1 Meta‐analysis of knowledge management studies The first category of our review subsumes studies that were carried out in form of a meta‐analysis investigating general issues and topics concerning KM such as most frequently used definitions of knowledge, often used research methodologies and most cited related work or productivity rankings of e.g. authors and countries. Scholl et al. (2004) focused on several research questions dealing with challenging research issues in the field of KM, theoretical approaches that best fit these research issues and with theoretical and practical developments observed in the discipline.
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Nora Fteimi and Franz Lehner Based on a citation analysis of individuals, institutions and countries in three selected journals Serenko and Bontis (2004) surveyed the research fields of KM and Intellectual Capital (IC) addressing the following research questions: who are the most frequently cited KM/IC related authors and what are the most frequently cited KM/IC papers and publications. A similar study was conducted by Serenko et al. (2010). The authors analyzed 2175 papers published in 11 KM and IC journals concerning productivity ranking of countries, institutions and individuals of these two research areas. In 2007, Nie et al. (2007) published a meta‐analysis taking into account two studies that handle KM from different perspectives. The first study used the methodology of domain analysis to answer questions about the importance of KM, actions and operations in the KM‐field, the factors that enable the birth of KM, ways to implement and to support KM and applications of KM. The second study aimed to build a KM ontology trying to highlight the linkage between KM and other disciplines. Two years later, the authors presented a second study (Nie et al. 2009) in which they developed a general framework to understand a research area. Subsequent, this framework was applied to the domain of KM. In an attempt to harmonize KM‐frameworks Heisig (2008) applied the method of content analysis to compare and analyze 160 frameworks with regard to the following categories: source (in the sense of title, author and year), origin according to country and region, type, knowledge definitions, frequently mentioned KM‐activities and critical success factors. Finally, Lee and Chen (2012) did a literature analysis of 10.974 articles in the space of time from 1995 to 2010. The main contributions of this paper lied in the identification of common research trends and developments in the KM area as well as in the presenting of the evolution of this research discipline. Although all of the presented studies represent meta‐analyses, they take into account heterogeneous perspectives on KM and differ in research aims and applied methodology. Most of the analysis consider a huge amount of papers to collect statistical data (most cited authors, most frequently used pairs of KM‐activities, critical success factors etc.) about KM and IC. Depending on context and intended purposes, these studies can serve as a starting point and useful guide to implement KM in enterprises. Research can use these meta‐ analyses to get an overview of trends and common themes interesting to the KM‐community.
3.2 Classification proposals of models and approaches in knowledge management The second category (cf. table 2) contains studies that examined and classified models, perspectives, schools of thought and approaches for KM. Holsapple and Joshi (1999) compared 10 existing KM‐frameworks and classified them into the categories of descriptive and prescriptive frameworks at which the former can be furthermore subdivided into broad or specific frameworks. The category of broad frameworks consists of five components such as the framework of KM pillars (Wiig 1993) and the framework of core capabilities and knowledge building (Leonard‐Barton 1999). Each one of these frameworks was analyzed with regard to the dimensions focus and framework roots/origins, knowledge resources, knowledge manipulation activities and influences on the conduct of KM. In the context of specific frameworks the authors compared e.g. the model of knowledge transfer (Szulanski 1996) with the model of intellectual capital (Petrash 1996) or framework of knowledge conversions (Nonaka 1994). McAdam and McCreedy (1999) referred to the lack of classification for KM models and proposed, based on a critical review of three different typical model types, an adapted KM model that could be taken as a starting point for further research. The first type called knowledge category models and divide knowledge into different concrete elements. Into this category falls the Model of Nonaka and Takeuchi (1995) that splits knowledge into tacit and explicit knowledge and distinguishes between the processes of socialization, externalization, internalization and combination. The second type of models treats knowledge as an asset in sense on an intellectual capital. A representative model of this category is the intellectual capital model of KM (Chase 1997). The last category includes the socially constructed models for KM and interprets knowledge as a resource that is integrated into the organizational and social learning processes. The KM‐model proposed by Demerest (1997) is kind a model, as suggested by McAdam and McCreedy.
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Nora Fteimi and Franz Lehner Kakabadse et al. (2003) investigated five KM‐models that represent different KM‐perspectives. In summary they examined the philosophy‐based, the cognitive, the network, the community and the quantum model in terms of treatment of knowledge, dominant metaphor, focus, primary aim, critical lever, primary outcomes and the role of IT based tools. Relating to the focus the authors stated that the philosophy based model is interested in ways of knowing, whereas the cognitive model is focusing on the processes of knowledge capture and storage. In contrast, the network model investigates the acquisition of knowledge and the community model aims to find out how knowledge can be created and applied. Finally the quantum model focuses on how to solve and handle complex problems. Lloria (2008) stressed the absence of a common understanding and consensus regarding KM and the different attempts of model classifications. Addressing this gap the author reviewed seven different classifications of approaches, schools and models in this discipline. Lloria also integrated and ordered them in an own classification proposal. In a first approach Andreu and Sieber (1999) identified three main perspectives on KM through information, technology and the culture of the firm. The second perspective refers to McAdam and McCreedy (1999) and was discussed at the beginning of this section. The third perspective picked up four KM‐ orientations (Alvesson and Kärreman 2001) which form the frames of a 2*2 matrix (cf. table 3) and differ according to the mode of management intervention (coordination or control) and the medium of interaction (social or technostructural). Table 3: Classification of Alvesson and Kärreman (Alvesson and Kärreman 2001; Lloria 2008) Medium of interaction Social Technostructural
Mode of management intervention Coordination Control Community (sharing of ideas) Normative control (prescribed interpretations) Extended library (information exchange) Enacted blueprints (templates for action)
The approach by Takeuchi (1995) assigned KM processes to countries or regions and stated that these views are increasingly merging with each other. In doing so the author proposed the following: whereas European countries are interested in the process of measuring knowledge, American ones manage knowledge and Japan is associated with the creating of knowledge. Earl (2001) specified three schools of KM: the technocratic school with its subdivisions into the system, the cartographic and the engineering school, the economic school and the behavioral school with its subdivisions into the organizational, the spatial and the strategic school. Swan and Scarbrough (2001) distinguished between the perspectives of codification of knowledge and creation/sharing of knowledge. The last discussed approach refers to Moreno‐Lozón et al. (2001) and distinguished between the knowledge‐based theory of the firm and KM. To order these seven classifications Lloria proposed an own classification taking the approach of Takeuchi, whilst being the broadest approach, as a starting point and framework to order and classify the other approaches. Vorakulpipat and Rezgui (2008) examined and evaluated different models which fall into the category of knowledge creation models. First, the authors highlighted Nonaka’s SECI model (Nonaka et al. 2000) that differentiate between the processes of socialization, externalization, internalization and combination. Subsequent they presented four models namely the extended SECI model (Uotila et al. 2005), the 7c model (Oinas‐Kukkonen 2004), the combined research model (Heinrichs and Lim 2005) and the community‐based model (Lee and Cole 2003). Similar to the studies discussed in subsection 3.1 (cf. Subsection 3.1) the studies of this category reflect different perspectives on KM models and approaches. Some papers discuss KM models and approaches in terms of related processes and activities as in the study of Vorakulpipat and Rezgui (2008). Other researchers propose general own classification schemas or taxonomies to classify existing models and frameworks (cf. (Lloria 2008) or (Holsapple and Joshi 1999)). The frameworks enable research and practitioners to get an overview of existing related work. Thus, the choice process to find a suitable approach or model is simplified and can be carried out faster.
3.3 Classification proposals for knowledge management systems Depending on the intended use, the literature contains a variety of different classification proposals for knowledge management systems.
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Nora Fteimi and Franz Lehner One of the most frequently used approaches described KMS according to their support for the processes in the knowledge life cycle e. g. transfer, storage and retrieval, transfer, application, socialization, internalization, combination and externalization (e. g. Alavi and Leidner 2001; Beccera‐Fernandez and Sabherwal 2011; Carvalho and Ferreira 2011). Each one of these processes can be facilitated through the use of several technologies such as web 2.0‐based systems, workflow‐ and modeling systems, business intelligence‐systems, knowledge portals, databases and expert systems. Binney (2001) developed a KM‐spectrum that should help organizations implementing KM. One of the elements of this spectrum described taxonomy for KMS based on six theoretical KM‐approaches: transactional KM, analytical KM, asset‐Management‐KM, process‐based KM, developmental KM and innovation‐based KM. The technological support can be achieved by using e. g. expert systems and semantic networks in context of transactional KM, workflow and process modeling systems in context of the process‐based KM and groupware systems or simulation technologies in context of an innovation‐based KM. Saito et al. (2007) followed a strategy‐oriented approach and classified KMS according to their support for strategy. The authors distinguished three types of technologies: component technologies, KM applications and business applications. All three categories can be subdivided into collaboration, dissemination, discovery and repository technologies and support the creation or transfer of knowledge according to a personalization or even a codification approach. Liao (2003) did a literature review and classified 234 articles on knowledge management applications from 1995 to 2002. In his framework, he made a distinction between seven categories of technologies: KM frameworks, knowledge‐based systems, data mining, information and communication technology, artificial intelligence, expert systems, database technology and modeling. All of the 234 reviewed papers were assigned to one of the proposed categories. Furthermore several applications of the categories mentioned in the framework were identified. Jennex has suggested to classify the systems based on the context content captured in the system into process/task based KMS or generic/infrastructure KMS (Jennex 2006). This is grounded on the idea that using knowledge in a correct manner depends on a common understanding of the context in which this knowledge was generated and used. Besides the above taxonomies, numerous other attempts of KMS‐classifications can be found in literature. Since the focus of this study lies on frameworks proposed in high ranking scientific journals and conference proceedings (cf. chapter 2) we did not consider frameworks published in books. Summing up, KMS‐ classifications are diversified due to different approaches and heterogeneous technologies and applications. Some approaches are process‐oriented; meanwhile other are more strategy oriented or even technology or context oriented. Nevertheless, this diversity may sometimes be helpful depending on the considered context and application.
4. Conclusions and outlook Based on a systematic literature review this paper provides an overview of several classification proposals for KM‐frameworks. The classifications were categorized according to four self suggested categories: Meta‐ analysis in KM, classification proposals for models, schools and approaches in KM, classification proposals for knowledge management systems and classification proposals for KM in general. After a categorization and classification of the identified frameworks, the frameworks were systematically compared and reviewed with regard to their research aims and applicability in research and practice. To observe is the lack of a common understanding of definitions as in the case of describing models or approaches for KM (cf. subsection 3.2). Some studies used the term model, others referred to approaches or schools of thought. Future research should take this into account to consolidate and unify used terms and definitions. Thus helps in creating one common understanding and enable to foster discussion in the KM community. Moreover the variety and huge amount of different existing classification proposals could hinder the process of selecting the right classification proposal e. g. in enterprises which implement KM. Nevertheless it could be helpful to choose from a variety of proposals regarding the intended purpose and application area.
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Nora Fteimi and Franz Lehner We contribute to research by presenting a first step towards consolidation and obtaining a single common understanding of the KM‐discipline. One unified view helps to reflect the research field with its core values, assumptions and attitudes, and ensures that the developments in this field progress towards specific goals. The systematic comparison and the proposed categorizations of the frameworks can be used as a starting point for further research in order to get an overview of the state of the art and to classify new research projects. In regard to the practical impact, businesses receive a guide that offers help and direction in introducing and implementing KM within the company.
References Alavi, M. and Leidner, D.E. (2001), “Knowledge Management and Knowledge Management Systems: conceptual Foundations and Research Issues”, MIS Quarterly, Vol. 25 No. 1, pp. 107–136. Alvesson, M. and Kärreman, D. (2001), “Odd couple: making sence of the curious concept of knowledge management”, Journal of Management Studies, Vol. 38 No. 7, pp. 995–1018. Andreu, R. and Sieber, S. (1999), “La gestion integral del concimiento y del aprendizaje”, Economica industrial, Vol. 326, pp. 63–72. Asl, N.S. and Rahmanseresht, H. (2007), “Knowledge Management Approaches and Knowledge gaps in Organizations”, Managing worldwide Operations & Communications with Information Technology, pp. 1427–1432. Azmi, M. Al and Zairi, P.M. (2005), “Knowledge Management: A Proposed Taxonomy”. Becerra‐Fernandez, I. and Sabherwal, R. (2011), “The role of information and communication technologies in knowledge management: A classification of knowledge management systems”, In Schwartz, D. and Te’eni, D. (publ.): Enzyclopadie of knowledge management. IGI global, Hershey; PA. Binney, D. (2001), “The knowledge management spectrum ‐ understanding the KM landscape”, Journal of Knowledge Management, Vol. 5 No. 1, pp. 33–42. Vom Brocke, J., Simons, A., Niehaves, B., Reimer, K., Plattfaut, R. and Cleven, A. (2009), “Reconstructuring the Giant: On the importance of rigour in the literature search process”, ECIS 2009 Proceedings Paper 161. De Carvalho, R.B. and Ferreira, M.A.T. (2011), “Knowledge management software”, In Schwartz, D. and Te’eni, D. (publ.): Enzyclopadie of knowledge management. IGI global, Hershey; PA. Chase, R. (1997), “The knowledge based organisation: an international survey”, Journal of Knowledge Management, Vol. 1 No. 1. Cooper, H. (1998), “Organizing Knowledge Syntheses: A Taxonomy of Literature Reviews”, Knowledge in Society 1, In: Knowledge in Society 1. 1988. Demerest, M. (1997), “Understanding knowledge management”, Journal of Long Range Planning, Vol. 30 No. 3, pp. 374– 84. Earl, M. (2001), “knowledge management strategies: toward a taxonomy”, Journal of Management Information Systems, Vol. 18 No. 1, pp. 215–233. Fettke, P. (2006), “State‐of‐the‐Art des State‐of‐the‐Art Eine Untersuchung der Forschungsmethode „ Review “ innerhalb der Wirtschaftsinformatik”, Wirtschaftsinformatik, Vol. 48 No. 4, pp. 257–266. Heinrichs, J. and Lim, J. (2005), “Model for organizational knowledge creation and strategic use of information”, Journal of Amercian Society for Information Science and Technology, Vol. 56 No. 6, pp. 620–629. Heisig, P. (2009), “Harmonisation of knowledge management – comparing 160 KM frameworks around the globe”, Journal of Knowledge Management, Vol. 13 No. 4, pp. 4–31. Holsapple, C.W. and Joshi, K.D. (1999), “Description and Analysis of Existing Knowledge Management Frameworks”, Proceedings of the 32nd Hawaii International Conference on System Sciences, pp. 1–15. Jafari, M., Akhavan, P. and Mortezaei, A. (2009), “A review on knowledge management discipline”, Journal of Knowledge Management Practice, Vol. 10 No. 1, pp. 1–23. Jennex, M.E. (2006), “Classifying Knowledge Management Systems Based on Context Content”, Proceedings of the 39th Hawaii international conference on system sciences, pp. 1–8. Kakabadse, N.K., Kakabadse, A. and Kouzmin, A. (2003), “Reviewing the knowledge management literature: towards a taxonomy”, Journal of Knowledge Management, Vol. 7 No. 4, pp. 75–91. Lee, G. and Cole, R. (2003), “From a firm‐based to a community‐based model of knowledge creation”, Information and Management, Vol. 14 No. 6, pp. 633–649. Lee, M.R. and Chen, T.T. (2012), “Revealing Research Themens and trends in knowledge management from 1995 to 2010”, Knowledge‐Based Systems, Vol. 28, pp. 47–58. Leonard, D. (1999), Wellsprings of Knowledge ‐ Buidling and Sustaining the Sources of Innovation, Harvard Business School Press, Boston, MA. Liao, S. (2003), “Knowledge management technologies and applications—literature review from 1995 to 2002”, Expert Systems with Applications, Vol. 25 No. 2, pp. 155–164. Lloria, M.B. (2008), “A review of the main approaches to knowledge management”, Knowledge Management Research & Practice, Vol. 6, pp. 77–89. Mcadam, R. and Mccreedy, S. (1999), “A critical review of knowledge management models”, The Learning Organization, Vol. 6 No. 3, pp. 91–101.
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Nora Fteimi and Franz Lehner Moreno‐Luzon, M.D., Oltra, V., Balbastre, F. and Vivas, S. (2001), “Apprendiazie organizativo y creacion de conocimiento: un modelo dinamico integrador de ambas corrientes”, In Proceedings of the XI Congreso Nacional de ACEDE. Zaragoza, Spain. Moteleb, A.A. and Woodman, M. (2007), “Notions of Knowledge Management Systems: A Gap Analysis”, The Electronic Journal of Knowledge Management, Vol. 5 No. 1, pp. 55–62. Nie, K., Ma, T. and Nakamori, Y. (2007), “Building a Taxonomy for Understanding Knowledge Management”, Electronic Journal of Knowledge Management, Vol. 5 No. 4, pp. 453–466. Nie, K., Ma, T. and Nakamori, Y. (2009), “An Approach to Aid Understanding Emerging Research Fields — the Case of Knowledge Management”, Systems Research and behavioral Science, Vol. 26 No. 6, pp. 629–644. Nonaka, I. (1994), “A dynamic theory of organizational knowledge creation”, Organization Science, Vol. 5 No. 1, pp. 14–37. Nonaka, I. and Takeuchi, K. (1995), The knowledge creating company: How Japanese companies create the dynamics of Innovation, Oxford University Press, Oxford. Nonaka, I., Toyama, R. and Konno, N. (2000), “SECI, Ba and leadership: a unified model of dynamic knowledge creation”, Long Range Planning, Vol. 33, pp. 5–34. Oinas‐Kukkonen, H. (2004), “The 7C model for organizational knowledge creation and management”, Proceedings of the 5’th European Conference on Organizational knowledge, Learning and Capabilities. Innsbruck. Petrash, G. (1996), “Dow’s Journey to a knowledge value management culture”, European Management Journal, Vol. 14 No. 4, pp. 365–373. Saito, A., Umemoto, K. and Ikeda, M. (2007), “A strategy‐based ontology of knowledge management technologies”, Journal of Knowledge Management, Vol. 11 No. 1, pp. 97–114. Scholl, W., König, C., Meyer, B. and Heisig, P. (2004), “The future of knowledge management: an international delphi study”, Journal of Knowledge Management, Vol. 8 No. 2, pp. 19–35. Serenko, A. and Bontis, N. (2004), “Meta‐review of knowledge management and intellectual capital literature: citation impact and research productivity rankings”, Knowledge and Process Management, Vol. 11 No. 3, pp. 185–198. Serenko, A., Bontis, N., Booker, L., Sadeddin, K. and Hardie, T. (2010), “A scientometric analysis of knowledge management and intellectual capital academic literature (1994‐2008)”, Journal of Knowledge Management, Vol. 14 No. 1, pp. 3– 23. Swan, J. and Scarbrough, H. (2001), “knowledge management: concepts and controversies”, Journal of Management Studies, Vol. 38 No. 7, pp. 913–321. Szulanski, G. (1996), “Exploring Internal Stickiness: Impediments to the transfer of Best Practices within the firm”, Strageic Management Journal, Vol. 17, pp. 27–43. Uotila, T., Melkas, H. and Harmaakorpi, V. (2005), “Incorporating futures research into regional knowledge creation and management”, Futures, Vol. 37 No. 8, pp. 849–866. Vorakulpipat, C. and Rezgui, Y. (2008), “An evolutionary and interpretive perspective to knowledge management”, Journal of Knowledge Management, Vol. 12 No. 3, pp. 17–34. Wiig, K. (1993), Knowledge managment foundations, Schema Press, Arlington.
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Organizational Characteristics That Influence the way Middle Managers and Their Subordinates are Available to Each Other Zoltán Gaál, Lajos Szabó, and Anikó Csepregi University of Pannonia, Department of Management, Veszprém, Hungary gaal@gtk.uni‐pannon.hu szabola@gtk.uni‐pannon.hu csepregia@gtk.uni‐pannon.hu Abstract: How knowledge is shared by organizational members plays an essential and central role in the success of their organizations. We should remember that those taking part in the knowledge sharing process also benefit from it. Middle managers after playing a significant role in the vertical communication their organization influence the knowledge sharing process within their organization as well. Our paper makes an attempt to present those organizational characteristics of middle manager’s organizations that result in differences in their maturity of knowledge sharing. The method and results of revealing these differences are introduced in this paper. Since 2007 an empirical survey has been conducted during which 400 middle managers working at medium‐ and large‐sized enterprises in Hungary have been investigated by a questionnaire. The answers of this survey have been analysed first using decision tree than using analysis of variance or post hoc test. Our paper presents one of the elements of middle managers’ maturity of knowledge sharing which is the availability among middle managers and their subordinates. According to our research availability is the time and willingness of a person to find the time to help other colleagues when they ask for help. The investigated organizational characteristics are the type, the activity and the customer claims fulfilled by the middle managers’ organizations. Findings of the research have indicated that difference has be found in the availability among the middle managers and their subordinates who work at medium and large sized enterprises in Hungary on the basis of at least one of the organizational characteristics which are the type and the activity of the investigated organizations. Keywords: availability, knowledge sharing, maturity, middle managers, Hungary
1. Introduction Knowledge sharing (KS) is considered to be a fundamental means through which organizational competitive advantage can be reached (Jackson et al. 2006). The way knowledge is shared within the organization is essential and central not only to the success of the organization where it takes place but also among those who share it. The sharing of knowledge requires the employee’s willingness to collaborate with each other within an organization since their reluctance indisposition to share knowledge can result in inaccurate, incomplete, ill‐ timed knowledge sharing or in some cases in knowledge sharing based on false information (Assudani, 2005; Zboralski, 2009, Casimi et al., 2012) Inspite all of these features, many employees lack the desire to share their knowledge with others (Denning, 2006).
2. Theoretical background 2.1 Middle managers There has not been a universally accepted definition of middle managers, in the recent literature. While Chandler (1977) emphasised that middle managers’ jobs cover exclusively the supervision of the lower hierarchical levels, now a large body of literature discusses their role in other fields. Bower (1986:297‐298) emphasises that middle managers are the only ones within their organization “who are in a position to judge whether issues are being considered in the proper context”. From another viewpoint Uyterhoeven (1989:136) argues that a middle manager is someone “who is responsible for a particular business unit at the intermediate level of the corporate hierarchy”. Ireland (1992) provides a more concrete definition regarding middle managers and describes them as employees working between an organization’s first‐level and top‐level managers. Furthermore their jobs contain the integration of “the intentions of top‐level managers with the day‐to‐day operational realities experienced by first‐level managers” (Ireland, 1992:18). This article defines middle managers as being those employees who work below the top management of the organisation—the CEO and / or top managers—and who are responsible for and work with employees hierarchically lower than themselves.
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2.2 Knowledge sharing Regarding the definitions of KS, it is mainly described as an activity during which information or other important contents are shared (Bartol, Srivastava, 2002; Möller, Svahn, 2004; Li, 2010). The approach of Bartol and Srivastava (2002) contains information as an element of knowledge sharing and defines it as the action in which relevant information is diffused by employees to others across the organization. Möller and Svahn (2004:220) emphasize that knowledge sharing is “sharing not only codified information, such as production and product specifications, delivery and logistics information, but also management beliefs, images, experiences, and contextualized practices such as business‐process development”. Li (2010:40) defines knowledge sharing as an activity “in which participants are involved in the joint process of contributing, negotiating and utilizing knowledge”. After reviewing these definitions it can be seen that neither do they deal with middle managers and nor they investigate elements that are important regarding the knowledge sharing of middle managers. This has inspired us to create our own definition of knowledge sharing from the combination of the above mentioned ones. Thus our research defines knowledge sharing as a two‐way process (giving and receiving knowledge) between the knowledge giver(s) and the knowledge receiver(s), who as participants of knowledge sharing, exchange the knowledge found in their minds or the knowledge found in electronic or paper documents. Furthermore knowledge sharing can occur at the same time when the participants are present or at different times when they make their knowledge explicit.
2.3 Measurement of knowledge sharing According to Turner and Minonne (2010:167) “in many organisations there is no synchronised approach to measuring the effects of KM practices”. For lack of the synchronised approaches to measure these effects in the following however we make an attempt to review the various measurements of knowledge sharing to reveal those approaches that measure the management of knowledge in organizations. The majority of studies have measured individual knowledge sharing from the point of view of willingness (or intention) of employees towards knowledge sharing or investigated self‐reported knowledge sharing behaviours (Lin 2007; Jiacheng et al. 2010). In other studies knowledge sharing has been influenced by the organization (Yang, Chen 2007; Bosua, Scheepers 2007) and thus the organizational perspective has been dominant in the research. While other research has been conducted from the behavioural perspective (Bock et al. 2005; Matzler et al. 2008; Chow, Chan 2008) and knowledge sharing has been influenced by individual behaviour. Since the above mentioned research did not investigate middle managers, their individual characteristics and their knowledge sharing our research focuses on these fields. Regarding middle managers’ knowledge sharing we have considered and investigated the development level of middle managers’ vertical and horizontal relationships. Analysing these relations draw attention to the fact that our research is not an investigation concerning middle managers’ leadership function in which only middle manager‐subordinate relationships are examined. Our research investigates the knowledge sharing function and focuses on how mature the function of knowledge sharing is. The development level of this knowledge sharing function is called maturity. Availability, investigated deeper in this paper, is an element of middle managers’ maturity of knowledge sharing (Gaál et al. 2012a), and represents the time and willingness of a person to find the time to help other colleagues when they ask for help. Concerning availability it has been revealed by Kankanhalli et al. (2005) that knowledge sharing can appear as a result of reciprocation or simply as the enjoyment of helping others as well. Furthermore the middle managers’ investigated individual characteristics are their age, working years and functional area at their organizations.
3. Empirical study 3.1 The purpose of the research and the research question The purpose of our research has been to reveal those components of organizational characteristics that result in differences in the availability among those middle managers and their subordinates who work at medium‐ and large‐sized enterprises in Hungary.
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Zoltán Gaál, Lajos Szabó, and Anikó Csepregi Regarding this purpose the following question has been needed to be answered: Question: How do organizational characteristics (the type, the activity, the customer claims) influence the availability among the middle managers and their subordinates who work at medium‐and large‐sized enterprises in Hungary? In order to answer the research question the following Hypothesis has been stated: Hypothesis: Difference can be found in the availability among the middle managers and their subordinates who work at medium‐ and large‐sized enterprises in Hungary on the basis of organizational characteristics. The arrows in Figure 1 represent the elements that are examined regarding this Hypothesis.
Figure 1: Elements under investigation
3.2 Data collection The data collection has been supported by Department of Management, University of Pannonia since 2007. 4000 medium‐ and large‐sized enterprises in Hungary covering a wide range of economic sectors were selected randomly from the average number of 5780 of such enterprises and were sent questionnaires, by post or electronically, with the request to be filled in by at least one middle manager. The questionnaire of the survey comprised seven categories: 1, Structure Oriented Features; 2, Organizational Culture; 3, Leadership; 4, Knowledge Management Programs; 5, Individual Competences; 6, Maturity of Knowledge Sharing, 7. General Information. Maturity of Knowledge Sharing has contained questions regarding the extent of availability and usefulness of knowledge based on a 5‐point Likert scale. Availability among the middle managers and their subordinates, which is investigated here, is an element of middle managers’ maturity of knowledge sharing. It consists of the availability of the investigated middle managers’ subordinate towards the investigated middle managers and the investigated middle managers’ availability towards their subordinates. It has been revealed with principal component analysis. (Gaál et al., 2012a). General information includes the three investigated features of the enterprise of the middle managers: the type, the activity and the customer claims fulfilled by the organizations. These are investigated here as organizational characteristics. The type of the middle manager’s organization contains the following combination the organization: national or foreign owned, privately or state owned. The activity of the middle manager’s organization aims to reveal which activity dominates within the organization: the service or the production. Only the categories concerning customer claims fulfilled by the middle manager’s organization, that refers to the demand by the customer, consists of questions containing answers based on a 5‐point Likert scale in which the two extremes are not changing and fix customer claims, and often changing and complex customer claims. The answers for this category have been also divided into two groups. This paper focuses on these topics however other parts of the questionnaire were already published [e.g. maturity of knowledge sharing (Gaál et al. 2012a), availability influenced by individual characteristics (Gaál et al. 2012b) competences found important for knowledge sharing (Szabó, Csepregi 2011)]. Since 2007, 400 completed questionnaires were returned from middle managers in manufacturing / production, maintenance, logistics, finance / accountancy / controlling, quality management, human
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Zoltán Gaál, Lajos Szabó, and Anikó Csepregi resources, project management, commerce / purchase / sale / marketing, and research and development. The organisations they represented were in commerce, building trade, processing, logistics / warehousing, mining, telecommunications, agriculture, tourism / catering, education, government, healthcare / social support, estate agency, financial intercession, information technology, electricity / gas / fume / water supply, and other economic sectors — and were involved either only in production activity, or mainly in production activity, or mainly in service activity, or only in service activity.
3.3 Available methods for testing the hypothesis After the usage of decision tree alternating conditional expectations or (multivariate) analysis of variance and post hoc test could be applied for testing the hypothesis.
3.4 Method chosen for testing the hypothesis We have decided to use the method of a decision tree to reveal the differences within the investigated element of maturity of knowledge sharing (availability among the middle managers and their subordinates) regarding the influencing factors. By using organizational characteristics as influencing factors it has been possible to reveal classes within the investigated elements. After separating these classes with the usage of decision tree, we have compared in pairs the group means of these classes with the use of analysis of variance. This has been followed by the step when the groups with the most favourable results within each class have been separated from the groups with the least favourable results. The groups with the most favourable results contain high value for availability, while the groups with the least favourable results consist of low value for availability. Knowing this, we have combined the most and the least favourable results and based on these combinations additional subgroups have been formed. Depending on the number of these subgroups from the available three methods we have chosen an analysis of variance or post hoc test, since we have aimed to reveal whether significant differences exist based on organizational characteristics in the availability among the middle managers and their subordinates.
3.5 Results In this part of the Empirical study the main results using the methods mentioned above are presented. 3.5.1 Results of decision tree During the investigation based on organizational characteristics the classes found in Figure 2 have been revealed with the usage of a decision tree.
Figure 2: Classes revealed within the availability among the middle managers and their subordinates based on organizational characteristics
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Zoltán Gaál, Lajos Szabó, and Anikó Csepregi Within the availability among the middle managers and their subordinates element classes have been revealed regarding organizational characteristics primarily by the type of the investigated organization and secondly by the activity of the investigated organization. The type of the investigated organization is the strongest classifier, while the activity of the investigated organization is the second strongest classifier. This means that the availability among the middle managers and their subordinates is primarily influenced by the type and secondly by the activity of the organization. 3.5.2 Results of analysis of variance and post hoc test The methods of analysis of variance or post hoc test have been used on the classes revealed by the decision tree. With the usage of analysis of variance we have compared in pairs the group means of the classes identified by the decision tree within the availability among the middle managers and their subordinates. Following this step, groups with the most favourable results within the availability among the middle managers and their subordinates have been separated from the groups with the least favourable results. The separated classes according to being the most and the least favourable ones can be seen in Table 1. Table 1: The most and the least favourable classes based on organizational characteristics
Further analysis has been needed when by using a decision tree more than two classes have been formed as a result of organizational characteristics as influencing factors. In this case with the combination of the most and the least favourable results of the classes within availability among the middle managers and their subordinates, additional groups have been formed. On these groups we have conducted a post hoc test, since the post hoc test compares pairwise all combinations of group means (Field 2005) and investigates whether these means significantly differ. To prove that the means of the new groups with the most and the least favourable results actually differ first we have conducted a Levene’s test of homogeneity of variance. With Levene’s test it has been possible to determine whether the variance within the investigated groups has been homogeneous (Sajtos, Mitev 2007) and to decide whether Tamhane or LSD tests should be used during the post hoc analysis. When variances are assumed to be equal (variances have been homogeneous) as the result of Levene’s test the LSD test can be used and when variances are not assumed to be equal (variance were not homogeneous) the Tamhane test can be applied. We have combined the most and the least favourable results of the type and the activity of the investigated organization regarding the organizational characteristics. Based on these combinations four‐four groups have been formed. Within the availability among the middle managers and their subordinates element these groups contain the following combinations: the most‐most, the most‐least, the least‐most, the least‐least favourable results (Figure 3). In most cases the combination of the most‐most group shows the highest mean value and the combination of the least‐least group results in the lowest mean value. However in this case both elements are exceptions, since regarding the availability among the middle managers and their subordinates element the combination of the most‐least favourable results show the highest mean value. Furthermore the combinations which have not belonged to the most and the least favourable results have been left out of the analysis (foreign owned‐production, foreign owned‐service). Further analysis has been needed to reveal whether the mean value of the group with the most favourable result has significantly differed from the mean value of the group with the least favourable results. Thus the mean value of the groups with the most‐most favourable result have been compared with the mean values of the groups with the least‐least favourable result in order to reveal whether significant difference can be found between them. Although the most‐least favourable results show the highest mean value in Figure4, we have used the combination of the most‐most favourable result in order to be able to prove that the means of the groups with the most and the least favourable results differ. The group with the most favourable knowledge sharing result has consisted of national and state owned organizations which produce mostly and only physical
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Zoltán Gaál, Lajos Szabó, and Anikó Csepregi products. On the other hand the group with the least favourable knowledge sharing result has included national and privately owned organizations that provide mostly and only services.
Figure 3: The group means based on organizational characteristics The results of the group means of the four groups within the availability among the middle managers and their subordinates have been compared and can be found in Table 2. Table 2: The ANOVA result based on individual characteristics
The statistical significance of the F test in the ANOVA has only shown that there has been at least one significant difference in the means, but it has not proved that the means of the groups with the most and the least favourable results have significantly differed. Thus further analysis has been carried out to find out whether the two investigated groups really differ. The post hoc test has been chosen in which all different combinations of the investigated groups have been compared with pairwise comparisons. However to determine which (Tamhane or LSD) test should be applied during the post hoc analysis, the test of homogeneity of variance has been conducted. Table 3: The result of the test of homogeneity of variances based on individual characteristics
The 0.475 significance level of Levene’s test of homogeneity of variance has been above the accepted limit of 0.05. Thus the variances of the investigated groups have been homogeneous (equal) and as a result of which the LSD test had to be used during the post hoc test to account for whether the investigated groups have been significantly different.
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Table 4 shows the results obtained by LSD test which presents that there have been significant differences between the mean values of the groups with the most and the least favourable results. Based on these results the following statements can be made: Whilst those middle managers who primarily have worked at rather national and state owned organizations and secondly have worked at organizations which produce mostly and only physical products are also more available for their subordinates and vica versa. While those middle managers who primarily have worked instead at national and privately owned organizations and secondly have worked at organizations which provide mostly and only services are less available for their subordinates and vica versa. 3.5.3 Summary of the results The analysis above proves that significant differences have been revealed within the availability among the middle managers and their subordinates regarding individual characteristics. Table 5: Summary of the results
Figure 4 demonstrates the research model emphasising the revealed relationship between individual characteristics and the availability among the middle managers and their subordinates.
Figure 4: Revealed relationships Based on the above mentioned results the following Thesis can be stated. Thesis: Difference is found in the availability among the middle managers and their subordinates on the basis of organizational characteristics primarily by the type and secondly by the activity of the middle manager’s organization. The Thesis shows that those middle managers who primarily have worked at national and state owned organizations and secondly have worked at organizations which produce mostly and only physical
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Zoltán Gaál, Lajos Szabó, and Anikó Csepregi products are more available for their subordinates and vice versa. Additionally, those middle managers who primarily have worked at national and privately owned organizations and secondly have worked at organizations which provide mostly and only services are less available for their subordinates and vice versa. 3.5.4 Interpretation of the Results Within state owned organizations since the middle mangers and their subordinates are not afraid of loosing their jobs and since fierce competition does not exist within the organization, they can find time for helping each other. On the other hand, apart from the red‐tapism, the rules and regulations that surround them, they also have time for each other, when needed because they work in the same area. This is also confirmed by Willem and Buelens (2007), according to whom formal systems are less effective in facilitating the sharing of knowledge. The availability within the same area between the middle managers and their subordinates is thus the key to success. Furthermore if an organization produces products, the different work areas are separated and the middle managers and their subordinates belong to the same area, this also helps the availability between the middle managers and their subordinates. Since on this level again in case of problem appearing during the production or related activities it fosters subordinates to be available and help solving it, since it is in their interest as well. The fierce competition that exists at privately owned organizations also determines the relationship of the middle managers and their subordinates. In such situations the middle managers assume that their subordinates know what they need to know and they can accomplish their work without their help. This may result in a gap between them. Especially in organizations providing services damages occur when individual features dominate, because as a result of this approach the middle manager and the subordinates are not motivated to work together and thus they are less available to each other.
4. Significance of the research results and the future plans The results of our research could help not only the middle managers of medium‐ and large sized enterprises in Hungary but also other employees. Thus these beneficiaries of this research will be able to determine which organizational characteristics affect the availability among middle managers and their subordinates. As a continuation of our research the following options could be taken into consideration:
if our research is carried out among middle managers in a few years changes regarding organizational characteristics could be revealed;
if our research is extended to other countries then the Hungarian results of our research could be compared with the results of other countries considering the national cultural differences as well.
Research partners have been found in Bulgaria, Croatia, Romania and Serbia with the help of whom our research has been extended. As a result of the extension of our research we will be able to compare these countries’ results. Since these countries show similarities and/or differences regarding national culture, the results from these countries should also take into consideration the features and influences of national culture background as well (Heidrich 2002; Szabó et al. 2010).
5. Conclusion This paper has presented the results of an empirical research that has been conducted since 2007 among 400 medium‐ and large‐sized enterprises in Hungary. The paper has focused on the research methodology and the results of data analysis. Findings of the research have indicated that difference has been found in the availability among the middle managers and their subordinates who work at medium and large‐sized enterprises in Hungary on the basis of at least one of the investigated organizational characteristics which are the type and the activity of the organization. Our findings have drawn attention to the fact that further examination would be needed in the future to reveal other influencing factors as well that influence the availability among the middle managers and their subordinates.
Acknowledgements This article was made under the project TÁMOP‐4.1.2.A/1‐11/1‐2011‐0088. This project is supported by the European Union and co‐financed by the European Social Fund
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A Knowledge‐Based Reference Model to Support Demand Management in Contemporary Supply Chains Sotiris Gayialis, Stavros Ponis, Ilias Tatsiopoulos, Nikolaos Panayiotou and Dimitrios‐ Robert Stamatiou National Technical University of Athens, School of Mechanical Engineering, Sector of Industrial Management and Operational Research, Athens, Greece sotga@central.ntua.gr staponis@central.ntua.gr itat@central.ntua.gr panayiot@central.ntua.gr drstam@central.ntua.gr Abstract: Supply Chain Management (SCM) has been in the epicenter of numerous research efforts for, at least, the last two decades. One of the most prominent issues identified in literature, directly related with Supply Chain Integration and Collaboration, is information sharing between supply chain entities, especially for planning and monitoring purposes. The establishment of efficient mutual information sharing mechanisms and the transformation of meaningful information into actionable knowledge is an object of continuous research amongst academics and supply chain practitioners all over the world. The scrutiny of literature sources not only leads to the identification of a specific thematic area dealing with the applications of Knowledge Management (KM) to support decision making and enhance Supply Chain integration, planning and coordination, but also brings to light a significant gap regarding the application of KM for demand variability management and demand – supply alignment purposes. This paper aims to bridge the identified gap by providing a methodology for developing a knowledge enhanced reference model for supply chain operations, focusing on demand management across the supply chain network. The resulting reference model will be able to indicate critical activities and decision points for demand variability and to monitor demand variations through intra‐ and inter‐organizational processes. For this purpose, reference model integrates different modeling views for the various business process perspectives, such us decision view, risk view and knowledge view. The proposed methodological approach utilizes a set of process modeling methods for the construction of the reference model, consisted of a set of reusable business process models, which can be applied and specialized in various industries to support decision making for demand management. The generic reference model resulting from the application of the methodological approach incorporates and transfers insights and experiences from other well‐established process reference models and case studies to those organizations that adopt the model in order to design or redesign their supply chain business processes. Keywords: demand management, supply chain, reference model, knowledge management, business processes
1. Introduction Knowledge is a powerful asset to whoever possesses it. It is even greater if one knows how to take advantage of the positive effects it offers. There is no exception in the science of SCM. Especially when knowledge concerns how demand fluctuations affect the supply chain. Knowledge is created in and between the participants of a supply chain through the process of filtering and documenting the information that flows along the supply chain. Existing reference models intend to lead organizations that implement them to a state of high efficiency in their supply chains through modeling and measuring the supply chain processes. Although these reference models tend to get more complex and cover more aspects of the supply chain, none of them has attempted to approach the knowledge creation and management aspect. This article attempts to describe the process of creating and sustaining a knowledge‐based reference model supporting demand management in contemporary supply chains. To this end, a literature review is presented in the following three sections covering the current reference models on supply chain process modeling, knowledge modeling and demand management. An applied methodology for developing the supply chain reference model follows, presenting the necessary steps. The flow of knowledge transfer in the proposed reference model is described and the article is summed up in the final section where conclusions and directions for further research are presented.
2. Supply chain process modeling Porter’s value chain model (Porter, 1985) describes a high‐level chain of processes common to all businesses and establishes that core processes like inbound logistics, production operations or outbound logistics are those that add value to the products or services delivered by a company. Since then, most process modeling efforts are dealing with the value created for companies and their customers. In today’s business environment,
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Sotiris Gayialis et al. supply chains involve a number of autonomous organizations. The nature of supply chain processes with inter‐ organizational activities, involving different enterprises, calls for their design, analysis, control and evaluation in a well‐designed and structured manner (Panayiotou et al., 2010). The increasing importance of business processes inevitably puts process models, in the epicenter of the majority of the efforts for achieving the required interoperability and agility in dynamic supply chains (Ponis, 2009). As a consequence, it is necessary to design new or adjusted business process models rapidly and at low cost. This can be achieved by reusing knowledge captured in reference process models. A reference model depicts structures, attributes, relationships and behaviors of objects for a given domain. It is represented in a general, reusable and applicable form, so that specific application models can be created by adaptation and modification. It serves as a recommendation and framework for future modeling and design tasks (Klingebiel, 2008). In demand‐driven supply chains, reference process models should support the diversity of configurations in various industries. Although standard blueprints do not always comply with such an approach, Verdouw et al. (2010) argue that reference models should be set up as configurable models that enable rapid instantiation of specific supply chain configurations. In the current literature the efforts to create generic models applied to supply chains are scarce. According to Fettke et al. (2005) thirty reference models are documented in literature, of which only two refer to supply chains, a) the SAP R/3 Reference Model and b) the Supply Chain Operations Reference Model (SCOR model). The SAP R/3 reference model is a publicly available model that contains more than 600 non‐trivial process models and 10.000 submodels, expressed in terms the ARIS typology, mostly EPC diagrams in particular (Mendling et al., 2006). The SCOR model is a reference model for designing and implementing supply chain operations (Supply Chain Council, 2010). As a standard for supply chains, SCOR model provides standard terminology and representations of supply chain processes. It provides a unique framework that links business process, metrics, best practices and technology into a unified structure to support communication among supply chain partners and to improve the effectiveness of SCM and related supply chain improvement activities. A further survey for available articles on business process modeling and reference models, utilizing mostly the variety of tools provided by the Scopus and Springerlink databases, reveals that most writers tend to use the aforementioned models and adapt them to specific cases (company cases, industry specific cases). Two articles stand out for their efforts to build a generalized reference model that supports demand management. The first comes from Verdouw et al. (2011), who present a framework based on the terminology and definition of SCOR processes. They use the Viable System Model (VSM) and Business Process Modeling Notation (BPMN) logic to create a toolkit for modeling the supply chain processes. Next, they apply the presented toolkit to a process in the Dutch flower industry. Secondly, Klingebiel et al. (2008) attempt to create a build‐to‐order reference model focusing on high‐level process characteristics in the automotive industry. In addition the authors define the framework for build‐to‐order concepts leading to the adaptability of the model in other industry cases. Although these models cover vast areas of the supply chain, there is very little or no specific references and model support on how organizations should manage or model the knowledge that is created by the processes executed. In the next section, a short literature review on knowledge modeling is provided.
3. Knowledge modeling A detailed look in contemporary literature proves that knowledge management (KM) attracts the interest of scientists from a wide range of disciplines, mainly organizational science, strategy and management science, computer science, as well as management information systems that have attempted to define and structure the KM domain and thus, provide guidance to practitioners (Ponis et al. 2008). In the SCM context, knowledge constitutes a dynamic and essential asset which is generated, passed on, used, and in turn, contributes to its regeneration. In order for this to happen, an intensive cooperation and an open real‐time knowledge exchange between participants in the global supply chain information environment are required, so that the right knowledge from distributed sources can be integrated, transferred and utilized in an efficient way to support important supply chain decisions and demand variability management in particular. Surprisingly, despite the wide acceptance and the proliferating implementations of KM, many organizations have failed to realize its expected results and, as presented in the next section, literature proves that KM
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Sotiris Gayialis et al. applications for SCM and demand management in particular are scarce and fragmented. According to Ponis et al. (2009), these failures and shortcomings form the ground for severe criticism, which cannot be easily overlooked, thus the need for the design and development of a reference model, integrating methods, processes, tools, and knowledge resources in a holistic fashion, is of great significance. Nonaka and Takeuchi (1995) described the knowledge transformation process within organizations and proposed a spiral knowledge model with four tacit and explicit knowledge conversion mechanisms: socialization, externalization, internalization, and combination. The spiraling knowledge interaction between explicit and tacit knowledge set the basis for individual, group and organizational learning and innovation. Since then, numerous efforts have been made in the area of knowledge modeling and standardization of KM processes, in other words creating generic models and frameworks, which provide transparency by achieving a common understanding and a common terminology for all involved parties. Such a model is the Fraunhofer IPK Reference Model for KM (Heisig, 2000). This model integrates Knowledge Management into daily business processes, which are seen as the application fields of knowledge, integrating the knowledge domains and providing context. Another model is the Knowledge Chain Model (Holsapple and Singh, 2001). It identifies five major knowledge manipulation activities that occur in various patterns within KM episodes and four major managerial influences that affect the knowledge manipulation activities. The model is further decomposed since both primary and secondary activities involve sub‐activities, in the form of actual business actions that instantiate the high level processes of the model (Holsapple and Joshi, 2005). Narrowing down the literature search on research efforts aiming to conceive, develop and apply KM enhanced process reference models to support supply chain integration, planning and coordination, brings to light a significant gap regarding the application of KM for demand variability management and demand – supply alignment purposes. In this paper, the authors will attempt to realize the different views of supply chain processes, including function, information, decisions, and organization view taking into account the supply chain risk dimension that affects the demand variability throughout the supply chain. In order to understand how demand management and knowledge management intertwine, the following section presents a review on demand management.
4. Demand management in supply chains Demand management is the creation, across the supply chain and its markets, of a coordinated flow of demand (Mentzer et al., 2007). This flow is managed by various processes in any global supply chain, like sales forecasting and demand planning (Mentzer and Moon, 2004). Sales forecasting is used to estimate the independent demand which is derived from the final customer of the supply chain. Demand management is not limited to sales forecasting but it includes the planning of derived and dependent demand between members of supply chain. Demand management processes are becoming important as part of the evolving breadth of SCM (Lapide, 2006). Demand management is strongly related to effective SCM, as this process can match supply with demand and execute the plan with minimal disruptions, increasing flexibility, and reducing variability. According to Croxton et al. (2002) demand management is a process that balances the customers' requirements with the capabilities of supply chain. Information sharing between members of the supply chain has been shown to significantly affect the total effectiveness and profitability (Shaw et al. 2003). Furthermore, recent literature (Koh and Gunasekaran 2006; Dwivedi and Butcher 2009; Esper et al. 2010; Marra et al., 2012) has stated that in order to succeed in SCM, an organization must possess and share knowledge about the different aspects of the supply chain. Knowledge management can enhance the degree of success of existing SCM efforts as well as increase the likelihood of success of new SCM undertakings. Although knowledge management has been emerged as a hot issue in SCM, there is little literature in knowledge management for demand variability management and demand‐supply alignment purposes. Kahn and Adams (2000) identified the relationship between demand and knowledge management early and they discussed how companies might envision sales forecasting as a knowledge management process, from the perspective of managing intelligence exchange networks to support the sales forecasting process. Since then, little work has been done on the subject. Moreover, there are no knowledge‐based reference models in the current literature, for demand management in supply chains.
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5. An applied methodology for supply chain reference model development The proposed methodology aims at the creation of a supply chain reference model which is focused on demand management. The emphasis on demand is given through demand variability management and decision making along the supply chain. For this purpose, the reference model incorporates a set of modeling methods for the different business process perspectives, such as decision view, risk view or knowledge view, trying to control the factors that influence demand management. The supply chain reference model resulting from the proposed methodology is a generic reference model which can be applied and specialized in various industries to support decision making for demand management. The methodological approach is depicted in Figure 1 and discussed later in this article.
Figure 1: Reference model creation methodological approach Step 1: Review of demand management theoretical background As illustrated in Figure 1 the first step for the development of the supply chain reference model for demand management is the review of contemporary theories and practices for demand management. Current trends in sales forecasting, demand planning, collaborative planning and replenishment, supply chain planning and controlling as well as the information systems supporting all these processes are thoroughly studied. The outcome of this step is the application of the current theories for demand management in the reference model in the form of basic directions and requirements for model design and implementation. Step 2: Study of supply chain reference model The main idea behind the creation of the reference model is that it should follow a hybrid top‐down and bottom‐up approach. According to this approach the creation of supply chain reference model integrates knowledge both from other well established supply chain reference models and real‐life business processes of companies facing the problem of demand variability. The second step of the methodological approach applies the top‐down approach, studying other supply chain reference models. Such models are SCOR which is a process model focused in performance measurement and improvement, and SAP reference model which represents business processes using ERP system and other advanced planning and scheduling (APS) software solutions of SAP AG. These reference models incorporate best practices and they are widespread both in academia and industry. The adaptation and customization of the existing reference models can offer the starting point for the development of our reference model.
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Sotiris Gayialis et al. Step 3: Study of supply chain business processes in case studies As illustrated in Figure 1, the reference model for demand management can adopt experience and knowledge from various business process modeling case studies, following the bottom‐up approach. The selected cases deal with supply chain planning and execution processes of typical companies from various industrial sectors (energy, wood & furniture, metal forming, consumer goods, food & beverages, apparel, pharmaceuticals & cosmetics). The experience and knowledge from the case studies can guide to the identification and critical evaluation of the consequences of poorly managed variability to companies and global supply chains. They can also assist the identification and documentation of the operational, financial and environmental risks that affect variability management, and present the trade‐offs between conflicting decisions on the company and the supply chain level. Step 4: Review of methods and tools for business process modeling The elaboration of the generic reference model is based on a set of business process modeling methods and tools which are selected after an extensive literature review and market research. Based on reference model requirements and design specifications concluded from steps 1, 2 and 3 the selection of business process modeling architecture is based on a set of criteria, including:
Representation and integration of the different supply chain views, like process view, organization view, information view, decisional view, risks view and knowledge view.
Application in different types of business processes: public, private and collaborative business processes.
Development of reusable models in the form of a reference model.
Ease of use and understanding by users.
Existence of a software tool that supports the use of various methods in an integrated way.
The selection of an integrated modeling architecture, such as ARIS (Scheer 1999), enables the graphical representation of different views of an organization and its environment, and supports the redesign and improvement of business processes considering their different perspectives. Step 5: Creation of the supply chain reference model for demand management The creation of the supply chain reference model for demand management is based on the outcomes of the previously described methodological steps, following the combined top‐down and bottom‐up approach. The graphical representation of various perspectives of the supply chain processes is done using the selected methods and tools, in step 4. The application of the previously described methodological steps concludes to the design specifications of the supply chain reference model. The proposed reference model characteristics are presented in Figure 2 and described below. A basic idea for the development of the supply chain reference model is to minimize the demand forecasting errors in the various levels of supply chain, through the integration of information flow and business processes. For this reason, enterprise models include private, public and collaborative business processes for demand planning, production planning, inventory management and replenishment, in order to effectively support decision making throughout the supply chain. This reference model realizes the different views of supply chain processes: function (process) view, organization view, information view, decisions view and knowledge view, taking into account the risk dimension that affects the demand variability throughout the supply chain. An enterprise or a global supply chain can be analyzed and integrated through its business processes. This integration is achieved by developing models for the various enterprise views, mentioned above.
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Figure 2: Proposed reference model characteristics The proposed reference model is elaborated using ARIS methods resulted from step 4. These methods can be adapted and used in an integrated way using “ARIS Platform” software. Each one of the formerly mentioned modeling views is covered by the various ARIS methods. Extended event driven process chain (eEPCs) is the core method for modeling the process view as well as the decision and knowledge views. A combination of other ARIS methods together with eEPCs (Figure 2) can represent supply chain business processes in an integrated way. Business process models are enhanced with operational, environmental and financial risks covering the risk management aspect of supply chain reference model, using a dedicated for this reason ARIS method (business control diagrams). Knowledge is an important company resource for demand management. It encompasses development, monitoring and improvement of processes, organizational structures and technologies for effective knowledge processing within an organization or the global supply chain. Although knowledge processing in operational and scheduling business processes can be represented using various ARIS methods (eEPCs, organizational charts, eERMs), Knowledge Structure Diagrams are selected together with eEPCs as the modeling methods of the reference model for accurate representation and analysis of knowledge. Knowledge objects types of these diagrams (knowledge category and documented knowledge) are connected in eEPCs in order to relate knowledge with critical functions and decisions for demand management. These relations can represent knowledge which is acquired while carrying out a function and knowledge required to carry out a function, as well as documented knowledge while carrying out a function. Finally, the generic reference model for demand management can be instantiated in partial reference models for industrial sectors and in particular industry specific business models. This characteristic can be easily treated through the variants of business process models supported by ARIS software. Step 6: Validation of reference model The generic supply chain reference model for demand management should be set up as configurable model that enable rapid instantiation of specific supply chain configurations. This requirement is examined in this methodological step where the generic reference model is instantiated and adapted in a diversity of configurations in various industries. For this reason, partial reference models are created following an instantiation process from the initially developed generic reference model of supply chain, concluding to business models for selected sectors.
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Sotiris Gayialis et al. Step 7: Integration of reference model with quantitative models A further enhancement of the reference model (in its generic or partial version) is the integration of the decisional functions of business processes with a set of quantitative models for the calculation of demand variability and risks influence on supply chain operations. Models should cover specific supply chain issues like: sales forecasting in all echelons, contract configuration between contracting partners of supply network, multiple sourcing practices for the achievement of capacity flexibility of associate companies.
6. Knowledge transfer and management through the reference model As stated previously in the paper, reference models are reusable business process models that cover the different views of an enterprise or a system. The application of the proposed methodological approach concludes to such reusable models in the form of a generic reference model which can be instantiated to partial reference model for different industry sectors. Furthermore, partial reference models can be specialized to particular business models of specific supply chains (Figure 3). Hence, partial models can be used from organizations as useful tools for business process design or redesign in order to achieve effective demand management. Model reuse and replication is very important especially when it has to do with the transfer of knowledge between organizations. The proposed reference model can effectively support the transfer of knowledge to those organizations that select to adopt the model in order to improve their business processes. As depicted in Figure 3, the development of the generic reference model for demand management is based on best practices incorporated in well‐established supply chain reference models, like SCOR model or SAP business models, together with insights and experiences transferred from a diversity of process modeling case studies. The reference model can represent and distribute such experiences embedded in supply chain business processes, organizational structures and information systems, incorporating graphical representations of knowledge with the use of suitable knowledge modeling methods. In doing so, reference model can enable the adoption, processing and sharing of knowledge within a company and between the members of a supply chain.
Figure 3: Flow of knowledge transfer through the reference model As knowledge significantly affect decisions for the management of demand variability, reference model considers knowledge as a controllable element, like the other business factors affecting the organizations’ operation. Knowledge view of the reference model meets the objective to represent what knowledge is available in an organization, as well as the distribution of the knowledge in business processes. It can show which organizational unit, position, or role has the expertise in certain knowledge categories. Therefore, the categorization of knowledge is an important task, as knowledge categories can assist the organization of insights and experiences constituting knowledge and the detection of information carriers storing the
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Sotiris Gayialis et al. knowledge. Another important objective in modeling the knowledge view of the reference model is to show where knowledge is generated, modified, and required in business processes so that the most efficient use of knowledge resource can be determined. The aforementioned objectives and tasks for modeling knowledge is achieved through the use of knowledge structured diagrams and knowledge‐specific modeling object types (knowledge category, documented knowledge), described in step 5 of the methodological approach.
7. Conclusions and further research Although there are several research efforts for modeling the supply chain processes, only a few reference models for supply chain identified in the literature. Thereby there is no captured knowledge for supply chain business processes in the form of reusable models which can be applied in specific organizations. The presented research effort aims at the creation of a reference model for supply chain which is focused on demand management. This reference model covers different perspectives of business processes, including process, organization, information, decisional, risks and knowledge views, and it is represented in a general form, so that specific application models can be created by adaptation and modification. The creation of the reference model is based on a methodological approach introduced in an on‐going research project and presented in section 5 of this paper. Following steps 1 to 5 of the methodological approach, an early version of the generic reference model for demand management has been developed aiming to address the shortcomings of current literature as presented in section four. This model is a useful tool for successfully manage demand throughout the supply chain in order to create value for companies and their customers. This reference model consists of a diversity of integrated business process models which can represent the relationships between organizations, activities, information, and knowledge and it can effectively manage complexity by selecting and analyzing specific modeling views. It offers reusable models in the form of a generic reference model which can be instantiated to partial reference model for different industry sectors, and furthermore in particular business models (Figure 3) taking into account the characteristics that differentiate the nature of demand throughout the supply chains. The first and the most important note that can be made for further research is reference model instantiation in order to validate the outcomes of the methodological approach and the reference model itself. Reference model instantiation should go beyond the development of partial reference models for a diversity of industrial sectors and it should be specialized in particular business models for specific supply chains and companies, as presented in Figure 3. Doing so, the proposed reference model will prove its applicability and usefulness to support real‐life problems in increasing flexibility and reducing variability in contemporary supply chains. Apart from enhancing reference model with quantitative models for coping with demand variability and making risk management related decisions, as defined in the methodological approach, a set of appropriate algorithms to solve these quantitative models should be embedded in the reference model, offering an integrated solution for potential users of research outcomes. In addition to quantitative models and algorithms, further research should be done to develop information technology models, to support the application of the methodological approach and the reference model described in this paper.
Acknowledgements The research efforts described in this paper are part of the research project “A Holistic Approach for Managing Variability in Contemporary Global Supply Chain Networks” in research action: “Thales ‐ Support of the interdisciplinary and/or inter‐institutional research and innovation”, which is implemented under the Operational Programme: Education and Lifelong Learning, NSRF 2007‐2013 and is co‐funded by European Union (European Social Fund) and Greek Government.
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Sotiris Gayialis et al. Fettke, P., Loos, P. and Zwicker, J. (2005) Business process reference models, in Bussler, C. J. and Haller A. (Eds.) Business Process Management Workshops, Springer Berlin Heidelberg, pp. 469–483. Heisig, P. (2000) Process modelling for knowledge management, in Proceedings of the EKAW Workshop on Common Approaches on Knowledge Management, 12th International Conference on Knowledge Engineering and Knowledge Management. Holsapple, C.W., and Joshi, K. D. (2005) “Exploring secondary activities of the knowledge chain” Knowledge and Process Management, Vol. 12, No.1, pp. 3–31. Holsapple, C.W., and Singh, M. (2001) “The knowledge chain model: Activities for competitiveness”, Expert Systems with Applications, Vol. 20, pp. 77–98. Kahn, K.B. and Adams, M.E. (2000) “Sales Forecasting as a Knowledge Management Process”, The Journal Of Business Forecasting, Winter 2000‐2001, pp. 19‐22. Klingebiel, K., (2008) A BTO Reference Model for High‐Level Supply Chain Design, in Parry G. and Graves A. (Eds.) Build To Order: The Road to the 5‐Day Car, Springer London, pp. 257–276. Koh, S.C.L., Gunasekaran, A., (2006) A knowledge management approach for managing uncertainty in manufacturing, Industrial Management & Data Systems, Vol. 106 No. 4, pp.439 – 459. Lapide, L. (2006) “Demand Management Revisited”, The Journal Of Business Forecasting, Fall 2006, pp.17‐19. Marra, M., Ho, W., Edward, J.S. (2012) “Supply chain knowledge management: A literature review”, Expert Systems with Applications, Vol. 39, pp. 6103–6110. Mendling, J., Moser, M., Neumann, G., Verbeek, H.M.W., van Dongen, B.F. and van der Aalst, M.P. (2006), “Faulty EPCs in the SAP Reference Model”, Lecture Notes in Computer Science Vol. 4102, pp. 451‐457. Mentzer, J.T. and Moon, M.A. (2004) Sales Forecasting Management: A Demand Management Approach, California: Sage Publication. Mentzer, J.T., Moon, M.A., Estampe, D. and Margolis, G. (2007) Demand Management, in: Mentzer, J. T., Myers, M. B., Stank, T. P. (Eds.) Handbook of Global Supply Chain Management, California: Sage Publication, pp. 65‐85. Nonaka, I. and Takeuchi, H. (1995) Knowledge‐Creating Company: How Japanese Companies Create the Dynamic of Innovation, New York: Oxford University Press. Panayiotou, N., Oiconomitsios, S., Athanasiadou, C. and Gayialis, S. (2010) Risk Assessment in Virtual Enterprise Networks: A Process‐Driven Internal Audit Approach, in Ponis S. T. (Ed.) Managing Risk in Virtual Enterprise Networks: Implementing Supply Chain Principles, New York: Hersehy, pp. 290‐312. Ponis, S.T. and Spanos, A.C. (2009), “ERP II Systems to Support Dynamic, Reconfigurable and Agile Virtual Enterprises”, International Journal of Applied Systemic Studies, Vol. 2, No.3, pp. 265‐283. Ponis, S.T., Vagenas, G. and Koronis, E. (2009) Exploring the Knowledge Management Landscape: A Critical Review of Existing Knowledge Management Frameworks, in Harorimana D. (Ed.) Cultural Implications of Knowledge Sharing, Management and Transfer: Identifying Competitive Advantage, Information Science Reference, New York: Hershey, pp. 1‐25. Ponis, S.T., Vagenas, G. and Tatsiopoulos I.P. (2008) Knowledge Management in Virtual Enterprises: Supporting Frameworks and Enabling Web Technologies, in Bolissani E. (Ed.) Building the Knowledge Society on the Internet: Sharing and Exchanging Knowledge in Networked Environments, Information Science Reference, New York: Hershey, pp. 302‐324. Porter, M. (1985) Competitive Advantage: Creating and Sustaining Superior Performance, New York: Free Press. Scheer, A.W. (1999) ARIS‐business process frameworks, Berlin: Springer Verlag. Shaw, N.C., Meixell, M.J and Tuggle, F.D. (2003) A case study of integrating knowledge management into the supply chain management process, in Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03). Supply Chain Council (2010) Supply Chain Operations Reference Model, Version 10.0, The Supply Chain Council, Inc. Verdouw, C.N., Beulens, A.J.M., Trienekens, J.H. and Vorst, J.G.A.J. (2011) “A framework for modelling business processes in demand‐driven supply chains“, Production Planning & Control, Vol.22, No. 4, pp.365–388. Verdouw, C.N., Beulens, A.J.M., Trienekens, J.H. and Wolfert, S. (2010) Business Process Modelling in Demand Driven Agri Food Supply Chains, in Proceedings of the 4th International European Forum on System Dynamics and Innovation in Food Networks, Innsbruck.
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Loosely‐Coupled Networks of Knowledge Production and Diffusion Gianna Giudicati 1 and Massimo Riccaboni 2 1 eni SpA (Milano) and STEIN Group, University of Trento, Italy 2 IMT Lucca (Lucca), Italy gianna.giudicati@eni.com massimo.riccaboni@imtlucca.it Abstract: Timely recombination of dispersed knowledge is key to meet unexpected needs and emerging opportunities in multinational companies. Firm knowledge systems are organized in multiple interdependent networks of collaboration and communication including R&D team and community membership, e‐mail exchange, scientific co‐publishing, and patent co‐ inventorship. Whereas most of the literature so far has focused on one specific network at a time, in this paper we develop a new methodology to analyze multilevel knowledge networks. By jointly analyzing the communities of practice (CoPs) of a multinational oil firm together with patent and publication co‐authorships, we find different layers of knowledge production and exchange networks are loosely coupled: scientific competencies and positions in knowledge networks are misaligned and the transfer of critical knowledge from research into practice is severely constrained. Keywords: communities of practice, recombination of knowledge, multiple network analysis
1. Introduction Criticalities emerge when companies operating in diversified and multinational contexts need to rapidly access and recombine disperse knowledge. The need to rapidly identify and activate experts is a crucial aspect for problem‐solving in increasingly dynamic environments having heterogeneous areas of intervention and facing unexpected events. Problems arise whenever the two domains of information and knowledge exchange, on one hand, and identification and competence of experts, on the other, do not overlap. The Knowledge Management (KM) literature has increasingly focused on Communities of Practice (CoPs) as innovative tools to improve knowledge and information exchange in organizational settings (Roberts 2006; Fox 2000; Breschi and Lissoni 2005; Newman 2004, 2001; Lave and Wenger 1991; Wenger, 2007). Despite their increasing importance and implementation (Schenkel and Teigland 2008), these tools are not always successful and relevant limitations emerge in their use when urgency and unexpectancy are in place (Ardichvili et al. 2006 2003; Roberts 2006; Henderson and Cockburn,1994). This paper applies a multilevel network perspective to the analysis of rapid mobilization of dispersed knowledge in complex multinational organizations. We focus on the energy sector also because of the importance and the critical consequences of failures in this sector. We apply multiple networks theory (Padgett and Ansell 1993) and multilevel analysis (Gao et al. 2011a; 2011b) for better understanding the efficacy of on‐line CoPs introduced by a multinational oil company, in facilitating the identification of experts and knowledge recombination. Inspired by the cited literature we develop a new indicator of centrality in multiple networks (cascading centrality index, CCI) to identify the structurally relevant nodes in guaranteeing knowledge exchange and sharing across networks. By exploring a biannual dataset of e‐mail exchanges, the KM network is studied to examine the domain of the knowledge spillover both within and among CoPs, and the degree of knowledge diffusion within the whole company. The knowledge exchange network is compared with the networks of knowledge production of both patents and scientific publications. This paper contributes to the existing literature in this field, mainly based on questionnaires and interviews, by examining the overlap among the domains of research, development and practice. More specifically, four main issues are examined: (1) Is there any overlap between the domains of experts and that one of knowledge exchange? (2) Is their knowledge easily accessible to colleagues? (3) How active are they in sharing their knowledge? (4) How do communities improve the overlap between the experts' domain and the practitioneers’ domain? To the best of our knowledge this is one of the few attempts to simultaneously investigate multiple networks of knowledge production (co‐authorships), and exchange (e‐mail networks and CoPs) to check for the effectiveness of KM tools in facilitating access to critical knowledge. In addition, the email data used in this study are neither easily available nor reachable.
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Gianna Giudicati and Massimo Riccaboni The paper is organized as follows. Sections 2 and 3 describes the contextual and empirical frameworks, research questions and data sources. Section 4 illustrates our results. Section 5 concludes.
2. Contextual framework and research questions
Multilevel network approach
Despite from the theoretical viewpoint the role of multiple networks of formal and informal collaborations has been repeatedly stressed, most of the empirical work so far has focused on a single network at a time: R&D collaborations, co‐patenting, inventors’mobility, citations, joint publications and affiliations. The crucial role of brokers (Fleming et al. 2007) in spanning structural holes through weak ties (Granovetter 1973; Burt, 1992) has been recognized. However, this view must be complemented by looking at the robust (or fragile) action (Padgett and Ansell 1993) of innovators across multiple networks. How to measure network coupling? The simplest approach is to look at network composition and at individual positioning in the various networks (Figure 1).
Figure 1: Multilevel approach in studying innovation networks However, this simple view does not allow to take into consideration the structure of the system as a whole, for example we are not able to identify whether individuals are central in one network and peripheral in another (node i in Figure 1). Therefore, inspired by the literature on multiple networks theory (Padgett and Ansell 1993) and on multilevel network analysis (Gao et al. 2011a; 2011b), we introduce a new indicator of centrality in multiple networks (cascading centrality index, CCI) to identify the structurally relevant nodes in guaranteeing knowledge exchange and sharing across networks. First, the interpretation of CoPs as unique, specialized groups of affiliation (Granovetter 1973; Watts and Strogatz 1998; Newman 2001) is a myopic view of the various types of relations and ties needed to improve internal cohesion and homogenization of knowledge within a company. Each subject involved in the innovation process should be involved in multiple roles and relations, to improve communications in the stages forming the innovation process. Second, multiple relations among individuals across networks may give rise to the emergence of multivocal robust action (Padgett and Ansell 1993) or reveal the fragility of the network structure (Gao et al. 2011b). Recent contributions in physics and natural science also improved the literature on multiple dependent networks by applying percolation models to the analysis of their structural properties (Gao et al. 2011a). By introducing the notion of cascade of failures, scholars emphasized the importance of nodes' positions in one network in determining other nodes' failure across networks and the segmentation of the whole network system (Watts and Strogatz 1998b ; Boccaletti et al 2004; Buldyrev et al. 2010). First, we want to measure to what extend knowledge production and exchange networks are related. Padgett and Ansell (1993) improved previous research in social network studies by adding one dimension to the debate
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Gianna Giudicati and Massimo Riccaboni to generalize the notion of structural holes (Burt 1992) to multiple interdependent networks. In this context, a simultaneous and multilevel analysis of the information exchange network and the coauthorship networks is performed, to identify the simultaneous presence of subjects in multiple networks, or network overlap. Issue 1. Knowledge network coupling. Is there any overlap between the domains of experts in knowledge production and knowledge exchange? Second, the presence of links across networks and stages of the innovation process and in any single network among CoPs is a pre‐condition for individual access to knowledge. Access to relevant knowledge depends on the distance in the network between experts and practitioners. Despite the effective activation of top experts in sharing their knowledge, the flow of information may be guaranteed and reached by those experts' neighbors in the e‐mail network who are highly proactive in information exchange. Issue 2. Knowledge reachability . How difficult is it to access critical knowledge across networks? And, even without the likelihood that experts will share their competencies, is their knowledge easily reachable by colleagues using the e‐mail exchange system? Third, once the presence of experts is tested, further analysis is needed to check for effective activation of the skilled technicians. Apart from criticalities stemming from the lack of individuals with multiple roles across networks, members' participation has been proved to be the main determinants of CoPs success or failure (Brown and Duguid 1991; Lave and Wenger 1991; Probst and Borzillo 2008). Issue 3. Knowledge activation. Are the top experts effectively active in sharing their technical knowledge through KM tools? In the following we will investigate the three issues of coupling, reachability and activation both for individuals and CoPs.
3. Empirical framework In this section we analyze networks of co‐publishing, co‐patenting, and an e‐mail exchanges to deal with basic research, applied research, and the intra‐organizational practices of a multinational company in the energy sector. The analyzed multinational company operates in the field of oil and gas, petrochemicals and oilfield services construction, and is committed to improve the exploration, production, transformation and transportation of oil and gas. This sector is becoming even more knowledge‐intensive because of its high risk and complexity and the role played by KM systems and knowledge spillover is even more crucial in problem‐ solving and particularly in immediate and short‐term decision‐making processes. Three datasets are examined: a dataset of e‐mail exchange and two datasets of co‐authorships in patenting and scientific publishing. The first dataset contains e‐mail exchanges from 09/01/2009 to 04/05/2010, provided by one of the KM division of the company. The exchange only covers the internal e‐mail accounts of the company, and no private accounts are included. The dataset contains information about 15 CoPs. The communities covered both practical fields, i.e., production, materials, and constructions, and other fields based on research, i.e., geology, geophysics, etc. For each CoP, at least two supervisors, an official facilitator and at least one alternate are identified. There are 1,567 effectively active senders and receivers of 103,474 e‐ 1 mails messages . This dataset is particularly important in a multinational context. Indeed, despite the crucial role played by private communication tools in small environments such as laboratories, small offices, and family businesses, professional e‐mail exchange is a key success factor for multinational companies needing to connect and share information among worldwide subsidiaries, laboratories, and platforms. Therefore, although employees can communicate by phone, intranet chatting, or in person, the communication network is represented by focusing on e‐mail exchanges.
1 In this framework, e‐mails were considered as one‐to‐one communications: whenever the receiver was the general account of the CoP, the e‐mail was sent to all subjects belonging to the receiving CoP.
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Gianna Giudicati and Massimo Riccaboni The co‐authorship networks aim at verifying the existence of experts by analyzing the patents and publications produced by employees since 1996 2 . A publication database (SciVerse‐Scopus 3 ) and a patent dataset (Thompson’s Delphion 4 ) were used to obtain information on individual patent and publication rates, respectively. These datasets gave the identity of those subjects who, according to their frequency of patenting and publishing, were considered here as experts. However, the experts defined according to these two criteria do not always coincide with the 49 skilled technicians appointed by the management of the company as official experienced specialists. In the time window in question, Delphion reports 250 single patents produced by members of the analysed company, with 305 inventors and 29 as maximum number of patents per author. The dataset on scientific publications lists 1,703 authors and 1,638 publications recorded as documents having the analyzed company as main affiliation. In our framework, social network instruments were used to answer our research questions. The three datasets result in three networks: a patent network (P), a scientific network of publications (S), and an e‐mail exchange network (E). The overlap of the three reported datasets and networks were computed after manual matching of each employee across networks.
4. Results 4.1 Knowledge network coupling In this section the match among the three networks is examined to check for overlap between the domains of experts and of knowledge exchange at both individual and CoPs’ level. The answer to our first research question may be sought in recent multiple network theories measuring the overlap and simultaneous presence and role of subjects in the various networks. We simultaneously focus on individual in various networks (Burt 1992, 2004; Ahuja 2000). In our framework, social network instruments are used to study the overlap of the three networks P , S, and E. Complete overlap between the information exchange through CoPs and co‐authorship networks is found whenever all the experts, publishers of publications or patents, are CoP members and whenever an improvement in individual scientific publications and patenting corresponds to a higher degree of centrality in the information exchange network. Between the two extremes of total and no overlap, partial overlap exists when there are some subjects whose roles enable them to exploit the advantages of being embedded in multiple networks. Table 1 lists the percentages of overlap for each combination of individual simultaneous presence in the networks as well as the percentage of subjects belonging to one, two or three networks. Table 1: Percentage of individual members of multiple networks Subjects in: 1 network
2 networks 3 networks
Combinations
Overlap (%)
P
2.82
S
63.12
E
22.05
SE
8.54
PS
2.60
PE
0.07
PSE
0.80
87.99
11.21 0.80
Most subjects of the knowledge production networks are not active in the KMS and not involved in e‐mail exchange. In addition, almost 25% of the employees are KMS users who had neither published nor patented (E, 22%). Despite a high number of subjects belonging to either one (87.99%) or two (11.21%) networks, only 40 subjects were simultaneously active in all three networks. 2
The choice of the time window was due to the availability of data. In addition, knowledge needs a long time to ripen, and examination of individual productivity must therefore also focus on longer period before the introduction of CoPs. 3 SciVerse‐Scopus registered by Elsevier Properties S.A., is accessible at: http://www.scopus.com/home.url (last access on August 10th 2010). 4 The link to Delphion by Thomson Reuters is http://www.delphion.com (last access on July 11th 2010)
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Gianna Giudicati and Massimo Riccaboni The absence of common central subjects in the networks is a signal of the vulnerability of the network system upon possible cascade of failures (Buldyrev et al. 2010; Gao et al 2011b). Inspired by the seminal contribution of John Padgett on robust action in multiple networks (Padgett and Ansell 1993) and recent work on multilevel networks in the analysis of critical infrastructures (Gao et al. 2011a; 2011b) we develop a new indicator of centrality in multiple networks to pinpoint the structurally relevant nodes in ensuring knowledge interchange across networks. The cascading centrality index (CCIedges) of node i is given by the number of linkages that will disappear due to cascading failures when node i is removed from networks. We take a normalized version of the index by dividing the number of disappearing linkages by the total number of edges. By removing a node in a single network we drop all the node’s linkages, thus the CCIedges index correspond to the (normalized) degree index. At the same time we computed a cascading centrality index (CCInodes) based on nodes and it represents the normalized number of nodes that will disappear due to cascading failures when node i is removed by the multilevel network. In multiple networks the removal of a critical fraction of nodes may indeed lead to a failure cascade ending in the global fragmentation of independent networks. To apply the model we develop a Matlab code that computes the CCI indices which is available upon request. We compute CCI for a two‐level system made by a network of knowledge production (patents and publications) and a network of knowledge exchange (online CoPs). Table 2 reports the cascading failures resulting from the removal of each node. In particular, once all members of the Cops reported in row are removed, we report the consequent failure cascades, i.e. the percentage of nodes and links that will be disconnected. Table 2: Cascading failure results as the percentages of edges and nodes failed after the removal of each CoP’s nodes. Removed COPs' nodes
% of failed EDGES (CCI edges )
% of failed NODES (CCI nodes )
CoP14 CoP10 CoP12 CoP6 CoP9 CoP4 CoP8 CoP7 CoP3 CoP13 CoP2 CoP5 CoP1 CoP11 CoP15
51,55 35,52 29,33 28,30 23,80 19,42 9,96 6,78 3,20 2,81 1,68 0,85 0,46 0,09 0,01
30,17 15,44 24,21 20,70 14,37 11,23 6,31 6,67 2,80 3,86 3,16 1,40 2,81 0,35 0,70
Results in Table 2 show the crucial role played by a few CoPs, in particular CoPs 14 and 10. The removal of their members produces a failure cascade of 51 and 35 per cent 5 of the whole number of edges in the network of knowledge production and exchange. A more detailed analysis has been performed at the level of single nodes. Figure 2 shows the connectivity distribution as percentages of edges and nodes failed after the removal of the most central individuals. The graph emphasizes the importance of mainly four subjects in determining the greater proportion of both edges and nodes cascades. In particular, the removal of the most central node determines a cascade of failure characterized by the crash of more than twenty per cent of the actual linkages. Interesting enough, despite the fact that the complete crash of the whole network needs the removal of a high number of actors having lower impact, the cut of only three nodes would delete more than half of the existing links. The sum of the percentages is higher than hundred per cent because subjects may belong to more than one CoP.
5
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Figure 2: Connectivity distribution Overall, we find that less than 1% of the total number of subjects simultaneously belong to the domains of experts and of knowledge exchange. In addition, less than 9% of total subjects are either publishers or inventors using the e‐mail exchange system. The results show no multivocality identity in individual roles, and no subject acts in the various domains to improve communication exchange by recombining theoretical and practical knowledge. Knowledge production and exchange networks are only loosely coupled. This conclusion is confirmed by the computation of cascade centrality indexes. As already mentioned, despite the fact that the complete crash of the network requires the cut of a remarked number of nodes, the removal of only three central nodes ends up in deleting more than half of the existing links and nodes. These results can also be interpreted in terms of network security since a few individuals are responsible for knowledge circulation between researchers and practitioners
4.2 Knowledge reachability In this section we further develop the measures of multilevel network connectivity to account for difficulties in reaching critical knowledge. The concept of geodesic distance has been widely used as a proxy for measuring costs to access physical assets in logistic networks (Combes and Lafourcade 2005, 2003; Cavalletti 2011). By analogy, we apply a measure of closeness as a proxy to measure the costs an individual incurs to access dispersed knowledge. We proxy knowledge resources by patents and scientific publications and measure how close individuals in the networks are to the author of any patent/publication. Closeness is 1 if all individual have a direct link to the author of all patents and the cost of accessing knowledge is low. Conversely closeness is low when individuals have only indirect connections to most of the authors of patents and scientific publications, and therefore the cost of accessing knowledge is high. Comparisons among the normalized indexes of the three networks aimed at checking whether subjects belonging to one network are closer to or farther from their colleagues in another network, and therefore at determining the efforts and costs needed to reach the required information. We compute four indicators (see Table 3). Table 3: Closeness to knowledge sources closeness to knowledge production sources e‐mail exchange, all e‐mails e‐mail exchange, technical e‐mails only
CES 0.620 0.714
CPS 0.936
CEP 0.836 0.960
CSP 0.967
CEP measures the cost to access patenting knowledge, that is the closeness of all the members of the email network (E) to patents’ inventors in the patent network (P). Similarly we compute CES to measure the distance of nodes in the email network form the authors of scientific publications; CPS and CSP measure the distance of the authors of patents from the authors of scientific publications, and vice versa. The first row of Table 3 lists the values of indexes for total e‐mail exchanges, whereas the second row focus on technical e‐mails only.
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Gianna Giudicati and Massimo Riccaboni Experts' contributions are especially crucial for technical aspects and problems directly related to production processes, not necessarily for other daily routines or organizational communications. Viewing the whole e‐mail dataset, the results emphasize the fact that experts are not close enough to those colleagues who can benefit from those messages (CES and CEP << CPS and CSP). Therefore, the cost of employees to acquire expert knowledge is high. Indeed, the low values of closeness prove that those who generate knowledge through patenting or publishing respectively are far from all subjects within the e‐mail network. The low level of closeness confirms the lack of overlap between knowledge production and exchange networks, causing higher costs to access knowledge. This is particularly true when knowledge production is more dispersed, as in the case of scientific publications. The higher values of CPS and CSP shows increasing overlap between networks P and S: subjects in network S are quite close to subjects in network P. Experts incur lower costs whenever they need to reach other experts' knowledge, because experts, either publishing or patenting, are much closer to each other than to those who have a better chance of benefiting, exploiting, and sharing knowledge. In a nutshell, access to critical knowledge through e‐mail exchange is difficult, due to low overlap and interchange between the communities of knowledge production and diffusion. As a result, critical knowledge competences and resources are difficult to reach by colleagues through the e‐mail exchange system.
4.3 Knowledge activation In this section we examine technical e‐mails in more detail to check the proactivity and participation of experts on specific and technical issues. How do skilled technicians behave in e‐mail exchanges? Do the authors of publications and patents answer the technical e‐mails they receive? By focusing on the subject matter of each message, forwards and answers have been identified by the prefixes Fw:, R:, Re:. The first answer usually appears within 2 hours of the original message and, in case of more than one level of answer or forward, the mean time lag of each level of answer is no more than 12 hours. The time of persistence of each message is on average 3 days. Messages may also be on stand‐by for a certain period of time and then reconsidered as crucial issues: for these outsider cases, answers may be recorded even more than one month after the original 6 message. Table 4 shows the share of messages’ answers or forwards based on the position and role of individuals in networks and CoPs. Table 4: Forwards and answers divided by networks' overlap, subjects’ role, and CCI
The upper part of Table 4 focuses on subjects' roles and lists the percentage of answers and forwards sent by CoPs facilitators, alternates and skilled technicians. Although only 4% of senders are facilitators, 32% and 22% of technical messages are respectively forwarded and re‐discussed by CoP facilitators. This result shows that very few subjects play official roles in CoP, sending many messages to various colleagues. In addition, skilled technicians defined by the company do not seem to be technical communicators for problem‐solving, and more than half the technical issues are discussed by people, who are not in the co‐authorship network and play no specific role in the KMS. These results confirm the need to revise the official role and position of currently defined skilled technicians and to involve other people having publications on specific issues who are more likely to enrich discussions. Second, despite the low number of subjects belonging to all three networks, the results show that more than half both answers and forwards are sent by subjects involved in scientific publishing (SE). Therefore, technical problem‐solving is partially enriched by the participation of experts 6
This descriptive survival analysis has been computed by examining only those cases in which more than one level of answer or forward was reported.
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Gianna Giudicati and Massimo Riccaboni publishing in those technical areas, whereas the authors of patents do not seem to be directly enrolled in knowledge‐sharing. Also in this case, the company's interests must be considered, because incentive policies to boost either patenting or scientific publishing, or both, may be implemented. In sum, experts are only partially proactive in sharing their technical knowledge. Instead, inventors do not seem to contribute to problem‐solving through a frequent involvement in knowledge spillover and are not likely to use CoPs as a KM tool to improve and speed information‐sharing. Overall, the firm knowledge networks is extremely fragile as it depends on a single multivocal agent for large part of total knowledge interchange.
5. Concluding discussion Multivocality is a critical success factor in knowledge mobilization. However, difficulties arise in matching incentives, roles and positions of individuals across communities and multiple networks of knowledge production and exchange. The success of CoPs as transversal tools with respect to exploration and exploitation derives from CoPs contributions to the recombination of dispersed knowledge. The case reported in this study emphasizes the risk multinational companies face in coping with critical contingencies, which require urgent recombination of crucial knowledge and a short‐term decision‐making. The case under analysis reveals the inefficiencies in CoPs, especially with respect to knowledge sharing in email networks. Our contribution highlights the lack of alignment between scientific competencies and the roles and positions covered by subjects in the communication networks. This result has negative implications on the accessibility of disperse knowledge. Two main reasons can be used to explain the reported lack of alignment from organizational and motivational points of view. First, the partition in the organizational structure of the various areas and divisions of the company is far from being lined up with the partition of the online communities. Therefore, the classification of the communities does not correspond with the organizational design of the company itself. Second, motivational issues arise when subjects are not involved in incentive policies aimed to promote the use of networking tool for spreading their knowledge. Despite the increasing trust and resources invested in networking tools such as CoPs, doubts and problems emerge when scientific knowledge has to be motivated. Despite the difficulties in including professionals in on‐line social networks, the system lacks subjects favoring communication exchanges between practice and research. CoPs turn out to be not adequately connected, and the resulting structural holes prevent the development of feedback along the chain of the innovation process. Transversal communications need to be improved by the presence of subjects trying to match different languages and procedures, and codifying and translating knowledge among the various domains. The proposed methodology is innovative and has a potential general application in other contexts. However, the actual state of the research is still a case study and does not claim to generalize the presented results. Therefore we do not claim to give general conclusions in the paper. Some other steps may be useful to improve the study, i.e. focus on private communication, intranet, etc, network simulation and cluster analysis).
Acknowledgements We are grateful to Lee Fleming, Keld Laursen, Laura Magazzini, Stefano Schiavo, Gianmario Verona, Enrico Zaninotto, and the reviewers and participants to the AOM 2012 for helpful comments.
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Gianna Giudicati and Massimo Riccaboni Buldyrev S.B. Parshani R., Paul G., StanleyH.E, and Havlin S., (2010) Catastrophic cascade of failures in dependent networks, Nature, No.464, pp.1025‐1028. Burt, R., (1992) Structural holes, Harvard Univ. Press, Boston. Burt, R., (2004) Structural holes and good ideas, American journal of sociology, pp.349‐399. Cavalletti, F., (2011) A strategy for non‐strictly convex distance transport cost and the obstacle problem, Arxiv preprint arXiv:1103.2797 . Combes, P. and Lafourcade, M., (2003) Core‐periphery patterns of generalized transport costs: France, 1978‐98, Discussion Paper Series ‐ Centre for Economics policy Research London . Combes, P. and Lafourcade, M., (2005), Transport costs: measures, determinants, and regional policy implications for france, Journal of Economic Geography, Vol.5 No.3, pp.319. Fleming, L., Mingo, S. and Chen, D., (2007) Collaborative brokerage, generative creativity, and creative success, Administrative Science Quarterly, Vol.52 No.3, pp.443‐475. Fox, S., (2000) Communities of practice, foucault and actor‐network theory, Journal of Management Studies, Vol.37 No.6, pp.853‐868. Gao, J., Buldyrev, S.V., Stanley, H.E. and Havlin, S., (2011a) Networks formed from interdependent networks, Nature Physics, Vol.8 No.1, pp.40‐48. Gao, J., Buldyrev, SV, Havlin, S. and Stanley, HE, (2011b) Robustness of a Tree‐like Network of Interdependent Networks, Arxiv preprint arXiv:1108.5515. Granovetter, M., (1973) The strength of weak ties, American journal of sociology, pp.1360‐1380. Henderson, R. and Cockburn, I., (1994) Measuring competence? exploring firm effects in pharmaceutical research, Strategic management journal, Vol.15 No.S1, pp.63‐84. Lave, J. and Wenger, E., (1991) Situated learning: Legitimate peripheral participation, Cambridge university press. Newman, M., (2001) The structure of scientific collaboration networks, Proceedings of the National Academy of Sciences of the United States of America, Vol.98 No.2, pp.404. Newman, M., (2004) Who is the best connected scientist? a study of scientific coauthorship networks, Complex networks, pp.337‐370. Padgett, J. and Ansell, C., (1993) Robust action and the rise of the medici, 1400‐1434, American Journal of Sociology, pp.1259‐1319. Probst, G. and Borzillo, S., (2008) Why communities of practice succeed and why they fail, European Management Journal, Vol.26 No.5, pp.335‐347. Roberts, J., (2006) Limits to communities of practice, Journal of Management Studies, Vol.43 No.3, pp.623‐639. Schenkel, A. and Teigland, R., (2008) Improved organizational performance through communities of practice, Journal of Knowledge Management, Vol.12 No.1, pp.106‐118. Watts, D. and Strogatz, S., (1998) Small world, Nature, No.393, 440‐442. Wenger, E., (2007) Communities of practice: Learning, meanings, and identity, Cambridge university press.
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The Factors of Knowledge Sharing in a Self‐Organisation Based System Kristina Grumadaite Kaunas University of Technology, Kaunas, Lithuania kristina.grumadaite@ktu.lt Abstract: The factors of knowledge sharing in a self‐organisation based system are presented in this article. Self‐ organisation based system can be understood as a successful contemporary knowledge based organisation (Bennet and Bennet 2005). It is a dynamic, complex and adaptive system, characterised by a continuous learning, distributed problem solving, self‐organisation, and phenomena, emerging from bottom‐up dynamic processes based on local interactions of autonomous agents – knowledge workers (Firestone and McElroy 2005). Knowledge sharing factors in this article are analysed at the individual and organisational levels, taking Hofstede’s cultural dimensions into account. Individual factors of knowledge sharing discussed in this article are internalisation, identification and compliance. Leaders, organisational culture and organisational structure were chosen as the organisational factors that promote or inhibit knowledge sharing process in a self‐organisation based system. A research in a Lithuanian organisation that has many features of a self‐ organisation based system revealed that knowledge sharing of employees is more based on internalisation: knowledge is an interesting process that allows them to learn something new and feel being self‐efficient by helping to fulfil team tasks. Also, the elements of identification can be seen in this organisation. For example, respondents believe that knowledge sharing can strengthen the relationships between team members and encourage a better cooperation. However, this research revealed some beliefs and attitudes that still can be met in many Lithuanian business organisations and act as inhibitors of knowledge sharing and the formation of a self‐organisation based system, that is – attitude towards power’s expression, an insufficient belief that knowledge sharing helps to earn the respect, appreciation and trust of team members, and thoughts about a probable danger to the workplace because of knowledge sharing. Keywords: knowledge sharing, knowledge sharing factors, self‐organisation based system, complex adaptive system
1. Introduction Because of growing complexity and uncertainty in this world, organisations have to move to creative and intellectual manufacture and services, creating high added value. Knowledge hereby becomes the main resource for the survival and success of organisations (Gottshalk, Holgersson and Karlsen 2009). As business guru Peter F. Drucker (1993) stated, the essential resource is no longer capital, land or labour, but knowledge. It can be defined as a whole of experience, values, contextual information and expert insights that build a new basis for evaluating and incorporating new experiences and information (Kumaraswamy and Chitale 2012). However, it isn’t enough just to have some knowledge. If a contemporary organisation would like to be successful, it should be able to manage its knowledge properly. Bennet and Bennet (2005) propose the concept of an intellectual complex adaptive system to describe a successful contemporary organisation. Complex adaptive organisational systems, according to Gupta and Anish (n.d.), are self‐organising, but they differ from other self organising systems in that they learn to adapt to changes in their environment. This adaptation is possible because of continuous learning, distributed problem solving, self‐organisation and phenomena, emerging from bottom‐up dynamic interactions (Firestone and McElroy 2005). In other words, complex adaptive systems function successfully if knowledge sharing is maintained because knowledge sharing is a prerequisite for organizational learning (Senge 2006), innovativeness (Hau et al. 2012), self‐organisation based processes (Laihonen 2006) and could be deservedly described as an essential process of knowledge management (Matzler and Mueller 2011). Research problem: Despite the importance of knowledge sharing to the organisational success, there is still a lack of research analysing individual attitudes, intentions and behaviour towards knowledge sharing. Usually fragmentary models that include only some aspects of knowledge sharing behaviour and don‘t reveal the complexity of knowledge sharing factors are presented in the articles. There is also a lack of scientific publications where knowledge sharing behaviour in a complex adaptive system (in a self‐organisation based system) is analysed. It shows that knowledge sharing in a successful contemporary organisation, as a self‐ organisation based complex adaptive system, is an actual research area. Research aim – to substantiate a model of knowledge sharing factors in a self‐organisation based system. This paper consists of three sections. First, the importance of the process of knowledge sharing in a self organisation based system will be explained. Second, the factors that have an influence on knowledge sharing
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Kristina Grumadaite behaviour in a self‐organisation based system will be defined and structuralised. Third, the results of a pilot research in a Lithuanian organisation will be presented. Research methods – analysis of scientific literature and case analysis.
2. The importance of knowledge sharing process in a self‐organisation based system Plowman et al. (2007) cite Chiles, Meyer and Hench who describe the concept of self‐organisation as complexity theory‘s anchor point phenomenon. Originated from physical science disciplines (He, Rayman‐ Bacchus and Wu 2011), complexity theory was applied by organisational scientists on purpose to analyse organisations and processes occurring in them (Plowman et al. 2007). Contemporary business organisations that can be understood as complex adaptive systems (Bennet and Bennet 2005) are complex, dynamic and don’t evolve in a steady and predictable way (De Toni et al. 2012). They are composed of many self‐organising components (agents) that seek to maximise their own goals but operate according to rules in the context of the relationship with other components (agents) (Gottshalk, Holgersson and Karlsen 2009). Those agents working on the ground of self‐organisation in knowledge based organisations are knowledge workers that possess intellectual abilities, aptitudes and experience to create and apply knowledge (Markova and Ford 2011). Mitleton‐Kelly (2003) proposes that the main characteristics of complex adaptive system are emergence, creation of a new order and self‐organisation. Self‐organisation can be understood as a bottom‐up dynamic process conditioned by spontaneous local interactions without a centralised control (Laihonen 2006, De Toni et al. 2012, and Keshavartz et al. 2010). Self‐organisation isn’t possible without knowledge sharing (Laihonen 2006). Knowledge sharing can be understood as a social interaction culture that involves the exchange of employee knowledge, experience and skills through the departments or the whole organisation (Lin 2007). So, what factors in a self‐organisation based system maintain knowledge sharing process?
3. Knowledge sharing factors in a self‐organisation based system According to O‘Neill and Adya (2007), the most successful organisations are able to attract and retain talents by entering into psychological contracts with their employees. These psychological contracts are particular implicit beliefs that often influence attitudes towards knowledge sharing. According to Vu and Zhu (2012), attitudes are based on the beliefs about expected consequences of a specified behaviour and favourable and unfavourable evaluation of these consequences. Various scientists define many factors that could influence attitudes to knowledge sharing. However, the models of knowledge sharing, presented by various authors, emphasise only some factors of knowledge sharing. In this paper, individual and organisational factors that have an influence on knowledge sharing in a self‐organisation based system are analysed. Some authors, for example, Wang and Noe (2010), suggest analysing factors of knowledge sharing also at the team level. However, if an organisation is really a successful complex adaptive system, knowledge sharing processes occur not just in some teams but in the entire organisation.
3.1 Individual factors of knowledge sharing Individual factors have a big influence on knowledge sharing. We can find the following individual knowledge sharing factors in the scientific literature: ability to express tacit knowledge into explicit knowledge (Lao et al. 2008), ability to learn (Lao et al. 2008), education (Wang and Noe 2010), work experience (Wang and Noe 2010), interpersonal trust (Wickramasinghe and Widyaratne 2012, Wang and Noe 2010, Fathi et al. 2011), self‐ efficacy (Tohidinia and Mosakhani 2010, Sh.‐Sh. Chen, Chuang, P.‐Y. Chen 2012, Wang and Noe 2010), perceived enjoyment to share knowledge with others (Vu and Zhu 2012), perceived reputation enhancement (Vu and Zhu 2012, Kumaraswamy and Chitale 2012), perceived reciprocity (for example, long‐term relationships with others) (Tohidinia and Mosakhani 2010, Wang and Noe 2010, Vu and Zhu 2012), perceived loss of knowledge power (it is understood as a negative knowledge sharing factor) (Vu and Zhu 2012, Wang and Noe 2010, Fathi et al. 2011), perceived organisational incentives (Tohidinia and Mosakhani 2010, Vu and Zhu 2012, Wickramasinghe and Widyaratne 2012, Wang and Noe 2010, Fathi et al. 2011). These factors can be structuralised referring to the work of Jiacheng, Lu and Francesco (2012). Applying Kelman’s theory of social influence, attitudes towards knowledge sharing depend on the three following types of a voluntary commitment to share knowledge – internalisation, identification and compliance. These types of commitment are influenced also by national culture (Jiacheng, Lu and Francesco 2012). Internalisation: Motivational mechanisms attributed to this commitment arise from the inside of individuals. Such people value knowledge sharing itself and appreciate the values of knowledge sharing, which correlate
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Kristina Grumadaite with their values: individuals share knowledge, if this process seems interesting, enjoyable, enhances their self‐ worth and allows feeling proud about enhanced team’s productivity and solved problems (Jiacheng, Lu and Francesco 2012). Identification: This process is related to socio‐psychological forces: individuals share knowledge because they are willing to attain the identification of group and create long‐term reciprocal relationships with others (Jiacheng, Lu and Francesco 2012). Compliance: Motivational mechanisms attributed to this commitment arise only from the outside: individuals share knowledge, if they receive rewards or punishment. According to Jiacheng, Lu and Francesco (2012), received rewards don‘t influence intention to share knowledge directly, but an employee, receiving various rewards, feels appreciated and identifies with a group better. These rewards and other organisational incentives are related to various organisational factors.
3.2 Organisational knowledge sharing factors in a self‐organisation based system Knowledge sharing is closely related to creativity processes because innovative ideas are new knowledge forms that are created because of individual ingenuity and communication with others (Roffe 1999). It means that both processes of creativity and knowledge sharing should be encouraged in contemporary business organisations. Scientists define the following organisational knowledge sharing and creativity factors:
leadership characteristics (Wang and Noe 2010, Shalley and Zhou 2008);
organisational structure (Wang and Noe 2010, Andriopoulus 2001, Cook 2002, Zdunczyk and Blekinsopp 2007);
organisational culture (Vu and Zhu 2012; Tohidinia and Mosakhani 2010; Wang and Noe 2010; Sh.‐Sh. Chen, Chuang, P.‐Y. Chen 2012; Kumaraswamy and Chitale 2012, Andriopoulus 2001, Zdunczyk and Blekinsopp 2007);
resources (Wickramasinghe and Widyaratne 2012, Kumaraswamy and Chitale 2012, Andriopoulus 2001).
According to scientific literature, leadership as a factor that promotes creativity and knowledge sharing is described by the following characteristics:
ability to formulate and communicate organisational vision clearly (Tierney 2008);
empowerment of employees to define personal tasks to themselves (Tierney 2008);
empowerment of employees for creative activity and improvement (Zhou 2008);
continous and clear feedback (Obolenskyj 2010; Tierney 2008; Zhou 2008). Various organisational incentives are also included in this feedback.
Organisational structure that promotes knowledge sharing and creativity should be flexible (Andriopoulus 2001), organic (De Toni et al. 2012) and based on networks (Wang and Noe 2010, Fathi et al. 2011, Wang et al. 2009). Organisational culture that is expressed by values, which are emphasised in a particular organisation (West and Richter 2008), encourages knowledge sharing and creativity, if challenges, freedom, support of ideas, dynamism, playfulness/humour, trust (openness), tolerance of risk, (creative) conflicts and time to generate ideas are valued (Ismail 2005):
trust promotes voluntary cooperation, especially in the context of complex interdependent actions (Casimir et al. 2012);
creative conflicts (or “creative tension” (Gulbrandsen 2004) occurring because of diversity and dynamism in a complex adaptive system (Lao et al. 2008, Laihonen 2006) encourages the creation of many new original ideas;
playfulness/humour can be used to facilitate the process of conflict resolution: a funny remark could be a tool of thoughts training and the condition for the emergence of new ideas (Ind and Watt 2004);
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taking on challenges, freedom to act, tolerance of risk and support of ideas, are the sources of innovativeness;
free time is an essential resource: without this resource many innovations just wouldn‘t be possible (Murphy and Pauleen 2007). According to scientists, free time should contain from 15 percent (Martins and Terblanche 2003) to 30 percent of all work time (Murphy and Pauleen 2007).
Resource:. Zu and Zhu (2012), Kumaraswamy and Chitale (2012) emphasise information and communication technologies that facilitate collaboration and knowledge sharing. Previous research of information technologies revealed that tools and technologies have a positive impact on knowledge sharing, if they are understood as easily accessible (Vu and Zhu 2012). Wickramasinghe and Widyaratne (2012) defined the following mechanisms of knowledge sharing that are based on information technologies: teleconferencing, newsgroups, e‐mail, Wikis, web‐based discussions, knowledge sharing boards. However, knowledge sharing can be facilitated not only by information technologies but also by other tools that not always require information technologies, such as brainstorming and collaborative problem solving, teamwork, storytelling, trainings, informal communication, etc. (Wickramasinghe and Widyaratne 2012). On the ground of scientific analysis, a pilot research in a Lithuanian organisation that has many features that characterise a self‐ organisation based system was conducted.
4. A review of research in a Lithuanian organisation Lithuanian organisation (in this article it will be named “Organisation N”), that was chosen as an object to substantiate knowledge sharing factors mentioned in scientific literature, creates information and communication technology solutions. Business area of this organisation demands continuous learning, distributed problem solving and self‐organisation processes where various knowledge workers – project managers, project workers, engineers, technicians – create flexible work teams on purpose to find new solutions to unique problems and adapt to always changing business reality. Because of changing technologies, the qualifications of employees, creativity, the spread of new ideas and communication are very valued in this organisation. On purpose to learn more about this organisation, a semi structured interview with the employees – all knowledge workers (in total 20) working in the main office in Lithuanian city of Kaunas was performed. They were asked about leadership characteristics in their organisation, organisational structure and organisational culture. The questions were given to entire teams, so the respondents had a chance to complement each other’s thoughts and statements. The answers confirmed the existence of organisational factors that influence knowledge sharing in a contemporary organisation – a self‐organisation based complex adaptive system (see Figure 1).
Figure 1: The relationship between cultural, organisational and individual knowledge sharing factors (prepared by K. Grumadaite, according to Lucas (2006), Jiacheng, Lu and Francesco (2012), etc.)
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Kristina Grumadaite Table 1: Individual knowledge sharing factors evaluated by the knowledge workers of “Organisation N” The type of a voluntary commitment to share knowledge(Jiacheng, Lu and Francesco 2012) to whom the statement belongs
A statement of the questionnaire It is interesting to share knowledge because that helps me learn something new. Knowledge sharing is a pleasant activity for me. I share knowledge because, first of all, it gives a benefit to me. I share knowledge because that helps fulfil team tasks. Knowledge sharing with a new employee (while teaching him) helps me show my status and control. I share my knowledge because it helps other team members solve their problems. I share knowledge because it at first helps me strengthen the relationships with team members and encourage a better cooperation. It is very important to share knowledge because it helps earn respect, appreciation and trust of other team members. When I am trying to decide whether to share knowledge or not, at first I am thinking about the punishment of not sharing knowledge and decide to share knowledge anyway. I share knowledge because I am rewarded for it.
Internalisation
Identification
Compliance
Individual factors of knowledge sharing in “Organisation N” were identified using a questionnaire that was prepared on the ground of Figure 1. These questionnaires were handed out to all knowledge workers of “Organisation N”. They were asked to evaluate various statements from “1” to “5”, where “1” means “absolutely disagree” and “5” means “absolutely agree” (see Table 1). In addition, respondents were asked to evaluate their intention to share knowledge (“I intend to share my knowledge as often as possible”) and possible danger of knowledge sharing (“Before I share my knowledge, I think about the possible danger to my workplace”). Research results in “Organisation N” revealed that:
All respondents absolutely agree that knowledge sharing is an interesting process that helps them learn something new.
20 percent of respondents absolutely agree and 50 percent of respondents agree that knowledge sharing is a pleasant activity, while 30 percent of respondents (or six respondents) agree partially. The latter respondents also just partially agree that they intend to share knowledge with their team members as much as possible. This opinion is determined by the following reasons:
a disbelief that the behaviour of knowledge sharing can influence a bigger respect, trust and appreciation of team members (three respondents who partially agree that knowledge sharing is a pleasant activity, also partially agree that they intend to share knowledge as much as possible);
a belief that knowledge sharing could endanger the safety of their workplace (three respondents mentioned it).
As Figure 1 shows, Hofstede’s dimensions, such as individualism/collectivism, high/low uncertainty avoidance, high/low power distance and femininity/masculinity, have an influence on internalisation, identification and compliance. However, although internalisation is much more expressed in individualistic cultures (Jiacheng, Lu and Francesco 2012) and Lithuania belongs to them (Huettinger 2008), self‐efficacy in “Organisation N” is more related to a personal ability to help others than just personal benefit. Respondents think that knowledge sharing helps other team members solve their problems (50 percent agree, 50 percent absolutely agree) and fulfil team tasks (25 percent of respondents absolutely agree, 65 percent of respondents agree and 10 percent of respondents partially agree) while 40 percent of respondents disagree and 10 percent of respondents partially agree to the statement “I share knowledge because, first of all, it gives a benefit to me”).
25 percent of respondents absolutely agree, 55 percent of respondents agree that knowledge sharing will strengthen the relationships with team members and encourage a better cooperation.
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However, only 40 percent of respondents agree that knowledge sharing helps them earn respect and trust, while 50 percent of respondents agree just partially to this statement. The respondents, who partially agree that knowledge sharing can strengthen relationships, also partially agree that knowledge sharing can earn respect and trust, but they believe it helps solve others’ problems and fulfil team tasks.
Research results also revealed the relationship between power index and attitudes towards knowledge sharing. Lithuanian power index is moderate (Huettinger 2008) so it means that Lithuanians still express their power, although moderately. In “Organisation N” 60 percent of respondents partially agree, agree or absolutely agree that knowledge sharing with a new employee in the organisation is a way to show their status and control. Jiacheng, Lu, and Francesco (2012) stated that in contrast to internalisation and identification a received reward doesn‘t influence intention to share knowledge directly (it was showed using a dotted line in Figure 1), but allows to identify with a group. All these various incentives are related to organisational factors. Research results also confirmed the existence of features of leadership, organisational culture, organisational structure and resources that are important to a complex adaptive system (see Figure 1). The attitudes of every knowledge worker in “Organisation N” were based on internalisation and identification and not on expected punishment or rewards for knowledge sharing. Also, a good organisational atmosphere helps knowledge workers in “Organisation N” cope against embedded beliefs of insecurity. An educated and experienced individual has an influence on organisational factors in a complex adaptive system and even cultural dimensions, although indirectly (a dotted line) because acquired scientific knowledge allows recognising a need to share knowledge and correct individual actions according to it. As it was noticed, historical realia still have an impact on the attitudes towards knowledge sharing. For example, the lack of trust and the feelings of insecurity are still deeply embedded in the minds of people. Even 40 percent of respondents belong to the category that partially agree, agree or absolutely agree that knowledge sharing could endanger the safety of the workplace (although there a real danger doesn’t exist). As it was mentioned above, all three respondents that just partially describe knowledge sharing as a pleasant activity, belongs to the category of those who think about the safety of their workplace. In fact, knowledge sharing behaviour of a concrete knowledge worker depends not only on individual, cultural and organisational factors, but also on knowledge sharing behaviour of other knowledge workers (Wang et al. 2009, Small and Sage, 2011) whose behaviour is also influenced by cultural dimensions, organisational factors and individual characteristics. These processes of knowledge sharing are an area of future research.
5. The main conclusions
In this article, a self‐organisation based system is understood as a complex adaptive system that is a successful contemporary knowledge organization. It is a complex, dynamic system, characterised by a continuous learning, distributed problem solving, and phenomena, emerging from bottom‐up dynamic processes without any intervention of a central controller (in other words ‐ self‐organisation processes) based on local interactions of autonomous agents ‐ knowledge workers.
Knowledge sharing in this article is understood as a process of the exchange of knowledge, experiences, and skills between knowledge workers. It is a prerequisite for self‐organisation based processes in a complex adaptive system.
Knowledge sharing factors in this article are analysed at individual and organisational levels, taking Hofstede’s cultural dimensions into account. A research in a Lithuanian organisation that has many features of a self‐organisation based system revealed that:
Knowledge sharing of employees is more based on internalisation (as that is common for individualistic cultures): knowledge is an interesting process that allows one to learn something new and feel being self‐ efficient by helping fulfil team tasks. However, the elements of identification can be seen in this organisation too, for example, respondents believe that knowledge sharing can strengthen the relationships between team members and encourage a better cooperation.
Organisational factors that encourage the members of this organisation to improve themselves, to learn and to acquire a good experience, are as follows:
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a leader that communicates organization’s vision clearly, always gives a response to the needs of employees, empowers knowledge sharing and creativity;
a flexible organisational structure based on the principle of networks;
an organisational culture that values risk taking, freedom to act, experimentation, trust, support of ideas, dynamism and creative conflicts, time to generate new ideas;
a diversity and quality of the tools and technologies of knowledge sharing.
However, this research revealed some beliefs and attitudes that still can be met in many Lithuanian business organisations and act as inhibitors of knowledge sharing and the formation of a self‐organisation based system, for example, the attitude towards power’s expression, an insufficient belief that knowledge sharing helps to earn the respect, appreciation and trust of team members, thoughts about a probable danger to the workplace because of knowledge sharing.
It’s necessary to conduct a research in the future on purpose to analyse knowledge sharing processes and knowledge sharing factors in a self‐organisation based system much deeper. The pilot research, presented in this article, just allows to get acquainted with knowledge sharing factors in a self‐organisation based system in some way.
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Mapping Research Community and Interests in KM: A Case of JKM Meliha Handzic1,2 and Nermina Durmic1 1 International Burch University, Sarajevo, Bosnia and Herzegovina 2 Suleyman Sah University, Istanbul, Turkey mhandzic@ibu.edu.ba ndurmic@ibu.edu.ba
Abstract: This paper reports an exploratory pilot study of KM researchers and their research interests based on articles published in one specialised academic journal: JKM. For each published article, keyword and author analysis was used to discover the main contributors and dominant themes and topics examined. The study suggests that KM is more popular in Euro-Africa than Americas or Asia-Pacific; published authors tend to be collaborative, but not very productive contributors to JKM; KM is explored in a wide variety of contexts; Core KM elements (enablers, processes and stocks) are explored more than the extended KM elements (drivers and outcomes). These findings need to be interpreted and applied with caution due to limitations in the single case journal, the selected framework, focus on the keyword rather than full text analysis and subjective classification of words. Future research is recommended to address these limitations and extend current research to a more comprehensive investigation of a wider range of publication outlets in KM including books and conference proceedings. Keywords: knowledge management (KM), KM domain mapping, KM community, keyword analysis, JKM
1. Introduction Journals play an important role in the recognition and development of any academic field. Given that the field of KM is relatively young, there are very few specialised journals that currently exist to support the recognition of KM as a distinct and reputable scientific discipline. Therefore, a comprehensive study of KM journals has been undertaken with a purpose of mapping knowledge management (KM) research to-date. This is carried out by analysing key characteristics of KM researchers and their research interests discussed in articles published in major academic journals in KM over the past two decades. A couple of other researchers have recently published similar reviews of ten years of KM theory and practice (Ribiere and Walter 2013) and a tenth anniversary assessment of Davenport and Prusak (1998/2000) Working Knowledge (Oliver 2013). This paper reports the results of an initial pilot study based on a single case journal: The Journal of Knowledge Management or JKM. The Journal of Knowledge Management (JKM) is one of the first and most successful. It was established in 1997 and has a sixteen-year-old legacy. Its coming-of-age â&#x20AC;&#x153;sweet sixteenâ&#x20AC;? birthday in 2012 coincided with obtaining its first impact factor of 1.248 in the Thomson Reuters Social Sciences Citation Index. More importantly, it has been recognised as the top journal by the KM community (Serenko and Bontis 2009, Bontis and Serenko 2009). Specifically, JKM was ranked number 1 in the recent global ranking of KM and IC academic journals. The ranking study concluded that the major factors affecting the quality of JKM were the importance of published research (inclusion in citation indexes, citation impacts and ranking lists) and people involved (leading researchers, the review board reputation and the editor). Due to its established position as a leading publication outlet for KM researchers, JKM may exert a great influence on both research and practice of KM. Therefore, the purpose of this study is to: (i) identify key characteristics of KM researchers who contributed to JKM in the period of 1997-2012; and (ii) discover dominant KM themes and topics that preoccupied these KM researchers over the past 16 years. It is hoped that the study of influential KM trends in the past may help plan its future course.
2. Approach A variety of methods have been used so far as a tool for scientific evaluation and strategy in a KM domain. Popular methods include bibliometric analysis (Gu 2004), citation impact (Serenko and Bontis 2004) and scientometric analysis (Serenko et al. 2010). Furthermore, subjective expert opinions (Edwards et al. 2003) and visual representations (Epler and Burkhard 2007) have also been applied to the analysis of a KM domain.
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Meliha Handzic and Nermina Durmic Compared to prior research, the focus of this study is on the analysis of researchers and topics published in a single top KM journal in order to provide a deeper understanding of the most influential research in the field. The study applied a combination of quantitative and qualitative content analysis of articles published in JKM in the period of 1997-2012. The process took place in three steps. In the first step, data were extracted from each article: year, volume, issue, article number, article type, title, authors, countries, keywords. A total of 793 articles from 82 issues in 16 volumes were sourced. Included were all published papers except editorials. In the second step, authors and their countries of origin were classified, counted and presented graphically. A total of 1380 different authors from 57 different countries from all 3 world regions were identified. In the third step, all extracted keywords were coded and counted according to the frequency they were mentioned. The Handzic et al. (2008) knowledge management framework presented in Figure 1 was used as a theoretical basis for keyword coding and classification. This framework identifies six major interrelated components of knowledge management: contexts, drivers, enablers, processes, stocks and outcomes. Two additional categories considered in the study were theoretical approaches and research methods based on Schwartz and Teâ&#x20AC;&#x2122;eni (2011). Prior work on consolidation and harmonisation of KM concepts (Heisig 2009) was also helpful in the process of classifying similar terms into appropriate categories.
KM contexts
socio-technical enablers KM drivers
learning processes
KM outcomes
knowledge stocks
adapted from Handzic et al. 2008
Figure 1: Knowledge management framework
3. Results The results of the analyses performed are presented in the following way. Firstly, the nature of the published work is investigated by looking at the distribution of different types of articles. This is followed by the analysis of authors in terms of their collaboration (number of authors per article, world regions of authors) and productivity (number of articles per author). Finally, topical analysis is performed in terms of six major KM elements (number of keywords per KM element), as well as relevant theoretical approaches and research methods. The resulting overall topical distribution is presented in the third sub-section.
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3.1 Types of published articles The analysis of 763 published articles presented in Figure 2 reveals that a wide variety of papers were contributed to the journal. Most articles were regular research papers (62%), followed by conceptual papers (18%) and case studies (10%). A small percentage of articles were general reviews (3%) and literature reviews (3%). Finally, a few articles represented viewpoints (2%) and technical papers (2%). Such a distribution seems to be fairly typical of an academic journal. Literature Review 3% General Review 3%
Viewpoint 2% Technical Paper 2%
Case Study 10% Conceptual Paper 18% Research Paper 62%
Figure 2: Distribution of articles by type
3.2 Characteristics of contributing authors Figure 3 shows the results of our analysis of authorship of each article. The results indicate that the majority of articles (64%) were co-authored by two or more individuals, while 36% were from a single author. Among collaborative papers, 33% were written by two, 22% by three, 6% by four, 2% by five and 1% by six co-authors. The results also indicate 0.1% of articles with ten co-authors. These results suggest the collaborative nature of the KM community of researchers. four 6%
five 2%
six 1%
ten 0% one 36%
three 22%
two 33%
Figure 3: Number of authors per article The analysis of regional distribution of authors was based on 709 articles in which this information was available. The results are presented in Figure 4. The division into these three world regions was adopted from the Association for Information Systems (AIS) classification (http://start.aisnet.org/?AISRegions). The results indicate that most articles (40%) originated from region 2- Europe/Africa. A similar percentage of articles originated from region 1- Americas (27%) and region 3-Asia/Pacific (24%). Only a small percent of articles resulted from inter-regional or global collaborations (9%).
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Global 9%
Americas 27%
Asia/Pacific 24%
Europe/Africa 40%
Figure 4: Regional distribution of articlesâ&#x20AC;&#x2122; authors A list of 57 countries of origin by regions is provided in Table 1. Individual countries were identified on the basis of the authorsâ&#x20AC;&#x2122; institutional affiliation. These countries are listed in alphabetical order. The list suggests that European researchers dominate the KM field. An additional analysis indicated that most contributors from regions 1, 2 and 3 came from USA, UK and Australia respectively. Table 1: Countries of origin by world regions World region Region 1: Americas (7 countries)
Country of origin Brazil, Canada, Colombia, Jamaica, Mexico, Puerto Rico, USA Austria, Belgium, Bosnia and Herzegovina, Czech Republic, Denmark, Egypt, Finland, France, Germany, Ghana, Greece, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Netherlands, Nigeria, Norway, Poland, Portugal, Russia, Slovenia, South Africa, Spain, Sweden, Switzerland, Tunisia, UK Australia, Bahrain, China, India, Iran, Israel, Japan, Jordan, Korea, Kuwait, Lebanon, Malaysia, New Zealand, Pakistan, Saudi Arabia, Singapore, South Korea, Taiwan, Thailand, Turkey, UAE
Region 2: Europe/Africa (29 countries)
Region 3: Asia/Pacific (21 countries)
A total of 1380 different authors published their work in JKM over the past 16 years. The overwhelming majority of 87% published only one article. Among the remaining 23% of returning authors, 9% published two and 2% three articles. Only 1% of authors published four or five articles, and even less than 1% published six (0.14%) or seven (0.07%) articles. This finding is almost identical to that reported for KMR&P journal by Handzic (2012). On this basis, one may infer that KM researchers are not very productive writers. three 2%
four 1%
five 1%
six 0% seven 0%
two 9%
one 87%
Figure 5: Number of articles per author
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Meliha Handzic and Nermina Durmic The ten most prolific authors were: Kostas Metaxiotis, Kostas Ergazakis, Nick Bontis, Alexander Serenko, Chong Ju Choi, Francisco Javier Carrillo, Jay Chatzkel, Jennifer Rowley, Karl M. Wiig and Mirghani Mohamed. No contributions were found by Nonaka, Nonaka&Takeuchi and Davenport&Prusak, who are considered the most important authors and co-authors in KM (Edwards et al. 2003).
3.3 Classes of KM topics discussed A total of 3189 keywords from 793 articles were analysed. They were coded and counted according to KM elements (2397), theoretical approaches (739) and research methods (53) discussed. The most frequently mentioned keywords by classes of topics are listed in Table 2. With respect to theoretical approaches, knowledge management was the most frequently named approach, followed by intellectual capital, organisational learning and human resources management. Table 2: Dominant classes of topics in articles Classes of topics 1. Theoretical approaches 2. Six KM elements a. knowledge contexts b. knowledge drivers c. knowledge enablers d. knowledge processes e. knowledge stocks f. knowledge outcomes 3. Research methods
Most frequent keywords (repeated >10 times) knowledge management, intellectual capital, organisational learning, human resources management regions: cities, China, Spain; institutions/industries: organisations, SMEs, public sector organisations; business activities: management, project management, decision making; knowledge economy, knowledge work, knowledge organisations, learning organisations, motivation social: organisational culture, leadership, trust, communities, networks; technical: communication technologies, knowledge management systems, information technology, information systems; knowledge transfer, knowledge sharing, knowledge creation, learning, knowledge processes, modelling, research, information exchange tacit knowledge, information, knowledge, social capital, explicit knowledge, competencies innovation, organisational performance, competitive advantage case studies
The most frequently explored contexts were nations (China, Spain), cities, organisations (SMEs, public sector organisations) and business activities (management, project management, decision making). Among drivers, knowledge economy was mentioned more often than others. With respect to enablers, culture was dominant among social enablers and communication technology among technical enablers. With respect to processes, stocks and outcomes, knowledge transfer/sharing, tacit knowledge and innovation were most popular. Regarding research methods, only a very small number of keywords explicitly specified these. Case studies were dominant. Surveys and action research were also mentioned, but less frequently (less than 10 times). Further results for six KM elements are provided in Figure 6. The figure shows that the greatest attention was payed to KM contexts (31%), followed by enablers (21%) and processes (19%), then knowledge stocks (11%) and outcomes (12%). The least discussed topic was KM drivers (6%).
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outcomes 12% contexts 31%
stocks 11%
processes 19%
drivers 6% enablers 21%
Figure 6: Six KM elements discussed
4. Discussion In summary, this study contributed two main findings. It identified the character of JKM’s community of KM scholars and their KM interests on the basis of their work published in the journal since its beginning in 1997 th up to its 16 birthday in 2012. Given that the findings for JKM are comparable with those for KMRP (Handzic 2012), they may be representative of the wider KM community and research trends.
4.1 KM research community The majority of examined articles published in JKM were regular research papers. With respect to their authors, the study suggests the collaborative nature of these KM researchers, as evidenced by the high percentage (64%) of co-authored articles. However, these co-authorships are limited to intra-regional, rather than inter-regional or global collaborations. Only 9% of articles resulted from collaborations between two or three regions. With respect to intra-regional results, the findings suggest that KM is much more popular in Europe/Africa than in Americas and Asia/Pacific. European researchers seem to dominate the field. Furthermore, our analysis reveals that the overwhelming majority of authors (87%) published only one single paper in JKM over the past 16 years. One possible reason may be that the journal was not ranked before 2009 and indexed before 2012. “Publish or perish” is a dire warning to both current and prospective KM researchers and they should all seek to publish in reputable outlets. Peer-review publications in SSCI indexed journals such as JKM (and KMRP) represent the standard for one’s credibility as a researcher. They are also required for faculty advancements, promotions and tenure at most universities (Serenko and Bontis 2009). A somewhat disappointing finding of our investigation is a visible absence of contributions from the “founding fathers” of KM in JKM. On the other hand, the presence of several new names is indicative of the possible rising “KM stars”.
4.2 KM research trends The majority of articles approached the KM issues from the holistic perspective of knowledge management or organisational learning. Some others concentrated on the economic perspective of intellectual capital and the behavioural perspective of human resources management (Earl 2001). The prevailing reliance on integrative approaches to KM advocated by many authors (e.g. Holsapple 2003, Handzic and Hasan 2003) is encouraging. The current literature offers a variety of such KM frameworks that can serve as a good basis for future empirical research (Heisig 2009). The issues that preoccupied KM researchers mostly concern elements of appropriate KM solutions. These were discussed in terms of socio-technical knowledge enablers, processes and stocks. They were examined mostly in organisational contexts, especially SMEs and public sector organisations. The most frequently discussed knowledge stock was of tacit type, the most frequently mentioned process was knowledge
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Meliha Handzic and Nermina Durmic transfer/sharing/exchange, and the most frequently named social and technical enablers were organisational culture and communication technology. Knowledge (based) economy was most frequently cited as a driver of KM, while innovation was mentioned most frequently as an outcome of KM. However, there were much less discussions about drivers and outcomes of KM than other issues. Yet, aligning KM with business strategies and linking KM to business performance are essential if the field is to remain relevant to practice (Hansen et al. 1999). Future research may address this limitation. Generally, research orientated towards innovation, tacit knowledge, sharing, culture and communication technology is considered most valuable for developing innovative advancement strategies and achieving competitive advantage (Von Krogh et al. 2000). Very few articles mentioned research methods in their lists of keywords. Thus, it is hard to make any firm conclusions about methodological preferences in KM research without deeper analysis of each individual article. Nevertheless, the most frequently named method gives us a hint that “case studies” were the most popular method. The strength of case studies is in that they allow the examination of complex phenomena in natural settings, however they are weak for making causal inferences (Miles and Huberman 1994). Future KM research should “triangulate” in order to enhance the validity of current findings. In addition, it might be helpful to readers if the list of keywords associated with articles would include their theoretical basis and method of research.
5. Conclusions The current study provided a descriptive analysis of KM authors and topics in articles published by JKM over the past 16 years. The key findings suggest that KM is most popular among European researchers, who are likely to be collaborative, but not overly productive authors. So far, they have been more preoccupied with core KM issues (i.e. enablers, processes and stocks) than with business reasons behind KM (i.e. drivers and outcomes). The study makes two important contributions to research and practice. For research, it points to underinvestigated issues that may guide future research in the KM domain. For practice, it provides a quick reference guide to the field of KM from the authoritative source (JKM) that can be fruitfully employed for strategic planning. However, current findings need to be interpreted and applied with caution due to limitations in the selected single case journal, theoretical framework, focus on the keyword rather than full text analysis, and subjective classification of words. Future research is needed to address these limitations and extend current research to a more comprehensive investigation of specialised publication outlets in KM.
References Bontis N. and Serenko A. (2009), A follow-up ranking of academic journals, Journal of Knowledge Management, Volume 13, Issue 1, pp. 16-26. Earl M. (2001), Knowledge Management Strategies: Toward a Taxonomy, Journal of Management Information Systems, Volume 18, Number 1, pp. 215-233. Edwards J., Handzic M., Carlsson and Nissen M. (2003), Knowledge management research & practice: visions and directions, Knowledge management research & practice, Volume 1, Number 1, pp. 49-60. Epler M. and Burkhard R. (2007), Visual representations in knowledge management: framework and cases, Journal of Knowledge Management, Volume 11, Issue 4, pp. 112-122. Gu Y. (2004) Global knowledge management research: a bibliometric analysis, Scientometrics, Volume 61, Number 2, pp. 171- 190. Handzic M. and Hasan H. (2003), The Search for an Integrated KM Framework, chapter 1 in Hasan H and Handzic M (eds) Australian Studies in Knowledge Management, UOW Press, Wollongong, pp. 3-34. Handzic M., Lagumdzija A. and Celjo A. (2008), Auditing Knowledge Management Practices: Model and Application, Knowledge Management Research & Practice, Volume 6, Number 1, pp. 90-99. Handzic M. (2012), Surveying the field of KM: evidence from KMR&P, Presentation at the first IAKM workshop, 16 April 2012, Padua, Italy. Hansen M.T., Nohria N. and Tierney T. (1999), What’s Your Strategy for Managing Knowledge?, Harvard Business Review, March-April, Volume 77, Number 2, pp. 106-116. Heisig P. (2009), Harmonisation of knowledge management – comparing 160 KM frameworks around the globe, Journal of Knowledge Management, Volume 13, Issue 4, pp. 4-31.
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Meliha Handzic and Nermina Durmic Holsapple C.W. (2003), Knowledge Management Handbook, Springer, Berlin. Miles M.B. and Huberman M.A. (1994), Qualitative Data Analysis, Sage, London. nd Schwartz D.G. and Teâ&#x20AC;&#x2122;eni D. (2011), Encyclopedia of Knowledge Management, 2 ed., IGI Global. Oliver G. (2013), A tenth anniversary assessment of Davenport and Prusak (1998/2000) Working Knowledge: Practitioner approaches to knowledge in organisations, Knowledge Management Research & Practice, Volume 11, Number 1, pp. 10-22. Ribiere V. and Walter C. (2013), 10 years of KM theory and practices, Knowledge Management Research & Practice, Volume 11, Number 1, pp. 4-9. Serenko A. and Bontis N. (2004), Meta review of knowledge management and intellectual capital literature: citation impact and research productivity rankings, Knowledge and Process Management, Volume 11, Number 3, pp. 185-198. Serenko A. and Bontis N. (2009), Global Ranking Of Knowledge Management and Intellectual Capital Academic Journals, Journal of Knowledge Management, Volume 13, Issue 1, pp. 4-15. Serenko A., Bontis N., Booker L., Sadeddi K. and Hardie T (2010), A scientometric analysis of knowledge management and intellectual capital academic literature, Journal of Knowledge Management, Volume 14, Issue 1, pp. 3-23. Von Krogh G., Ichijo K. and Nonaka I. (2000). Enabling Knowledge Creation, Oxford University Press Inc., New York.
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Developing a Knowledge Strategy Using Tacit Knowledge Measurement: Implications for the Balanced Scorecard Innovation and Learning Perspective Harold Harlow Porter Byrum School of Business, Wingate University, USA h.harlow@wingate.edu Abstract: My research proposes the use of the tacit knowledge index (TKI) to assess the level of tacit knowledge within firms and develop practical measures‐key performance indicators (KPIs) that can be used by managers. Knowledge strategy is defined and proposes using the TKI to choose the most effective knowledge management methods needed to achieve the company strategic key performance indicators (KPIs) for the balanced scorecard (BSC) innovation and learning perspective. I used regression and correlation to statistically analyze relationship of knowledge strategy (KS) to the innovation and financial outcomes of the surveyed firms. Significant relationships were found between a firm’s knowledge strategy, level of TKI and the firm’s innovation performance. Keywords: tacit knowledge management, knowledge management. knowledge management systems. balanced scorecard, innovation
1. Introduction Many executives in the 1980’s argued that financial measures alone did not allow them to manage effectively and wanted to replace those measures with operational measures. David Norton and Robert Kaplan (1992) proposed and championed the Balanced Scorecard (BSC) that included both operational and financial measures that would lead to a better understanding of whether or not the company was effectively achieving its long‐term strategy (Kaplan & Norton 1996). A model is developed and empirical research applied in this paper to further the idea of creating a knowledge strategy that can use both measureable inputs for knowledge development in the Innovation and Learning Perspective of the BSC and develop key performance indicators and outputs to measure business results. The late Peter Drucker (1999) invented the term “knowledge worker’ said that that “knowledge has become the key economic resource and the dominant‐and perhaps even the only‐source of competitive advantage.” Further, a firm’s knowledge and intellectual capital can be dynamically deployed and redeployed to form a basis for competitive advantage (Teece 2000). Strategic frameworks have been proposed to relate the role of knowledge to strategy (Von Krogh, Ichijo, & Nonaka 2000) with astute management of the value in a firm’s competence/knowledge base is a central issue in developing firm strategies (Teece 1986). Business has recognized that not all knowledge yields competitive advantage (Von Krogh et al. 2000). Of the two types of knowledge (tacit and explicit), tacit knowledge is the more strategically valuable since it is hard to duplicate, cannot be easily transported to another firm and is embedded in the group culture and social understandings. The first part of my research develops the concept of a knowledge strategy that in turn produces (1) a culture that rewards and encourages knowledge sharing and (2) selection of knowledge management (KM) methods to produce firm results. Further, my empirical research has developed an operational definition of a tacit knowledge index (TKI) that provides a measurement tool for managers to use in determining if a knowledge strategy and appropriate knowledge management methods produce the desired strategic knowledge outcomes (innovation and learning perspective). Finally, the connection to the Innovation and Learning Perspective is developed and performance based measurements that relate the strategy and TKI are developed. The innovation and learning perspective has been the most difficult perspective for which to develop adequate managerial metrics and is often the area least represented in strategy linked KPIs for the firm (Kaplan & Norton 1996). By defining knowledge strategy using the drivers of the innovation and learning perspective outlined by Kaplan and Norton (1996) and using TKI as a measure, it is an objective of this research to allow managers to develop more user‐friendly innovation and learning KPIs at both a micro and macro level.
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2. Literature review 2.1 The balanced scorecard The BSC uses four parameters (financial, customer, internal processes and learning and innovation) to develop metrics that directly link to the strategy of the firm (Kaplan and Norton, 1996b). By tying each of these parameters to the overall firm strategy (Kaplan & Norton 2001), firms link the strategy to programs and actions(Kaplan & Norton, 1996) and gain from the inter‐relational effect of each parameter’s metrics resulting in even better firm performance. Norton and Kaplan (1992) propose using technology leadership, manufacturing learning, product focus and time to market as goals for the innovation and Learning perspective. Metrics from these goals are proposed as time to develop the next generation, process time to maturity, percent of products that equal 80% of sales and new product introduction vs. competition. Straightforward measures for the financial, customer perspective and internal processes parameters have been developed. However, many companies implementing BSC have struggled to devise scorecard metrics for the learning and innovation parameter. Kaplan and Norton (1996) have found that companies draw from a common core of three outcome measurements‐employee satisfaction, retention and productivity. Within this core, the employee satisfaction objective is considered the driver of the other two dimensions. They explain that staff competencies, technology infrastructure and a climate for action enable the core measurements. The drivers for staff competency are strategic skills, training levels and skill leverage. Drivers for technology infrastructure include strategic technologies, strategic databases, experience capture, proprietary software and intellectual property. The climate‐for‐action driver includes key decision cycle, strategic focus, staff empowerment, personal alignment, morale and teaming. These drivers are the same survey measures that determine the extent of the firm’s Knowledge Strategy (KS) used in this research and form the basis for the use of the TKI to implement these drivers.
2.2 Knowledge, intellectual capital and knowledge strategy What is knowledge? Ikujiro Nonaka and Noburu Konno (1998) think that knowledge is a “shared space for emerging relationships that can be either a physical space, virtual, mental or any combination of the above.” This concept is known as “ba”‐and was proposed originally by Japanese philosophers Kitaro Nishida and refined by Shimizu. “Ba” provides a shared place that provides meaning. According to the theory of “ba”, knowledge is not information nor is it tangible. Knowledge may be created and shared using “ba” but knowledge is constantly undergoing change and transformation to new levels of knowledge. This change is presented in the SECI (socialization, externalization, combination, internalization) model of spiral evolution of knowledge creation and the self transcending process (Nonaka and Konno 1998) that uses the concept of an ever changing spiral evolution of knowledge from tacit to tacit through internalization and socialization and from tacit to explicit through externalization and combination. This is the definition used in this research because it succinctly presents that knowledge exists as a continuum and the interplay of tacit and explicit knowledge creates ever more knowledge. According to a survey conducted by the International Center for Business Information, 97% of executives in eleven countries considered knowledge an essential part of value creation(ICBI 1997). According to Krogh, Ichigo and Nonaka (2000), “the first responsibility of managers is to unleash the potential of an organization’s knowledge into value creating activities”. The firm specific concept of intellectual capital was introduced in the early 1990s which connected the idea of a firm’s knowledge to the concept of firm intellectual capital to address valuation of intangibles and to further explain the idea of value creation and its relationship to firm performance (Edvinsson & Malone, 1997; Roos and Roos 1997; Stewart 1997; Sveiby 1997). It is not sufficient to have knowledge assets, patents, or other marketable intellectual property. In a knowledge creating company, managers have the responsibility to unleash that knowledge into value‐creating actions aimed at customers and to generate and exploit that knowledge‐either public or proprietary‐more effectively than their competitors. In addition, managers are also responsible to generate and exploit current firm knowledge better than their competitors and to use public knowledge better than their rivals (Von Grogh & Ichigo, et al 2000). Von Krogh, Roos and Slocum (1994) suggest that there are essentially only two strategies used and that those are advancement and survival. Ansoff (1990) also uses these two distinctions as operational effectiveness strategy and developing future profit potential strategies. Both authors’ survival
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Harold Harlow strategies target securing current firm profitability while the advancement strategy focuses on future firm profitability. As a knowledge strategy, these can be broken a strategic knowledge framework with the role of knowledge in survival strategies that of creating trade secrets or using public knowledge in ways that competitors cannot easily duplicate. Processes associated with this type of strategy are knowledge transfer and continuous improvement with their ultimate metric profitability higher than the industry average. The role of knowledge in an advancement strategy is much different and includes new product or process knowledge and transferable new knowledge. Processes associated with the advancement strategy strategic framework include new knowledge creation and radical innovation. The goal of this strategic knowledge strategy is to attain higher than industry average future profitability(Von Grogh & Ichigo, et al 2000). Firms differ in their industry life cycle stage and future direction so employing one of these strategic knowledge strategies over another depends on the firm strategic thrust and may be based on one of Porter’s strategies or the Miles and Snow strategy topology. All of the definitions of intellectual capital imply that knowledge is both known to the management and can be converted into value (Edvinsson & Sullivan 1996) and is about knowledge and knowing capability of a social collectivity (Nahapiet & Ghoshal 1998), packaged useful knowledge (Stewart 1997), " and Intellectual capital= competence × commitment” (Ulrich 1998).
2.3 Knowledge management The definition of knowledge management (KM) is that it is the formal process of determining what internally held information could be used to benefit a company and ensuring that this information is easily and systematically (Love 2000) made available to those who need it (Roy 2002). A firm’s overall economic, strategic, and innovation performance is dependent on the degree to which the firm can use all of the knowledge created by the firm and turn this knowledge into value‐creating activities (Krogh, 1998). KM is a strategic process, the desired goal of which is to harness the value of information by integrating it with processes that govern the manipulation of intellectual assets (Loshin, 2001). The use of KM enables firms to have more effective decision‐making processes and enables firms both to create new knowledge and to apply this knowledge to generate more innovation in products, strategy, and processes (Probir 2002). Greater levels of innovation and improved processes in turn lead to enhanced market and financial performance. Empirical studies (Ernst & Young 1994) have made surveys that show that 46% of executives believe that their firm’s KMS performance is good to excellent at creating new knowledge but only 4% rate their firm’s performance as good in measuring the value of knowledge assets and/or the impact of KM (Ernst and Young 1994). In developing these processes, surveys have shown that the people side of the KMS, dealing mostly with sharing and creating tacit knowledge, is the most difficult area of KMS‐56% rate this as the most difficult area‐and measuring knowledge assets and their value is the second most difficult process ‐43%‐(Ruggles 1998). This lack of empirical information on the impact of a KMS that includes both tacit and explicit methods has meant that firms often choose technology solutions that are designed to capture and disseminate mostly explicit knowledge (Almeida & Kogut 1999). While these systems offer the advantage of ready usage metrics, their actual contribution to effective KM within the firm is less clear (Berman, Down & Hill 2002). The degree of explicit codification‐ more manuals or product plans do not presage success at firms‐does not indicate that the knowledge encoded is valuable or unique. Firms may have extensive libraries of codified knowledge that is rarely accessed or is bypassed by unmapped tacit processes. Gaps in the current research reveal that there is no validation of which KM methods (either explicit or tacit or a combination of both) are more or less effective, and there has been little research that looks at the relationship of KMS to the firm’s outcomes (Grant 1996). This research focuses on developing a measure of the value of tacit knowledge assets and/or impact of knowledge `management by having senior experienced executive’s rate knowledge management methods according to their degree of tacitness or explicitness. A firm can determine its degree of usage and hence use the underlying tacitness to evaluate its relationship to the innovation and financial impact of knowledge management at the firm. Further, this research can help managers determine which knowledge management strategy is being used‐either explicitly or implicitly‐at the firm to allow managers to adjust their strategy to achieve better financial or innovation outcomes.
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Harold Harlow Firms are able to develop a sustainable competitive advantage in KM by developing a mix of KM methods that complement and enable their core strategies (Hansen 2002). However, despite large investments in KM technology, many of the performance outcomes are not clear and the causal relationship between what works and what does not work has not been established empirically (Liebeskind1996). This gap in the causality is another rationale for this research. It is further argued that firms with greater degree of managing knowledge, and specifically tacit KM, will achieve higher than average returns. The measures of economic effectiveness of KM systems have frequently used the Return on Sales (ROS), share price, growth of sales, and other financial metrics as a test to the success of KM systems (Sveiby 1997). These metrics provide useful information but may be hard to measure in large global firms that use KM in only part of their operations. . A firm’s overall economic, strategic, and innovation performance is dependent on the degree to which the firm can use all of the knowledge created by the firm and turn this knowledge into value‐creating activities (Krogh 1998). These firms are able to use the tacit knowledge component of KM to create hard‐to‐duplicate core competence in managing, identifying, capturing, systemizing, and applying tacit knowledge to create customer value as measured by innovation and economic outcomes. In order to measure the innovation and economic outcomes of the firm, it is important to understand how and why tacit KM is both crucial and necessary in today’s firms.
2.4 Tacit knowledge Polyani (1965) states that “ We know more than we can tell”. Despite over fifty years of study and research, a definition accepted by all researchers as to what tacit knowledge is and how to measure and use it is elusive (Harlow, 2012)The identification of what is explicit knowledge is relatively straightforward. Drawings, e‐mails, policy manuals, product manuals, and other forms of explicit knowledge lend themselves to the application of metrics. While tacit knowledge and explicit knowledge coexist in a continuum (or as a knowledge spiral) complementing each other, the explicit knowledge forms are more easily extracted and measured (Nonaka 1998). The measurement of tacit knowledge is less clear. Tacit knowledge can be part of the group collective knowledge (Spender 1996). This socio‐cultural knowledge (Castillio 2002) drives the organization, but it is difficult to measure. The term practical intelligence has been used as a proxy for tacit knowledge (Sternberg 1997). Others have developed tools for measuring tacit knowledge as part of their work on quantifying managerial intelligence (Wagner & Sternberg 1992). Measuring tacit knowledge is also seen as “risky business” (Nonaka & Takeuchi 1995). Somech (1999) details how tacit knowledge is quantified in college freshmen and can be measured as the students gain more tacit knowledge as they progress to seniors. Wagner & Sternberg (1985) defined tacit knowledge as “that work‐related practical knowledge learned informally on the job”. This definition defines only one part of tacit knowledge, that is, the part that encompasses know‐how. The other part of tacit knowledge is the cognitive dimension (Beamer 2001) which consists of beliefs, values, attitudes, ideals, mental maps, and schemata which are related to the cultural shaping of the individual and the group. This cognitive dimension of tacit knowledge is a most important, yet most difficult, part of enabling knowledge creation and dissemination.
3. Methodology 3.1 Sampling The primary research survey was a random survey sent to 628 knowledge management professionals who were selected based on their titles from a list of over 68,000 knowledge management industry professionals in the United States and Canada. The full responses were 112 executives and knowledge management professionals.
3.2 Method The main research variable was operationalized by asking industry experts (Delphi method) to rate the tacit‐ ness of the top 15 knowledge management methods used in firms in the USA and Europe. Usages rating at each of the companies were then used to multiply the expert ratings by this usage to arrive at a method TKI. Finally, the method TKI was totaled and an overall firm TKI was used in a regression analysis against the various performance outcomes. The two‐stage approach and experts’ pretest used in this research to
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Harold Harlow determine tacit‐ness has been used previously to measure tacit knowledge levels between subjects (Somech & Bogler 1999; Harlow 2004).
3.3 Definition of key variables Innovation, Financial and Knowledge Strategy defined as follows: Table 1:‐Key variables Innovation(Dependent)
Financial(Dependent)
Product Turns as Related to Competitors Number of New Products as Related to Compeititors
Return on Sales Cost of Goods Sold
Patents as compared to competitors # New Products Compared to Competitors Market Share Product Line Age
Earnings Per Share Share Price over the Last Three Years Return on Equity Revenues
Marketing Effectiveness
Profits
Knowledge Strategy(Independent) Investment in the Capability to Share Knowledge Internally Use and Investment in the Capability to Measure Knowledge Sharing Rewards for Sharing Knowledge Employee Satisfaction Retention & Productivity Information Technology Choices Compared Competitors Knowledge Management Processes Knowledge Content
3.4 Research hypotheses A firm’s overall economic and innovation performance is dependent on the degree to which the firm can use all of the knowledge created by the firm and turn this knowledge into value‐creating activities (Krogh, 1998). This led to the following hypotheses: Hypothesis 1: There is a positive association between the Tacit Knowledge Index (TKI) and Firm Outcomes. Hypothesis 2: TKI has a positive relationship to innovation and financial outcomes. Hypothesis 3: There is a positive relationship between firms that have a knowledge strategy and innovation and financial outcomes.
4. Results The highest tacit rated KM methods were collaboration (4.8), master craftsman (4.8) and communities of practice (4.7). Teaming was rated lower (4.3) which was unexpected. The resultant TKI variable was one that combined the reliable tacitness (TK) measurement with the survey usage to arrive at the TKI for the firm. Table 2 below presents the results of the regression of the TKI variable against the Innovation and Financial variables. Tacit Knowledge Index(TKI) is determined from the summation of the total tacit knowledge scores developed in the research. A higher regression value of TKI vs, the innovation(R2=.389) value indicates a stronger relationship of TKI to Innovation rather than Financial outcomes(R2=.237). Table 2:‐Summary results of regression analysis TKI (I) R R2 F
Innovation (D) .616 .389 21.04***
**P<.005 ***P<.001
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Financial (D) .487 .237 6.03**
Harold Harlow Table 3 below depicts a significant finding of a strong relationship between the KS independent variable and innovation, R2 =.448, and financial variable, R2=.388, variable of the firm in this study. The TKI has a strong relationship to the KS variable, R2=.563. The relationship between these two variables is an indicator that firms that develop a knowledge strategy (KS) also develop higher levels of tacit knowledge. The innovation performance outcome is most highly predicted by the KS factor. This means that there is a relationship between firms that perform those activities that score high on the KS and those that develop strong performance that, over time, may lead to sustainable competitive advantage. There was also a strong relationship of KS to financial outcomes. This high Beta value and R2 indicate that KS predicts both innovation and financial outcome to a high degree. The results indicates a strong relationship between those firms that have a specific and recognizable knowledge strategy and firm performance. This has implications for implementing BSC Innovation and Learning metrics and connecting the use of TKI to this BSC implementation. Table 3:‐Regression of the Knowledge Strategy (KS) independent variable to the innovation, financial outcome and TKI variables Dependent variable
R
R2
Adjusted R2
Beta
t
.669
.448
.443
.669
9.278
.000
.623
.388
.382
.623
8.192
.000
p
Innovation Financial
TKI .750 .563 .542 .750 7.123 .000
5. Results of the empirical research The experts confirmed that what is being measured in each method is a measure of the medium of knowledge sharing or the method’s throughput capability of tacit knowledge. When combined with usage at a firm, using a Likert scale measure, TKI is positively associated with firm performance. The following summarizes the results of this research: Hypothesis 1‐There is a positive association between the Tacit Knowledge Index (TKI) and Firm Outcomes. This hypothesis was accepted and the null rejected because there was a positive relationship between TKI and Innovation and Financial outcomes. Hypothesis 2‐Firms that have a high TKI will have a higher degree of innovation and better financial results. This hypothesis was accepted and the null rejected since TKI had a strong relationship to Innovation outcomes and a positive relationship to financial outcomes. Hypothesis 3‐There is a positive relationship between firms that have a knowledge strategy and innovation and financial outcomes. This hypothesis was accepted and the null rejected since there was a moderate relationship between Knowledge Strategy (KS) and firm performance. Firms whose environments require more innovation would be advised to develop a knowledge strategy and use the methods that are highest in TKI throughput such as experting, collaboration and master craftsman. In addition, the research results also showed a strong relationship between firms that have a knowledge strategy (KS). Armed with these recommendations, managers are now able to measure the KS and TKI of their firm by determining the usage of the various KM methods and using our expert rating of the underlying tacit‐ness of each method. This is a significant step because it sets the stage for more detailed studies with more definition of each of the variables and perhaps a look at how this tacit measure affects firm strategic choices.
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Harold Harlow TKI measure should allow firms to make better strategic decisions, since firms that identify TK as important make better decisions during the strategic decision‐making process (Brock & Anthony, 2002). The study by Brock and Anthony provided an integration of the cognitive and strategic literatures to show that TK is accessible and how it plays an integral role in the context of strategic decision‐making. Brock and Anthony proposed that better decisions would occur when TK is employed overtly during strategy sessions. This lends itself to the creation of a knowledge strategy and development of the KS to drive the business performance.
5.1 Research limitations The small relationship of TKI to financial outcomes limits this study’s use in predicting financial performance. Also, new research is needed to determine how to develop and use TKI as a predictor of strategic performance. The research methodology of using managers to rate their usage of various methods at firms could differ systematically from actual usage of KM at the firms. Manager’s might reflect either more or less actual usage than is occurring and measurement use of actual occurrences over a long period of time might produce an entirely different result, either meaning less or more relationship to the TKI variable. This study also may raise questions as to which knowledge methods should be included and to the use of an overall scale to capture what is a tacit attribute of each method. The five point Likert scale used in the study provides a limited measurement scale and may miss significant resolutions in the data set. Further research using a seven point scale might produce results that would be more clearly defined.
6. BSC innovation and learning perspective metrics The TKI solves the BSC innovation and learning measurability problem by giving managers a way to increase the company’s learning and innovation parameters through knowledge strategy implementation programs (such as experting, communities of practice and collaborative) that can be directly measured using the TKI. For example, BSC metrics for experting would be calculated by identifying the number of experts and multiplying that number times the reported usage of these experts by staff (another number) times the tacit rating of each method as provided by the this research(the last number). This can be repeated for each of the fifteen (15) factors (i.e., communities of practice, collaborative, teaming) to arrive at a final score for the base and improved TKI. Finally, these metrics can be related to improvements in financial and innovation outcomes by regressing the resultant TKI against these two variables. The development of a KM strategy within the BSC Innovation and Learning Perspective framework enables firms to address survival and advancement strategies with appropriate measures and resources. Tacit knowledge plays a key role in both of these strategies on the one hand in survival of ensuring that firms maintain a competitive advantage by easily transferring hard to imitate knowledge and in the case of advancement creating new knowledge through radical or disruptive innovation. The use of a TKI based metric within the BSC framework could help assure that both operational and strategic knowledge use and creation was being supported and accomplished.
References Almeida, P. & Kogut, B. (1999). “Localization of Knowledge and Mobility of Engineers in Regional Networks”. Management Science, Vol. 45: 905‐917. Barney, J. B. (1991) “Firm Resources and Sustained Competitive Advantage”, Journal of Management, Vol. 17: 99‐129. Berman, S. L., Down, J., & Hill, C. W. L. (2002) “Tacit knowledge as a Source of Competitive Advantage in the National Basketball Association”, Academy of Management Journal, Vol. 45: 13‐31. Beamer, L. Varner, I.(2001) Intercultural Communication in the Global Workplace. McGraw‐Hill Boston. Brock, E. N., & Anthony, W. P. (2002) “Tacit Knowledge and Strategic Decision‐Making”, Group & Organization Management, December, Vol.27: 436‐455. Castillio, J. (2002) “A Note on the Concept of Tacit Knowledge”, Journal of Management Inquiry, Vol. 11(1): 46‐57. Drucker, P. (1999) Managing in a Time of Great Change, Harper Business, New York. Drucker, P. (1959) The Landmarks of Tomorrow, Harper and Brothers, New York. Edvinsson, L., Sullivan, P. (1996) “Developing a Model for Managing Intellectual Capital”, European Management Journal, Vol. 14(4): 356‐365. Edvinsson, L., Malone, M. (1997) Intellectual Capital: Realizing Your Company's True Value by Finding its Hidden Roots, Pratkus, London. Grant, R. M. (1996) “Toward a Knowledge‐Based Theory of the Firm”, Strategic Management Journal, Vol. 17 (summer special issue): 109‐122 Hansen, M. T. (2002) “Knowledge Networks: Explaining Effective Knowledge Sharing in Multiunit Companies”, Organization Science, Vol.1: 232‐249.
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Harold Harlow Harlow, H.D. (2008) "The effect of tacit knowledge on firm performance", Journal of Knowledge Management, Vol. 12 Is: 1, pp.148 ‐ 163 Harlow, H.D.(2012) “Fifty‐Plus Years On and the Question Remains: Why do we still not have a Theory of Tacit th Knowledge?” Proceedings of the 13 annual European Conference on Knowledge Management. pp. 450‐458. Cartegena, Spain. Kaplan, R.S., Norton, D.P. (1996), Translating Strategy into Action. Harvard Business School Press. Boston. Kaplan, R., & Norton, D. (1992, January‐February) “The Balanced Scorecard: Measures that Drive Performance. Harvard Business Review, 71‐79.Kaplan, S. (2002) “Knowledge Management the Right Way: A Step‐by‐Step Approach That Will Ensure That Your Expensive Knowledge Management System Actually Gets Used”. CIO, 15(19), 75‐81.Leonard, D., Sensiper, S. (1998) “The Role of Tacit Knowledge in Group Innovation”, California Management Review, Vol. 40(3): 112‐132. Liebeskind, J.P. (1996) “Knowledge, Strategy and the Theory of the Firm”, Strategic Management Journal, Vol.17: 93‐107. Loshin, D. (2001) Enterprise KM, Morgan Kaufmann, San Francisco Nahapiet, J. and Ghoshal, S. (1998) “Social Capital, Intellectual Capital and the Organisational Advantage”, Academy of Management Review, Vol. 23(2): 242‐266. Nonaka, I. (1994) “A Dynamic Theory of Organizational Knowledge Creation”, Organization Science, Vol. 5(1): 14‐38. Nonaka, I., & Takeuchi, H. (1995) The Knowledge Creating Company: How Japanese Companies create the Dynamics of Innovation, Oxford University Press, New York. Polanyi, M. (1966) The Tacit Dimension, Doubleday Anchor, Garden City Probir, R. (2002). “Tacit KM in Organizations: A Move towards Strategic Internal Communications Systems”, Journal of American Academy of Business, Vol.2 (1): 28‐33. Roos, G. and Roos, J. (1997) “Measuring Your Company's Intellectual Performance”, Long Range Planning, Vol. 30(3): 413‐ 426. Roos, J., Roos, G., Dragonetti, N. and Edvinsson, L. (1998), Intellectual Capital: Navigating in the New Business Landscape, University Press, New York. Roy, P. (2002) “Tacit KM in Organizations: A Move towards Strategic Internal Communications Systems”, Journal of American Academy of Business, Vol. 2(1): 28. Ruggles, R. (1998) “The state of the Notion: Knowledge Management in Practice”, California Management Review, Vol.40 (3): 80‐89. Somech, A., & Bogler, R. (1999). “Tacit Knowledge in Academia: Its Effects on Student Learning and Achievement”, Journal of Psychology, Vol.133: 605‐616. Spender, J.C. (1996) “Competitive Advantage from Tacit Knowledge?” In Moingeon, B., Spender, J. C. (1994) “Organizational Knowledge, Collective Practice and Penrose Rents”, International Business Review, Vol.3: 353‐368. Sternberg, R. J. (1997) “Managerial Intelligence: Why IQ Isn’t Enough”, Journal of Management, Vol. 23, pp. 475‐493. Sternberg, R.J., Wagner, R.K. (1995) “Testing Common Sense”, American Psychologist, Vol. 50(11): 912‐927. Stewart, T.A. (1997). Intellectual Capital: The New Wealth of Organizations. Nicholas Brealey Publishing, London. Teece, D. J. (1998) “Future Directions for KM”, California Management Review, Vol. 40(3): 123‐126. Teece, D. J. (2001). Managing Intellectual Capital: Organizational, Strategic,and Policy Dimensions, Oxford University Press, Oxford. Ulrich, D. (1998) “Intellectual Capital = Competence x Commitment”, Sloan Management Review, Vol. 39(2): 14‐18. Von Krogh, G., Ichigo, K, & Nonaka, I. (2000) Enabling Knowledge Creation: How to Unlock the Mystery of Tacit Knowledge and Release the Power of Innovation, Oxford University Press, New York. Von Krogh, G. (1998) “Care in Knowledge Creation”, California Management Review, Vol.40 (3): 133‐153. Von Krogh, G., Roos, J., and Kleine, D., (1994) “An Essay on Corporate Epistemology”, Strategic Management Journal. 15: 53‐72 Special Issue. Wagner, R. K., & Sternberg, R. J. (1985) “Practical Intelligence in Real‐World Pursuits: The Role of Tacit Knowledge”, Journal of Personality and Social Psychology, Vol.49: 436‐458. Wagner, R. K., & Sternberg, R. J. (1992) Tacit Knowledge Inventory for Managers: User manual, Psychological Corporation, San Antonio.
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Applying the Concept of Communities of Practice: An Empirical Study of Innovative Collaboration Between Academia and Industry Päivi Iskanius1 and Ilpo Pohjola2 1 University of Oulu, Department of Mechanical Engineering, Oulu, Finland 2 University of Eastern Finland, Department of Business, Service Management, Joensuu, Finland ilpo.pohjola@carelian.fi paivi.iskanius@oulu.fi Abstract: The purpose of this study is to apply the concept of Communities of Practice (CoP) to the development of the Northern Research and Innovation Platform (NRIP). The NRIP is a forum for collaboration between academia and industry that aims to promote know‐how and expertise in the field of environment, energy, and natural resources, with a strong geographical emphasis on arctic aspects. The aim is to bring the right people together, and provide a social context for collective learning in which people exchange knowledge based on shared practices and collective identity. The basic structure of CoP is a combination of three fundamental elements: a domain of knowledge, which defines a set of issues; a community of people who care about this domain; and the shared practice that they are developing in order to be effective in their domain. The domain that integrates people into the NRIP community is the common emphasis on research and development (R&D) issues related to the multidisciplinary and interdisciplinary field of environment, energy, and natural resources. A total of 90 members from different regions of Northern Finland, diverse scientific and industrial fields, and various organisations constitute the NRIP community. They defined the future research needs of the field, as well as the cooperation methods, vision, strategy, research agenda, and joint operational programme. Several workshops were arranged and the web portal was designed to share practices and knowledge in the community. For the community, we propose the Virtual Café‐type model, whereby research‐based business ideas are contemplated by potential companies for the joint creation of new businesses. The community shows the positive effects of innovations and new business opportunities. The study contributes to the research of CoPs and enhances the understanding of shared knowledge as a basis for collaboration between academia and industry. Keywords: communities of practice, collaboration, knowledge sharing, case study, northern research and innovation platform, virtual café
1. Introduction The Arctic and Barents regions have received international attention due to the growing business potential of their natural resources, and the new transport routes that may open as a result of climate change. Achieving the sustainable use of natural resources, preventing climate and environmental changes, and protecting the livelihood and culture of indigenous peoples require new technological, organisational, and social innovations. Special emphasis needs to be placed on the development of technology and know‐how that are compatible with arctic conditions. The importance of this for problem‐oriented multidisciplinary research has increased and solving research problems requires greater cooperation beyond organisational boundaries. Particular attention should be paid to intensifying the collaboration between academia and industry. Scientific knowledge from universities should be deployed more effectively for the benefit of businesses. New methods of action to transform scientific knowledge and research‐generated ideas and inventions into commercial profit are badly needed. This paper proposes the concept of Communities of Practice (CoP) to improve collaboration between academia and industry. The aim is to bring the right people together and to provide the social context for collective learning by means of which people exchange knowledge based on their shared practices and collective identity. In this case study, the concept of CoP is applied to the development of the Northern Research and Innovation Platform (NRIP). The NRIP is a forum for collaboration between academia and industry in order to promote know‐how and expertise in the field of environment, energy, and natural resources, with a strong geographical emphasis on arctic aspects. The NRIP is essentially providing the platform for private and public knowledge‐intensive organisations that are searching for possibilities to cooperate with others in order to innovate and to more quickly and efficiently match customer expectations. These demands for knowledge and know‐how are increasingly important and experts are seeking others to establish a community in which they can resolve the challenges associated with their business and research areas.
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2. Literature review 2.1 Innovation and knowledge creation Innovation can be understood as a process in which the organisation creates and defines problems and then actively develops new knowledge to solve them (Nonaka, 1994). In the innovation process, knowledge is acquired, shared, and assimilated with the aim of creating new knowledge, but also advancing and modifying existing knowledge in order to result innovations (Herkema, 2003). Knowledge can be defined as ‘justified true belief’ that increases an organisation’s capacity for effective action (Nonaka and Takeuchi, 1995). Knowledge is dynamic, relational, and based on human actions; it depends upon the context and people involved rather than on an absolute truth and artefacts. Knowledge creation is focused on the generation and application of knowledge that leads to new capabilities for an organisation. Innovation, in turn, is concerned with how these new capabilities may be transferred into products, processes, and services that have economic value in markets (Popadiuk and Choo, 2006). Innovations are often made in groups, where actors of different backgrounds are involved in the interactive process (Asheim and Cooke, 1999). Nonaka and Takeushi (1995) distinguish between individual and collective knowledge. Individual knowledge is created by, and exists within, the individual according to his/her beliefs, attitudes, opinions, and the factors that influence his/her personality formation. Collective (social) knowledge, on the other hand, is created by the collective actions of a group and involves the norms that guide intra‐group communication and coordination. Nonaka and Konno (1998) identify two types of knowledge based on its visibility and expressiveness. If knowledge is visible and expressible, it is called explicit knowledge, which is articulated, codified, and communicated in a formal, systematic way. Tacit knowledge, on the other hand, is associated with individual experiences, thinking, and feelings, and is difficult to code. It is subjective and intuitive and is, therefore, not easily processed or transmitted in any systematic or logical manner (Nonaka and Takeuchi, 1995). Tacit knowledge is often specific to its original context; it is collective rather than individual (Lundvall and Johnson, 1994). Tacit knowledge can also be associated with scientific intuition and the development of craft knowledge within scientific disciplines (Delamont and Atkinson, 2001). Scientific knowledge is produced by individuals who imbue their search for new knowledge with deeply personal contacts (Polanyi, 1966). In other words, the knowledge of scientists is not fully reducible to a clearly articulated set of axioms, rules, algorithms, and statements (Sveiby, 1997). Tacit components, which are based on interpretations, perceptions, and value systems, can be shared, communicated, and transferred through types of network relationships. Organisations create new knowledge through the conversion of tacit and explicit knowledge, which is a social process between individuals (Nonaka and Takeuchi, 1995). Effective knowledge creation and sharing depends on an enabling context that is physical, virtual, mental, or, more likely, all three. Knowledge creation and sharing is a collective process that requires complex mechanisms of communication and transfer (Saviotti, 1998).
2.2 Open innovation and communities of practice Traditionally, innovations have been created in a closed system; the entire innovation process takes place within a company that generates, develops, and commercialises its own ideas. Rather than relying on internal R&D, companies today are actively looking for ideas, research results, and technology outside of the boundaries of their own organisation and are utilising these in their own business. Companies also openly share their own unused ideas and innovations with other actors for the purpose of commercialisation. The boundary between a company and its surrounding environment is more open, enabling innovations to move easily between the two. In such an open innovation system, companies need to open their business models in order to obtain more outside ideas and technologies and to transfer inside information and knowledge to the outside (Chesbrough, 2006). Chesbrough (2006) argues that there is an abundance of knowledge in virtually every field around us. The proliferation of public scientific databases and online journals and articles, combined with low‐cost Internet access and high transmission rates, can enable access to a wealth of knowledge that was far more expensive and time‐consuming to obtain as recently as the early 1990s. He continues to explain that the rise of excellence in universities’ scientific research and its increasingly diffuse distribution means that the knowledge monopolies established by the centralised R&D organisations of the 2000s have ended.
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Wenger (1998) proposes Communities of Practice (CoP) as a social context for creating and using knowledge. He determines CoPs to be groups of people who share a concern or passion for an activity they undertake and learn how to do it better as they interact regularly. Companies have shown tremendous interest in CoPs because they see the vast potential for benefits. Such benefits include growing competencies in areas of high need, becoming more responsive to customers, capturing and sharing good practices and lessons learned from experienced staff, getting new staff to become productive quickly, sharing lessons learned, and sparking innovation across the community. Working in communities supports organisational learning and individual development (Millen et al., 2002). The key elements of a CoP are (Wenger et al., 2002): 1) a recognised domain of interest that the members share and to which they commit; 2) relationships between members that allow them to engage in joint activities, share information, and help each other; and 3) the development of shared practices that consist of shared resources, experiences, stories, tools, etc. The domain creates common ground and a sense of mutual identity that provides value to members and other stakeholders. The domain inspires members to contribute and participate, while guiding their learning and giving meaning to their actions. Knowing the boundaries and the leading edge of the domain enables members to decide exactly what is worth sharing, how to present their ideas, and which activities to pursue. It also allows them to recognise the potential in tentative or half‐baked ideas. The community creates the social forum for learning. A strong community fosters interactions and relationships based on mutual respect and trust. It encourages a willingness to share ideas, expose ignorance, ask difficult questions, and listen carefully. The practice is a set of frameworks, ideas, tools, information, styles, language, stories, and documents that community members share. Whereas the domain denotes the topic on which the community focuses, the practice is the specific knowledge the community develops, shares, and maintains (Wenger et al., 2002).
2.3 Scientific knowledge transfer Scientific knowledge is not an automatic outcome of scientific research but rather the product of a long social process, the major part of which occurs after—even long after—the research is completed. Although scientific knowledge is primarily produced in universities and research institutes, it also emanates from companies and public organisations. Scientific knowledge is generated as a result of basic and applied research, through policy‐making and strategy development, as well as in practical operations and local communities (Ravetz, 1971). Scientific knowledge can be classified as multidisciplinary or mono‐disciplinary research. Knowledge has traditionally been developed by specialists who are organised according to discipline. However, at the edge of knowledge development, the boundaries between such disciplines are often fuzzy, and combinations of knowledge from different disciplines are necessary to achieve progress. Another way to classify knowledge is related to the basic or the applied nature of research. Basic research is aimed at gaining insight into the world surrounding us, while applied research focuses on the creation of actual knowledge that can be used, for example, in artefacts. Knowledge can also be identified as experimental. Experimental research tries to identify whether a certain variable has an effect on another variable. Taken simplistically, the distinction between these three types of research may suggest a linear view of technological development, starting with basic research, progressing through applied and experimental work, and leading to innovation. Scientific knowledge transfer mechanisms differ at various stages of the innovation process. In Figure 1, we present how the role of science as a knowledge provider decreases when the role of customers and suppliers increases. At the invention stage, the importance of mobility of researchers and technology‐based spin‐offs and start‐ups is high. Beneficial innovation milieus are incubators, science parks, and technology centres, where small early‐stage firms can utilise scientific knowledge and research results. At the stage of adaptation to market needs, the role of contract‐based research and joint R&D projects between academia and industry increases. Knowledge transfer is informal, e.g., via the mobility of researchers. At the stage of diffusion of technology, the role of consulting, mobility of students, and training expands. At the stage of product/process differentiation, the importance of science and research is low. Perhaps the most archetypical method of transferring scientific knowledge is the publication of research; thus, knowledge becomes public and accessible for many people. Only explicit knowledge can be transferred. Besides publishing, academics are encouraged to attend conferences, fairs, and workshops, where they are able to communicate and interact directly with many international colleagues. Such events are important for creating social networks of people within a certain field of science.
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Figure 1: Role of science as a knowledge provider (modified from Polt et al., 2001) The mobility of people from university to industry and vice versa is an important knowledge transfer mechanism. Many contacts between industry and universities are informal—for example, personal networks based on friendships and alumni societies. Cooperation in joint R&D projects and shared facilities can be induced by different rationales. Academia and industry can also transfer knowledge by cooperation in education and by the influence of industry experts on the curriculum. By doing this, they can assist the university to keep abreast of economic developments and provide them with a well‐educated labour market. Contract research and advisement is typified by the industry asking questions to universities and paying for the answers. This leads to a flow of knowledge from academia to the industry and a flow of capital in the opposite direction (See Agrawal, 2001). The IPRs have the intention of stimulating innovation by temporarily monopolising and publicising new knowledge. A rationale for universities to become involved in IPR can be to ensure that the outcome of the research actually flows to society. One can argue that a vast majority of the results of university research is not yet applicable. A company has to invest significant amounts of resources to transform the results of scientific research into a product. Spin‐offs are commercial companies capitalising on knowledge that has been created at public institutes or companies. Although definitions regarding spin‐offs differ, the knowledge they use is often handed over in the form of licences or a full transfer of patents. Universities often own equities in the spin‐offs that use their knowledge. Table 1: Knowledge transfer between academia and industry (modified from Brennenraedts et al., 2006) Knowledge transfer
Publications
Scientific publications Co‐publications Consulting of publications Participation in conferences Participation in fairs Exchange in professional organizations Participation in boards of knowledge institutions Participation in governmental organizations Graduates Mobility from public knowledge institutes to industry Mobility from industry to public knowledge institutes Trainees Double appointments Temporary exchange of people
Participation in conferences, professional networks & boards
Mobility of people
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Other informal contacts and networks
Networks based on friendship Alumni societies Other boards Joint R&D projects Presentations of research Supervision of a trainee or PhD student Financing of PhD research Sponsoring of research Shared laboratories and common use of machines Common location or building (science parks) Purchase prototypes Contract education or training Retraining of employees Working students Influencing curriculum of university programs Providing scholarships Sponsoring of education Contract‐based research Contract‐based consultancy Patent texts Co‐patenting Licenses of university‐held patents Copyrights and other forms of intellectual property Spin‐offs Start‐ups Incubators at universities Stimulating entrepreneurship
Cooperation in R&D
Sharing the facilities
Cooperation in education
Contract research and advisement IPR
Spin‐offs and entrepreneurships
3. Case study 3.1 Development framework The concept of CoP is applied in the development of the NRIP community. The NRIP community is an open, informal forum for promoting knowledge and expertise in the field of environment, energy, and natural resources, with a strong geographical emphasis on arctic aspects. The main aim of the NRIP community is to generate multidisciplinary R&D projects based on scientific knowledge and to speed up innovations. Wenger et al. (2002) found that CoP continually evolves through the five stages of community development (Figure 2):
Potential; people face similar situations without the benefits of shared practice.
Coalescing; members come together and recognise their potential.
Maturing ‐ active; members engage in developing a practice.
Stewardship ‐ dispersed; members no longer engage very intensely, but energy and activity continue.
Transformation ‐ memorable; people leave the community, but they still remember it as a significant part of their identities.
The development of community begins with an extant social network. People with similar issues and needs find each other and identify the potential for forming a community. Typically, the key issue at the beginning of a community is to find sufficient common ground among members for them to feel connected and see the value of sharing insights, stories, and techniques. The most important factor in a community’s success is the vitality of its leadership and especially its coordinators. Coalescing is crucial in order to have activities that allow the building of relationships, trust, and awareness of their common interests and needs. The communities thrive when members find value in participating, and the community coalesces as activities develop to meet the needs of its members. At the maturation stage, the main issue that a community faces shifts from establishing value to clarifying the community’s focus, role, and boundaries. It is a very active stage for community coordinators and support staff and is often the time when they break apart or reorganise the community. As a community matures, its
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members begin to plan directions, set standards, and engage in joint activities. The value of the community has been established and it begins to clarify its focus, role, and boundaries. As communities mature, members get better at being a community; through community building, they push their capabilities to new heights and, eventually, may form the single largest vessel for creating knowledge assets in an organisation.
Figure 2: Development framework of CoP (modified from Wenger, 1998) At the stewardship stage, the community begins to plateau. Although energy and activity continue, members who were once enthusiastic may take a sideline position. The radical transformation or death of a community is just as natural as its birth, growth, and life. Even the healthiest communities come to a natural end when changing markets, organisational structures, and technology render the community domain irrelevant. During the transformation, people leave the community when it is no longer useful or pertinent to them. New people join and the focus changes, returning the community to a new growth stage or moving it toward closure (Wenger et al., 2002; Saint‐Onge and Wallace 2003). In Figure 3, the level of energy and visibility of the community is presented. The jagged line represents the level of energy and visibility that the community typically generates over time. Level of Energy and Visibilty
Stewardship
Coalescing Maturing Transformation Potential
Development Tensions
Time Discover/ Imagine
Incubate/Deliver Immediate Value
Focus/ Expand
Ownership/ Openness
Let Go/ Live On
Figure 3: Stages of community development (Modified from Wenger et al. 2002) At the first (potential) stage of NRIP community development, the aim was to encourage people to find each other and to become more conscious of the domain. The NRIP project was financed by the European Regional
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Development Fund, and the recruited project coordinator played an important role in the initial stages. She informed and had discussions with the potential members of the community. These potential members came from different scientific and industrial fields, regions, organisations, companies, universities, research institutes, financiers, etc. The strengths of the coordinator were her ability to find persons with the same interest. When she gathered core group members to work actively and started discussions about the community’s agenda, it was a starting point for the community and provided a robust basis for debates between community members. Based on the face‐to‐face meetings, potential members were invited into a kick‐off meeting, the objective of which was to activate and motivate people. A total of 50 experts participated in this meeting. At this stage, most of the attendees did not know each other, nor were there many joint R&D projects. At the second stage (coalescing), the aim was to define joint research themes and negotiate community rules and practices. Three think tanks were arranged with the objective of gathering members in order to recognise their potential to function as a community. Between the sessions, individual exercises were undertaken to gather information for further development. During the workshops, members examined and made forecasts of the trends affecting the Arctic and Barents regions. Guided by the futurists, they analysed the manner in which the regions should prepare for various possible developments. Additionally, they evaluated the innovation system and drafted the common vision and research agenda for the community. Based on the workshop process, the content, future research needs, cooperation methods, vision, strategy, research agenda, and joint operational programme of the community were formulated. A total of 90 experts participated in the workshops. At this stage, over 300 R&D ideas were identified. At the third stage (maturing ‐ active), the aim was to engage in joint activities, create artefacts, adapt to changing circumstances, and renew interests, commitment, and relationships. Four workshops were arranged, during which small thematic groups developed their R&D projects quite independently. First, thematic research fields were selected, around which small interest groups were established. A total of eight R&D projects were initiated. As a result of this stage, members engaged in developing practices; they began to trust each other and numerous informal contacts were established. The coordinator edited the material generated during the development process and published five reports in the field. A high‐level seminar was also arranged to inform the community about the results. At the fourth stage (stewardship ‐ dispersed), members were no longer intensively engaged; however, the community was still loosely alive as a force and a centre of knowledge. As the supported project ended, the activities were decreased. The NRIP community was not mature enough to live without support. Face‐to‐face meetings for this purpose were no longer arranged; however, some activities were seen in particular thematic areas. The background organisations involved in the NRIP community were not interested in coordinating the process. The R&D projects were not yet realised and, even today, universities are looking for short‐term (1‐2 years) outcomes. Funding was requested from the EDRG and Interreg programmes; however, they were not interested in investing in the scientific collaboration. Some members began to maintain contact by communicating and requesting advice in other forums. Some returned to the ad hoc activities. Altogether, the NRIP development work activated people who now know each other and there exists the possibility for systematic development of joint R&D projects and other collaboration methods. At the fifth stage (transformation ‐ memorable), the NRIP community was no longer the central actor in the field, but people still remembered it as a significant aspect of their identities. The members of the NRIP community had positive feelings and memories of the time when the community was active. It was a time of telling stories, preserving artefacts, and collecting memorabilia.
3.2 Virtual Café – the virtual platform for collaboration between academia and industry In many ways, the NRIP is a distributed community and it, therefore, cannot rely solely on face‐to‐face meetings and interactions. In the NRIP area, there are long distances between members and organisational affiliation. Also, cultural differences create barriers between members. Distributed communities are generally less accessible for their members and consequently need more intentional effort and facilities in order to communicate properly. Communities are based on communication between members by designing accessible, easy‐to‐use technology that can be a helpful method of staying connected. In addition to local members, virtual participation brings global knowledge sources and world‐class experts to the same discussion table,
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e.g., via online discussion forums. The NRIP community is informal and operates on a voluntary basis; thus, participation in its activities should be as easy as possible. For the NRIP community, we propose the Virtual Café‐type collaboration model (Figure 4), by means of which research‐based business ideas can be considered by potential companies for the joint creation of new businesses. Virtual Café is an open forum for all members and stakeholders and its atmosphere is positive, active, and interactive. Companies, in particular, appreciate the one‐stop shop for chewed information to complement their own knowledge and attempts to identify new business opportunities. Distributed communities, such as the NRIP, need reasonable ways to stay connected and cooperate. In Virtual Café, physical space, in which to meet each other, and personal participation and communication through the boundaries are simultaneously combined by means of different kinds of new interactive technology. The aim of NRIP is to support the mobility of researchers by enabling them to work in various businesses. Working methods and technology unite members and keep all at the same level of knowledge. Virtual Café will benefit all members and stakeholders because scientific‐driven ideas can be quickly transferred for business purposes. New business opportunities and even new companies may be established. Optimally, the NRIP community could produce knowledge that enables members to become entrepreneurs, and create new businesses in existing companies. It is clear that all community members cannot become entrepreneurs; however, the objective of the community is to activate business by means of high‐quality R&D cooperation. The community needs different kinds of persons at various stages of the innovation process; these persons take the form of researchers and developers, but also business‐oriented people who have the ability to detect new commercial opportunities. The company establishment can be activated by the joint venture capital company, owned by the university and local businesses, which invests seed money in feasible business ideas and innovations developed by students, researchers, and businesses.
Figure 4: Virtual Café model for collaboration between academia and industry
4. Conclusion This study presented how the concept of CoP has been applied in the development of collaboration between academia and industry. In this case study, we develop the NRIP community to promote know‐how and expertise in the field of environment, energy, and natural resources, with a strong geographical emphasis on arctic aspects. The basic structure of CoP is a combination of three fundamental elements: a domain of knowledge, which defines a set of issues; a community of people who care about this domain, and the shared practice that they are developing in order to be effective in their domain. The domain that integrates people into an NRIP community is the common emphasis of the R&D issues related to this multidisciplinary and
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interdisciplinary field. For the NRIP community, we propose the Virtual Café‐type model, by means of which research‐based business ideas are able to meet potential companies for joint creation of new businesses. Overall, the CoP model is suitable for collaboration between academia and industry and effectively generates R&D activities. The NRIP community, with all its human resources, has a positive effect on the creation of innovations and new business opportunities. The study contributes to the research of CoPs and incorporates the understanding of shared knowledge as a basis for collaboration between academia and industry. This study provides new empirical evidence of the power of working in communities in a more efficient and innovative way. We recommend that people in academia and industry select an open innovation strategy for their communities of practice in order to achieve the next level of collaboration.
References Agrawal, Ajay K. (2001) “University‐to‐industry knowledge transfer: Literature review and unanswered questions.” International Journal of Management Reviews, Vol. 3, No. 4, pp. 285–302. Asheim, B.T. and Cooke, P. (1999) “Local learning and interactive innovation networks in a global economy.” Making connections: Technological learning and regional economic change, pp. 145–178. Brennenraedts, R., Bekkers, R. and Verspagen B. (2006) The different channels of university‐industry knowledge transfer: Empirical evidence from biomedical engineering, Eindhoven Centre for Innovation Studies, Technische Universiteit Eindhoven. Chesbrough, H. (2006) Open Innovation: The new imperative for creating and profiting from technology. Harvard Business School Press, Boston, Massachusetts. Delamont, S. and Atkinson, P. (2001) “Doctoring uncertainty: Mastering craft knowledge.” Social Studies of Science, Vol. 31, No. 1, pp. 87–107. Herkema, S. (2003) “A complex adaptive perspective on learning within innovation projects.” Learning Organization, Vol. 10, No. 6, pp. 340–346. Hildreth, P. and Kimble, C. (2004) Knowledge networks – Innovation through communities of practice, IGI global, London, UK. Lundvall, B.‐Å. and Johnson, B. (1994) “The learning economy.” Journal of Industrial Studies, Vol. 1, No. 2, pp. 23–42. Millen, D.R., Fontaine, M.A. and Muller, M.J. (2002) Understanding the benefits and costs of communities of practice, Technical report 2002.01. Nonaka, I. (1994) “A dynamic theory of organizational knowledge creation.” Organization Science, Vol. 5, No. 1, pp. 14–37. Nonaka, I. and Takeuchi, H. (1995) The knowledge‐creating company: How Japanese companies create the dynamics of innovation. Oxford University Press, USA. Nonaka, I. and N. Konno (1998) “The concept of ‘ba’: Building a foundation for knowledge creation.” California Management Review, Vol. 40, pp. 1–15. Polanyi, M. (1966) The study of man, University of Chicago. Popadiuk, S. and Choo, C.W. (2006) “Innovation and knowledge creation: How are these concepts related?” International Journal of Information Management, Vol. 26, pp. 302–312. Ravetz, J.R. (1971) Scientific knowledge and its social problems, Transaction Publishers. Rogers, E. M. (1983) Diffusion of innovations, The Free Press, New York. Saint‐Onge, H. and Wallace, D. (2003) Leveraging communities of practice for strategic advantage. Saviotti, P.P. (1998) “On the dynamics of appropriability, of tacit and of codified knowledge.” Research Policy, Vol. 26, No. 7, pp. 843–856. Sveiby, K.E. (1997) The new organizational wealth: Managing & measuring knowledge‐based assets. Berrett‐Koehler Pub. Wenger, E. (1998) Communities of practice: Learning, meaning, and identity, Cambridge University Press. Wenger, E., McDermott, R., Snyder, W.M. (2002) “Cultivating communities of practice: A guide to managing knowledge.” Harvard Business School Press, p. 284.
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A Scientifically Grounded Model to Reduce Knowledge Loss in Organisations Thomas Jackson, Paul Parboteeah and Nicola Wilkinson Loughborough University, Loughborough, UK t.w.jackson@lboro.ac.uk p.parboteeah@lboro.ac.uk Abstract: The importance of knowledge sharing and preventing knowledge loss in organisations is well established. For example, building on the work of Riege (2005), numerous barriers to knowledge sharing at the organisation level have been identified. Coupled with high level, strategic, models of KM; the corporate perspective on supporting knowledge sharing and preventing knowledge loss has been well explored. The problem identified by this paper lies in lower, or operational, levels of organisations, an area largely ignored by existing research. This paper attempted to address this imbalance by creating a framework to articulate and assess the risks to knowledge loss at the employee level. The model was theoretically grounded using Dubin’s (1978) model creation theory. The model has 8 elements, 4 which support knowledge sharing and help reduce knowledge loss, and 4 which hinder knowledge sharing and encourage knowledge loss. The output from this paper (theoretical model of factors affecting knowledge loss) represent a unique, concerted, effort to create a theoretically grounded model that has the potential to aid knowledge managers in translating corporate KM initiatives into specific and actionable advice. Using Dubin’s (1978) model creation theory has enabled the creation of a theoretically sound model for preventing knowledge loss in organisations, and is an approach that has not been taken before in creating knowledge loss models. As summarised by this paper, the next stage for this research is the creation of a toolkit that will enable knowledge mangers to identify and quantify each part of the model and provides actionable information that will ultimately reduce the risk of knowledge loss to their organisation. Keywords: KM barriers, knowledge loss, knowledge sharing, model creation, risk management
1. Introduction The importance of KM increased dramatically since the 1980s and awareness is increasing of the benefits held within intangible assets. This is making the effective management of knowledge in organisations an important and even decisive competitive factor” (Hanisch et al., 2009, p.149). Today, businesses have a KM strategy to “ensure that the alignment of organizational process, culture, and the KM‐related information technology deployment produce effective knowledge creation, sharing, and utilization” (Davis et al., 2008, p.235). Managers use many knowledge sharing (KS) techniques, however, it is still unclear whether they are doing enough to reduce the business risks involved in managing knowledge. It is up to a manager to utilise the knowledge from an employee’s head but a risk can be identified when an employee leaves, taking all knowledge with them. Preparation and processes should be put in place as part of a KM strategy to ensure the knowledge remains in the team. Therefore, the aim of this paper is to identify the factors that reduce knowledge sharing in organisations, identify the risks to knowledge loss and develop a model to understand the relationship between the two. This paper begins by providing the research design that was used to create the knowledge sharing and knowledge loss model. Section 3 reviews the literature and defines the factors (units) that contribute to either effective knowledge sharing or knowledge loss, and section 4 goes through the model creation process created by Dubin (1978). The paper concludes by discussing the model, its contribution to the literature and its implications for managing knowledge loss in organisations.
2. Research design The purpose of this research was to investigate the relationship between KS techniques and KL, to construct a conceptual model, based on past literature, and then analyse it to create a toolkit based on a real‐life case study to highlight KL risks regarding KS behaviours. This section describes and justifies the research strategies and approaches used for this project. Dubin’s model creation theory (1978) was used to create the model identifying the risks to knowledge loss in organisations. Dubin’s method consists of a two‐part, eight‐step theory building method. The first part represents the structural components and the second part is the process of empirical research/validation (Ardichvilli et al., 2003). This paper will follow the first part of the theory to create the model and framework, and the second part will form part of future research to test and apply the theory to a real world scenario. The steps to be followed in this paper are: identification of the units of the theory, determining the laws of interaction, determining the boundaries of the system, outlining the system
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Thomas Jackson, Paul Parboteeah and Nicola Wilkinson states and finally the propositions of the theory. Part 2 of Dubin’s method was not followed, as the extensive research needed to carry out the steps was restricted by elements of the study.
3. Background to model creation Knowledge, at a high level, can be defined as ‘understanding based on experience’ or in more detail as: Knowledge, while made up of data and information, can be thought of as much greater understanding of a situation, relationships, causal phenomena, and the theories and rules that underlie a given problem.” Bennet and Bennet cited in Firestone (2003, p.107). However, it can be argued that due to the intangibility of knowledge “it is difficult to give a definition of knowledge value that is widely recognized” (Bernard and Xu 2011, p.167). Accepting there are two types of knowledge: tacit and explicit, it can be argued that the key to generating value is to tap into the pool of tacit knowledge and convert it into explicit knowledge (Liebowitz 2000, p.14). Jantunen et al. (2011, p.273) state that competitive advantage within a company is shifting focus to “intangible assets like knowledge and intellectual property rights” in order to stimulate success. Fuller (2002, p.26) contradicts this view and suggests that competitive advantage is gained only through tacit knowledge and lost once codified. Desouza and Paquette (2011 p. 47) however argue that tacit and explicit knowledge is only one dimension of knowledge and others should be considered when determining how to identify, acquire, and use knowledge in organisations.
3.1 Barriers to knowledge sharing Song and Teng (2011) argue there are two types of KS: solicited and voluntary. The difference being that voluntary KS “refers to the sending and receiving of knowledge without any prior socialisation” (Song and Teng 2011, p.105). Arguing that it is voluntary KS that managers need to encourage to prevent substantial knowledge loss (KL), there are three kinds of barriers to be overcome (Riege, 2005). 3.1.1 Individual barriers The number of employees reporting into a manager can determine the KS tools and techniques adopted. The website Team Building (2009) suggests that the ideal team size to achieve collaboration and co‐operation is either five or six, and research shows that if the number of employees “goes above 9, communication tends to become centralized because members do not have adequate opportunity to speak to each other” (Matrix Teams, 2010). As the team increases in size, sub‐groups can emerge due to the “degree of overlap across multiple demographic characteristics among a subset of team members” (Gibson and Vermeulen 2003, p.202). These can positively affect the team by dividing the workload appropriately however when formed naturally they can discourage KS between the subsets and whole team. The importance of KS increases when a team contains experts as the techniques of shadowing and mentoring less experienced employees can be utilised in order to share and maintain knowledge within the team (Rainmaker Group, 2012). After Action Reviews occur between peers to “capture lessons learned immediately after an event, project, or an activity” (Faul and Camacho, 2004) and helps to build “collective operational knowledge” (Knoco Ltd, 2010). It is essential for the meetings to be continuous and not just a one‐off, as the more regularly they occur, the more effective they can be (Commonknowledge Associates, 2012). The criticism of these techniques is that they only focus on knowledge regarding an event, project or activity and in order for the business to see a long‐term benefit. Team meetings are a common KS technique and “are arranged at a regular time and of a regular length each week or two” (Young 1995, p.25) however nowadays communities of practice (CoPs) “have emerged as one of the most researched and widely praised techniques for knowledge sharing” (Bartholomew 2005, p.15). The Institute for Research on Learning, cited in Liebowitz (2000), states a ‘community’ must have similar value and lifestyles; however Jashapara (2004) states that the group should be self‐selecting. Retna and Ng (2011, p.42) suggest common interests and activities bring the community together. Therefore, when Jashapara’s concept of self‐selection, should take into consideration the individual ‘s interest in sharing knowledge for that particular CoP. Goh and Yahya (2002) highlight documentation in their five areas of KM. “It is evident that once knowledge is fully documented and expressed in writing, knowledge can be shared smoothly” (Renzi, 2008) however knowledge should be “shared with others through interpersonal contact and access to documentation” (Serrat 2009, p.3), highlighting a combination can lead to a more effective KM process. Documentation is very useful
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Thomas Jackson, Paul Parboteeah and Nicola Wilkinson for knowledge learning, can be relied upon when personal KS is restricted and can reduce KL as “compared to the time it takes to rediscover knowledge the amount of time it takes to document a situation becomes insignificant” (Frank, [n.d.]). 3.1.2 Organisational barriers In the 1990’s it was recognised that ‘alternative officing’ was beneficial and Duffy (1997) created a theory of work patterns and space shown in Figure 1. Duffy created 4 work environments and suggested types of work incorporated into each one. From 2000 the technology boom caused the workspace to adapt accordingly to a “digitally‐driven type of workforce that is more flexible […] and more geared to the needs of knowledge interactions” (Bichard et al., 2010, p.7). Interactive workspaces evolved “where devices of different natures are used in conjunction with each other” (Wallace and Inkpen, 2006) incorporating the combination of both a physical and information system environment. Thomas Allen researched elements of workspace design and found that personalization of the workspace can improve attitudes to work (Bartholomew 2005, p.42) highlighting the benefits of a good physical environment. However, even when that exists, 50% of office workers regularly emailed colleagues who were only 10 feet away (Bartholomew 2005). The concept of a learning organisation has moved from defining interrelationships within a business to Huber (1991) highlighting that an entity successfully learns through processing information to change its range of potential behaviours. A decade later, Sanchez (2001) still confirms this by stating that Organisational Learning aims to generate, disseminate, and apply knowledge within an organisation, although somewhat different language. Evans (1998, p.201) states that a learning organisation is one that promotes learning among its employees – but, more importantly, is an organisation that itself learns from that learning, whereas Matlay (1997, p.4) states “knowledge emerging from collective learning is much more complete and is usually recorded formally for corporate access and benefit”. Matlay highlights collective learning, highlighting the importance of KS in teams, contrasting Evans, who suggests that an organisation can learn through its employees learning individually.
Figure 1 Work patterns and space (Duffy, 1997) 3.1.3 Technological barriers The Enterprise Knowledge Portal (EKP) was created as “the intersection between knowledge management and the enterprise portal” (Collins, 2003, p.xi). They can be costly and time‐consuming however a long‐term benefit can be gained. These encourage greater sharing of explicit knowledge (Viney, 2006) and provide companies with a rich and complex shared information workspace (Belbaly et al., 2004). Knowledge portals allow KS between organisational levels however only permits codified knowledge. This is why, in addition to an EKP, many other KS techniques are implemented to capture the un‐codified and tacit knowledge. “The emphasis today is on people‐centred techniques, understanding and meeting real business and knowledge needs, and fitting in with organisational culture. IT is invaluable, but it is a supporting actor, not a star” (Bartholomew, 2005).
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Thomas Jackson, Paul Parboteeah and Nicola Wilkinson Begley (2004) argues that when interacting it is “often helpful to go back to the basics and get face‐to‐face” however the constraints of time and budget makes it not always possible (Koning, 2010) making employees turn to KS tools such as email communication and teleconferencing. Many researchers and employees recognise the lack of richness in electronic communication is its most limiting aspect (Young, 1995) however in some circumstances it can be most appropriate, for example, for auditing purposes or geographical restrictions. Davenport cited in Bichard, Erlich and Myerson (2010, p.23) recognised the task relevance of IT Systems, otherwise employees may spend up to 40% of their working day struggling with IT systems that aren’t properly integrated into their knowledge tasks.
3.2 Financial value of knowledge It’s “very difficult for accountants and economists to allocate an orthodox valuation to intangibles, as they rarely have an exchange value” (Bontis and Choo 2002, p.625). However, “more than ever, knowledge workers can see and feel the direct relationship between the work they do and the market value of their companies” (Cope 2000, p.121). Marr (2005, p.189) recognises approaches to measuring knowledge through an intellectual capital approach calculating “the difference between the market value of a publicly held company and its official net book value” (Jashapara 2004, p.268). Tobin’s Q, originated by James Tobin in 1969, approximates the ratio of the market value of the firm to the replacement cost of its assets and “Knowledge‐based assets are traditionally associated with high Q values” (Marr 2005, p.189). However the replacement costs for knowledge assets are difficult to calculate, suggesting that Tobin’s Q should be supported by additional measurements. The Balanced Scorecard, devised in the 1950s and further developed by Kaplan and Norton in 1992. It was thought to be the first tool used for Intellectual Capital that included other aspects other than finance. Marr (2005, p.190) suggests, “The learning and growth perspective is the natural home for indicators measuring knowledge‐based assets”.
3.3 The risk of knowledge loss It has been shown that intangible assets such as knowledge and learning capability are highly beneficial and that organisations have started to assign focus to KM strategies at a corporate level. Commonly, corporate level strategies are pushed down to the lower managers to take control. However, the issue of KL is a less acknowledged part of the strategy. Massingham (2010) produced a knowledge risk management framework aimed at corporate‐level and focuses upon risk management. The gap in the research is for not only a risk management framework at a lower level but to also have a risk management framework focused solely on knowledge and KL. This would give the managers the ability to analyse their KM strategy and adapt it appropriately to reduce risks and increase performance.
4. Model creation Dubin’s theory‐building methodology (1976; 1978) was chosen for this study, and concepts from this methodology with the positivism paradigm were used to develop the conceptual model of factors associated with knowledge sharing. Dubin’s model addresses the ‘paradox of embracing prior research while at the same time not being bound by it’ (Holton and Lowe, 2007). Dubin’s eight‐step theory building methodology consists of two parts, conceptual development and research operation. This research focused on developing the conceptual model and providing a starting place for further research and debate. To do this, an interdisciplinary approach was used to compile a comprehensive list of factors. As a result data were collected from articles from various fields of study, such as psychology, computer science, information system management, marketing, organisational studies and accounting, as well as library and information science. The four steps followed in this study are part one of Dubin’s method:
Identification and definition of the units of the theory;
Determination of the laws of interaction that state the relationships between the units of the theory
Definition of the boundaries of theory to help focus attention on forces that might impact the interplay of the units; and
Definition of the theory’s system states.
The four steps of the second part of Dubin’s methodology were not part of this research, but will be part of future research in taking the theory into a real world context to conduct empirical research.
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4.1 Creating the knowledge loss prevention model Units of a theory are “things out of which the theory is built” (Dubin 1976, p.26). Dubin created 5 classes of units: enumerative, associative, relational, statistical and summative and each class can be broken down further into unit properties shown below (Garcia 2008, p.113).
Attribute vs. Variable
Real vs. Nominal
Sophisticated vs. Primitive
Collective vs. Member
From the literature review the main units of the theory can be derived, shown in Table 1. Table 1 Units of knowledge loss model
Units Discouraging Knowledge Sharing
Units Encouraging Knowledge Sharing
Unit No. 1
Unit Name Collaborative workspace
2
People centred tools and techniques
3
Team knowledge portal
4
Small team size
5
Learning organisation
6
Individualistic workspaces
7
IT centred tools and techniques
8
Enterprise knowledge portal
9
Large team size
Description Workspaces have adapted due to technology and the realisation of the advantages of intangible assets, creating a work environment that is more geared to the needs of knowledge interaction (Bichard et al., 2010). The emphasis today is on people centred techniques, understanding and meeting real business and knowledge needs and fitting in with organisational culture (Bartholomew, 2005). Many companies have an enterprise knowledge or information portal, creating the opportunity for top level KS, however a lower level, team specific site allows teams to have a personalised experience, enabling them to gain and share knowledge relevant to their everyday projects. Groups or teams perform better when they are small, with the ideal size for collaboration and cooperation being 5 or 6 (Team Building, 2009). A learning organisation is one that promotes learning among its employees (Evans, 1998) and therefore enables organisations to gain a large resource based advantage. This style of office is old, but is still seen in organisations today. They tend to feature cubicles or offices for individual work, and often “hard to book” conference rooms for meetings (Richardson, 2011). Wittenberg, cited by Knowledge@Warton (2008) argues that teams that rely solely on electronic communication are less successful than those that understand the importance of face to face meetings. Corporate level knowledge portals allow KS to be conducted between different departments or across different organisations, and form a key link between top management and other levels of the organisation. If the size of a team goes above 9 then communication becomes centralised because it is harder for members to communicate directly with all other members (Matrix Teams, 2010).
The laws of interaction of a model details “how changes in one or more units of the theory influence the remaining units” (Ardichvilli et al., 2003): Law 1: A collaborative workspace, use of people‐centred tools and techniques, existence of a team knowledge portal and a small team all collaborate together to encourage KS and decrease the risk of KL and loss of intellectual capital. Law 2: An Individualistic workspace, IT‐centred tools and techniques, existence of an enterprise knowledge portal only and a large sized team collaborate together to discourage KS and therefore increase the risk of KL and loss of intellectual capital. Dubin (1978) describes the boundaries as the domain over which the theory will apply. For this project the boundary is the LO and therefore a closed boundary exists as the domain stands still while the boundary extends. A system state of a theory describes “a state in which all the units of the system take on characteristic values that have persistence through time” (Ardichvilli et al., 2003). There are two systems states for the model of factors affecting KS, namely, increasing KS and discouraging KS.
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Thomas Jackson, Paul Parboteeah and Nicola Wilkinson Increasing KS – This term was chosen to reflect that during this system state, the manager is increasing the KS activities included within their team. Discouraging KS – This term was chosen to reflect that during this system state, the manager is discouraging KS activities within his/her team as both KS tools present and environment are individually focused. The weighing axis is the point at which the system state can alter from being increasing KS to discouraging KS. Dubin (1978) states that the propositions of a theory involve predictions of the values of the units in the model. This project contains 2 propositions for the conceptual model: Proposition 1: the manager will be encouraging KS when a collaborative workspace, people‐ centred tools and techniques, team knowledge portal and small size of team are present. Proposition 2: KS is discouraged when an individualistic workspace, IT‐centred tools and techniques, enterprise knowledge portal only and a large size of team are present.
4.2 The final model As a result, the conceptual model of factors affecting knowledge sharing was developed (Figure 2). The left side of the model describes factors that encourage KS and the right describes factors discouraging KS. The weighing axis in the middle was a development upon a previous model developed by Jackson and Farzaneh (2012).
Figure 2 Model of factors affecting knowledge sharing The axis is tipped according to which factors exist on either side. If more factors exist on the left‐hand side then this shows KS is encouraged, resulting in reduced risk of KL and retention of intellectual capital. If more factors exist on the right side, KS is discouraged, KL is at risk and there’s potential loss of intellectual capital. If an equal balance occurs, the team is not encouraging or discouraging KS and a state of equilibrium is present. Surrounding the entire model is the boundary of the LO. The elements within the model are all described at a team‐level, and can be impacted upon whether a LO exists or not.
5. Discussion and conclusion The main aim of this research was to analyse the relationship between knowledge sharing and knowledge loss. A problem existed because people could leave an organisation for various reasons, and sometimes suddenly, meaning the knowledge they had would be lost. A lot of research already exists on encouraging knowledge sharing and preventing knowledge loss, but a gap was found to exist regarding how encouraging knowledge sharing related to preventing knowledge loss. This need created the foundation of this research: a model of the factors affecting knowledge sharing and loss using Dubin’s (1978) theory building methodology. Previous literature was used to define the units of the model and the laws of interaction, to end up with the model
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Thomas Jackson, Paul Parboteeah and Nicola Wilkinson shown in Figure 2. The model shows that having a collaborative workspace, people oriented processes, team, as well as organisational, portals and small team sizes helped to mitigate the risk of knowledge loss when a person left an organisation. The practical implications of this research are that it provides a theoretically grounded model for knowledge managers to actively reduce the risk of knowledge loss for their team. The model helps managers start to articulate the risk, and therefore cost, when a person leaves the organisation. The next stage of this research is create an associated toolkit that asks a series of questions to the knowledge manger and starts to quantify the cost associated with different elements of the model. This, coupled with the model, will really enable organisations to take advantage of the model provided in this paper. If there is a limitation to the research, it’s that the model is currently untested. However, later research will test the model, again following Dubin’s theory and ultimately lead to a framework that employers can use to highlight and manage risk. The model shown in Figure 2 also has wider implications for not just information and knowledge management, but organisations and their management as a whole. For example, to move away from individualistic workspaces and towards an office that encourages communication and working together means this research provides a reason for information managers to be involved with office design. Whilst architects and interior designers work together to create visually pleasing, comfortable and supposedly productive environments, this research argues that they also need input from an expert that understands how people interact and share knowledge and what design features will work to support that. This research also highlights the need to properly manage the balance between the technology adopted, the information held and the people using the technology/information. As Figure 2 shows, processes should be designed around people conducting them and what their goal is – processes should not be technology driven. In other words, just because lots of technology exists that does lots of interesting things, doesn’t mean they should all be used. Figure 2 also highlights the importance of managing communication throughout the organisation. For instance, having methods of communications that teams or departments could use themselves could make their use less stressful. This also leads to the argument that organisations should start to use social media style tools for their internal communication, although more research is needed to determine in which cases and how social media should be used. Social media style tools would also mean employees are able to communicate using tools and technologies they have been using at home for some time now. Finally, the model in Figure 2, along with the possibility of using social media brings for bear one aspect that is crucial for preventing knowledge loss in organisations: cultivating and maintaining relationships (both internal and external). This research ultimately helps to reinforce the idea that activities to try prevent knowledge loss and encourage knowledge sharing centre around networking and relationships, and that no matter how technology evolves and develops, that will always remain constant.
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Knowledge Management, Call Centres and Customer Satisfaction: A Case Study From the Transport Sector Mahsa Jahantab and Alexeis Garcia‐Perez Faculty of Engineering and Computing, Coventry University, UK jahantam@uni.coventry.ac.uk alexeis.garcia‐perez@coventry.ac.uk Abstract: A recent collaboration between Coventry University and one of the largest service companies in the UK (referred to in this paper as Express Mobility) revealed the extent to which customer satisfaction can rely on the success of internal knowledge management strategies. Express Mobility provides a range of services to over five million customers across the UK on a daily basis. Customer satisfaction is therefore one of their key corporate values. During a period of six months the researchers engaged with Express Mobility in a project set out to identify and understand the main drivers to their customers’ satisfaction. As part of the project a questionnaire was used for the collection of a large volume of data from a random selection of Express Mobility customers, representing all regions being served by the company and all customer groups. A detailed analysis of more than 9,000 responses was conducted. The analysis revealed that the key areas of concern for customers were, in this order, the call centre at Express Mobility, followed by the price of specific services and billing‐related issues. In relation to the call centre, we found that more than 35% of complaints received had their roots in the lack of access by customer service representatives to up‐to‐date information and knowledge about Express Mobility’s products and services. This experience led to the study of the importance of knowledge management initiatives including staff from customer service departments which take the form of call centres. Given the similarities between Express Mobility and organisations providing services for transport, conclusions of this study focused on understanding the value of its findings for organisations which are related to the provision of services within the transport sector. Keywords: knowledge management, customer satisfaction, customer service, call centre
1. Introduction The last decade has witnessed a growing number of customer representation groups and regulatory bodies in the UK, regulating services provided by a number of sectors including transport. This has highlighted the increasing recognition of public interest in the quality of services provided by sectors for which there is limited competition and little (or no) customer choice (Chau, 2009), such as transport by rail or road. As a consequence, existing transport‐related companies are under an increasing pressure to achieve higher level of customer satisfaction. Express Mobility (EM) provides a range of transport and logistics services to over five million customers over a 10,000 square miles region in the UK on a daily basis. The company, based in the UK, was established in the late 1980s. It has approximately 10,000 employees and its annual revenue in 2012 was nearly £2,000 million. EM has two call centres which deal with all sorts of customer enquiries. Being the largest service provider in its region, customers felt that the gap between their expectation and the service they received from EM in the late 1990s was growing larger than expected. The root causes of customer dissatisfaction were hidden in the complaints EM began to receive on a regular basis. Thus, in the early 2000s a customer relations department was created at EM to respond to such a growing need for improvements in customer satisfaction. In addition to the services the company provides, the customer relations department started gathering customer satisfaction intelligence through a range of surveys and innovative reports. Customer satisfaction has thus become one of the key corporate values at EM. EM has recently put extra value on developing a strategy to gain a clear understanding of the UK customer expectation to enhance customer satisfaction through improving the quality of their ‘customer contact point’, which includes face to face, telephone (including its call centres) and Internet‐based communications. However, despite its efforts to minimise the number of customer complaints, evidence shows that there is still a gap between customers’ needs and expectation and the service they receive from EM. The nature of service provided by EM advisors at their ‘customer contact points’ (CCPs) suggests that there is a need for a range of information resources to be shared between EM staff in order for them to be able to provide customers with accurate and consistent information. This includes, for example, location, status and
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Mahsa Jahantab and Alexeis Garcia‐Perez condition of their network of physical assets and infrastructure, passenger information, ticketing and journey information, freight‐related information, the nature of traffic and disruptions caused by accidents and other reasons and even status of EM’s information systems. To such aims, not only having quick access to information is sufficient. Customers’ feedback shows that they know whether advisors are experienced or they just ‘read a script’. Knowing the reasons leading to a request from a customer and how the information will help that customer to overcome the problem are two of many skills that staff must have in order for a customer to feel satisfied with the service provided. These issues underline the importance of knowledge sharing skills required by staff in transport‐related organisations. This is a situation that affects not only EM and the transport sector but most organisations which success relies heavily on a direct interaction with a large customer base. This study was therefore set to evaluate the potential effects of effective intra‐organisational knowledge and information sharing practices covering direct ‘customer contact points’ (CCPs) on maintaining customer satisfaction. The focus of the research was on information and knowledge sharing between EM staff and also between EM staff and its customers.
2. Knowledge management and customer satisfaction in different fields Steiner (2008) acknowledges that despite a do it right the first time policy, a customer complaint is still common for most companies. Nevertheless, a customer complaint represents an opportunity for a firm to extract valuable information and gain insightful knowledge: ‘complaints are no longer seen as a source of blame but as a unique learning opportunity’ (Bosch & Enríquez, 2005). For this reason, the activity that initiates the process of deeper understanding of customer needs is the complaint from the user. Fundin & Elg (2006) define that, this complaint is as the level where a user reaches a threshold of dissatisfaction with the product/service. Knowledge Management (KM) is one of the main categories of Customer Relationship Management (CRM) research areas (Kevork & Vrechopoulos, 2009). The basis of Customer Relationship Management (CRM) is analysing data to understand customers which depends on Information Technology (IT) but it is misleading to see it as technology, rather it is a process that helps to understand customer needs and develop ways to meeting these needs while maximizing profitability (Slack et al., 2007). KM, in particular, has been defined as the process of capturing the collective expertise and intelligence in an organization and using them to foster innovation through continued organizational learning (Nonaka, 1991; Quinn et al., 1996). Since a major part of that expertise and intelligence refers to customers, it is concluded that CRM is strongly related to KM and especially to customer KM (Massey et al, 2001). Research shows that customer dissatisfaction with service failure increases rapidly when the recovery procedures are lengthy, or when the problem is passed on from one employee to another (Tax & Brown, 1998), and that customers are far more likely to be satisfied with service recovery process if the first employee to whom the complain demonstrates both the willingness and the authority to solve the problem (Miller et al, 2000). The important point is that customers become more negatively disposed towards the service when they recieve no concern from CCPs advisors and become more positively disposed towards the service when the advisors accept the responsibilty, and understand the trouble the customer had been through, on the behalf of the company for the reason that although the advisors did not cause the problem but in fact they are representing the company and from the customer’s point of view the advisors are the company. According to La & Kandampully (2004), service workers who are knowledgeable of the service system in its entirety and the interconnectedness among people, activities, and processes within the system are more likely to be able to find quick and effective solution when problem arise. Thus, characteristic of knowledge being transferred are important in determining the rate at which knowledge is accumulated and retained, how much of it is retained, and how easily it diffuses within and across boundaries (Argote et al, 2003, p.580). Keeping customers informed is an additional requirement in the current environment. Service consumers typically have limited knowledge of how the entire service system works (Gummesson, 1993). This is because only a small section of the service operation, often referred to as front‐of‐house areas, is visible to customers. Although it provides the essential supports for front‐line areas to create and deliver service, the unseen part of
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Mahsa Jahantab and Alexeis Garcia‐Perez the organization, often referred to as back‐of‐house areas, seldom receives recognition from the customers (La & Kandampully, 2004). It is embedded in the vision of EM that the company aims to get things right, first time, and every time. However, despite its efforts to provide quality services, occasionally things can go wrong and customers may complain. The literature shows that this is not uncommon, and it is important to face the fact that customers may complain and seek to understand and address the reasons leading to such complaints. With this principle in mind, the authors engaged in a rigorous process of understanding customer complaints at EM, particularly focused on the potential relationship between KM and customer satisfaction in the context of this organisation.
3. Understanding EM customers’ complaints 3.1 Collecting data about customer satisfaction In order to gain an understanding of the needs and expectations of EM customers, this research aimed at analysing data collected directly from EM’s customer. In addition to its currency, data to be analysed would need to be collected by a representative sample of the varied nature of EM’s customers and related to all services provided by EM. As part of their gathering of customer satisfaction intelligence, the customer relations department runs a survey which seeks to capture customer satisfaction following any interaction between a customer and the organisation, regardless of the means used for such an interaction. We were then provided with a sample of 9,000 customer responses to such a survey, randomly selected from a volume of data that exceeded 100,000 responses. This set contained feedbacks from customers from all regions served by EM and all customer groups, collected in the seven months prior to the this project (between January and July 2012). Additionally, it was found that approximately 50% of the feedback analysed originated from customers who have experienced the service provided by EM for more than a decade and the other 50% have been experienced the service for at least two years. This added additional value to the data available and therefore to the findings of this study.
3.2 Data analysis All prior research involving customer complaints at EM had looked at the problem from a purely quantitative perspective. Given the cost associated with it, never had the content of customer complaints been explored to a significant level. On this basis, this qualitative study was conducted to categorise and understand EM customer feedback. We sought to add confidence to the finding by following a replication strategy as described by Yin (2009), looking at both negative and positive feedback, linking qualitative and quantitative data analysis as discussed by Miles & Huberman (1994) and exploring both main categories of complaints and subcategories embedded within the main categories.
3.3 Customer complaints at Express Mobility Although finding the root causes of customer dissatisfaction was one of main concerns of this study, it would be more accurate to analyse customer satisfaction factors also. As Miles & Huberman (1994) suggest that it is important to consider the factors that could work against the predictions. Thus, this study started by categorising the types of comments embedded in the feedback and analysing whether these were positive or negative in relation to the service provided by EM. Table 1 shows that more than 44% of feedback received from customers was either specifically or leading to a complaint.
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Mahsa Jahantab and Alexeis Garcia‐Perez Table 1: Percentage of complaints in the data set Type of feedback
Compliments (Satisfied) Complaints (Dissatisfied) Neither satisfied nor dissatisfied Suggestion Total
Total number from sample data set 4241 4022 562
Percentage
175 9000
1.94% 100%
47.12% 44.69% 6.24%
From those 4,022 pieces of customer feedback identified as complaints, the authors found that 1,407 (35%) had their roots in either an unprofessional or unreliable services customers had received through ‘customer contact points’, mostly through call centres. From the analysis of such responses, the areas of concern were grouped as described in table 2. Table 2: Breakdown of call centre complaints Category
Example
Gaining access to the advisor Speed and quality of the communication with advisor Complaints related to the advisor
Cost of calls Time taken to handle the customer enquiry Advisor’s ability to understand the enquiry and identify the problem Accuracy of information provided
Standard of advice General
Having to call more than once to request support with the same issue
Percentage of complaints* 27.02% 6.11% 25.20% 32.68% 8.99%
* Percentage from the total 1,407 dissatisfied customers A further study of the complaints specifically related to the call centres showed that 25.41% of these were directly derived from lack of availability and sharing of relevant knowledge at the point of contact with the customer. The feedback received from customer in this area included:
The adviser was unable to understand the enquiry and identify the problem (12.93% of complaints)
The advice or information given was not easy to understand by the customer (6.01% of complaints)
The advice or information given to the customer was not correct (4.85% of complaints)
There was contradictory information or advice given to the customer (1.62% of complaints).
3.4 Additional findings It was also found that there is a positive relationship between performance of the advisors (responsiveness, assurance, empathy, etc.) and customer dissatisfaction as in cases where:
The issue was not resolved to customer’s satisfaction
The customer did not feel valued
Lack of willingness to help customer resolve the issue.
On the other hand, some dissatisfying transactions were compensated for by other actions leading to customer satisfaction. For example, a service failure was being reported and a good advisor was able to resolve the issue. The above discourse shows that the intangible aspects of the CCPs advisors‐customer interface have both negative and positive effect on the service quality. For that reason, customers’ knowledge gained through experiencing the service they receive through customer contact point is not only a detailed source for better
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Mahsa Jahantab and Alexeis Garcia‐Perez understanding of their needs but also it is valuable source for better understanding of their expectations from the service provider.
4. Conclusions This research has found that customer contact points such as call centres play a key role within organisations such as Express Mobility, which need to provide customer advice as part of their provision of transport‐related services. Furthermore, the authors understand that such contact points are an essential component of the marketing and customer care strategy of any companies that deals with customer queries regardless of its industry. The findings have shown that one in four complaints which involve customer service advisers are related to the lack of information and knowledge within the call centres at Express Mobility. This confirms that not only attitude of call centre representatives but also information and knowledge available within the call centre could determine customer perception of the organisation and its services. By having a well informed support strategy, call centre advisers can satisfy the customer needs and help develop brand loyalty in their customer base. Meaningful intra‐organisational knowledge sharing strategies must therefore involve customer‐facing staff whenever the organisational knowledge (in the form of experience, skills or information) can lead to better customer service. Knowledge management and in particular the principles of information and knowledge sharing within organisations and with their customers can drive the delivery an informed approach to customer support. Finally, Express Mobility has been able to take the findings of this research on board and respond to their customers’ feedback in a positive manner. New measures are currently being implemented, which include a number of initiatives leading to involvement of call centre staff in a continuous, formal process of information and knowledge sharing between themselves and with the rest of the organisations. The effects of such actions are being studied as a continuation of this research.
References Argote, L., McEvily, B. and Reagans, R. (2003). Introduction to the Special Issue on Managing Knowledge in Organizations: Creating, Retaining, and Transferring Knowledge. Management Science , Vol 4 (April), pp. v–viii. Bosch, V. G. and Enríquez, F. T. (2005). TQM and QFD: exploiting a customer complaint management system. International Journal of Quality & Reliability Management , Vol 22, No. 1, pp. 30 ‐ 37. Boulding, W., Kalra, A., Staelin, R. and Zeithaml, V. (1993). A dynamic process model of service quality: from expectation. Journal of Marketing Research , Vol. 30, No. 1, pp. 7‐27. Chau, V. S. (2009). Benchmarking service quality in UK electricity distribution networks. Benchmarking: An International Journal , Vol 16, No. 1, pp. 47 ‐ 69. Fundin, A. and Elg, M. (2006). Exploring routes of dissatisfaction feedback: A multiple case study within a machine industry segment. International Journal of Quality & Reliability Management , Vol 23, No. 8, pp. 986 ‐ 1001. Gummesson, E. (1993). Quality Management in Service Organizations. In International Service Quality Association, ISQA. New York. Kevork, E. K. and Vrechopoulos, A. P. (2009). CRM literature: conceptual and functional insights by keyword analysis Intelligence & Planning. Marketing , Vol 27, No. 1, pp. 48 ‐ 85. La, K. V. and Kandampully, J. (2004). Market oriented learning and customer value enhancement through service recovery management. Managing Service Quality , Vol 14, No. 5, pp. 390 ‐ 401. Massey, A. P., Montoya‐Weiss, M. M. and Holco, K. (2001). Re‐engineering the customer relationship: leveraging knowledge assets at IBM. Decision Support Systems , Vol 32, No. 2, pp. 155‐170. Miles, M. B. and Huberman, A. M. (1994 ). Qualitative data analysis : an expanded sourcebook (2nd ed.). London : SAGE Publications. Miller, J., Craighead, C. and Karwan, K. (2000). Service recovery: a framework and empirical investigation. Journal of Operations Management , Vol 18, No. 4, pp. 387‐400. Nonaka, I. (1991). The Knowledge‐Creating Company. Harvard Business Review , Vol 69, No. 6, pp. 96‐104. Quinn, J. B., Anderson, P. and Finkelstein, S. (1996). Managing professional intellect: making the most of the best. Harvard Business Review (March), pp. 71‐80. Slack, N., Chambers, S. and Johnston, R. (2007). Operations management. Harlow : Prentice Hall/Financial Times. Steiner, G. (2008). Supporting sustainable innovation through stakeholder management: a systems view. International Journal of Innovation and Learning ,Vol 5 , No. 6, pp. 595‐616. Tax, S. S. and Brown, S. W. (1998). Recovering and learning from service failure. Sloan Management Review , p. 75‐88. Yin, R. K. (2009). Case Study Research: Design and Methods (4th ed.). London: SAGE Publications.
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Social Media in Knowledge Management – Overcoming Fundamental Knowledge Problems Harri Jalonen Turku University of Applied Sciences, Turku, Finland harri.jalonen@turkuamk.fi Abstract: It has been argued that social media leads us towards a social economy which manifests itself as a new way of doing business based on a new kind of collaboration within and across organisations. Presumably, this means new possibilities to organisations' knowledge management practices. Social media provides a context for new ways of creating, searching, sharing, and applying knowledge. Although social media promises novel possibilities for organisations, it is still a poorly understood phenomenon. Particularly, this is the case in the knowledge management (KM) context. This paper proposes that the value of social media in KM can be evaluated on the basis of how social media can be used for overcoming four generic knowledge problems – i.e. uncertainty, complexity, ambiguity and equivocality. Drawing upon the relevant KM and social media literature, the paper discusses the four knowledge problems surrounding the knowledge management and the role of social media in order to address these problems. The paper contributes to both the KM research and practice by providing theoretically founded framework which illustrates the relationship between social media and knowledge problems. The framework can be used not only for identifying and understanding epistemological differences between knowledge problems but also for developing social media guidelines for KM purposes. Keywords: social media, knowledge problem
1. Introduction Knowledge management (KM) is traditionally defined as a process which consists of several activities, such as knowledge creation/construction, knowledge storage/embodiment, knowledge transfer/dissemination and knowledge exploitation/use (e.g. Alavi & Ledner 2001). Although numerous studies have shown the benefits of KM in leveraging knowledge and fostering innovation within organisations, however, the real business value of KM is yet debatable – especially when considering the role of information technology in KM. Several researchers have identified major challenges in adoption knowledge management systems (Alavi & Ledner 2001; Bock et al. 2005; Kankanhalli et al. 2005). Presumably the challenges related to the role of technology in KM are increasing and complicating due to the emergence of social media. The promise of social media is not confined to technology, but involves cultural, societal and economic consequences (Gurteen 2012). A widely acknowledged view is that social media has and will transform the ways of communication, collaboration and networking. However, social media is a double‐edged sword because it does not only improve knowledge processes, but also complicates them. Therefore, this paper argues the need to explore some fundamental knowledge problems faced by organisations. It is argued that the value of social media in KM should be evaluated on the basis of how social media helps to overcome four generic knowledge problems – i.e. uncertainty, complexity, ambiguity and equivocality. Until this is explored and defined, organisations run the risk of addressing symptoms rather than causes. The methodology of the paper can be characterised as a literature synthesis involving inductive interpretation of qualitative research. Reflecting the practices found in literature and practice, the paper aims to establish associations between social media and knowledge problems not previously known.
2. Uncertainty, complexity, ambiguity and equivocality as knowledge problems Seemingly, knowledge management implies the existence of particular knowledge processing requirements or problems which wait to be solved. Zack (2001) has incisively urged to ask: if managing knowledge is the solution, then what’s the problem? Zack has divided knowledge problems into four categories: uncertainty, complexity, ambiguity and equivocality. Uncertainty, by definition, means lack of information and knowledge about facts (Daft & Langel 1986). Information refers to a situation or a phenomenon which exists irrespective of people involved with it. Uncertainty is a gap which opens between information required in a certain task and information possessed by an individual or organisation (Galbraith 1977).
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Harri Jalonen Complexity arises from connections between situations or phenomena. Complexity refers to situations and phenomena interacting in a nonsimple way (Simon 1962). Complexity also means that the direction and strength of the development of situations and phenomena are difficult, but not necessarily impossible, to predict (e.g. Zack 2001). The amount of information that is needed to describe a phenomenon on a certain scale can be used as a measure of complexity (Gershenson 2011). Ambiguity means difficulty in interpreting a situation or phenomenon. Zack (2001) has distinguished two levels of ambiguity, which are surface and deep ambiguity. In surface ambiguity, the interpreter has got relevant interpretative knowledge which is difficult to use because available information does not trigger the process of construction of meaning, where individual information hints are arranged as part of a larger framework of interpretative knowledge (Weick 1995). In deep ambiguity, the interpretation difficulties arise from the lack of relevant interpretative knowledge. Equivocality manifests itself as different interpretations of a situation or phenomenon. Equivocality means a situation where the actors look at the phenomenon at hand through different 'lenses' (Daft & Langel 1986). Even if each interpretation was unambiguous and logical as such, when combined with the interpretations of others, the end result is typically a contradictory explanation of things and phenomena, and it contains mutually exclusive views (Weick 1995).
3. Managing knowledge problems through social media 3.1 Reducing uncertainty by decent problem formulation and effective information acquisition Since uncertainty refers to a lack of information, it sounds reasonable to suggest that uncertainty can be reduced by acquiring information. Although uncertainty is an annoying situation to find oneself in, however, it is a condition which can be fixed. This is because in uncertainty there is not just a shared view about the existence of uncertainty but also rather congruent understanding about the causes that produce the uncertainty. Overcoming the uncertainty requires two interlinked processes: the explicit problem formulation and acquiring the missing information. The problem formulation refers to the proper identification of the problem to avoid the risk of solving wrong problems (Simon 1962). Problem formulation involves several steps such as the description of the problem, analysing causes, identifying alternatives, assessing each alternative, and choosing one to be addressed (Goldstein & Levin 1987). Information acquisition, in turn, refers to the process of collecting and filtering new information (Choo 2002). Information acquisition reflects to the extent of individuals’ and organisations’ desire to accumulate information related to the formulated problem. The processes are intertwined meaning that problems cannot be formulated without information acquisition and information acquisition is useless without the problem to be formulated. Social media helps both processes. It does it in two main ways: firstly social media provides a context for organisational discussion which significantly improves the possibilities of understanding the nature of the problem causing the uncertainty, and secondly, social media increases the connectivity within and across organisation lowering the thresholds of sharing knowledge. There are several research findings that support the assumption that uncertainty can be reduced, even if not eliminated, through social media. Social media influences the ways problems are formulated. Wagner & Bollojou (2005), Schneckenberg (2009) and Vuori & Okkonen (2012), among others, have found that social media enables employees to participate in collaboration activities and informal discussions within the organisation. Informal discussions are extremely important as they enable the integration of “human factor” (Boddy et al. 2005) into the problem formulation process. This is congruent with the very nature of KM, which is not about “universal truth” but more about “serviceable truth” (Demarest 1997). Social media complements the problem formulation process’ knowledge base by providing a more multifaceted understanding than what can ever be achieved with static databases (Vuori & Okkonen 2012). Following the thoughts of Schumpeter (1934), Moran & Ghoshal (1996) have argued that all new resources, including knowledge, are created through combination and exchange. Applied to social media, the argument proposes that social media can be viewed as a virtual context where knowledge problems based on uncertainty are overcome either by combining elements previously unconnected or by developing novel ways of combining elements previously associated (Cronk 2012). It is the internal and external connectivity and
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Harri Jalonen communication networks which largely determine the success of acquisition and transfer of information, and hence the reduction of uncertainty. This is reported in several studies. Grace (2009), Cronk (2012), Vuori & Okkonen (2012), among many others, have found that wikis, blogs and other social media tools/platforms significantly improve the connectivity within and across organisations. The importance of the connections enabled by social media can be explained by the concepts of ‘strong’ and ‘weak’ ties (Granovetter 1973; Hansen et al. 1999). Strong ties manifest themselves as relationships between individuals or groups that regard each other as similar, whereas weak ties refer to relationships that connect individuals and groups that usually operate in various social environments. Weak ties enable information variety and promote the combination of elements previously unconnected. Strong ties, on the other hand, improve the distribution of complicated and context‐bound knowledge and preface the development of new ways of combining elements previously associated. At best, social media helps to cope with uncertainty as it enables organisations a new kind of modus operandi (Vuori & Okkonen 2012). Social media promotes a change process in which individuals transform from ‘passive’ information users to ‘active’ information ‘prosumers’ (cf. Toffler 1980). Social media supports information behaviour which Grudin (2006) has called as ‘produsage’ meaning that individuals can simultaneously produce and use information. Producing information is important in problem formulation, whereas using implies information acquisition.
3.2 Simplifying complexity by increasing knowledge process capacity and decomposing problems Complexity cannot be reduced by increasing information, because complexity arises from the intricacy and connectivity of various elements. A knowledge problem is complex one when there are many potential and interrelated variables, solutions and methods (Zack 2001). Although complex problems are tricky to solve, the complexity they involve is not absolute. Therefore, two approaches are proposed to cope with complex knowledge problems: the one that focuses on the organisation’s knowledge capabilities and the other one which address the decomposition of complexity (Zack 2001). The improvement of knowledge capabilities is based on developing rules and routines which promote the organisation’s members’ ability to locate, develop and bring appropriate knowledge, expertise, and skills to bear on the issues at stake, while the decomposition of complexity rests on restructuring and redefining the problems to resemble something more familiar (Zack 2001). Both approaches can be supported by social media. Firstly, social media enriches and diversifies organisation’s knowledge resources. The richer and more diversified the knowledge resources of the organisation are, the greater complexity the organisation can handle. The argument resonates with the law of requisite variety (Ashby 1956), which states that the system’s (e.g. organisation) internal diversity should match the variety and complexity of the environment. Several studies have recognised that by increasing the diversity of knowledge, social media potentially lifts organisation’s KM practices into the upper level (see Gurteen 2012). Essential part of this “upgrading” is the way how the organisation’s external knowledge resources are integrated into the organisation’s KM practices. As social media provides unbounded interaction, collaboration and participation of people (Bebensee et al. 2012), it has created new ways to the internal use of external knowledge. Many researchers have argued that by engaging customers and other stakeholders, organisations are able to increase needed diversity (e.g. Berthon et al. 2007; Gorry & Westbrook 2011). It has been found, for example, that social media is an appropriate context for customer stories, which can be used for stimulating and challenging organisational “wisdom” (Li & Bernoff 2011). Secondly, social media provides new means for decomposing complexity by breaking things into simpler parts (Zack 2001). Simplifying complexity can be aspired by using different social media tools such as wikis (allowing users to freely create and edit content), social bookmarking (enabling users to add, annotate, edit, and share bookmarks of web documents) and collaborative filtering (determining the relevance of information and knowledge resources according to the actions of individuals). Common for all above mentioned tools are that they help to redefine complex problems “to resemble something more familiar” (Zack 2001). The understanding of complex issues can be promoted if individuals are encouraged and rewarded to add, edit and comment content (Grace 2009). Another technique for dealing with complexity through social media is information visualisation. Information visualisation refers to technologies that support visualisation and help in the interpretation of information (Ware 2004). It is a question of combining the information and the situation into a whole and visualising it in a way that activates the cognitive processes of the mind, i.e. perception,
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Harri Jalonen memory, problem solving, comprehension. Visualisation also improves intuitive thinking and the observation of unexpected elements which would otherwise remain undetected. For visualisation purposes, social media can be exploited, for instance, for mapping and graphing organisational knowledge resources whether they are people‐based or IT‐based (Davenport & Prusak 2000). The importance of mapping the locus of knowledge within the organisation is increasing due to the proliferation of various virtual working settings. Without understanding of individuals’ expertise and interdependences among them, the risk is that the organisation’s KM underperforms (Janhonen & Johanson 2012). At best, social media enables the organisation to harness collective intelligence and wisdom of crowds (Levy 1997). Social media includes the potential to create a context where independent individuals can come up with a solution to a cognitive problem in a way that cannot be achieved by isolated individuals. Providing means for enhancing the organisation’s knowledge resources and for simplifying complex problems, social media also improves the organisation’s absorptive capacity (Cohen & Levinthal 1990), its ability to adopt and apply new knowledge. The greater the absorptive capacity is, the more likely the organisation can make complexity accessible.
3.3 Dissipating ambiguity by sensemaking Ambiguity refers to a lack of interpretative knowledge. It represents an inability to make sense of something (Weick 1995). An ambiguous situation is challenging as it does not lend itself a simple question‐answer approach (Daft & Lengel 1986). Instead of providing an answer to an explicit question, information may stimulate several interpretations. Essential, therefore, is that an attempt is made to meet ambiguity by sensemaking (Weick 1995). Sensemaking refers to the process of structuring the unknown and placing stimuli into some kind of framework. Sensemaking builds on several components including identity, retrospection, enactment, social, ongoing, cues and plausibility over accuracy (Weick 1995). Identity, meaning one’s sense of oneself, affects one’s behaviour. Sensemaker’s identity cannot be detached from the object of sensemaking as they are interdependent recursive relation with each other. Weick (1995) has put this as follows: “Depending who I am, my definition of what is ‘out there’ will also change. Whenever I define self, I define ‘it’, but to define it is also to define self.” Retrospection is a necessary condition for sensemaking. Adapting Mead (1956), Weick (1995) argues that we can be conscious only of what we have done, never of doing it. As the point of retrospection in time affects what people notice (Dunford & Jones 2000), the attention and interruptions to that attention explain a great deal of sensemaking (Gephart 1993). By enactment Weick (1995) refers to dialogues and narratives which help people to understand their thinking, organise their experiences and even predict events. Sensemaking is a social process meaning that plausible narratives are preserved, retained and shared. It is also an ongoing process as it emerges from simultaneous efforts to create order and to make retrospective sense of what happens. Sensemaking is not dealing with ‘facts’, but with information cues that are considered relevant and acceptable by their observers. Extracted cues provide points of reference for linking ideas to broader networks of meaning and are “simple, familiar structures that are seeds from which people develop a larger sense of what may be occurring" (Weick 1995). The interpretation of information cues is based on the principle of plausibility over accuracy. For Weick (1995) plausibility means the avoidance of obsession with accuracy which he judges as fruitless and impractical in a postmodern world infused with conflicting interests. All of the above mentioned components are strongly influenced by social media. It has been suggested that social media changes the process of identity formation. Identity becomes visible to others through the conscious or unconscious ‘self‐disclosure’ of subjective information such as thoughts, feelings, likes, and dislikes (Kaplan & Haenlein 2010; Kietzmann et al. 2011). As social media increases the speed and volume of information flows, it simultaneously provides more points for retrospection. Many studies have shown that social media increases organisations’ ability to respond quickly to changes in their environment (e.g. Constantinides & Fountain 2008; Yates & Paquette 2011). Loosely adapting Mead (1956), it can be thought that social media improves organisations’ ‘sensory processes’. Social media also supports the enactment of the environment. It does it by providing a social context for ongoing dialogues and narratives to be preserved, retained and shared. Kietzmann et al. (2011), Hanna et al. (2011), to name a few, have argued that social media have engendered radically new ways of interacting within and across organisations. This, in turn, has meant new possibilities for the extraction of information cues. By increasing the number of information cues, social media improves the possibilities to get insight what may be occurring. Finally, social media also affects
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Harri Jalonen the plausibility of information as it provides a collaborative space for negotiation between different views inhabited by people with multiple shifting identities (Kietzmann et al. 2011). Social media underpins the organisation’s KM enabling to handle with ambiguity. Social media is an organisational boundary element providing reciprocal interaction with its environment (cf. Maula 2006). In a way social media acts as the organisation’s ‘senses’ enabling interactive openness. By enabling the context for individuals’ interpretations become evident through narratives which convey the sense they have made of events, social media also creates common knowledge (Grant 1996). Common knowledge refers to those “elements of knowledge common to all organizational members” (Grant 1996). Manifesting itself as “intersection of their individual knowledge sets”, the common knowledge “permits individuals to share and integrate aspects of knowledge which are not common between them” (Grant 1996). Common knowledge is required as no actor alone has the capacity to solve epistemic problems manifesting themselves as ambiguity.
3.4 Encountering equivocality by creating trust and allowing polyphony of perceptions Equivocality arises from contradictory points of view. Equivocal problems are wicked in a sense that they do not lend themselves to answers that can be accepted by all involved (Rittel & Webber 1973). Equivocality involves political and ethic‐moral tensions and contains mutually exclusive views. Therefore, instead of “solving” problems including equivocality, this paper argues that, it should be a matter of how to encounter them. In encountering equivocal knowledge problems it is essential to accept the fact that one and the same event can be interpreted in different ways and from different starting points. Whether multiple views yield to potentially useful “polyphony of perceptions” (Hazen 1993) or definitely harmful “social deadlock” (Brunsson 1985) depends on trust between individuals. Trust is tested first, only after that the organisation has the ability to process meanings (cf. Luhmann 1995). Trust promotes interaction processes, which, in turn, may help to encounter and exploit the polyphony of perceptions. Trust acts as a kind of social adhesive, which provides the necessary coherence in which different actors can express their views based on their interests and values. Trust is based on imperfect knowledge manifesting as a belief that “others will not knowingly or willingly harm us” (Valenzuela et al. 2009). Social media helps to deal with equivocality in two main ways: firstly, social media enhances reciprocal trust building within and across organisations by enabling individuals to share and check each other’s identities before they engage with others, and secondly, social media promotes “polyphony of perceptions” by allowing different individuals get a voice. Correlation between trust building and social media can be explained in terms of identity. In the social media setting, identity refers to information that portrays individuals in certain ways (Kietzmann et al. 2011). Social media changes the ways of how we deal with identity. It allows individuals to learn “detailed information about their contacts, including personal backgrounds, interests and whereabouts” (Valenzuela et al. 2009). This information, in turn, reduce uncertainty about other individuals’ intentions and behaviours, helping to develop norms of trust and reciprocity, which Putnam (2004) and Valenzuela et al. (2009), among others, have deemed a necessary condition for developing norms of trust and reciprocity. It is to say that trust carries on when the knowledge ends. For the organisation’s KM the message is explicit: social media helps to build trustful atmosphere within the organisation, which, in turn, enables individuals to share different – including conflicting – insights (cf. Wagner & Bollojou 2005; Schneckenberg 2009; Vuori & Okkonen 2012). Drawing on language‐based approaches to organisation studies, Clegg et al. (2006) have suggested that management is enactment through language. It means that the organisational discourse not merely mirrors or represents the world, but it enacts the organisational reality (see also Weick 1995). Clegg et al. (2006) argue that “discursive enactment of reality affects and is affected by organisational power relations, since the position of having voice is powerful in itself in that it can set the frame for how further arguments might be evaluated”. To avoid the situation in which power is tied up with language that constitutes organisational realities, Clegg et al. (2006) proposes a polyphonic perspective. Organisational polyphony is more than just “simple assertion that everyone has their own point of view” as it “alerts attention to the play of multiplicities, the relations of power that operate between them and the unfinalisability of truth as it is enacted through different people” (Clegg et al. 2006). Organisational polyphony opposes the singular voice whether it belongs to a manager or someone else. Social media represents itself as the context of organisational polyphony enabling the voice for different individuals. By creating, searching, sharing and applying knowledge through
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Harri Jalonen social media, people engage in discursive moves, which Clegg et al. (2006) call ‘translations’ required “in order to make sense of past events and to seek legitimacy for future action”. From the organisation’s KM perspective, the polyphony argument requires the sensitivity to different voices including the ‘quiet’ ones. If the organisation fails to hear or silence the different voices, it risks its sensemaking capability. Social media improves the organisation’s KM ability to encounter equivocality. The usage of social media increases trust between individuals, which, in turn, may yield to higher level of social capital – i.e. intangible resources available to people through their social interaction (Putnam 2004; Valenzuela et al. 2009). It allows individuals to access information that is otherwise unavailable (Lin 2001). Instead of seeking ‘truth’, social media enables the discussion about issues that are not sure and verified (Vuori & Okkonen 2012).
4. Conclusions This paper has discussed four knowledge problems, their manifestations and possible solutions supported by social media. The paper concludes that social media can be used for easing knowledge problems whether they manifest themselves as uncertainty, complexity, ambiguity and equivocality. The paper speaks to the studies which argument for paradigm shift from conventional KM to conversational KM and the convergence between codification and personalisation KM strategies. However, more research needs to be done. One possible avenue for further research is to study what differences there are between different social media platforms in terms of knowledge problems. Essentially, this study can be understood as a “springboard” for further empirical research. Further research should be carried out to validate the framework.
Acknowledgements This paper has been funded by Yksityisyrittäjäin säätiö (Foundation for Sole Traders), Liikesivistysrahasto – the Foundation for Economic Education, and Turku University of Applied Sciences.
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Customer Experiential Knowledge Management (CEKM) ‐ Concept Proposition and Research Framework Development Dhouha Jaziri Bouagina and Abdelfattah Triki Marketing Department, Institut Supérieur de Gestion de Tunis (ISG), University of Tunis, Tunisia dhouhajaziri@gmail.com abdel.triki@gmail.com Abstract: This conceptual paper advances the customer experiential knowledge management approach (CEKM) as an attempt to contribute to the marketing management theory. Hence, the challenge of this approach is to connect the customer knowledge management theory to that of customer service experience. First, we assert that the externalized customer experiential knowledge can be used in order to innovate in terms of an experiential strategy implementation. In this case, we focus on the innovation by experience offer creation which fits into the experiential marketing paradigm. Second, the current research relates the customer tacit knowledge theory and that of customer experience in order to deduce the customer experiential knowledge aspects. Third, a preliminary exploratory research regarding the well‐being tourism field is presented in order to substantiate the research problem. A progressive literature review highlights respectively the managerial and theoretical gaps which support the proposition of a new concept labelled CEKMC (customer experiential knowledge management competence) by drawing upon the competence management theory. Finally, the CEKMC is integrated in a conceptual research framework that highlights its relationships with the absorptive capacity of organization and the experience innovation performance. Keywords: the customer experience, the experiential marketing, customer knowledge management (CKM), the tacit knowledge (TK), the well‐being tourism
1. Introduction Regarding “Thalassotherapy and Spa centres”, the stakes are high for Tunisia. In the long term, Tunisia needs to maintain its second position in the international ranking of the thalassotherapy sector. Centres need continuously to develop and improve their offers in order to differentiate their products, especially after the crisis caused by the revolution of 2011. Consequently, the main question raised here is: which managerial approach is most appropriate for well‐being tourism in order to achieve a successful innovation, especially regarding innovation through experience staging? The literature review focuses on the customer experience and knowledge theory. Specifically, we draw upon the tacit knowledge in order to define the various aspects of customer experiential knowledge. We give the results of preliminary exploratory research analysing well‐being tourism’s online and off‐line documentary resources in order to identify the business arguments used by thalasso centres in practice. As a principal result, the practice field reveals a lack of use of the theory of customer experience. We also show that externalized customer experiential knowledge can be used to innovate in terms of experiential strategy implementation. In this case, we focus on the experience based innovation which is defined as the result of experience staging (Voss & Zomerdijk 2007). The limits inherent to managerial and theoretical aspects will be summarized so that the Customer experiential knowledge management (CEKM) approach can be supported. The latter reflects the connection between two important fields of research: "the consumption experience" and "the customer knowledge management", and leads us to define a new concept labelled “customer experiential knowledge management competence” (CEKMC). Finally, the current research integrates the new concept of CEKMC in a conceptual model which stresses its relationship with the absorptive capacity (ACAP) of organization and the experience innovation performance. In this case, the ACAP is defined as the ability to use prior knowledge, to recognize the value of new information , assimilate it and apply it to create new knowledge and capabilities (Hou & Chien 2010). Furthermore, the research questions explored are presented in section III while highlighting the theoretical and managerial contributions.
2. Literature review 2.1 The customer experience theory Today, the tourist is a postmodern individual who wants to differ from others through his lived experiences (Cinotti 2007). Two perspectives of research regarding the customer experience are identified. The first perspective is based on the experiential marketing paradigm. In this case, Pine & Gilmore (1998) consider the
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Dhouha Jaziri Bouagina and Abdelfattah Triki experience as an exclusive offer which is memorable and has emerged as the next step in what we call the progression of economic value. The second perspective is represented by consumer behaviour research. It follows that the experience is defined as a personal lived, subjective episode in the construction/transformation of the person (Carù & Cova 2002 ; Holbrook & Hirchman 1982). Nonetheless, experiential marketing is believed to offer some freedom to the consumer to participate in the co‐creation of his own experience. However, this experience always keeps individual subjectivity and requests the appropriation of it by the consumer (Carù & Cova 2002). Two experiential strategies were identified in the literature: (1) the creation of the experience offer which follows the experiential marketing, and (2) the strategy of differentiation by experience, which consists of introducing the experiential perspective regarding an aspect of the marketing mix (Roederer, 2008). The implementation of these two strategies is confronted mainly with constraint related to the reception of the experiential proposal made by the company. That is, according to Roederer (2008), essentially the gap between the experience implemented by the company and the consumer perception (Roederer 2008). The present research targets the field of experience‐based innovation, and especially concerns, the new offers proposition in which the experience is the core. There is scarce research regarding this type of innovation except that of Candi et al. (2012) and Sundbo et al. (2010). On the other hand, the research on the experiential marketing is underdeveloped in the tourism field. Remaining with the experiential marketing case, postmodern researchers such as Hetzel (2002), Pine & Gilmore (1998) and Schmitt (1999) propose managerial processes to create an experience offer. However, these tools of experience conception neglect the participation of the customer in the co‐production of his desired experiential offer. Moreover, in order to reduce the gap between the implemented company experience and the perceived customer experience, Schmitt (2003) defined the customer experience management (CEM) as: “the process of strategically managing a customer’s entire experience with a product or a company” (Schmitt 2003, p.7). This process focuses essentially on the brand experience. Hence, drawing on the five steps process (see Table 1), CEM starts with the analysis of the experiential world, and continues to the stage of engaging continuous innovations. In this case, CEM recognizes the collection of experiential data on all customers’ points of contact with the company and its relationship with innovation to improve customer experience. In other words, the CEM is a fundamental, theoretical basis to support the fact that the customer experiential data may be processed to become experiential customer knowledge used by the company. Table 1:I The customer experience management process (Schmitt 2003) Step‐1 The first step is to analyse the experiential world of the customers, which provides customer insight
Step‐2 Building an experiential platform for your company and brands. This platform helps develop a positioning strategy for a company, product or brand. It is a strategic connection between analysis and implementation
Step‐3 Designing the brand experience. Once the experiential platform is decided it must be implemented in the brand experience – this includes all the static elements that a customer will come across‐the product, logo, and signage, packaging, brochures and advertising
Step‐4 The experiential platform is implemented in the customer interface. The customer interface is dynamic and interactive. This includes all types of dynamic exchanges and contact points with the customer
Step‐5 The final step is to engage the customer in continuous innovations. These innovations must be planned, properly managed, and marketed to improve customer experience
As the CEM is a global approach that is not only interested in the core consumption experience, this research focuses on the customer’s lived experience as potential experiential knowledge to exploit. From the same perspective, the service dominant logic (SDL) paradigm which is a service‐centred logic emerging in marketing (Vargo & Lush 2004; Lush et al 2007). It offers a broader understanding of marketing than the traditional goods‐dominant view (Schembri 2006). This paradigm supports on the one hand, the phenomenological service experience view where the main focus is the individual experience of service (Helkkula, 2010), and on the other hand, it recognizes through its premises the importance of knowledge as an essential unit of exchange and a source of competitive advantage. Additionally, the lived experience of customer service has been extensively highlighted as transformed knowledge (Carù & Cova 2003, Curbatov 2003 , Helkkula, 2011, Pine & Gilmore 1999, Schmitt 2003, Vargo & Lush 2008; 2007), which implies a cumulative learning for the
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Dhouha Jaziri Bouagina and Abdelfattah Triki consumer (Edvardsson et al. in Helkkula 2010: 41) and corresponds to customer knowledge for the company that can be used in order to innovate in terms of service experience proposals. Thus, we noted the non‐ existence of a conceptualization of customer knowledge management theory based on the customer service experience. Moreover, an important contradiction was marked in the customer knowledge management (CKM) literature that supports our ideas. It will be presented as follows.
2.2 The customer knowledge management (CKM) and the tacit knowledge (TK) theory Customer knowledge is “the dynamic combination of customer experience, values, scenarios and expertise, which are required, created and absorbed in the transaction and communication processes between companies and customers” (Sun 2010, p. 40). Especially, the “knowledge from customer” type of customer knowledge includes the comprehension of customer experience which is a tacit form of knowledge. The latter is defined as profoundly connected with people, which makes it hard to formalize and communicate. (Nonaka and Konno 1998, Dinur 2011). Simultaneously, we noted an important overlap regarding the conceptualization of CKM of Gebert et al. (2003), who consider that the management of knowledge flows in the customer relationship management (CRM) process integrates knowledge about, for, and from the customer. However, ‘the knowledge from customer experience’ concerns rather the case of customer experience management, whereas the CRM deals with the “knowledge about customer” category. Hence, we associate the customer experience with the tacit knowledge on the basis of the dynamic theory of organizational knowledge creation, developed in 1994 by Ikujuro Nonaka. Boisot (1998) highlights that it is fundamental to determine, acquire, use and convert tacit knowledge to an explicit form to transform a firm’s knowledge assets into competitive capabilities. The present research focuses on the tacit knowledge externalization process in order to convert the experiential knowledge to an explicit form and use it to obtain competitive capabilities. It is a challenge to shed light on research into the customer’s tacit knowledge, especially as the literature review showed there was little such research.
2.3 The customer service experience and the customer tacit knowledge correspondence A detailed investigation showed that customer experiential knowledge can result from customer experience through three dimensions: physical or sensorial, praxiological, and rhetorical (See Table 2). All are integrated in a dynamic interaction between the person (customer), object or stimuli (product or service), and the situation (Roederer 2008). Table 2: Summary of consumption experience dimensions (Roederer 2008) Dimension Physical dimension Praxeological dimension
Definition It covers all the sensory aspects involved by an interaction between a subject and an object of consumption in a given context. The different categories of actions starting from the individual to its environment (exp interactions between persons, actions in the experience place...)
Rhetoric dimension
it reflects the production of meaning associated with consumer experiences, real or fictional. The individual interprets objects as signs.
In parallel, a deeper understanding of tacit knowledge aspects in literature leads us to identify some taxonomies of tacit knowledge, and hence, to express the customer experiential knowledge in terms of knowledge aspects. The physical dimension corresponds to the embodied tacit knowledge as defined by Bennet & Bennet, (2008). The rhetorical dimension is connected to the semantic tacit knowledge as defined by Castillo (2002). Moreover, we think it is necessary to integrate the affective tacit knowledge as it represents unexpressed feelings (Bennet & Bennet 2008; Dinur 2011) that may be important for the customer service experience and may have a close relationship with other knowledge aspects (See Figure 1).
3. Documentary research: Analysis and results The previous literature discussion was followed by a preliminary exploratory study consisting in a documentary analysis. The investigation of the thalassotherapy and spa tourism segment starts with an exploration of different online and offline resources. Two methods of analysis were carried out. The first concerned Tunisian thalasso guidebooks and especially sites specializing in well‐being tourism such as that of a French tour operator. In this case, a lexical analysis of 40 thalasso‐spa centres’ e‐advertising presentations on a French tour operator’s website was made. The identification of major repeated segments led us to summarize it into two
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Dhouha Jaziri Bouagina and Abdelfattah Triki main categories: experiential and technical arguments.This first analysis concluded that the use of experiential aspects was very limited. Instead, the emphasis was on the technical arguments.
Figure 1 : The customer experience and the customer tacit knowledge correspondence The concept of experience was restricted only to sensorial aspects. The second analysis is thematic and it concerned directly the websites content of 36 thalasso and spa centres. This analysis included texts and images. The results supported the earlier conclusions and showed there were only six centres trying to present themed cures. In this case, we can connect the aspects of this offer to the definition of Roederer (2008, p.38) concerning the experience offer creation, namely : “the ability to create experience offers, that is to say, the ability to deliberately assemble products and services in order to stage experiences,‐ which are valued by the consumer, can be a significant competitive advantage." Thus, we noticed the lack of innovation in terms of experience offer. The thalassotherapy and spa tourism is a core‐experience industry. However, there is a lack of recognition related to the concept of experience in this industry. Really, on the one side, the experience exists when we consider the lived experience of customer service. On the other side, it is important that the well‐being organizations also define the experience desired by their customers through the proposal of themed cures. What is the best process to achieve a desirable and innovative service experience offer? What managerial competence can help well‐being organizations succeed in producing innovation based on the concept of experience?
4. The CEKM competence concept Following the previous global reflection, the central question posed by this research is: to what extent can knowledge‐based customer experience help managers to implement a successful experiential innovation? Thus, on the theory level, this research first aims to respond to the lack of research in the CKM field that addresses the customer’s tacit knowledge. Second aim is to conceptualize the CKM on the basis of the customer service experience and to enrich the research innovation by giving it more precision. In this case, the research is interested in a specific type of innovation, which is the innovation through experience creation. On the empirical level, the research aims to explore the use of knowledge‐based customer experience and its contribution to the implementation of a successful experiential offer –themed cures. The previously mentioned gaps represent a basis to propose the customer experiential knowledge management approach, which is defined as follows: the CEKM is the association of the knowledge management process with the customer service experience in order to enhance the future customer service experience or to create an offer of service experience. As suggested by the competence‐based management theory, we have noted a perceivable co‐evolution of knowledge and competence management in recent research and practice (Hong & Stahle 2005). Day (1994) uses interchangeably the words ‘capabilities’ and ‘competencies’ and defines them as
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Dhouha Jaziri Bouagina and Abdelfattah Triki “complex bundles of skills and accumulated knowledge exercised through the organizational process that enable firms to coordinate activities and make use of their assets”. He concludes that there is a direct connection between distinctive capabilities and superior performance (Day 1994). Based on the knowledge‐ based competencies literature, we summarize critical competencies (See Table II). Table 3 : Summarize of knowledge based competencies Authors Li & Calantone (1998) (c) & (e)
Competence Market Knowledge competence
Definition Is the process that generates and integrates market knowledge
Campbell (2003) ©
Customer Knowledge Competence
Based on internal firms processes that generate and integrate specific customer information which enables firms to develop customer specific strategies
Rollins & Halinen (2005) ©
Customer Knowledge management competence
The management of 5 aspects that the generation, dissemination and use of customer knowledge are enhanced
Chen & Huang (2009) (e) Hou & Chien (2010) © & (e)
Knowledge management capacity Market Knowledge management competence
Is the extent to which the firm is able to acquire, share and apply new or improved Knowledge. The process capability to acquire, convert, apply to use and to protect the market knowledge
Sun (2010) © & (e)
Customer knowledge management competence Customer knowledge enabled innovation (CKEI)
Competitive organizational resources for implementing CKM in an organization which composes the capability to exploit, integrate and utilize CK. The degree to which an organization is endowed with the capability of managing effectively CK in order to foster innovation
Belkahla,(2012) © & (e)
Competence Dimensions (1).Customer knowledge process, (2).Competitor knowledge process (3). Marketing research and development interface (1).Customer information process (2).Marketing‐it (inf. technology) interface (3).Senior management involvement (4).Employee evaluation and reward system (1).Interfunctional cooperation (2).Supportive organizational systems (3).Cooperation with customers (4).Supportive (IT) systems (5).Organizational culture that support customer orientation ‐‐‐‐‐‐‐‐‐
(1).Acquisition (2).Conversion (3).Application (4).Use (5).protection ‐Customer knowledge process capability ‐Customer Knowledge infrastructure capability (1) Integrative capacity (Collaborative competence) (2) the structural capacity (3) The internal management capacity
Notes : © Conceptual study , (e) Empirical study. The presentation of the knowledge based competencies follows a chronological order. On the one hand, we deduce that they are mostly conceptual; few of them propose a measurement scale. On the other hand, we conclude that the competencies proposed deal with market knowledge, or more specifically, with the customer knowledge in general terms. However, the CEKM requires a specific organizational competence to make full use of the customer’s experiential knowledge in order to enhance performance. Hence, we define the CEKM competence (CEKMC) as follows: it is the degree to which an organization demonstrates competence to generate and to integrate the knowledge‐based customer experience in order to obtain a successful experience innovation. In other words, CEKMC is the competence of
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Dhouha Jaziri Bouagina and Abdelfattah Triki the organization to propose a new experience offer on the basis of effective management of customer experiential knowledge. It follows that main research questions regarding CEKMC are issued: (1) How can customer experiential knowledge be generated, integrated and utilized effectively within the well‐being organization ? (2) What methods and platforms are used by managers in order to externalize the customer experiential knowledge CEK? (3) What are the internal and external factors that may influence the CEKM in the context of an innovation through experience offer?
5. The research framework development The developed model is composed of three principal parts: input, process and output (see Figure II). The input is presented by implemented support systems, as conceptualized by Salojarvi & Sanio (2006). Their implementation determines the ACAP related to customer knowledge. The first hypotheses are: the support systems determine the global absorptive capacity of an organization (H1), but also their implementation determines the customer experiential knowledge management competence (CEKMC) (H2). The second input is the education level. In this case, Murovec & Prodan (2009) stressed the importance of highly educated employees for ACAP; hence on the one hand, a highly educated workforce will have higher levels of ACAP (H3) (this relationship was confirmed by the empirical study of Minbaeva et al. 2003 in Jurado et al 2008 : 396), and on the other hand, the education level is positively related to CEKMC (H4).
Figure 2: The CEKMC structural model The consequent hypotheses are: Workforce training is positively related to ACAP (H5) and CEKMC (H6). Moreover, we propose the firm size and age as control variables. In this case, Belkahla (2012) confirmed the positive influence of firm size on the innovation success. Chen & Huang (2009) demonstrate that firm size and firm age may influence innovation performance. Earlier, Deshpande & Farley (1999) underlined the influence of firm size and age on the capacity to innovate. The process part concerns the relationship ACAP => CEKMC concept, and here we propose that absorptive capacity determines the development of CEKMC. The better the ACAP, the greater the chance that a better CEKM competence will be developed (H7). As identified through service dominant logic paradigm premises, the absorptive competence corresponds to absorptive capacity (ACAP) in knowledge theory, and according to knowledge review, the ACAP is integrated in the debate on dynamic capabilities. The latter are defined as routines in a firm that guide and facilitate the development of the firm’s organizational capabilities by changing the underlying resource base in the firm (Hou & Chien 2010). It is important to distinguish between organizational capabilities, which enable the firm to produce goods and services (as is the case with the proposed new concept of CEKM competence) and the dynamic capabilities that ensure the renewal and development of the organizational capabilities (Hou & Chien, 2010). In regard to this important distinction, research such as that of Hou & Chien (2010) or Wang & Ahmed (2007) have confirmed that ACAP determines the MKMC (market knowledge management competence). We propose that the CEKMC concept plays a mediator role between ACAP and innovation performance (H8). This relationship is justified in the empirical study of Hou & Chien (2010) which confirmed the mediating effect of competence between dynamic capability (as ACAP) and business performance. Finally, regarding the output model, which is the performance of innovation through experience staging, two relationships are suggested. The ninth
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Dhouha Jaziri Bouagina and Abdelfattah Triki hypothesis (H9) asserts that ACAP is positively related to innovation performance. Previous studies, both conceptual and empirical, have supported this relationship. Hence, Zahra & George (2002) highlighted the conceptual relationship between ACAP and innovation. Chen et al. (2009) confirmed empirically the positive effect of ACAP on innovation performance. Similarly, ACAP affects firm’s performance (Hou & Chien, 2010). Finally, Kostopoulos et al. (2011) support the proposal that ACAP contributes directly to innovation performance. The last relationship posed by the present structural model is: a higher level of CEKM competence leads to a higher level of experience innovation performance (H10). As the CEKMC is a new concept, closely related concepts justify this last hypothesis. Furthermore, Belkahla (2012) asserts the CKEI construct positively affects the innovation success. Chen & Huang (2009) advance a positive relationship between knowledge management capacity and innovation performance. Gibbert et al. (2002) support the idea that the innovation success is an outcome of CKM practices. Practically, Helkkula (2010) demonstrates the contribution of customer experience through phenomenology to service innovation. Earlier, Li & Calantone (1998) showed a positive influence of market knowledge competence on new product advantage. Similarly, Revilla & Cury (2008) reported a positive relationship between the Knowledge based capabilities and the performance.
6. Conclusion This research proposes a new managerial approach labelled CEKM, which responds to a set of theoretical and managerial limits. CEKM led to define a new concept : the “Customer experiential knowledge management Competence (CEKMC)”, which connects management research field to that of marketing. A structural model was elaborated while integrating the CEKMC concept with other major concepts as absorptive capacity or the experience innovation performance. The future research aims to develop a measurement scale of the CEKMC construct. This scale will represent a considerable managerial tool to the well‐being centres that have either opted to the experiential innovation or that want to engage into an experiential strategy.
References Belkahla Hakimi, W. (2012), Proposing and validating a model of customer knowledge management and innovation, Ph.D thesis, ISG Tunis, University of Tunis. Bennet, D. and Bennet, A. (2008) “Engaging tacit knowledge in support of organizational learning”, The journal of Information and knowledge Management Systems, Vol. 38, no.1, pp 72‐94. Boisot, M.H. (1998) Knowledge Assets: Securing Competitive Advantage in the Information Economy, New York, NY : Oxford University Press. Campbell, A.J. (2003) “Creating customer knowledge competence: managing customer relationship management programs strategically”, Industrial Marketing Management, Vol. 32, pp 375‐383. Candi, M., Beltagui, A. and Riedel, J. C. K. H. (2012) “Innovation through Experience Staging: Motives and Outcomes”, Journal of Product Innovation Management. doi: 10.1111/j.1540‐5885.2012.00999.x Carù, A. and Cova, B. (2003) “ Approche empirique de l’immersion dans l’expérience de consommation : les opérations d’appropriation” , Recherches et Applications en Marketing, Vol. 18, No. 2, pp 47‐65. Carù,A. and Cova, B. (2002) “Retour sur le concept d’expérience : Pour une vue plus modeste et plus complète du concept” , Actes de Journées de recherche en Marketing de Bourgogne, Bourgogne, [online] http://www.u‐ bourgogne.fr/leg/CERMAB/z‐outils/documents/actesJRMB/JRMB07‐2002.pdf Castillo, J. (2002) “A note on the concept of Tacit knowledge”, Journal of Management Inquiry, Vol. 11, no. 1, p. 46. Chen, Y.S., Lin, M.J. and Chang, C.H. (2009) “The positive effects of relationship learning and absorptive capacity on innovation performance and competitive advantage in industrial markets”, Industrial Marketing Management, Vol.38, pp152–158. Chen, C.J. and Huang, J.W. (2009) “Strategic Human practices and innovation performance — The mediating role of knowledge management capacity”, Journal of Business Research, Vol. 62, pp 104‐114. Cinotti , Y. (2007) “Conceptualisation d’un loisir expérientiel”, Actes du colloque international IPAG/NBUS, Paris, [online] : http://yvcinotti.free.fr/Documents/IPAG_2007.pdf Curbatov, O. (2003), L’intégration du consommateur par le knowledge Marketing : conception, production et consommation d’un produit personnel , Thèse pour le doctorat ès Sciences de Gestion ; Université de Nice‐Sophia Antipolis.. Day, G.S. (1994) “The Capabilities of Market‐Driven Organizations”, Journal of Marketing, Vol.58, pp.37‐52. Deshpande, R., & Farley, J. U. (1999) “Corporate culture and market orientation: Comparing Indian and Japanese firms”. Journal of International Marketing, Vol.7, No 4, pp 111‐127. Dinur, A. (2011) “Tacit Knowledge Taxinomy and Transfer: Case Based Research “, Working paper, Institute of behavioral and Applied Management, pp 246‐283.
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F (2008) "Service‐dominant logic: Continuing the evolution", Journal of the Academy of Marketing Science, Vol.36, No.1, pp1‐10. Vargo, S. L. and Lusch, R. F. (2004) "Evolving to a new dominant logic for marketing", Journal of Marketing, Vol. 68, No. 1, pp1‐17. Voss, C. and Zomerdijk, L. (2007). “Innovation in Experiential Services – An Empirical View”. In: DTI (ed). Innovation in Services, pp 97‐134, London: DTI [online]: http://www.dti.gov.uk/files/file39965.pdf. Wang, C. L. and Ahmed, P. K., (2007) “Dynamic capabilities: A review and research agenda,” The International Journal of Management Reviews, Vol. 9, No.1, pp 31‐51. Zahra, S. A. and George, G. (2002) “Absorptive capacity: A review, reconceptualization, and extension,” Academy of Management Review, Vol.27, No.2, pp 185‐203.
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MNCs Innovation, Reverse Knowledge Transfer and Firm Absorptive Capacity Daniel Jimenéz‐Jimenéz, Micaela Martínez‐Costa and Raquel Sanz‐Valle University of Murcia, Murcia, Spain danieljj@um.es mili@um.es raquel@um.es Abstract: Organizational innovation is one of the main tools for attaining a competitive advantage. Multinational corporations operate in different countries may capture new knowledge from diverse markets, customers or suppliers. This paper focuses on the knowledge transfer from the subsidiaries to the headquarters (knowledge transfer reverse). Furthermore, we try to analyse how this transferred knowledge facilitates the generation of innovations. Its study has demanded the analysis of the mediator role of absorptive capacity. Our results show that reverse knowledge influences indirectly on the headquarters’ innovation trough the existence of an absorptive capacity. Several conclusions and managerial implications are derived. Keywords: absorptive capacity, knowledge transfer, MNCs and innovation
1. Introduction Innovation is increasingly considered to be one of the key drivers of the long‐term success of a firm and knowledge is frequently cited as antecedent of innovation (Kogut and Zander, 1992, Crossan and Apaydin, 2010, Nonaka and Takeuchi, 1995). The basic assumption here is that companies which are able to renew their knowledge stand a better chance of understanding the consequences of the changes in their environments and are better suited than competitors to respond faster and better to them (Tippins and Sohi, 2003, Sinkula, 1994). Multinational companies (MNCs) are considered to have better opportunities to acquire and exploit knowledge than domestic organizations since they are open to new experiences, markets, cultures and ideas (Bonache and Zárraga‐Oberty, 2008) which can foster their innovation capability. In this line, Almeida and Phene (2004) suggest that MNCs innovate by integrating and acquiring these culturally diverse knowledge bases from multinational locations to their own core capabilities. For this potential advantage to become real it is necessary to transfer knowledge from one location to the others (Kotabe et al., 2007). Knowledge transfer is a process of systematically organized exchange of information and skills between entities (Wang et al., 2004). Intra‐corporate knowledge transfer is a complex process in general, but it is even more difficult within the MNCs due to the distance among organizational units, both geographical and cultural. Among other factors, successful knowledge transfer requires that the business unit which receipts knowledge has the capacity to absorb it and use it for developing innovations (Andersson, 2003). According to literature, companies with superior knowledge‐processing practices are likely to be better positioned to develop innovations (Jantunen, 2005, Tsai, 2001, Nieto and Quevedo, 2005). The purpose of this paper is analyses the relation between MNC innovation, absorptive capacity and knowledge transfer. In particular, this paper focuses on knowledge transferred from subsidiaries to the parent business unit. Literature names this process as reverse knowledge transfer (Rabbiosi, 2011). Some studies have examined the process of knowledge transfer within MNCs but most of them have focused on the transfer from parent to subsidiaries. Very few papers examined the process of knowledge transfer from subsidiaries to the parent unit. Thus, literature dos not provide accurate information about how this process takes place.
2. Theoretical framework Innovation has been conceptualised in a variety of ways (Wolfe, 1994) but, according to Hage (1999), most of the authors define it as the adoption of an idea or behaviour –regarding a system, policy, program, device, process, product or service‐ that is new to the adopting organization. Furthermore, attending to the Oslo Manual (OCDE, 2005), it can be understood as ‘‘the implementation of a new or significantly improved product
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Daniel Jimenéz‐Jimené, Micaela Martínez‐Costa and Raquel Sanz‐Valle (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations’’. Innovation processes are considered crucial activities for the contemporary multinational corporation (Ciabuschi et al., 2012). MNCs need to attend to different market and are been exposed to a local and international competition. In this context, these companies have to look up new ways to be competitive by offering new products, making new changes in their operation processes or improving their general processes of managing the company. However, MNCs have the opportunity to acquire knowledge from different sources because they count with a great variety of subsidiaries that operate in different markets, customers, suppliers and institutions. Only companies that count with efficient international knowledge management initiatives will be in a position of generating innovation for competing overseas.
2.1 Knowledge transfer in MNCs Knowledge management has been showed as a crucial process for the majority of the companies. Furthermore, for those that have to operate with different subsidiaries distributed overseas, knowledge management is required for the transmission of knowledge and the adoption of right strategies on specific contest. Knowledge transfer can be understood as the process of a systematically organized exchange of information and skills between entities (Wang et al., 2004). It implies direct collaborative relationships between two entities within the MNC, involving creation, transfer, and/or exchange of valuable knowledge. In this process, the entities from an MNC acquire knowledge from other entities in order to improve their productive capability. Traditional models of knowledge transfer focus on the conventional forward transfer of knowledge from headquarters to foreign affiliates. However, one impact of globalization is that knowledge transfer takes place across multiple dimensions (space, time, language, culture etc.) as well as in multiple directions (forward, backward and lateral). The reverse knowledge transfer (RKT) could be understood as the knowledge transfer from foreign subsidiaries to local headquarters. RKT has important profits for local headquarters. They can benefit from their subsidiary knowledge coordinating a global strategy, so by improving processes in their own or other units in the network, or by simply providing the missing link in the quest to develop a new product (Ambos et al., 2006). Such knowledge transfer presumably contributes to the buildup of innovative capabilities of local parent firms (Li and Zhou, 2008). RKT is also useful for the development of new products, and the realization and use of innovations in different units (Hansen, 1999, Tsai and Ghoshal, 1998, Tsai, 2001)– all of which can crucially facilitate the development of competitive advantage. Some studies in international business offer valuable insights into how firms invest abroad (Ito and Wakasugi, 2007), create patents (Singh, 2008) and transfer knowledge across units (Kurokawa et al., 2007) to obtain competitive advantages (Kafouros et al., 2012). This recent trend is in line with the broader recognition that foreign subsidiaries can serve as sources of innovations (Birkinshaw et al., 1998, Pearce and Papanastassiou, 1999) that can be transferred to and used by parent companies. What is more, some results show how local headquarters increase their innovative skills and capabilities benefit from the use of knowledge transferred from foreign subsidiaries (Rabbiosi and Santangelo, 2013). Thus, RKT provides potential opportunities for headquarters to develop new products through the combination of existing and different complementary skills (Kotabe et al., 2011).. Thus, we propose that: H1. RKT from foreign subsidiaries positively influences local parent company’s innovation.
2.2 The mediation role of absorptive capacity Reverse knowledge transfer is called to be an important factor for developing parent innovations. Although knowledge acquisition is important for MNCs to catch up in the international environment, they need to possess organizational capabilities to deploy resources (Dierickx and Cool, 1989, Teece et al., 1997). One of the most frequently cited factors as determinant of knowledge transfer is absorptive capacity. Absorptive capacity is defined as the ability to use prior knowledge to recognize the value of new information, assimilate it, and apply it to create new knowledge and capabilities (Cohen and Levinthal, 1990). From an organizational learning perspective, firms need to possess a considerable level of realized absorptive capacity to capitalize on knowledge acquisition from external sources to facilitate organizational learning (Lane et al., 2006, Argote and Ingram, 2000).
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Daniel Jimenéz‐Jimenéz, Micaela Martínez‐Costa and Raquel Sanz‐Valle Firm’s absorptive capacity involves using mechanisms through which knowledge outside the firm is identified, acquired, assimilated, transformed and applied (Liu and Chen, 2012, Jansen et al., 2005). Consequently, local headquarters’ benefits from RKT will be positively related to its absorptive capacity (Ambos et al., 2006). Thus, according to some studies, the absorptive capacity is positively related to knowledge transfer. The knowledge transferred will foster the acquisition of new knowledge that could be used for developing innovations. In consequence, we consider that RKT will be a key determinant for the absorptive capacity of an MNC. In particularly, RKT from foreign subsidiaries to local headquarter will facilitate the acquisition of knowledge that could be assimilated, distributed and exploited for generating innovation on the headquarters. Thus, we propose: H2. A local parent‐firm’ absorptive capacity positively influences the RKT from foreign subsidiaries. Finally, literature often underlines the relation between absorptive capacity and organizational innovation (Chang and Cho, 2008, Lynn et al., 2000, Madhavan and Grover, 1998). As the firm's absorptive capacity and the processes that develop its innovative capabilities are difficult to imitate, companies with superior knowledge‐processing practices are likely to sustain innovativeness and thus be better positioned in long‐term competition (Jantunen, 2005). Cohen and Levinthal (1990) understood absorptive capacity as a highly important organizational capability to recognize, value and assimilate external knowledge in order to increase a firm’s innovativeness. Furthermore, many scholars have emphasized the extent to which innovation firm’s ability involves the integration of external knowledge with the existing organization (Powell, 1998). Thus, most studies consider that absorptive capacity injects new ideas into the organization, increases the capacity to understand new ideas and strengthens creativity and the ability to spot new opportunities (e.g. Chesbrough, 2003, Gray, 2006, García‐Morales et al., 2008). Furthermore, absorptive capacity facilitates the development of a company’s innovation capacity through the application of knowledge acquired from internal and external sources. Therefore, organizational innovativeness can be considered as the output of absorptive capacity deployment. Hence, we state that: H 3. A local parent‐firm’ absorptive capacity positively influences local parent company’s innovation. In consequence, we propose that absorptive capacity plays a mediation role on the relation between RKT and organizational innovation.
3. Methodology 3.1 Population, data collection and sample The sample for this research includes Spanish MNCs with more than 100 employees, tenure of more than 5 years, and having at least one subsidiary in a foreign country. According to the Amadeus database, the number of MNCs fulfilling these requirements in Spain is 1.397. The data were collected using a structured questionnaire through phone interviews. A specialized market research company managed the process. Different steps were followed to carry out the data collection. We contacted the CEO or innovation executive of each organization. The market research company then tracked completion of the questionnaire and helped organizations to complete it. All the processes were supervised and the quality of this activity was tested by contacting a randomly selected sample of firms that had answered the questionnaire. The authors monitored the performance of the companies that had completed the survey. No problems were found. The unit of analysis for this study was the company. Of the 1397 companies invited to participate, a total of 104 usable questionnaires were received (a response rate of 7,44%). The responding companies belong to different sectors of the economy, which allows for a good representation of companies in general (table 1). The food and beverage industry, the furniture industry and metal production have the highest representation in the sample. A routine check for industry bias indicated no significant differences in the mean responses on any construct across firms from different industries. In addition, Chi‐square distribution analysis revealed no significant differences between the sample and the population, which was drawn from in terms of industry distribution, the number of employees and sales volume.
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Daniel Jimenéz‐Jimené, Micaela Martínez‐Costa and Raquel Sanz‐Valle Table 1: Sample characteristics
Employees
Mean Min 25% 50% 75% Max
1388 100 179 387 654 27299
Operating Revenue Turnover 201965 694 34337 82237 159196 2175749
Num. of recorded shareholders 5 0 1 2 5 106
Num. of subsidiaries 19 1 5 9 17 209
Num. of countries with subsidiaries 10 1 3 5 11 78
Source: Amadeus database
3.2 Measures The key variables in this study were measured using 5‐point Likert scales based on previous literature. Reverse knowledge transfer was measured by asking the respondent the degree to which the knowledge they had acquired from their subsidiaries was useful in improving a list of tasks. We adapted the Rabbiosi (2011)’ scale. After the scale depuration process through CFA, the scale includes 6 items. Organizational innovation measure includes four scales, each referring to one of the four types of innovation (OCDE, 2005): innovations in product, process, commercialization and management. Absorptive capacity measure was based in the scales used on three academic papers (Egan et al., 2004, Yang et al., 2004, Marsick and Watkins, 2003), which focus on the degree in which the culture of the firm has a learning orientation. After scales depuration, a six‐scale measure was used. Control variables. Age (numbers of years since the headquarters’ constitution) and size (number of headquarters’ employees) were introduced from AMADEUS database. They were recoded on the same scale as the rest of variables.
3.3 Validity and reliability check We conducted our analyses with structural equation modelling (SEM) using the statistical program EQS 6.1 for Windows (Bentler, 1995). Following the two‐stage model‐building process for applying SEM (Hair et al., 1998, Jöreskog and Sörbom, 1996, Hoyle and Panter, 1995), in the following section, we carried out a confirmatory factor analysis (CFA) and then we tested the structural models corresponding to our hypotheses. To assess the single dimensionality of each construct, a confirmatory factor analysis of the five constructs was conducted employing all the items (Anderson and Gerbing, 1988), including all independent, mediator, and dependent variables so as to analyse their dimensionality, which is the relations between latent and observed 2 variables. The results of the confirmatory factor analysis (CFA) to test the validation of the measures (χ (74)= 103.477 CFI=.957 IFI=.958 BNNFI=.947 RMSEA=.068 SRMR=.068) indicate a good fit for the model. Reliability of the measures was calculated with Bagozzi and Yi’s (1998) Composite Reliability Index and with Fornell and Lacker’s (1981) Average Variance Extracted Index. Discriminant validity is indicated first since the confidence interval (± 2 S.E.) around the correlation estimate between any two latent indicators never includes 1.0 (Anderson and Gerbing, 1988). Secondly, discriminant validity was tested second by comparing the square root of the AVEs for a particular construct to its correlation with the other constructs (Fornell and Larcker, 1981). Table 2 provides an overview of the means and standard deviations of the constructs. The results show that there is no multi‐collinearity. In addition, the table shows basic information about each factor.
4. Results After satisfying the requirements discussed above, we tested the structural model, which summarizes the three proposed hypotheses. Conventional maximum likelihood estimation techniques were used to test the model (Jöreskog and Sörbom, 1996). The fit of the model is satisfactory, thereby suggesting that the nomological network of relations fits the data. This is another indicator that supports the validity of these scales (Churchill, 1979).
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Daniel Jimenéz‐Jimenéz, Micaela Martínez‐Costa and Raquel Sanz‐Valle Table 2: Reliability, validity and measurement model Lowest Cronbach SCRa AVEb t‐value alpha Reverse knowledge transfer 2.8974 1.05798 7.208 .910 .915 .642 Absorptive capacity 3.8264 .80121 6.587 .876 .888 .615 Innovation 3.7212 .74298 5.379 .732 .761 .515 CFA Goodness of Fit: χ2(74)= 103.477 CFI=.957 IFI=.958 BNNFI=.947 RMSEA=.068 SRMR=.068; a Scale composite reliability (qc=(Aki)2 var (n)/[(Aki)2 var (n) +Ahii]; (Bagozzi and Yi 1988); b Average variance extracted (qc=(Aki)2 var (n)/[(Aki)2 var (n) +Ahii]; (Fornell and Larcker 1981) Constructs
Mean
SD
Significant path
Age
Non significant path Direct effect (Indirect effect)
β=0.189
β=0.115(0.212) Size β=0.076
Absorptive capacity
β=0.011(0.049)
R2=0.304
RKT
Innovation
R2=0.425 (0.243)
Figure 1: Structural model We do not found support for supporting hypothesis H1 concerning the relationship between reverse knowledge transfer and organizational innovation (table 3). In this case, the knowledge acquired for the local headquarters from foreign subsidiaries are not affecting the development of organizational innovation in the central organization (β = .182) when we included the mediation variable (absorptive capacity) on the model. The findings also support H2 and H3. As table 3 shows, there is a positive relation between RKT and the absorptive capacity of the firm (H2; β = .535***) and a positive relation between the latter and the generation of innovations on the headquarters (H3; β = .520***). This supports the idea of the crucial role of absorptive capacity of headquarters for obtaining organizational innovations from the knowledge acquired from subsidiaries. Although we have not found evidence for supporting a relation between RKT and innovation, results show some evidence of positive, significant, but indirect, effects of RKT on organizational innovation (κ=0.278, p<0.01). Furthermore, in order to test that RKT has an indirect effect on innovation, we compared the propose model with an alternative model that does not include absorptive capacity (Andreson and Gerbing, 1988). In this alternative model, a direct path from RKT to innovation (table 3) was specified in order to apply Baron and Kenny´s general idea (1986) about mediating variables which has been adapted to causal models. The results of the mediation link support our hypothesis. Firstly, the mediation model (with absorptive capacity) explains 2 2 more variance on innovation (R =.425) than the direct effect model (R =.243). Secondly, positive relationships exist between RKT and absorptive capacity, and between absorptive capacity and innovation. Thirdly, the significant relationship between RKT and innovation in the direct effect model (β =.457, p < 0.01) is not significant in the model with mediation (β=0.182, p> 0.1). Together these three points provide evidence that there is a discernible mediating effect of absorptive capacity in the relationship between RKT and innovation and that the mediation model represents a significant improvement over the direct effect model. We can conclude that the effect of RKT on innovation is completely mediated by absorptive capacity (Baron and Kenny, 1986).
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Daniel Jimenéz‐Jimené, Micaela Martínez‐Costa and Raquel Sanz‐Valle Table 3: Construct structural model relationships Main relationships
Model with mediation Model without mediation Coefficient td Coefficient td Main paths RKT → Innovation 0.182 1.341 .457*** 3.333 *** RKT → Absorptive Capacity 0.535 4.126 Absorptive Capacity → Innovation 0.520*** 3.317 Control variables Age → Absorptive Capacity 0.189* 1.867 Size → Absorptive Capacity 0.076 0.769 Age → Innovation 0.115 1.067 0.212* 1.853 Size → Innovation 0.011 .103 0.049 0.446 Indirect effects RKT → Innovation 0.278*** 2.846 Goodness of Fit from the model with Goodness of Fit from the model mediator variable χ2(96)= 117.322 without mediator variable χ2(40)= CFI=.968 IFI=.969 BNNFI=.960 62.550 CFI=.947 IFI=.949 BNNFI=.927 RMSEA=.051 RMSEA=.079
5. Conclusions This paper has focused on the relationship between reverse knowledge transfer, absorptive capacity and organizational innovation. Despite the presumed positive effect of knowledge management on innovation, empirical studies do not always provide evidence to support it in international companies. This paper explores focus on the process of transferring knowledge from different subsidiaries to the headquarters in order to foster the generation of innovations in MNCs. A review of the literature on the relation between, on the one hand, RKT and absorptive capacity, and on the other hand, absorptive capacity and innovation, seems to support the idea that absorptive capacity may mediate the relation between RKT and innovation. However, no empirical research had examined this suggestion from the headquarters point of view. Many studies have focused on the paper of the headquarters for transmitting information and not for receiving from the subsidiaries. The purpose of this paper was to fill this gap. Our findings provide evidence, first, that there is a positive relation between RKT and absorptive capacity. In particular, we found that when subsidiaries distribute their knowledge to the headquarters, the last one will be more able to acquire and applied new knowledge for commercial ends. Thus it, companies count with new international knowledge that could be exploited for different uses. Obviously, one of the main purposes is the generation of innovations. Our results show, how absorptive capacity has a positive influence on the generation of innovation in the headquarters. Finally, according to the literature, in this paper we proposed that RKT could influence on generation of innovations. However, we do not found a direct effect between these two variables, but an indirect effect. The analysis shows that knowledge transferred from subsidiaries will improve the generation of innovations if companies have an absorptive capacity to acquire, assimilate, distribute and exploit this knowledge for innovative ends, what suggests that absorptive capacity plays a total mediation. This study has also implications for practitioners. On the one hand, like previous research, our data show that in order to achieve better performance, companies should foster their organizational learning capability. The reason is that the organizational learning capability and its output, organizational knowledge, enable companies to anticipate and understand better the customer needs and the competitive situation, to process this information faster and to develop new products, processes or systems which allow them to achieve a competitive advantage. Despite the contributions of this paper, its results should not be interpreted without recognizing the potential limitations of this study. The more important one is its cross‐sectional design, which may constrain both the observation of multiple long‐term effects of each variable and the elucidation of causal relationships between the variables. This limitation could be avoided by employing a longitudinal study design. Other recommendations for future research on the relationship between RKT and innovation emerge from the present study. Since the premise that RKT is based on the transmission of knowledge, it would be necessary to analyse how this knowledge is distributed. Two main ideas to examine are the use of expatriates (Minbaeva, 2008) and the role the knowledge management strategies (Edvardsson, 2008, Hansen et al., 1999). This could help to understand how this knowledge could be easily transmitted to the headquarters.
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Daniel Jimenéz‐Jimenéz, Micaela Martínez‐Costa and Raquel Sanz‐Valle
Acknowledgements The authors acknowledge the funding received from the Spanish Ministry of Science and Technology (research project ECO2009‐12825) to undertake this research
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Peculiarities of Organization’s Knowing Habil. Palmira Juceviciene1 and Vyda Mozuriuniene2 1 Kaunas University of Technology, Kaunas, Lithuania 2 Comfort Heat Ltd., Vilnius, Lithuania palmira.juceviciene@ktu.lt vim@comfortheat.eu
Abstract: Researchers devote considerable attention to organizational knowing, regarding it as the knowing, important for an organization. However, lately, special consideration has been given to informal knowledge at an organization, not yet formally accepted and, therefore, reckoned not important. Structurally, complete organization‘s knowing falls into two parts: a) knowing important for an organization, b) knowing not important for an organization. Each of those may contain a) explicit (the knowledge, revealed by employees in writing or orally and known to the organization) and tacit knowledge (unknown to the organization); b) knowledge of different levels: individual and collective, which might be common to a group and general to the whole organization. Such a structure of organization‘s knowing, based on works of a number of prominent researchers (Nonaka and Takeuchi, 1995; Choo, 2002; Tsoukas, 2006; Polanyi, 1962; Leonard and Sensiper, 1998), has already been validated by the authors of the present paper in their investigations (Juceviciene and Mozuriuniene, 2011). However, numerous questions arise in this context. Is the not important part of organization‘s knowing really insignificant, or unnecessary? Doesn’t it influence employee success, doesn’t it help create organizational value? Then, which level of knowledge prevails in organization‘s knowing: individual or collective? Which kind of knowledge dominates: explicit or tacit? What is the relation between the not important (informal) knowing and important (organizational) knowing? Is the country, i.e., company location, a significant factor influencing structural parts of organization’s knowing? All of the above raised issues constitute a research problem, not yet properly investigated. Its solution requires not only theoretical, but also empirical research. The aim of this paper is to determine the peculiarities of organization’s knowing. The paper consists of four parts. After the introductory (first) part, the second part describes the conception of organization’s knowing and its structure, already established in the previous works by the authors of the paper, and highlights the rationale of this structure. The third part discusses the methodology of empirical research. Literature analysis has been employed for completing the second and the third parts. The fourth part presents and analyses the results of the employee survey, carried out at organizations, located in three countries. The conclusions foreground the importance of both parts of organization’s knowing to employee success. It has been noted that employees place slightly more significance upon its formal part (important knowing) and are more inclined to gaining it. The gained formal knowledge becomes more explicit than the gained informal. Determinations obtained not only prompt further research, but are also beneficial for the practice of knowledge organizations. Keywords: organization’s knowing, organizational knowing, knowing important for organization, knowing not important for organization
1. Introduction In his theory of organizational learning, Nonaka (1994) claims that knowledge at an organization is created and used in the process of interaction between the explicit and tacit knowledge. Nonaka and Takeuchi (1995) investigate the creation of explicit and tacit knowledge as organizational knowing at an organization. Scholars have been devoting most of their attention to organizational knowing, which they consider to be the knowing, important for an organization (further referred to as KIO). Stankeviciute (2002) has been one of the first researchers to discuss organization’s knowing. She defines organization‘s knowing as a dynamic unity of the knowledge that exists and is created on the levels of individuals, their groups, and the whole organizations. There has been a discussion going on concerning non-formal knowledge at organizations, not formally acknowledged, but present as the knowledge of employees or their groups (or even of their informal networks) (Lawson at al, 2009), presumably called the knowing, not important for an organization (further referred to as KNIO). Thus, the structure of organization‘s knowing consists of KIO and KNIO. This logic, established on the basis of numerous investigations of researchers Nonaka and Takeuchi (1995), Johnson (2007), can be found in previous works by the authors of this paper (Juceviciene, Mozuriuniene, 2009). However, theoretical analysis has not allowed getting deep enough into the peculiarities of organization‘s knowing, and some issues remain unanswered. What is the relation between the not important (informal) knowing and important (organizational) knowing? Which level of knowledge prevails in organization‘s
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Habil. Palmira Juceviciene and Vyda Mozuriuniene knowing, individual or collective? What knowledge prevails, explicit or tacit? Is company’s locality, e.g. a country, a significant factor for structural parts of organization’s knowing? All those considerations constitute the research problem to be solved by means of empirical investigation. This paper aims at determining the peculiarities of organization’s knowing. Literature analysis has been used to describe the concept of organization’s knowing from the structural point of view (Part 2) and to provide rationale for the empirical study methodology (Part 3). Empirical research is a key-point of the paper (Part 4). It has been based on a survey of knowledge workers in three subsidiaries of a multinational company situated in the Baltic countries.
2. The conception of organization’s knowing In their previous research on the structure of organization’s knowing (Juceviciene and Mozuriuniene, 2009), the authors of the present paper identified two parts of organization’s knowing:
organizational knowing, which an organization considers important and attempts to increase – KIO;
organization’s informal knowing, the existence of which an organization does not consider important for its performance – KNIO.
In subsequent investigations (Juceviciene and Mozuriuniene, 2011), the essence of knowing was dwelt upon with the aim of finding theoretical answers to the following questions: What type of knowledge constitutes knowing? Who possesses this knowledge at an organization? Classical works in the field of knowledge management were initially very helpful, searching for answers (Polanyi, 1962; Nonaka and Takeuchi, 1995; Nonaka and Konno, 1998; Nonaka, Toyama and Byosiere, 2001). Then, the study of Bennet (2002), Choo (2002), Stankeviciute (2002), and Tsoukas’ (2006) research allowed outlining the concept of knowing and highlighting a complete structure of organization’s knowing. The idea of Bennet (2002), declaring that knowing focuses on the methods which aim at increasing the ability to consciously integrate sensory inputs with individuals’ tacit knowledge, was extremely valuable. However, the authors of the current research do not agree with the scholars who attribute the term of knowing to the meaning of tacit knowledge only. The authors consider Tsoukas’ (2006) notice of Polanyi work (1962) to be very useful in explaining the term knowing. Polanyi (1962), when speaking about knowing as embodied in action, uses the term tacit knowing as a fundamental statement. Thus, this part of knowing cannot be expressed, whereas the other part, on the contrary, can be made explicit. This has enabled Tsoukas (ibid) to draw a conclusion that Polanyi and Nonaka’ ideas, related to the possibility of making tacit knowledge explicit, are not quite conflicting. Thus, knowing covers the knowledge of both types, explicit and tacit, which are interdependent (Choo, 2002). This reminds of Leonard and Sensiper (1998) who claim that knowledge exists ‘on a spectrum‘, as a continuum. Organization’s knowing is not a simple sum of knowing of all organization members and their groups, ‘though the knowing of organization members and their groups is a part of organization’s knowing which also participates in the creation of this knowing as well as undergoes changes due to its impact, meaning that the interrelated connection exists between individuals and the context of their mutual performance’ (Stankeviciute, 2002:42). If organizational knowing is limited by the perceived knowing, important for the organization (KIO), then, according to previous investigations by Juceviciene (2007), organization’s knowing (tacit and explicit knowledge) structurally encompasses the total knowing (formal and informal) of all organization’s individuals and their groups, and also total knowing (formal and informal) at organization’s level (Figure 1).
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Habil. Palmira Juceviciene and Vyda Mozuriuniene
Figure 1: The structure of organization‘s knowing (Juceviciene and Mozuriuniene, 2009) Thus, the structure of organization’s knowing is comprised of two parts, KIO and KNIO. Each of those retains explicit and tacit knowledge on three levels: individual, group, and organization. For instance, organization‘s mission, vision, philosophy (if articulated), or aims belong to KIO as explicit knowledge on an organizational level. Not articulated informal organization‘s values or the existing behavioral models belong to the tacit knowledge of the same level. Regrettably, the structure of organization’s knowing does not reveal the dynamics of this knowing, already highlighted by Stankeviciute (2002). Organization’s knowing structure is applicable in the investigation of a KIO and KNIO effect upon the success of employee activity, in determining the expression of different types of knowledge within various organizational practices, etc. In other words, this structure helps reveal organization’s knowing peculiarities, for instance, the use of structural parts in organization’s knowing, such as different types of knowledge, upon employee activities, or allows disclosing the particularities of gaining knowledge, etc. This stands as the aim of empirical investigation.
3. Methodology of the empirical research When investigating the peculiarities of organization’s knowing, a number of research questions arise. Does KNIO influence employee performance? What is the relation between not important (informal) knowing and important (organizational) knowing? Which level of knowledge prevails in organization‘s knowing: individual or collective? Which type predominates: explicit or tacit knowledge? Is company location a significant factor, influencing the structural parts of organization’s knowing?
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Habil. Palmira Juceviciene and Vyda Mozuriuniene The last question has called for an empirical investigation in different countries. In order to assess the influence of a country factor on organization’s knowing, the research has had to be focused on several subsidiaries of one multinational company. In fact, such a choice limits author‘s possibilities to delineate all feasible differences among organization‘s knowing of the firms. According to (Macharzina, Oesterle and Brodel, 2001), the headquarters of the multinational company equips its subsidiaries with specific knowledge, thus, their organization‘s knowing, especially KIO, may assimilate over time. It should be also noted that, if differences among organization‘s knowing of subsidiaries are identified, it can be assumed that there are even greater differences among the firms outside one multinational company. Specifically, a multinational company X has been selected for the investigation with its headquarters in Finland and subsidiary companies, located in a number of countries, including all the three Baltic countries. 93 informants have been surveyed in three subsidiaries: 29 employees in Lithuania (LT), 32 in Latvia (LV), and 32 in Estonia (EE), with 75 male and 18 female respondents. Among them, two thirds of the informants were aged between 25 and 39, one fourth was aged 40-59, and just a few were aged between 20 and 24. All of the informants were sales and engineering personnel. Two thirds of them were university graduates; the rest had high school or college education. Research into organization’s knowing and knowledge creation usually requires qualitative research and an interview, in particular, but this approach is time consuming for respondents. Following time limitations, the present research has employed a quantitative approach. Before that, researchers had to secure all employees’ competence in evaluating their own knowledge creation process. Therefore, before the investigation, employees (i.e. functional specialists, not managers) were introduced to the fundamentals of knowledge management. The main questionnaire for researching organization’s knowing has been created according to the three levels of formal (organizational) and informal knowing: that of an individual, group, and organization. The emphasis has been placed on finding out a) how necessary this knowledge is at work (is it important in doing the job); b) if a particular employee already possesses the necessary knowledge; c) if a particular employee increases this knowledge; d) if he/she introduces his/her increased knowledge to others at the organization (is this knowledge converted into explicit, or does it remain tacit). In the process of constructing survey questions, the researchers considered that the problem of defining tacit knowledge was firstly related to its transformation into explicit knowledge. Thus, the questions encouraged employees’ reflection; reconstruction was stimulated with the aim to help employees make their tacit knowledge on past activities explicit. Considering research findings, two thirds of informants’ opinions on separate issues would account for the majority. The data obtained has been processed by SPSS 20. Descriptive statistics has been applied for data analysis (N,%). Statistical significance of the data has been analyzed by non-parametrical Kruskal Wallis Test (Exact sig), marked as follows: * - significant level, p<0,1; ** - significant level, p<0,05; ***- significant level, p<0,01.
4. Peculiarities of organization’s knowing, revealed by employee performance research The current chapter presents, analyzes, and discusses empirical research data obtained according to the research questions, presented in Chapter 3. Answers to those are provided seeking general tendencies and specific differences manifesting themselves in the subsidiaries, located in three different countries.
4.1 What kind of organization’s knowing is needed to perform successfully? Research results aim at answering the following questions: does the ‘not important‘ part of organization‘s knowing body really affect employee performance? What is the relation between ‘not important’ (informal) knowing and ‘important’ (organizational) knowing?
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Habil. Palmira Juceviciene and Vyda Mozuriuniene As seen in Table 1, employees acknowledge that they need not only formally recognized organizational knowing (KIO), but also informal knowing (the not important part of organization’s knowing - KNIO). As the data shows (Table 1), KIO is needed more than KNIO which is natural, as the organization, quite advanced in knowledge management, is able to provide its performance (possibly, anticipated) with the fundamental necessary knowledge (KIO) either acquiring, or producing it inside the organization (Macharzina, Oesterle and Brodel, 2001). However, acting in a turbulent environment, organization finds it difficult to predict overall activities and the needed knowledge. The knowledge, required for unforeseen acions, is sometimes created by employees or their groups instantly, ‚‘here and now’, during networking, or even over a cup of coffee. This has been supported by Lawson et al (2009). Though such informal knowing is less valued at organizations than formal, even in small amounts this knowledge (KNIO) can considerably influence the success of individuals, their groups, or organizations. Table 1: Structure of organization’s knowing required for successful performance at the subsidiaries situated in the Baltics Type of knowledge Knowledge on individual level Organization knowing Collective knowledge on important group level * for organization (KIO) Collective knowledge on organization level Knowledge on individual level ** Organization knowing Collective knowledge on not important group level for organization (KNIO) Collective knowledge on organization level *
Country
Knowledge needed to perform successfully (%) 1-10
11-20
21-30
31-40
41-50
51-60
61-70
LT
4,2
16,7
33,3
20,8
20,8
4,2
0,0
LV
7,1
25,0
46,4
14,3
7,1
0,0
0,0
EE
10,7
0,0
67,9
14,3
7,1
0,0
0,0
LT
12,5
41,7
37,5
4,2
4,2
0,0
0,0
LV
17,9
64,3
10,7
3,6
0,0
0,0
0,0
EE
17,9
46,4
32,1
3,6
0,0
0,0
0,0
LT
33,3
41,7
12,5
8,3
0,0
0,0
0,0
LV
46,4
39,3
7,1
3,6
3,6
0,0
0,0
EE
28,6
53,6
17,9
0,0
0,0
0,0
0,0
LT
70,8
20,8
0,0
0,0
0,0
0,0
0,0
LV
32,1
35,7
25,0
0,0
0,0
3,6
0,0
EE
53,6
39,3
7,1
0,0
3,6
0,0
0,0
LT
70,8
12,5
0,0
0,0
4,2
0,0
0,0
LV
75,0
10,7
7,1
0,0
3,6
0,0
0,0
EE
82,1
3,6
14,3
0,0
0,0
0,0
0,0
LT
70,8
12,5
4,2
0,0
0,0
0,0
0,0
LV
64,3
25,0
0,0
0,0
7,1
0,0
0,0
EE
96,4
3,6
0,0
0,0
0,0
0,0
0,0
* - p<0,1; ** - p<0,05 One should consider that the firms, relatively advanced in knowledge management, have been investigated here. It is not clear what findings would have been achieved in a less advanced sample of firms. Further research is needed to prove that KIO always prevails over KNIO. The current research intends to clarify which level of knowledge prevails in organization‘s knowing – individual or collective? The majority of the informants at LT, LV, and EE subsidiaries (more than 2/3) have acknowledged that, in the body of KIO, individual knowledge is most needed (31 to 50 percent). Less important is the knowledge on group and organizational levels, 21 to 30 and 11 to 20 percent accordingly, which contradicts a predominant scholarly opinion (Bougon, Karl, Binkhorst, 1997) stating that organizational knowledge is only collective knowledge. Presumably, this depends on organizational performance specifics (in the subsidiaries investigated individual sales of high technologies and consultancy dominate). It also has to be noted that the surveyed employees prioritize individual knowledge over group knowledge, and consider the knowledge on organization’s level as the least needed. This might account for the fact that in those organizations individual work dominates; group activities emerge upon project initiation or in its final stage, or during sharing
327
Habil. Palmira Juceviciene and Vyda Mozuriuniene experiences and helping each other overcome challenges. Organization’s level, however, limits itself to the understanding of essential organizational qualities, i.e. mission, vision, philosophy, aims, etc. KNIO is needed equally on all levels: individual, group, and organization. More than 2/3 of the informants have answered they need KNIO from 11 to 20 percent.
4.2 What kind of knowledge is possessed and enhanced by employees? The majority of informants in all the three subsidiaries have claimed the possession of 51 to 100 percent of knowledge, needed for knowing the important for an organization (KIO) (see Table 2). Answers on enhancing this knowledge have varied. Over 2/3 of Lithuanian employees enhance this knowledge ‘on average’, whereas the majority of Latvians and Estonians – ‘considerably’ and ‘highly’ (see Table 3). On the level of group knowledge, the majority of Lithuanian and Latvian employees have assessed themselves as possessing 26 to 75 percent of knowledge, needed for KIO, and Estonians have claimed to have 51 to 100 percent (see Table 2). Over 2/3 of informants suppose, they enhance this knowledge ‘on average’ or ‘considerably’ (Table 3). Regarding KIO possessed on the organization’s level, the distribution of opinions in the three subsidiaries has been uneven. The Lithuanian and Estonian majority agree having 51 to 100 percent of all the necessary knowledge whereas Latvians consider having 26 to 75 percent of it (Table 2). Again, the majority of all the three subsidiaries suppose, they enhance the necessary knowledge ‘on average‘ or ‘considerably‘ (see Table 3). Table 2: Employees’ possessed knowledge (%) in organization’s knowing structure (at the subsidiaries situated in the Baltics) Type of knowledge
Knowledge on individual level Organization knowing Collective knowledge on important group level for organization (KIO) Collective knowledge on organization level
Knowledge on individual level Organization knowing Collective knowledge on not important group level for organization (KNIO) Collective knowledge on organization level
Country
Possessed knowledge (percent ratio) 1-25%
26-50%
51-75%
76-100%
LT
3,4
13,8
41,4
41,4
LV
0,0
18,8
53,1
28,1
EE
0,0
9,4
37,5
53,1
LT
10,7
25,0
42,9
21,4
LV
15,6
37,5
28,1
18,8
EE
0,0
21,9
53,1
25,0
LT
13,8
27,6
27,6
31,0
LV
12,5
15,6
62,5
9,4
EE
3,1
21,9
40,6
34,4
LT
24,1
31,0
34,5
6,9
LV
15,6
31,3
46,9
6,3
EE
15,6
31,3
43,8
9,4
LT
34,5
20,7
31,0
10,3
LV
15,6
37,5
28,1
18,8
EE
21,9
28,1
40,6
9,4
LT
37,9
24,1
31,0
6,9
LV
15,6
34,4
46,9
3,1
EE
21,9
56,3
21,9
0,0
In the KNIO context, the opinion of all subsidiary employees has been more solidified, considering all the three levels of the knowledge possessed. The majority of informants claim having 26 to 75 percent of this knowledge. Nevertheless, Lithuanian employees claim possessing 1 to 50 percent of the knowledge on the group and organizational levels (Table 2). Respondents of all the three countries have estimated enhancing the necessary knowledge almost evenly. They think, they do this ‘little’ or ‘on average’. As exceptions, Latvian
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Habil. Palmira Juceviciene and Vyda Mozuriuniene employees on individual and organization’s levels and Estonian employees on a group level refer to ‘considerable’ enhancing (see Table 3). Comparably, the tendency is obvious for KIO and KNIO on all the three levels: employees reflect possessing more knowing ‚important‘ for an organization than ‚not important‘. Likewise, they admit enhancing KIO more than KNIO. Table 3: Employees’ enhanced knowledge in organization’s knowing structure (at the subsidiaries situated in the Baltics) Type of knowledge
Country
Knowledge on individual level Organization knowing important for organization (KIO)
Collective knowledge on group level
Collective knowledge on organization level*
Knowledge on individual level*** Organization knowing not important for organization (KNIO)
Collective knowledge on group level***
Collective knowledge on organization level***
Knowledge enhancement structure (percent ratio) Little
Average
Considerable
High
LT
6,9
31,0
44,8
17,2
LV
0,0
25,8
48,4
25,8
EE
6,3
12,5
59,4
21,9
LT
10,7
42,9
39,3
7,1
LV
3,2
45,2
41,9
9,7
EE
0,0
31,3
56,3
12,5
LT
13,8
48,3
24,1
10,3
LV
6,5
38,7
38,7
16,1
EE
6,3
28,1
46,9
18,8
LT
44,8
27,6
13,8
3,4
LV
9,7
41,9
41,9
6,5
EE
28,1
37,5
25,0
9,4
LT
41,4
27,6
6,9
3,4
LV
29,0
45,2
16,1
9,7
EE
18,8
40,6
31,3
9,4
LT
31,0
31,0
10,3
0,0
LV
13,3
46,7
33,3
6,7
EE
40,6
37,5
21,9
0,0
* - p<0,1; *** - p<0,001 It should be noted that the researchers of cross-organizational informal knowledge (Lawson et al, 2009) and the investigators of informal R&D knowledge networks (James, James, and Gamlen, 2007) specifically underscore the importance of the informal knowledge. The management of the subsidiaries should note the fact that organizations possess more knowledge than they consider present; moreover, this knowledge does make influence upon organizations’ performance. Nonrecognition of this knowledge leverages insufficient employee motivation which may possibly result in the devaluation of informal knowledge importance, even though the employees would have detected this knowledge applied in their jobs. This possible threat might be confirmed or refuted by finding out which knowledge, explicit of tacit, enters the organization explicitly as a result of the enhanced knowledge by employees. If, as a result , a considerable difference appears between the enhanced KIO and KNIO (explicit knowledge would be the effect of the enhanced KIO, and tacit knowledge would result from the enhanced KNIO), then, research would be able to conclude that organizations, not recognizing the informal part of their knowing (KNIO), lose the possibility to acknowledge and store a part of the knowledge, influential for its successful performance. As Table 4 shows, employees of the three subsidiaries acquaint their organizations, in part or completely, with their enhanced KIO on all the levels. However, having enhanced KNIO, they reveal it ‘little’ (‘,,,is little known to others’) or ‘partially’. A significant part of Lithuanian employees (31,0 and 42,9 percent respectively) do nor
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Habil. Palmira Juceviciene and Vyda Mozuriuniene reveal this knowledge at all. A part of Estonians (31,3 percent) keep the enhanced organizational formal knowledge to themselves. Research results have supported the assumption that an organization may lose a part of its knowledge and, consequently, competitiveness, if it is not sensitive to all – formal and informal - knowledge that exists at an organization. According to Chini (2004), an organization is a separate unit of unique resources, mastery, skills, and knowledge, deserves attention. To a large part, KNIO does provide this uniqueness, making organization’s knowledge hard to copy and, thus, triggering organization’s competitiveness. Table 4: Explicity of the employee enhanced knowledge (at the subsidiaries situated in the Baltics) Gained knowledge explicitly (percent ratio) Type of knowledge
Knowledge constructed on individual level Organization knowing important for organization (KIO)
Knowledge constructed on group level Knowledge constructed on organization level Knowledge constructed on individual level
Organization knowing not important for organization (KNIO)
Knowledge constructed on group level Knowledge constructed on organization level
Country
Is known only to oneself
Is little Is partially known to known to others others
Is completely known to others
LT
10,7
21,4
35,7
32,1
LV
0,0
6,3
56,3
37,5
EE
3,1
6,3
75,0
15,6
LT
14,3
10,7
50,0
25,0
LV
9,4
21,9
40,6
28,1
EE
3,1
25,0
50,0
21,9
LT
10,7
21,4
50,0
17,9
LV
3,1
18,8
50,0
28,1
EE
3,1
21,9
43,8
31,3
LT
31,0
13,8
41,4
13,8
LV
3,1
46,9
43,8
6,3
EE
21,9
40,6
31,3
6,3
LT
42,9
17,9
32,1
7,1
LV
9,4
46,9
43,8
0,0
EE
9,4
53,1
25,0
12,5
LT
46,4
14,3
32,1
7,1
LV
18,8
46,9
34,4
0,0
EE
31,3
40,6
15,6
12,5
4.3 Is the factor of the country of company location significant for the structural parts of organization’s knowing? Statistical data analysis with the Kruskal Wallis Test has enabled the identification of statistically significant differences in the knowledge, required for employee performance, among the surveyed subsidiaries (Table 1): a) in the case of KIO, (p<0,1) on a group level; b) KNIO - (p<0,01) on individual and (p<0,1) on organizational levels. No statistically significant differences have been observed among the countries by analyzing the knowledge possessed by the employees of subsidiaries, according to the Kruskal Wallis Test (Table 2). However, considerable significant differences have been noted among the subsidiary employees comparing their enhanced knowledge in the case of KNIO on all the three levels: individual, group, and organization, (p<0.01 for all levels). A minor statistically significant difference (p<0,1) has been observed among the employees of the Baltics considering their enhanced knowledge in the case of KIO (see Table 3). No statistically significant difference has been observed when employees’ enhanced knowledge remains tacit or becomes explicit (Table 4). Thus, in spite of the fact that some general tendencies in the organization‘s knowing structure have been identified, some differences among the countries have also been observed, especially in the case of KNIO. Informal knowledge is needed when meeting the challenges that can vary from country to country. However,
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Habil. Palmira Juceviciene and Vyda Mozuriuniene the discrepancies among the countries, concerning KIO, have been insignificant or undistinguished at all. This could be explained by the fact that all the informants are employed at subsidiaries within the same multinational company. According to Macharzina, Oesterle and Brodel (2001), the headquarters greatly influence the performance of subsidiaries, provide them with the necessary knowledge and, thus, determine similar knowing ‘important‘ for an organization. However, further research is required for finding out if general organization‘s knowing tendencies also occur upon the investigation of completely unrelated companies.
5. Conclusions Organization’s knowing structurally consists of two parts: a) knowing important for an organization (organizational knowing), recognized and encouraged by it; b) knowing not-important for an organization (informal knowing), existing at an organization and formally not considered by the organization as significant for its performance; it is mainly formed during informal learning processes. Each part of organization’s knowing usually has explicit and tacit knowledge on an individual, group, and entire organization’s level. Upon the investigation of subsidiaries, the following organization’s knowing peculiarities have been revealed. All the subsidiaries under investigation have demonstrated the domination of the knowing important for an organization, as opposed to the knowing not important for an organization (informal knowing); individual knowledge has appeared dominant, as opposed to the entire group or organization’s knowledge; explicit knowledge has been found dominating, as opposed to tacit knowledge. Informal knowing is not overbearing, but can be essential and, in some cases, crucial. However, employees enhance this knowledge less than the knowledge important for an organization, possibly, due to insufficient motivation of organizations. Employees’ enhanced informal knowledge remains tacit whereas the enhanced knowledge ‘important’ for an organization tends to turn explicit. The knowing important for an organization has not revealed statistically significant differences across the surveyed countries. On the contrary, the knowing not important for an organization has shown statistically significant differences, especially on an individual level. Considerably significant differences have been noted among the surveyed countries comparing employees’ enhanced knowledge in the case of KNIO on all the three levels: individual, group, and organization. An organization, not recognizing the informal part of its knowing (KNIO), loses the possibility to acknowledge and store for the future a part of the knowledge, influential for its successful performance. Managers should discuss possibilities of encouraging employees and their groups or teams to use and increase informal knowledge, when performing in the workplace.
References Bennet, A. (2002) “Knowing: the Art of War, In Educational innovation in economics and business VII, In Bentzen-Bilkvist, A., Gijselaers, W., Milter, R.G. (eds)”, Educating knowledge workers for Corporate Leadership, Kluwer Academic Publishers, Dordrecht, pp 197-218. Bougon, M.W., Karl, E., Binkhorst, D. (1997) “Cognition in organizations: an analysis of the Utrecht Jazz Orchestra”, Administrative Science Quarterly, No. 22, pp 606-639. Chini, T.C. (2004) Effective knowledge transfer in multinational corporations, Palgrave Macmillan, Hampshire, New York. Choo, C.W. (2002) The Knowing Organization, Oxford University Press, New York, Oxford. James, A., James, A.D. and Gamlen, P. (2007) “Formal versus informal knowledge networks in R&D: a case study using social network analysis”, R&D Management, Vol 37, No. 3, pp 179-196. Johnson, W.H.A. (2007) “Mechanisms of tacit knowing: pattern recognition and synthesis”, Journal of Knowledge Management, Vol 11, No. 4, pp 123-139. Juceviciene, P. (2007) Besimokantis miestas, Technologija, Kaunas. Juceviciene, P. and Mozuriuniene, V. (2009) “The relationship between organization‘s knowing and organization‘s knowledge: the boundaries of recognition and formalization”, Economics and Management, No. 14, pp 1129-1139. Juceviciene, P. and Mozuriuniene, V. (2011) “Organization’s Knowing or Organizational Knowing?” Proceedings of the 8th International Conference on Intellectual management, knowledge capital etc., Academic Conferences Limited, 2011. Lawson, B. et al (2009) “Knowledge Sharing in Interorganizational Product Development Teams: The Effect of Formal and Informal Socialization Mechanisms”, Product innovation Management, No. 26, pp 156-172.
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Habil. Palmira Juceviciene and Vyda Mozuriuniene Leonard, D. and Sensiper, S. (1998) “The role of tacit knowledge in group innovation”, California Management Review, Vol 40, No. 3, pp 112-132. Macharzina, K., Oesterle, M. J. and Brodel, D. (2001). “Learning in Multinationals”, Handbook of Organizational Learning & Knowledge, Oxford University Press, New York, pp 631-656. Nonaka, I. (1994) “A dynamic theory of organizational knowledge creation”, Organization science, Vol 5, No. 1, pp 14-37. Nonaka, I. and Konno, N. (1998) “The concept of 'Ba': building a foundation for knowledge creation”, California Management Review, Vol 40, No. 3, pp 40-54. Nonaka, I., Toyama, R. and Byosiere, P. (2001) “A theory of organizational knowledge creation: understanding the dynamic process of creating knowledge, In Dierkes, M., Antal-Berthoin, A., Child, J., Nonaka, I. (eds)”, Handbook of Organizational Learning and Knowledge Creation, Oxford University Press, New York, pp 491-517. Polanyj, M. (1962) Personal Knowledge, University of Chicago Press, Chicago. Stankeviciutė, J. (2002) Methodology of the Enhancing of Organization’s Knowing, Doctoral dissertation, Kaunas University of Technology, Kaunas. Tsoukas, H. (2006) Complex knowledge: studies in organizational epistemology, Oxford University Press, New York.
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The Dimension of Smart Specialisation in the Business System Robertas Jucevicius and Aukse Galbuogiene Kaunas University of Technology, Kaunas, Lithuania robertas.jucevicius@ktu.lt aukse.galbuogiene@stud.ktu.lt
Abstract: The Smart Specialisation topic is expected to be one of important priorities for scholars from different fields of research. The underlying rationale behind the Smart Specialisation concept is that by concentrating knowledge resources and linking them to a limited number of priority economic activities, countries and regions can become competitive in the global economy. This type of specialisation allows regions to take advantage of scale, scope and spillovers in knowledge production and use. Smart specialisation is about combining knowledge and innovation with specific strengths of the national or regional economy. In short, it is about generating unique assets and capabilities based on the region's distinctive industry structures and knowledge bases. The core idea of smart specialization is designing economic strategies that are location – specific and built on existing strengths such as quality of the business environment, composition of economic activities (Ketels, 2012). Entrepreneurship plays an important role in achieving targeted results. Entrepreneurial knowledge involves much more than science and technology. It combines and relates this to knowledge of market growth potential, business partners, competitors and the entire set of input and services required for business development. The synthesis and integration of fragmented knowledge should help to create a vision for opportunities in existing or new sectors. This type of knowledge needs to be activated and supported as the main ingredient in a process of smart specialisation. Understanding and employing the concept of a business system is very important in that case. The business systems approach is central to understanding the interaction among organizations, national contexts and international flows of capital, technology and knowledge and international rule systems for coordinating these flows. This stream of research examines how different institutions affect the strategy, structure, the organization of firms (Morgan, 2007, 2011). The business system could be understood as the way that different institutions, organizations or other structures of the state, the region or a particular industry are integrated into a social configuration of value creation processes. The core idea and the main objective of the article is to discuss the interplay between two concepts – Business systems and Smart specialisation trying to reveal the most important dimensions of the smartness in a particular business system. Keywords: Business system, smart specialization, knowledge, development, value creation, smartness
1. Introduction The concept of the Business System was first proposed by Foray, David and Hall (2009). However, they were focussing mainly on differences in R&D intensity in explaining growth differentials and especially on transatlantic differences. Later that concept has been expanded but still it is mainly about the development of innovation policy as the key tool for the economic and social development. The above-mentioned priorities can be applicable to any region striving for success. However, the adequate business system - national or regional has to be in place. Fragmented initiatives and achievements are of little value and they hardly can make a radical difference. The concept of the Business system firstly proposed by Whitley (1992) and later developed by other authors (Foss, 1997; Lundvall, 2002; Sorge, 2005; Redding, 2005, Crossland and Hambrick, 2007; Sluyterman, 2010; Valiukonyte, 2005, 2006, 2008, 2009, etc.) has a huge potential to be a conceptual platform combining the developmental objectives and approaches into a logical system. However, even if different theoretical approaches explaining the nature of the Business system could be found in scientific literature, the phenomenon still remains controversial and is understood by the authors differently. Due to the novelty of the concept of smart specialisation it is hard to find authors discussing the phenomenon of smartness of the business system. This article is one of the first attempts to make a bridge between those two concepts. The article consists of three parts. The first part is devoted to explaining the essence of the business system. Different approaches and interpretations of smart specialisation are discussed in the second part of the article. Finally, the attempt to reveal some key dimensions of the smart business system is presented in the third part.
2. Understanding the Business System Importance of business systems as a critical element of any competitive economy is stressed by Whitley (since 1992), Morgan (2007, 2011), Sluyterman (2010) and others. In the 1990s, ‘the business systems approach broke with the still dominant universalistic and contingency models of organizations’ which emphasized issues
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Robertas Jucevicius and Aukse Galbuogiene of size, technology and market structure as determinants of organization structure and strategy (see Morgan, 2007). Few could argue that self-adjusting market mechanisms are probably the most efficient as far as the use of economic resources is concerned. However, there are a number of arguments that markets are not always ideal mechanisms for coordinating transactions among businesses especially in industries with very complex technologies (Campbell et al. 1991; Hollingsworth, Schmitter, Streeck, 1994; etc.). Of course, the size and the structure of national economy as well as the national context play an important role in establishing coordinating mechanisms. For example, it is difficult to expect the French system of production to be applicable in the UK or Scandinavian contexts. From that perspective the business system concept comes into some contradiction with the liberal approach concerning the coordination mechanisms in the economy. Traditional economics usually relies on more or less universal models of economic organization with the possible patterns of economic efficiency. Economic literature shows that in this context institutions, diametrically oppositely, are seen merely as side-constrains and almost always are completely neglected. The similar position emerges when we talk about interorganisational cooperation and collaboration because in traditional economic understanding economic system is based on competition, not cooperation. However, there are no universal models of economic organization. Lilja (2005) makes a perception that after the rapid jump of Japanese companies into the global economic arena in 1980s, the dominant typical Anglo-American models were not the only ways to take leading positions in a market anymore. In result, this has forced researches in management (in a line with other disciplines, e.g. economic sociology, business history or geopolitical economics) to consider the companies and their management from the systemic positions by taking into account contextual environment, unfolding country’s historical, socio-cultural, institutional or geopolitical position which transforms existing economic mechanisms to unique period-specific paths. As the scientific concept and research problem a business system involves quite different issues and approaches. It would be difficult to distinguish one dominating concept. Most common generalised approaches for understanding particular socio-economic business organization as well as inter-organisational integration are paradigms, such as ‘country’s competitiveness’, ‘varieties of capitalism’, ‘divergent (managerial) capitalism’, ‘path dependency and institutional change’, ‘social systems’, ‘institutional complementarities’, ‘regional institutionalisations’, etc. (Valiukonyte, 2008, 2009). The wide discourse of different collaborative concepts could be found in scientific literature as well. They are ‘national or regional innovation systems’, ‘clusters’, ‘social systems of production’, ‘innovative milieu’, etc. All business systems in different countries or regions are always different and unique is because different institutional contexts make the problem of developing a common definition of the business system even more complicated. Some definitions and understandings of the concept of business system can be discussed. Whitley (1992) describes a business system as the sum of the general practices and values that characterise both the internal organisation of business units and their relations with their external environment. He defines business systems as distinct patterns of successfully organized economic activities in a market economy. These patterns emerge from, and are effective within, specific institutional environments. According to Whitley, business systems develop within a distinct institutional context that depends on intangible elements, such as knowledge, trust, loyalty, cooperation, shared attitudes toward authority, risk, and innovation, but the intangible elements assume concrete form in political and legal systems, the capital market, the state’s role, the structure of the labour market, and education (Whitley, 1992). According to his traditional sociological definition, ‘business systems’ are, first of all, national-level constructs and can be characterized as ‘distinctive configurations of hierarchy-market relations which become institutionalized as relatively successful ways of organising economic activities in different institutional environments’. Whitley argues that various structural variations and interactions in terms of social, political, economic systems, culture and history, and the dominance of different economic sectors produce distinctive forms of national business systems. In his later definition, Whitley (2000) defines business system as a set of interlocking structures and institutions in different spheres of economic and social life which are interconnected to create a distinct pattern of organising economic activity at local or national boundaries. He seeks to understand how distinctive patterns of economic organization become established and effective in different societies and how they change in the relation to their institutional contexts. He points out that business systems approach is ‘a comparative analysis of ways of organising economic activities, more than the cross-national study of micro-
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Robertas Jucevicius and Aukse Galbuogiene organisational phenomena’, but still he maintains the position that variations in market organisation among institutional contexts have important implications for the nature of firms and their internal organization. The institutional dimension of the business system and its predetermining role on its nature is quite strongly emphasised by most other authors, for example, Pedersen and McCormick (1999). According to Hollingsworth (2003), the nation's financial markets, educational system, industrial relations system, and other socio-political factors influence sectorial and national economic performance. In order to understand how and why society's economy performs, it is necessary to understand its entire social system of production (Hollingsworth, Boyer, 1997:266; Hollingsworth, 2003). Lane (1992) generalises business systems as the sum of general practices and value orientations which characterise both the internal organisation of business units and their relations with their external environment. He also confirms that business systems are long-term configurations, and ‘receive their distinctive character at a very early stage of the industrialisation process’ (following Whiltey’s case study of Asian business systems) but develop and adapt over time in response to broader economic and technological challenges as well as social and political pressures. Crossland and Hambrick (2007) use the term of national systems, which are described as the complex milieu of interrelated social and economic factors, or institutions that characterize the nation state, within which a firm is principally located. The main factors can be national values, corporate governance practices, legal systems, government regulations, etc. According to these notions, national business systems, as a study object, here are taken as a national economic system, too, and it demonstrates the dominant form of organization and coordination of economic activities in macro, i.e. national and regional, levels. Some authors emphasize different, more ‘soft’ aspects of the business system. For example, Redding (2005) states that culture together with national identity, social values, authority ‘underlie institutions, and institutions underlie the business system’. For this reason most societies do not contain a single business system in terms of standardising their organisational options into one format. Redding (2005) proposes the theoretical model in which culture and societies as such play a crucial role in the business system nature (Fig.1) It could be seen that formal institutions do not play a crucial role in the business system, as understood by Redding. Domination of soft, intangible aspects, implicit knowledge makes formalisation of such a system rather complicated. However, it would be difficult to disagree on their importance. At the same time such an approach opens a window for almost unlimited possibilities to develop the unique system based on a variety of distinctive competences and hard to imitate knowledge. It is a very good ground for employing smart specialisation as the key tool for competitiveness. This will be discussed in the next part of the article. While finalising the discussion about the nature of business systems, some generalisations can be made. First, the business system can be understood as the way that different institutions, organizations or other structures of the state, the region or a particular industry are integrated into a social configuration of the value creation processes. A set of interrelations among buyers and suppliers, business companies and training institutions as well as administrative bodies and the whole range of other relations should be counted. Such a system develops its own culture, vocabulary and ethics. Second, the term business system refers to the way a single company or all social and economic actors located in a certain region or industry conduct their business. There are three most important dimensions of any business system: organizational structure, organizational processes and organizational culture. Those three dimensions play an important role the way any company or business system enters into relationship with external partners while acquiring intellectual resources and knowledge. Third, the concept of a national business system serves as a framework for comparing and contrasting different ways of organising economic activities, and, contrary to the national innovation systems (where the main target is set on creating innovations and sharing knowledge), are used to describe socially embedded relationships for creating a general supportive environment for successful firms.
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Robertas Jucevicius and Aukse Galbuogiene
OWNERSHIP
NETWORKS
MANAGEMENT
Structures and systems for coordinating economic behavior and exchange.
The shaping of patterns of economic
MATERIAL LOGIC Impact of costs and technology on features and the interaction of features
CAPITAL
The evolution and growth
HUMAN CAPITAL
SOCIAL CAPITAL
Institutions: the humanly devised constrains that shape social interaction and provide a hospitable environment for cooperative solutions to complex exchange. Forms or order The adjustment of values and norms by experience
The conditioning of institutions by values and norms
RATIONALE
IDEATIONAL LOGIC (EXTERNAL) Impact of external ideas, norms, values on features and the interaction of features
IDENTITY
AUTHORITY
Culture: values, norms and socially constructed realities which act as the bases for the society's forms of order
Figure.1: The nature of business system (Redding, 2005).
3. Why should we talk about smart specialisation of business systems? The competitiveness of the business system at any level – national, regional, local or sector – depends mainly on a limited number of factors. Probably the most important factors are the ability to concentrate limited resources and first of all – knowledge resources and how to link them with a limited number of activities. It means finding the most appropriate specialisation of the business system. It is about positioning such a system in the global economy (Foray, David, Hall, 2009, 2011). According to Foray, David, Hall (2011), the first authors, who developed the concept of smart specialisation, state that ‘smart specialisation must not be associated with a strategy of the simple industrial specialisation of a particular region; smart specialisation is a process addressing the missing or weak relations among R&D and innovation resources and activities, on the one hand, and the sectorial structure of the economy, on the other”. Specifically, Foray, David, Hall (2011) state that the idea of smart specialisation has two facets in fact:
First, it is important to focus on certain domains in order to realise the potential for scale, scope and spill overs in knowledge production and use as these are important drivers of productivity in the domain of R&D and other innovation-related activities;
Second, it is important to focus on certain domains in order to develop distinctive and original areas of specialisation for the future.
Smart specialisation does not mean development based on fundamentally new knowledge. It is even not so much about creating new knowledge. It is rather more about innovation. The question is on which R&D and innovation activities the regional or national business system can be best developed. Smart specialisation means identifying unique characteristics and assets of each country and region, highlighting each region’s competitive advantages, and rallying regional stakeholders and resources around an excellence-driven vision of their future. It also means strengthening regional innovation systems, maximising knowledge flows and
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Robertas Jucevicius and Aukse Galbuogiene spreading the benefits of innovation throughout the entire regional economy (Guide to Research and Innovation Strategies for Smart Specialisation (RIS 3), 2012). The smart specialisation concept is important for both leading regions and for followers. However, the backbone, the axis of their development will be different. The frontiers are able to accumulate bigger resources, have better developed research and economic infrastructure – both hard and soft. At the same time less developed regions often have only limited resources and they rely on possibilities to attract and explore external resources. However, the ability to use external knowledge resources depends considerably on the existing knowledge base, its composition and research infrastructure. This is very much about the absorptive capacity of knowledge and networking capacity. It would not be promising to expect that those regions should radically change the investment policy towards increasing the intensity of creation of knowledge, higher education, public and private R&D, etc. Of course, such investments are very important and necessary but there always is a question about the outcome of such investments. It is especially true when the strategy of development of specialised fields of knowledge and competence is applied. This requires quite substantial investments that are not always attainable. And selection of the field of narrow specialisation is always quite risky. Regions cannot achieve everything in science technology and innovation, and, therefore, it is crucial to follow a thoughtful process of prioritisation, concentrating resources in certain domains of expertise based on the needs and available resources of each region (Ortega – Argiles, 2012) David, Foray and Hall (2009) use a very good example of General Purpose Technologies (GPTs) while explaining the core idea of Smart specialisation. According to them, major innovations often result from the commercialisation of the core GPT invention; there are myriads of economically important innovations that result from the co-invention of applications. Such applications drastically extend the market not only for other co-inventions but also to the core inventions by overcoming the gaps in the stages of the life cycle of technologies and new products. The market demand becomes much more diversified as well as the regions possessing specific competences and resources. This is exactly the idea of the European Union while developing the Platform for Smart Specialisation at the core of the Cohesion Policy 2014 - 2020. Cohesion policy 2014 – 2020, one in a series highlighting key elements of the future approach, has named that smart specialisation means identifying the unique characteristics and assets of each country and region, highlighting each region’s competitive advantages, and rallying regional stakeholders and resources around an excellence-driven vision of their future; it also means strengthening regional innovation systems, maximising knowledge flows and spreading the benefits of innovation throughout the entire regional economy (Cohesion Policy 2014 – 2020). Giannitsis and Krager (2009) state that the concept of smart specialisation and, in general, smart policies is attractive but has various practical difficulties; it assumes that we have criteria to judge which specialisation is smart and which is not and consequently which targets are smart. The significant aspect that makes a regional research and innovation strategy SMART is the process itself: smart specialisation is specialised diversification, structural change towards knowledge, innovation and creativity-driven growth (Erikson, 2012). Due to the complexity of the phenomenon, smart specialisation topic is expected to be one of the more important priorities for scholars from different fields of research. The term smart is largely used in publications of engineering and technology; however, it has made its way into social sciences only recently. In social sciences, the substance of smart is quite different and more complex compared to technological sciences. It is due to the nature of social systems because it is widely acknowledged that biological and social systems are among the most complex. This is why the scientific analysis of smartness in social systems and the substance of smart development of social systems as a business system, region, city or the state is an important and challenging scientific endeavour per se. Another aspect of the theoretical problem is the positioning of smartness category in social sciences amid other related categories, such as knowledge, knowing, innovativeness and intelligence. Some researchers regard smart development as integration of ICT into everyday life and state functions (Komninos, 2011, 2013; Bailey and Ngwenyama, 2011, etc.) while others emphasize the importance of knowledge management (Garcia, 2007; Yigitcanlaret et al., 2012). Others emphasize the coherence of infrastructure with objectives, the importance of learning, innovation and networks (Allwinkle and Cruickshank, 2011; Kuk and Janssen, 2011). It may not seem the important issue for practitioners but for researchers it is very much so. Without clear understanding of the nature and complexity of the phenomenon it is hard to expect professional advice in development of such systems.
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An important question is - where the smartness in the business system rests, what are the features of a smart business system? There still is no answer to that question that could build a more or less full set of indicators that could be applied in evaluating the smartness of the system. There still are just a number of different approaches proposed by researchers (Ketels, 2012; Ortega-Argiles 2012; Pen, Dorenbos and Hoogerbruge, 2012; Jhirad, Juech, Michelson, 2009; Foray, David, Hall, 2009, 2011; Mc cann, 2011; Aranguren, Magro and Navarro, 2011, etc.). Some specific features and qualities of smart specialisation of business systems could be discussed.
Relying on intelligence. Specialisation always leads not only to development and employment of key strengths but also may be a cause of failure. A certain level of smartness based on intelligence about the external environment should protect from direct competition. Good understanding of the main advantages as well as key challenges for the competitiveness of a particular business system reflects the quality of intelligence that allows the actors in a particular business system to be aware of what kind of resources could be employed, what strategies applied.
Combination of different assets. This is probably the key dimension of smartness of any social system. The strategy usually is based on key competences and fields of expertise possessed by the company. However, such competences and fields of expertise should not be based on easy to copy traditional areas of specialisation but should be based on innovative combination of different resources and capabilities. It is not so difficult to employ a set of strengths. However, to combine strengths with weaknesses while developing a new quality or ability to employ competing or even opposing concepts and directions requires a different level of strategic thinking. Creating innovative business models would be important.
Diversity of actors. A variety of different stakeholders representing business, academia, governmental institutions, and creative industries should be involved in strategy development. This is important not only because of the very nature of the business system but also because it opens a window for finding ways to combine different resources and approaches in development of innovative business models and sustainable advantage. Diversity of actors of the business system opens a window for innovation, better understanding the value expected by the market, allows building set of qualities hard to copy.
Networking – external and internal. The business system is a social system in its nature and this requires being dynamic and open. Otherwise the life span of the system very likely is going to be short. Clusters and competence networks are the backbone of the business system. Both individual and organisational competence networks are of the same importance because they serve as a source and channel of a variety of external resources. This allows development of a variety in areas of specialisation inside the business system and better combination of resources.
Contextuality. Most of business systems are based on location-specific strengths and are well integrated into the regional context. This principle is actual even if the system extensively employs the possibilities created by the IT. Every business system is target, place and resources specific.
Integrity. Every business system as well as every company faces the dilemma: to be a part or just a source for others in the value chain. The activities in the business system, its outcomes and strategies for the future development explicitly should indicate good integration and position in the value chain or at least it should be an explicit target. Otherwise it would be difficult to call such business system as possessing qualities of smartness.
Diversity of resources. Possessing and employing of the variety of different resources – material, financial, intellectual are one of preconditions for smart specialisation in the business system. Their wide use at different levels - regional, national, international - should be an explicit feature of the strategy. Transforming resources into technological, social and business innovations is important.
Those are only few qualities of smart business systems. Such qualities and the whole concept of smart business system require further investigation. The format of the paper does not allow discussing such qualities deeper and it remains for the future. There is little doubt that this topic will be one of priorities in the nearest future for a number of researches. The European Union Policy towards development of smart specialisation of the regions will stimulate such research.
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4. Conclusions The concept of business system is a systemic tool that is able to explain the anatomy of achieving the competitive advantage. Such elements as structure and systems of value creation, processes of interaction of different actors in value creation processes and the specific culture that is always an important factor in any socio – economic system are the key elements of any business system. The concept is applicable on different levels – regional, sectoral or national. The competitiveness of the business system is predetermined by its ability to focus on key competences and explore them in the most effective way. The concept of smart specialisation serves as a conceptual framework for grounding the strategy for the development of the business system in this way. Even if the concept of smart specialisation is rather new and still needs further development, a number of key qualities of a smart business system are already proposed.
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Robertas Jucevicius and Aukse Galbuogiene Komninos, N. (2011) “Intelligent Cities: Variable geometries of spatial intelligence”, Journal of Intelligent Buildings International, No. 3, pp. 1-17. Komninos, N., Schaffers, H. (ed.) (2013) “Smart Cities and the Future Internet in Europe”, Journal of the Knowledge Economy, Vol 3, No 3, pp. 119-134. Kuk, G., Janssen, M. (2011) “The Business Models and Information Architectures of Smart Cities”, Journal of Urban Technology, Vol 18, No. 2, pp. 39- 52. Lane, C. (1992) “European Business Systems: Britain and Germany compared”, in Whitley, R. (ed.), European Business Systems: Firms and Markets in Their National Contexts, London. Lilja, K. (2005) The National Business System in Finland: Structure, Actors and Change, Helsinki School of Econimics: HSE Print. Lundvall, B., A., Johnson, B., Andersen, E. and Dalum, B. (2002) “National Systems of Production, Innovation and Competence-building”, Research Policy, Vol 31, No. 2, pp. 213-231. Mc Cann, P. (2011) “Notes on the Major Practical Elements of Commencing the Design of an Integrated and Territorial Place Based Approach to Cohesion Policy”, Economic Geography Working Paper June 2011, Faculty of Spatial Sciences, University of Groningen. Mc Cann, P. (2012) “Smart specialization as Regional Policy.How to make it work?” Paper presentet at Conference: Regions for Economic Change. Transforming Regional Economies: “The Power of Research and Innovation Strategies for Smart Specialisation”, Brussels, 12 June, 2012. Morgan, D. (2007). National business systems research: progress and prospects. Scandinavian Journal of Management, No. 23, pp. 127-145. Morgan, G. (2011) “Reflections on the macro-politics of micro-politics”, in Dorrenbacher, C. and Geppert, M. (Eds), Politics and Power in the Multinational Corporation: The Role of Institutions, Interests and Identities, Cambridge University Press, Cambridge. OEDC, Innovation in science, technology and industry, What is smart specialisation?, [online], http://www.oecd.org/sti/inno/smartspecialisation.htm Ortega – Argiles, R. (2012) “Economic Transformation Strategies Smart Specialisation Case Studies”, University of Groningen, January 2012, [online], http://s3platform.jrc.ec.europa.eu/c/document_library/get_file?uuid=1f05532a9ab5-4324-8eeb-4acb7b72e17f&groupId=10157 Pedersen, P. O., McCormic, D. (1999) “African Business Systems in a Globalising World”, The Journal of Modern African Studies, Vol 37, No. 1, pp. 109-135. Pen, C., J.; Dorenbos, R., Hoogerbrugge, M. (2012) “A Strategic Knowledge and Research Agenda on Economic Vitality of European Metropolitan Areas - Towards a Smart Specialisation Strategy“, European Metropolitan network Institute, September, 2012. Redding, G. (2005) The Thick Description and Comparicon of Societal Systems of Capitalism, Journal of international business studies, No. 36, pp.123-155. Sluyterman, K. (2010) “Changing Business Systems in the Twentieth Century: The Case of the Netherlands”, Business History Review, Vol 84, No. 4, pp. 737-750. Sorge, A. (2005) The Global and the Local: Understanding the Dialectics of Business Systems, Oxford University Press, Oxford. Valiukonytė, D. (2009) “Overlapped or complementary? Multi-disciplinary approach to the concept of National Business Systems“, Interdisciplinary discourse in social sciences 2. Valiukonyte, D., Parkkonen, V. (2006) “Theoretical insights into the notion of business systems and its relation to other concepts of collaboration”, Socialiniai mokslai - Social Science, Vol 4, No. 54, pp. 20-31. Valiukonyte, D., Parkkonen, V. (2008) “Conceptual framework for the analysis of business systems: national perspective”, Economics and management – 2008, No 13, pp. 729-738. Valiukonytė, D., Parkkonen, V. (2006) “Theoretical insights into the notion of business systems and its relation to other concepts of collaboration“, Social Sciences = Socialiniai mokslai, Kaunas University of Technology, Vol 4, No 54, pp. 20-31. Valiukonytė, D., Zabotkaitė, V. (2005) “Business systems: national, institutional and cultural contexts“, Social Sciences = Socialiniai mokslai, Kaunas University of Technology, Vol. 2, No. 48, pp. 29-36. Whitley R. (2000) Divergent Capitalism: The Social Structuring and Change of Business Systems. 2nd ed., New York: Oxford University Press. Whitley, R. (1992) Business Systems in East Asia: Firms, Markets and Societies, London: Sage. Whitley, R. (1992) European Business Systems: Firms and Markets in Their National Contexts, London. Yigitcanlar, T., Metaxiotis, K., Carrillo, F. J. (2012) Building Prosperous Knowledge Cities: Policies, Plans and Metrics, Edward Elgar Publishing. This research was funded by the European Social Fund under the Global Grant measure.
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The Effectiveness of Storytelling in Transferring Different Types of Knowledge Marcela Katuščáková and Martin Katuščák Department of Cultural Heritage and Mediamatics, Faculty of Humanities, University of Žilina, Slovak Republic marcela.katuscakova@mediamatika.sk Abstract: The Information Society has shifted the possibilities in the field of education and brought new methods of using the latest information and knowledge technologies. However, the attention of managers and teachers is once again focused on storytelling as the oldest knowledge transfer method. The practical experiences of many professionals, managers and others working in different areas around the world show that the method has got significant advantages. If properly constructed, stories represent an effective and important knowledge management tool for motivation, persuasion, communication, interpretation and education, as well as sharing tacit knowledge and visualise the invisible. Such knowledge is also lectured at universities, and we often see that stories told are the deepest stored knowledge of a whole course. Therefore, we have decided to use this tool actively in the courses of knowledge management at the Department of Mediamatics and Cultural Heritage. In the first semester, students created the so‐called digital storytelling projects on specialised topics in the field of knowledge management. Frankly, we were surprised by their creative approach. Therefore, we continue in the research into the effectiveness of traditional storytelling in terms of transferring different types of knowledge. We are carrying out research to compare two groups of students. On the one hand, we analyse the effectiveness of the classical knowledge transfer method using lectures supported by PowerPoint presentations (the first group), and, on the other hand, the effectiveness by appropriately constructed story (the second group), while the content of the knowledge transfer is identical. The identical level of knowledge in both groups is ensured with pre‐tests before the lectures. Subsequently, we observe the effectiveness ‐ success rate in post‐tests in both groups. The levels of knowledge transfer are evaluated separately for each type of knowledge ‐ know‐what, know‐how, know‐why, immediately after the lecture and one month later. We assume that there will be a statistically significant difference in the success of knowledge transfer in these two groups. We also assume that the group with classical teaching will be successful in the first test in answering know‐what questions. At the same time, we expect that the group with storytelling will achieve better results in general , as the time of retention of knowledge transferred through storytelling should be longer. We also assume that storytelling is more suitable for transferring know‐how and know‐why. We realise that the results may also be affected by the quality of the story constructed, therefore its creation and presentation will receive great attention. Keywords: storytelling; knowledge management; education, knowledge sharing
1. Introduction In most companies, traditional presentations prevail nowadays, focused on quantities of data and statistical visualisations. The effectiveness of these tools is questioned and in the age of technology, growing customer demands, globalisation and cultural diversity, we are forced to use a more comprehensive and effective tool for knowledge transfer. Many have realised that knowledge cannot be completely abstracted to categorical and analytical forms. Modern organisations look for tools to synthesise rather than analyse (Sole ‐ Wilson, 2002). Stories can work as these tools. Although brain scan research has shown that if one tells a story of and someone else listens actively, their brains are actually starting to synchronise with one another (Stephens ‐ Silbert ‐ Hasson, 2010). Psychologists also provide evidence that the use of storytelling is better at keeping the meaning/purpose in mind than raw data and therefore they recommend this tool as a prevention of information overload (Heeg, 2011). People are not motivated to action by "dumb data" in PowerPoint slides or images full of charts. We know that statistics are modifiable and are often misleading. Our attitudes, concerns, hopes and values are strongly influenced by stories. When we read some dry facts and arguments, we read them on the lookout ‐ ready to "fight", we are critical and sceptical. But when we dive into a story, we dismiss our intellectual guards and let ourselves be drawn inside by emotions and become more defenceless (Gottschall, 2012).
2. Storytelling in organisations An organisation's story can be a detailed history of the management's actions in the past, employee interactions, or other internal or external organisation's events that are communicated informally within the organisation. A story's moral, or implication for action, is usually implied, or explicitly stated (Swap et al., 2001). A story is a good tool to capture all elements of knowledge, and combines both explicit and tacit
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Marcela Katuščáková and Martin Katuščák knowledge, information and emotions. Stories are varied in terms of their typology, depending on the division criteria, for example, according to the purpose, content, simplicity/complexity, and so on. (Denning, 2006) (Brown, 2005) (Snowden, 2005). Storytelling is only as good as the story itself. The narrator's goal is often to be able to recognise stories with an important integral message to bring about an epistemological shift in the listener's mindset and cause a change in the behaviour (Sfard ‐ Prusak, 2005). Knowledge Management focused on knowledge sharing has already been made familiar with the power of storytelling. Many managers have found that the organisation's common official languages (manuals, plans, reports, rules, etc.) are not able to make the invisible visible (Sbarcea ‐ Ward ‐ Bohn, 2001). Researchers have identified a number of examples of use of a story as a management tool, for example, to solve problems (McLellan, 2006), investigate actions, clarify meaning, develop new products, but also for entertainment (Prusak, 2001a). They use it to communicate with a large number of recipients (Prusak, 2001b), for non‐formal education, socialising new members, consolidating relationships (Sole ‐ Wilson, 2002), maintaining an organisation's history (Snowden, 2005), and for other purposes. In general we can state that communication through storytelling is quick, natural, clear, credible, compelling, contextual, intuitive and, especially, activating (Groh, 2001). Although companies shift their focus to knowledge, yet it is its actual application to the company's benefit which is important, and, therefore, storytelling is referred to as a suitable tool to support sharing norms and values, create an atmosphere of trust and commitment, and be able to share some types of tacit knowledge as well (Sole ‐ Wilson, 2002). Monitoring the success of transferring tacit knowledge was performed for example by the Sri Lankan University in the library domain (Wijetunge, 2012), or also by LILA at the Harvard University (Sole ‐ Wilson, 2002). They identified similar strategic models for knowledge sharing in organisations such as modelling (mentoring, apprenticeship, observation possibilities etc.), simulations (case studies, role playing, technology simulation etc.), an organisation's codified resources and so‐called symbolic objects that are combined in real business operations. They developed a summary table which shows the effectiveness of the tools in relation to different types and goals of knowledge sharing. On the basis of this study, the so‐called modelling and simulations were found to be a more suitable instrument for the transfer of tacit knowledge than storytelling. They noted that storytelling is highly effective for rapid transfer of tacit knowledge across a large auditorium, however, as far as experience‐based knowledge is concerned, then the so‐called modelling is preferable (musicians, pilots, surgeons etc.). They also mention situations in which storytelling seems wholly inappropriate (communication of rule‐based knowledge; addressing short‐term objectives under pressure ‐ e.g. landing training in a cockpit, or a rescue team taking care of an injured person (Sole – Wilson, 2002).
2.1 Problems of storytelling Many companies do not realise the true value of a story and consider it a difficult, additional (unnecessary) phase between data analysis and data presentation (Heeg, 2011). It can be viewed as a problem that they are construed from a perspective of one person (where their relevance to others can be questionable), and especially if they are not told in person, but recorded in some way (Sole – Wilson, 2002), (Wijetunge, 2012). Psychologists compare storytelling to the story of the Trojan horse, as people usually take a story because they perceive a good story as a gift. However, in fact it is a system of delivering the narrator's agenda, i.e. the story is a trick used to smuggle a message into a suspicious human mind. Therefore, one should realise, especially in the business sector that a story is a tool which can both help and hurt, just like natural elements. A storytelling master may want us to get drunk with emotions, to let our scepticism go and "make ourselves home" in his or her agenda (Gottschall, 2012). Yet it is true that storytelling is one of the most powerful forms of learning and knowledge sharing. A good story can make people talk about a brand. As stories have got a far‐reaching emotional impact, they can inspire people to change their behaviour in a direction expressed implicitly or explicitly (Heeg, 2011).
3. Using storytelling in schools In the educational context it must be pointed out that a story has got more depth than an example. A story tells about some events, someone particular and something which happened to that person. Stories awaken our minds, our emotions, and lead to the formation of mental images (Green ‐ Brock, 2000). A story provides a framework and context for individuals to easily understand others by giving them the key to his or her own
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Marcela Katuščáková and Martin Katuščák extensive list of adventures and experiences. This makes the listener able to connect and anchor in a meaningful the events of the story set in the narrator's context through personal experience, into the knowledge system. It has been evidenced that knowledge anchored in our minds in such a way penetrates deeper and is more meaningful than it would be achieved through traditional methods of education – through knowledge generalisation. The narrator and the listener are placed on a common cognitive and emotional level that allows the listener to simultaneously link to the narrator and his or her structure of personal knowledge and capture and understand the narrator's perception of the content (Abrahamson, 1998). The actual value of storytelling from the cognitive perspective is that there is a mutual creation involving interaction and understanding between the narrator and the listener. A story used in the classroom should represent a clear and unambiguous illustration of the principles we try to demonstrate. Since the listener has got his or her own interpretation of the story, it is the responsibility of the teacher to ensure that the message (the point) of the story is clear, and that also outline the links between the story and the abstract principles being explained. Attention should be paid especially to first‐year students who may not be able to make the links between the story and their own curriculum themselves, or it may happen that they tend to remember peripheral aspects of the story rather than the main point. Therefore, the story should be composed to be clear and "to the point". Furthermore, if the story is not entirely related to the concept taught, it is better to omit this story because students who interpreted the story incorrectly cannot be penalised for it in tests (Green, 2004). In education, stories serve multiple functions such as:
knowledge sharing,
encouraging curiosity in students (McDonald, 2009),
enliven students' interest in learning,
raise important issues for discussion (Shank, 2006)
support flow of lecture,
make learning content memorable,
stimulate the process of creating meaning,
overcome resistance or fear and establish the relationship between the teacher and the student and among students (Green, 2004),
stimulate imagination,
develop the skills necessary for making decisions (Baldwin ‐ Dudding, 2007),
create lessons to be learned (Hamilton ‐ Weiss, 2007),
in the information age, they act as a humanising element (Baldwin ‐ Dudding, 2007)
Storytelling is used in education to convey different types of knowledge, from history, science, arts, mathematics, economics, management and so on, encourages students to think about things, and creates enthusiasm in them.
3.1 Digital storytelling As stated by the authors of the study (Baldwin ‐ Dudding, 2007), qualitative and quantitative research studies have found that storytelling can really improve students' academic performance. Therefore, we decided to use this tool actively in the Knowledge Management course at the Department of Cultural Heritage and Mediamatics. In the first semester, students dealt with the so‐called digital storytelling on professional topics concerning knowledge management. Digital storytelling is the use of computer tools in order to tell a story. The main idea is to combine the art of storytelling with a set of multimedia. Digital storytelling is a good way to engage students into the two ways (traditional and innovative) of storytelling. Students can learn how to combine multimedia tools with basic skills such as research, writing, presentation, interview, problem‐solving, assessment skills etc. (Barrett, 2005). It is a flexible and adaptable tool, suitable for most purposes which can be used for most areas in education
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Marcela Katuščáková and Martin Katuščák (Signes, 2008). When compared with traditional storytelling, its advantage is also the possibility to share digital stories instantly with rest of the community. Daniel Meadows (2011) defined digital storytelling as “short, personal multimedia tales told from the heart.” Or as “multimedia sonnets from the people in which photographs discover the talkies and the stories told assemble in the ether as pieces of a jigsaw puzzle, a gaggle of invisible histories which, when viewed together, tell the bigger story of our time, the story that defines who we are.“ Our students were instructed to elaborate on the selected topics in the area of Knowledge Management and made attempts to work them out using digital storytelling. Frankly, we were surprised by creative approach of our students. We observed a positive effect on the results of written examinations and positive perceptions from teaching. Therefore, we continue with research on the effectiveness of traditional storytelling in terms of transferring different types of knowledge from the teacher's position.
4. Storytelling research in terms of transferring different types of knowledge We decided to carry out an experiment as part of our quantitative research into storytelling as a tool used in education. Based on several studies conducted, we wanted to test and present to students some results to show a significant difference between students who taught using the classical PowerPoint method, and students who received the same content presented in the form of storytelling. After a long consideration, we chose the subject of Competitive Intelligence (CI) as the lecture's topic. Due to the relatively limited options, we created a selection consisting of two groups with randomly assigned members (alphabetically) of our undergraduate students in the second year. The number of participating students was 30 (15 + 15). In both groups the conditions for achieving objective results were met such as the same school, the same teacher, subject, and time range. The presentations were given on the same day, we started with the test group, followed by the control group. To ensure uniformity of the level of knowledge in the test group and the control group, we organised a pre‐ test before the testing for which we had expected similar, i.e. almost no knowledge, in both groups. The students were given a pre‐test with 6 questions about CI. In total, students were examined 3 times using the same questions. The first test, as we mentioned, was the pre‐test to indicate the level of knowledge in both groups before the testing, the second test was given immediately after the lecture, and the last, third test was given after a time delay of three weeks. In all cases, the students were given the same time of 15 minutes to complete all 6 questions.
4.1 Test preparation In the beginning, we chose the CI as the topic to be tested, for which we reworked (shortened) a commonly used PowerPoint presentation to include the basic areas containing the necessary know‐what, know‐why, know‐how and know‐who types of knowledge. The lecture in both forms was planned to take a maximum of 20 minutes in both groups. Then we proceeded to create a story that would contain all the knowledge contained in the PowerPoint presentation. Since we were interested in relevant test results, we had to create a story following the recommended composition. Thus, the story included a brief introduction, an outline of the story, development of the story and, especially, the consequences and an implied lesson to be learned. Content‐wise, the story consisted of a report, a conflict (we face the problem that we have to deal with) and characters (a hero, an enemy, two rivalling parties) (Fog‐Budtz‐Yakaboylu, 2005). Several colleagues helped us to create the story, who saw it as a challenge, and also found it entertaining. We knew that we wanted to create something realistic, but entertaining and educational at the same time. We prepared and fine‐tuned the story for about 3 days.
4.2 Findings The students wrote all three sets of tests (pre‐test, test and post‐test) anonymously, and we also evaluated the tests without knowing whether it was the pre‐test, the test, or the post‐test, or whether it was the test group
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Marcela Katuščáková and Martin Katuščák or the control group. The test included six questions, and a student could achieve a maximum of 2 points for each question. The results of the PRE‐TEST demonstrated a low initial level of knowledge in both groups (as they averaged 3 % points of the maximum scores), with no statistically significant differences in the achievements of both groups of students. The results of the TEST which followed immediately after the presentations were as follows: students of the test group (story), averaged 8.2 points of 12, which represents approximately 68.3 % of the knowledge captured, while the students of the control group (PowerPoint) averaged 5.5 b, which represents 46 % of the knowledge captured. We were surprised that as early as in the testing phase there were considerable differences in the results achieved by the test group and the control group in favour of the test group. The variance in students' scores was between 50 % and 96 % in the test group and between 25 % and 75 % in the control group , which means that no student from the test group achieved less than 50 %. We had expected a fairly high level of points achieved in know‐how type of knowledge, where students had to describe a process ‐ a solution (what actions they would take in a small business, if they were in a given situation in terms of CI). The level of knowledge reached 55 %, but since it is one of the most difficult questions, we were quite satisfied, and chiefly observed the control group lag behind. Based on the answers supplied by the control group students it was possible to track that the steps to be taken were not thought out well, but merely reflects some proposals as seen on the screen since they used a much more specialised language than the words in the story told to the test group, however, the sequence of steps proposed did not make sense. It was clear that this concerned just the short‐term visual memory, and so we were curious what level they would achieve in the second test three weeks later. We had similar assumptions concerning the know‐who type of question, where the students were given clear instructions in the story who to talk to in the company in various situations and why. We expected better results of the test group than those achieved, but when compared to the control group, the achievements were good, and we were also interested in the results to be measured three weeks later. Figure 1 shows the level of knowledge of the test group and the control group immediately after the presentation, and the scores represent average number of points obtained under each question. There were six questions asked, the first one required some theoretical know‐what knowledge, the second one some general know‐why knowledge, the third one know‐what knowledge, the fourth one know‐how, the fifth one know‐who, and the sixth one asked for some specific know‐why knowledge. The students could obtain a maximum score of 2 points for each question, in 0.5 point increments (i.e. 0, 0.5, 1, 1.5, or 2 points)
Figure 1: The level of knowledge immediately after the presentation
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Marcela Katuščáková and Martin Katuščák The POST‐TEST followed three weeks after the presentations, and students had not been informed about repeating the tests in advance, so they had no reason to prepare for it. The students in the test group (storytelling), averaged 7.8 points of 12, which is approximately 65.1 % of the knowledge captured , while the control group's students (PowerPoint) averaged 3.36 p, which is 28 % of the knowledge captured. The variance in the students' achievements was between 46 % and 83 % in the test group and between 8 % and 54 % in the control group, i.e., the test group had the weakest students at the level of about 50%, which is the level attained by the most skilful members of the control group. Table 1 Knowledge gap (test and control group) and knowledge loss (test phase and post‐test phase) (Calculated for the whole test, maximum of 12 points) success rate/test phase success rate/post‐test phase Knowledge loss test vs. post‐test phase
Test Group (Storytelling)
Control Group (PowerPoint)
Knowledge gap Test vs. Control Group
68 % (8.2 p/12 p)
46 % (5.5 p/12 p)
22 % (2.7 p)
65 % (7.8 p/12 p)
28 % (3.36 p/12 p)
37 % (4.4 p)
3 % (0.4 p)
18 % (2.14 p)
Figure 2 shows the level of knowledge of the test group and the control group three weeks after the presentation, and the scores obtained represent average points for each question (a maximum of 2 points).
Figure 2: The level of knowledge three weeks later The Time Aspect While the difference in average success rate between the test group and the control group in the first test was between 68 % (8.2 points of 12) and 46 % (5.5 points of 12, i.e. 2.7 points), it was even greater in the tests taken three weeks later, as the difference in memory was between 65.1 % (7.8 points of 12) and 28 % (3.36 points of 12), i.e. 4.44 points, which represents a knowledge gap between these groups of almost 37 %. The test group worsened its performance on average (when calculated for question, maximum of 2 points) by 0.06 points three weeks later, i.e. the level of knowledge decreased from 68 % to 65 % , while the control group performed worse by 0.35 points , i.e., the level of knowledge dropped from 46 % to 28 %. The level of the know‐how type of knowledge decreased in the case of the control group from 0.53 points (27%) to 0.27 points (14%), while in the test group the decrease was from 1.1 points (55 %) to 0.88 points (43 %). We were pleasantly surprised at how well the students remembered the procedure after some time, and we have been convinced that students educated in such manner (without further learning ‐ studying for a test) are better prepared "for life".
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Marcela Katuščáková and Martin Katuščák Table 2: Knowledge loss and knowledge gap for know‐how KNOW‐HOW (calculated for question, maximum of 2 points) success rate/test phase success rate/post‐test phase Knowledge Loss test vs. post‐test phase
Test Group (Storytelling)
Control Group (PowerPoint)
Knowledge gap Test vs. Control Group
55 % (1.1 p/2 p)
27 % (0.53 p/2 p)
43 % (0.88 p/2 p)
14 % (0.27 p/2 p)
11 % (0.22 p)
13 % (0.26 p)
28 % (0.57 p) 29 % (0.61 p)
Even more apparent were the differences in the know‐who type of knowledge, where the level of knowledge decreased considerably in the control group from 0.87 points (43 %) to 0.47 points (23.5 %), while the drop was only from 1.53 points (76 %) to 1.38 points (70%) in case of the test group. We observed that even three weeks later the students knew without learning, who to who contact when necessary in a business company, and we were very satisfied about the results of the test group. Table 3: Knowledge loss and knowledge gap for know‐who KNOW‐WHO (calculated for question, maximum of 2 points) success rate/test phase success rate/post‐ test phase Knowledge loss test vs. post‐test phase
Test Group (Storytelling)
Control Group (PowerPoint)
Knowledge gap Test vs. Control Group
76% (1,53p/2p)
43% (0,87p/2p)
70% (1,38p/2p)
24% (0,47p/2p)
6% (0,15p)
20% (0,4p)
33% (0,66p) 46% (0,91p)
We realised that it would be interesting to evaluate the overall results of each student in a test for which both groups would prepare using the same learning materials, as well as to see the test results of students several months after the test in order to find out long‐term life the knowledge acquired. Therefore, we are determined to continue this experiment.
5. Conclusion The experiment confirmed our assumptions about the power of ST. Perhaps we had expected even better results of the test group, but in the end we realised that the absolute level cannot be assessed, as it is related to the qualities of the students themselves and the quality of our story. We are aware that these are undergraduate students in their second year, who do not have the necessary study habits and knowledge absorption capacity in lectures, and also that the skills needed to make stories are not obtained by studying theoretical publications on story composition, but through real‐world training in creating stories. The most important for us are the differences obtained in assessing the level of knowledge in different types of knowledge. According to our expectations, the levels of the more difficult and practically more usable types of knowledge such as know‐how, know‐who and know‐why were significantly higher even three weeks later. The students in this group were mostly positive about the story and after seeing the comparison of their average results and those of the control group they understood what we discuss only theoretically in lectures about the complexity and depth of knowledge transfer using ST. We believe that if some of the students tested once get to work in managerial positions, they will recollect the power of the story which will help them to implement storytelling in common business practice in Slovakia.
Acknowledgements This publication is a result of implementing the "Memory of Slovakia: National Centre of Excellence in Research, Preservation and Accessibility of Cultural and Scientific Heritage” Project (ITMS:26220120061)
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Marcela Katuščáková and Martin Katuščák supported by the Research & Development Operational Programme funded by the European Regional Development Fund.
References Abrahamson, C.E.(1998). Storytelling as a pedagogical tool in higher education. In Education, Vol 118, No.3, pp. 440‐451. [online] http://www.questia.com/googleScholar.qst?docId=5001330246 Baldwin, J. – Dudding, K. (2007). Storytelling in Schools. [online]. http://www.storynet‐advocacy.org/edu/ Barrett, H. (2005) . Storytelling in higher education: A theory of reflection on practice to support deep learning. In Technology and Teacher Education Annual . Charlottesville, VA: Association for the Advancement of Computing in Education, pages 1878‐1883. [online] http://electronicportfolios.com/portfolios/Kean.pdf Brown, J.S. – Denning, S. – Groh, K. – Prusak, L. (2005). Storytelling in organizations: Why Storytelling is Transforming 21st Century Organizations and Management. MA: Elsevier Butterworth‐Heinemann, 2005. ISBN 0‐7506‐7820‐8. Denning, S. (2006). Effective storytelling: strategic business narrative techniques. In Strategy and Leadership. Vol. 34, No.1, pp 42‐46. [online] http://spartan.ac.brocku.ca/~bwright/4P68/3_storytelling.pdf Fog, K. – Budtz, CH. – Yakaboylu, B.(2005). Storytelling: Branding in Practice. Berlin : Springer, 2005. 238 p. ISBN 3‐540‐ 23501‐9. Gottschall, J. (2012). Why storytelling is the ultimate weapon. [online]. http://www.fastcocreate.com/1680581/why‐ storytelling‐is‐the‐ultimate‐weapon Green, M.C. – Brock, T.C. (2000). The role of transportation in the persuasiveness of public narratives. In Journal of Personality and Social Psychology, 79, pp. 401‐421. Quoted in Green, M.C. 2004. Storytelling in Teaching. In Observer, Vol 17, No. 4 [online] www.education.ucsb.edu/webdata/instruction/hss/story_telling/Story_in_Teaching.pdf Green, M.C. (2004). Storytelling in Teaching. In Observer Vol. 17, No 4, [online] www.education.ucsb.edu/webdata/instruction/hss/story_telling/Story_in_Teaching.pdf Groh, K. 2001. (2001) What are the potential benefits of storytelling? [online]. http://www.creatingthe21stcentury.org/Intro6‐benefits‐story.html Hamilton, M – Weiss, M. (2007). Children Tell Stories: Teaching and Using Storytelling in the Classroom. [online] http://www.beautyandthebeaststorytellers.com Heeg, R. (2011). Tall Tales: The Strength of Storytelling. [online]. http://rwconnect.esomar.org/2011/03/25/tall‐tales‐the‐ strenght‐of‐storytelling/ McLellan, H. (2006). Corporate storytelling perspectives. In The Journal for Quality and Participation, Vol. 29, No 1, pp. 17‐ 20. [online]. http://www.scribd.com/doc/7296173/Corporate‐Storytelling‐Perspectives Meadows, D. (2011). Digital Storytelling. [online]. http://www.photobus.co.uk/?id=534 Prusak, L. (2001a). Why storytelling at this particular time? [online]. http://www.creatingthe21stcentury.org/Intro7‐Why‐ story‐now.html Prusak, L. (2001b). Storytelling in organizations. [online]. http://www.creatingthe21stcentury.org/Larry.html Sbarcea, K. – Ward, V. – Bohn, M. (2001). The power of voice: Why storytelling is knowledge management. In Inside Knowledge. Vol. 5 No. 4 [online]. http://www.ikmagazine.com/xq/asp/sid.0/articleid.D542AD10‐8535‐41A9‐ABDD‐ 7A508A6546AE/eTitle.The_power_of_voice_Why_storytelling_is_knowledge_management/qx/display.htm Sfard, A. – Prusak, A. (2005). Telling identities: In search of an analytic tool for investigating learning as a culturally shaped activity. In Educational Researcher Vol. 34, No. 4,pp. 14‐22. Quoted in McDonald, D. (2009). March of the not so perfect penquins: Storytelling as pedagogy. [online] www.kdp.org/publications/pdf/record/summer09/RSm09_McDonald.pdf Shank, M.J. (2006). Teacher storytelling: A means for creating learning within a collaborative space. In Teaching and Teacher Education Vol 22, No. 6, pp. 14‐22. Signes, C. G. (2008). Practical uses of digital storytelling. A pilot project at the University of Valencia. [online] http://www.uv.es/gregoric/DIGITALSTORYTELLING/.../DST_15_ene_08_final.pdf Snowden, D. (2005). The art and science of story or „are you sitting comfortably?“ Part 2: the weft and warp of purposeful story. [online]. http://cognitive‐edge.com/uploads/articles/5_Art_of_Story_1_‐ Gathering_and_Harvesting_v2_May05.pdf Sole, D. – Wilson, D.G. (2002). Storytelling in organizations: the power and traps of using stories to share knowledge in organizations. [online]. http://lila.pz.harvard.edu. Stephensa,G.J. ‐ Lauren J. S. – Hasson, U. (2010). Speaker–listener neural coupling underlies successful communication. [online]. http://www.pnas.org/content/early/2010/07/13/1008662107.full.pdf Swap, W. – Leonard, D. – Shields, M. – Abrams, L. (2001). Using mentoring and storytelling to transfer knowledge in the work‐place. In Journal of Management Information Systems. Vol 18, No. 1, pp 95‐114. [online]. http://www.learningwiki.com/files/Session‐250‐at‐Learning‐2011/Using+mentoring+and+storytelling.pdf Wijetunge, P. (2012). Organizational storytelling as a method of tacit‐knowledge transfer: Case study from a Sri Lankan university. In The International Information & Library Review (2012) 44, pp. 212‐223.
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Impact of Knowledge Management Practices (KMPs) on Competitive Advantage in Pharmaceutical Firms Radwan Kharabsheh and Ayman Aqrabawi Department of Business Administration, Faculty of Economics and Admin. Sciences, The Hashemite University, Zarqa, Jordan r.kharab@hu.edu.jo Abstract: It has been noted that knowledge management (KM) is becoming the basic building block of organization. Organizations are realizing that KM is a valuable instrument in improving performance. Liang et. al. (2007) stated that managers implement KM programs to gain advantage, increase productivity, and remain competitive. Within this context, an organization’s ability to effectively implement knowledge‐based activities becomes increasingly important for the development and sustenance of a competitive advantage (De Carolis, 2003, Grant, 1996). A firm can develop a competitive advantage through either becoming a cost leader or by using differentiation (Porter 1985). The later is the focus of this study. Once a company possesses such sources and knows how to transfer them into a competitive advantage it can reasonably expect to be successful. While a cost leadership advantage is gained by performing most activities at a lower cost than competitors while still managing to offer a parity product, differentiation advantage is built by performing value‐ adding activities that lead to perceived superiority along dimensions that are valued by customers (Day/Wensley 1988). Differentiation advantage can further take many sub‐forms, among which a superior product/service, the totality of supply, speed (fast delivery), flexibility and the positive image of a company (Kotha/Vadlamani 1995; Sashi/Stern 1995; Helms/Ettkin 2000) are most often mentioned in the literature. This study aimed to examine the relationship between knowledge management practices and a firm’s differentiation strategy. Using questionnaire survey of 16 pharmaceutical companies the study collected a total of 121 useable questionnaires. Multiple regression analysis was used to examine the impact of KMPs on competitive advantage in these firms. The study found that communication to share knowledge has a positive relationship with a firm’s differentiation strategy. The study also found that policies and strategies of knowledge management have a positive relationship with a form’s differentiation strategy. The study also found that firm’s size has appositive relationship with a firm’s differentiation strategy. Keywords: KMPs, differentiation strategy, communication, training
1. Introduction It has been noted that knowledge management (KM) is becoming the basic building block of organization. Organizations are realizing that KM is a valuable instrument in improving performance. Liang et. al. (2007) stated that managers implement KM programs to gain advantage, increase productivity, and remain competitive. Within this context, an organization’s ability to effectively implement knowledge‐based activities becomes increasingly important for the development and sustenance of a competitive advantage (De Carolis, 2003, Grant, 1996). A firm can develop a competitive advantage through either becoming a cost leader or by using differentiation (Porter 1985). The later is the focus of this study. Once a company possesses such sources and knows how to transfer them into a competitive advantage it can reasonably expect to be successful. The resource‐based perspective focused heavily on building a competitive advantage (Penrose 1959; Wernerfelt 1984; Barney 1991; Conner 1991; Grant 1991; Mahoney/Pandian 1992; Peteraf 1993). Its basic assumption is that a competitive advantage is proactively created by companies through their accumulation of unique resources, capabilities and knowledge. Despite the importance of both external and internal factors in building a competitive advantage most research states that (Spanos/Lioukas 2001), it is internal factors that seem to be more important. While a cost leadership advantage is gained by performing most activities at a lower cost than competitors while still managing to offer a parity product, the differentiation advantage is built by performing value‐adding activities that lead to perceived superiority along dimensions that are valued by customers (Day/Wensley 1988). Differentiation advantage can further take many sub‐forms, among which a superior product/service, the totality of supply, speed (fast delivery), flexibility and the positive image of a company (Kotha/Vadlamani 1995; Sashi/Stern 1995; Helms/Ettkin 2000) are most often mentioned in the literature.
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Radwan Kharabsheh and Ayman Aqrabawi With regard to the relative influence of cost and differentiation advantage on performance, several authors (Caves/Ghemawat 1992; Doyle/Wong 1998; Piercy et al. 1998) seem to believe that the differentiation advantage has a greater influence on a company’s performance than the cost‐leadership advantage. Differentiation is even more important in pharmaceutical firms. Ingelgard (2002) argued that the competitive advantage in the pharmaceutical industry is entangled with the company’s ability to generate new knowledge that can produce patents and new medicines that are turned into marketable products which is usually more associated with differentiation rather than a low cost leadership. This study aims to examine the effect of KMPs on a firm’s differentiation strategy. Using questionnaire survey of 16 pharmaceutical companies this study collected 121 useable questionnaires. Multiple regression analysis was used to test the hypotheses. The study found that communication to share knowledge has a positive effect on a firm’s differentiation strategy. The study also found that policies and strategies of knowledge management have a positive effect on a firm’s differentiation strategy. The study also found that firm’s size has appositive effect on a firm’s differentiation strategy. The stronger of the first two is for knowledge management strategies and policies and that is expected due to the nature of pharmaceutical firms.
2. Study model Fundamentally, knowledge activities include the creation and integration, of knowledge, the accumulation and utilization of knowledge, and the learning and sharing of knowledge (Shieh‐Chieh et. al., 2005). Zack, McKeen and Singh (2009) defined KMPs as “observable organizational activities that are related to knowledge management”.
Figure 1 shows the study model. Independent variables
-
Communication
to
Dependent variables
share
knowledge -
Ability to experiment
-
Knowledge
capturing
Differentiation Strategy
&
acquisition -
Training
&
competences
development
Figure 1: The study model Communication and sharing of is the dimension of KMPs that enhances employees’ knowledge by updating their employees’ knowledge across a firm. Oftentimes, those who seek information have difficulties finding correct information sources, reaching sources, and assessing quality and reliable sources. Similarly, those who provide information are frequently unaware of those whom their information could benefit, and therefore fail to share or store that information. It is not only important to determine what types of knowledge and information are available, but with whom that knowledge and information resides (Huizing, 2000). It argued that to maintain a communal knowledge space, people must be motivated to contribute to such systems and be available for information seeking colleagues. There must be arrangements within firms for knowledge transfer infrastructures in attempts to encourage human interaction. Although knowledge from others may
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Radwan Kharabsheh and Ayman Aqrabawi enlighten individuals’ thinking, it cannot replace it (Huizing, 2000). Communication to share knowledge in a firm is conducted in numerous ways: finding and supporting formal and informal training related to knowledge management practices (Earl, 2003; Bozbura, 2007), offering off‐site training to workers in order to keep skills current (Earl, 2003), using formal mentoring practices, including apprenticeships (Earl, 2003; Bozbura, 2007), encouraging experienced workers to transfer their knowledge to new or less experienced workers (Earl, 2003), encouraging workers to continue their education by reimbursing tuition fees for successfully completed work related courses (Earl, 2003; Bozbura, 2007), implementing a system to measure employee competences (Marque´s and Simo´n, 2006), and running a remuneration and promotion systems that influences on development of competences, ideas, and knowledge by employees (Marque´s and Simo´n, 2006). Therefore, this paper makes the following hypothesis: H1: there is a positive relationship between communication to share knowledge and differentiation strategy A firms’ ability to introduce a new product earlier than its competitors is an indicator of its differentiation strategy (Voola and O'cass, 2010). However, firms’ ability to develop and produce new products is closely related to firms’ ability to experiment and learn and its ability to create new knowledge (Zack et. al., 2009). Indeed, many firms view the ability to experiment and create new knowledge as a way to gain and maintain its differentiation strategy (Danskin et. al., 2005). Thus, it concluded that the relationship between ability to experiment and create new knowledge and differentiation strategy is tangible. Therefore, this paper makes the following hypothesis: H2: there is a positive relationship between the ability to experiment and create new knowledge and differentiation strategy. Knowledge acquisition has become a critical resource for creating and sustaining differentiation strategies as the competitive environment continues to intensify (Hitt et. al., 2000). As with other corporate assets, the processes surrounding creation and transfer of knowledge must be managed with significant insights in order to derive the most value from knowledge investments to create differentiation strategy (Bhagat et. al., 2002). The ability of firms development of new products and new knowledge creation which is important for a firms’ differentiation strategy is related to its ability to Therefore, this paper makes the following hypothesis: H3: there is a positive relationship between knowledge capturing and acquisition and differentiation strategy. Remuneration and promotion systems that has a significant influence on developing of employees’ competences, ideas, and knowledge (Marque´s and Simo´n, 2006). In addition, using formal mentoring practices (Earl, 2003; Bozbura, 2007) to measure firms’ employees’ competences (Marque´s and Simo´n, 2006) enhances the differentiation strategy of a firm. Kumarawadu (2008) argued that organization preparedness towards knowledge management initiatives, knowledge management tools and processes, knowledge management education and training and knowledge creation and transformation contribute firms to gain differentiation advantage. Therefore, training and competences development practices is strongly correlated to products; creation (Voola and O'cass, 2010), superiority (Parnell, 2011), and quality (Cater a nd Cater, 2009). Therefore, this paper makes the following hypothesis: H4: there is a positive relationship between the training and competences development and differentiation strategy. Knowledge management policies and strategies can have a great impact on a firm’s differentiation strategy. For example, periodically checking competitors' strategies and products, services to get new knowledge (Choi et. al., 2008) enables firms to develop and introduce new products faster than its competitors (Voola and O'cass, 2010). Firms can also conduct indigenous research within a firm to develop new products or develop collaborations and alliances with external institutions and organization (Voola and O'cass, 2010; Choi et. al., 2008). Therefore, this paper makes the following hypothesis: H5: there is a positive relationship between the policies and strategies of knowledge management and differentiation strategy. Based on prior literature, firm age and size appears as a control variable in various firm KM studies. Therefore, it is important to control for firm size and age effects when exploring the relationship between various aspects
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Radwan Kharabsheh and Ayman Aqrabawi of KM. Yang (2010) stated that firm KM strategy may be influenced by both the firms’ age and size. Therefore, this paper makes the following hypothesis: H6: there is a positive relationship between the firm size and differentiation strategy.
3. Research methodology There are 16 pharmaceutical companies in Jordan (JAPM, 2011) of which 12 companies only agreed to participate in this study. The study used a self‐administered questionnaire survey. A brief description of the study was provided and then an appointment was sought with the managers in the listed companies. A total of 121 useable questionnaires were collected. The data was codified and entered into SPSS. The Cronbach Alphas were acceptable exceeding the recommended value of 0.6 (Sekaran, 2003) as shown in table 2. With regards to the data distribution, it was found that the Asymp. Sig. (2‐tailed) values for each variable were above 0.05 indicating that the data are normally distributed. KMPs was measured by 5 items developed by (Zack et. al. 2009; Islam et. al. 2008; Maponya, 2004; Earl, 2003; OECD, 2002; Aurum et. al., 2007; Kasim et. al.,2008; Bozbura, 2007). Differntation strategy was measured by 5 items developed by Carter and Carter (2009). The size of the company was measured by number of employees (Ling et. al., 2007). Table 1 shows samples’ characteristics. It shows that 79% of the sample were male and 21% were female. This indicates that more men work in pharmaceutical firms in Jordan than woman because this sector requires long working hours which may conflict with women's' traditional roles in the family. Due to higher numbers of men working in this industry more opportunities exists for men to become managers. Moreover, due to cultural reasons more woman target education and health care sectors. With regards to respondents' education 88% of respondents held a bachelor degree and the rest held masters degree which shows the high emphasis on educational achievement by pharmaceutical firms in Jordan. With regards to the managerial levels of the respondents 29% were managers, 30% were supervisors and 39% were heads of sections. The respondents' distribution according to years in current position shows that 65.4% were in this position for less than 5 years, 14.9% were in their positions for 5‐10 years and the 3.3% were in their positions for more than 10 years. Table 1 Sample characteristics Variable Male Female BSc. Master Manager Supervisor Head Section Less than 1 years 1 ‐5 years 5 – 10 years 10+ years
Frequency Gender 95 26 Educational level 88 33 Position 35 36 50 Years in position 32 67 18 4
Percentage% 79.0 21.0 73.0 27.0 29 30 39 26.4 55.4 14.9 3.3
Table 2: Descriptive and goodness of fit statistics Crombach’s alpha
3.7769
Standard deviation 0.61762
3.843
0.58424
0.792
3.5723 3.7983
0.77017 0.64317
Policies and strategies of knowledge management
3.5667 3.6915
0.76819 0.71416
0.846 0.786 0.859
KMP total
3.6948
0.59403
Measure
Mean
Differentiation strategy (6 items) Communication The ability to experiment and create new knowledge Knowledge capturing and acquisition Training and competences development
352
0.856
0.879 0.947
Radwan Kharabsheh and Ayman Aqrabawi
3.1 Multiple regression analysis Table 3 shows estimation results of the regression analysis. Support was found for H1 that communication to share knowledge is positively related to differentiation strategy (B = 0.186). Support was also found for H5 that policies and strategies of knowledge management are positively related to differentiation strategy (B = 0.267). Support was also found for H6 that there is a positive relationship between firm size and differentiation strategy (B =‐ 1.218). No support was found for H2, H3, and H4. Table 3: Multiple regression analysis
Un standardized Coefficients Model (Constant) Communication to share knowledge ability to experiment and create new knowledge knowledge capturing and acquisition training and competences development Policies and strategies of knowledge management Firm size
S.d Coeff.
B 2.876
Std. Error 2.197
Beta
T 1.309
Sig. .193
.186
.102
.211
1.813
.072
.122
.111
.122
1.102
.273
‐.071
.112
‐.074
‐.638
.525
.039
.077
.067
.499
.619
.267
.085
.371
3.157
.002
1.218
.463
.189
2.633
.010
4. Results and discussion This study aimed to examine the relationship between knowledge management practices and a firm’s differentiation strategy. The study found that communication to share knowledge has a positive relationship with a firm’s differentiation strategy. The study also found that policies and strategies of knowledge management have a positive relationship with a form’s differentiation strategy. The study also found that firm’s size has appositive relationship with a firm’s differentiation strategy. The stronger of the first two is for knowledge management strategies and policies and that is expected due to the nature of pharmaceuticals. Personal interviews that were conducted at the time of questionnaire survey showed that pharmaceuticals in Jordan employed numerous strategies and policies for knowledge management aimed at the creation and sustaining of new products in the market. For example, these firms developed information system networks that allow employees to share their knowledge at the same time allowing the firm to gauge and reward employees’ involvement. Some policies for example ask employees who received training outside the firm (locally or internationally) to provide the same training to their colleagues. Communication on the other hand is positively related but has lesser B value. The interviews showed that these firms focus greatly on communication among employees both formally and informally. From regular daily meetings, to internal networks to conduction of retreats for employees in order to ensure that employees mingle with each other, get to know each other, exchange knowledge and expertise and provide opportunities for mentoring. With regards to firm’s size the study showed that there is a positive relationship and a firm’s differentiation strategy. This can be understood in the sense that smaller firms usually have the advantage of controlling their cost and that a differentiation strategy requires more capital investment, more employees (which is associated with departmentalization and specialization) which contradicts the more costly culture of trial and error dominant in firms adopting a differentiation strategy.
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The Impact of Knowledge Management Practices on Organizational Performance Aino Kianto, Paavo Ritala, Mika Vanhala and Henri Inkinen School of Business, Lappeenranta University of Technology, Lappeenranta, Finland aino.kianto@lut.fi paavo.ritala@lut.fi mika.vanhala@lut.fi henri.inkinen@lut.fi Abstract: While the importance of knowledge for firm’s success seems to be a widely accepted argument in the current management literature, there are relatively few empirical studies demonstrating whether and how engagement in knowledge management impacts firms’ objective financial performance. To bridge this gap, our paper examines the impact of knowledge management practices on financial performance of firms, measured with return on equity and return on assets. By using measurement points for objective performance measures from two different years – from the same year as the data was collected and from the following year ‐ we are able to examine this issue from causality‐oriented perspective. Unlike many papers on knowledge management which focus on the generic knowledge processes, such as knowledge sharing and knowledge creation, we focus on knowledge management practices, which are the systematic and conscious activities applied in an organization for better leverage and utilization of knowledge. Based on existing literature, we define six sets of such practices: strategic management of knowledge, structural arrangements, building a knowledge‐ friendly culture, information and communication technology practices, human resource management practices and learning mechanisms. To study the research setting empirically, we utilize a dataset of 399 Finnish companies collected at 2010‐2011. Using Spearman’s correlation analyses, we examine the relationship between the aforementioned six knowledge management practices on Return On Equity (ROE) and Return On Assets (ROA). We found consistent evidence on the positive relationship between most of the knowledge management practices and firm performance with different time lags, and with the two performance measures. Thus, overall our results demonstrate that engaging in systematic activities for managing knowledge significantly increases firm performance, and thus underlines the importance of a systematic approach to knowledge management for company competitiveness. The model presented in the paper is the first step of a major international research project “Intellectual Capital and Value Creation”, where the impact of intellectual capital and knowledge management practices on firm performance is tested in a dataset collected from eight countries (Finland, Russia, China, Italy, Spain, Portugal, Romania, Serbia). Keywords: knowledge management, knowledge management practices, performance, competitiveness, survey
1. Introduction Knowledge management (KM) has gained increasing visibility and popularity during the past decade or so. However, while the beneficiality of KM is taken for granted by scholars engaged in the debate within this field, it seems that practicing managers tend to be more skeptical concerning the utility of investing in KM activities. For example, an international survey conducted in 2010 in 222 companies in Finland, China and Russia (Andreeva et al. 2011; Kianto et al. 2011) found that while 91% of companies claimed that knowledge is a key strategic asset for them, only 43% of companies had a dedicated budget for KM activities. A major reason for this lack of engaged activity might be a doubt in terms of its actual pay off for company viability. Thus in terms of improving practitioner commitment to KM it seems important to produce tangible proof of the financial benefits engaging in KM brings to a firm. From the academic perspective, it also seems that there is a shortage of empirical studies connecting systematic KM activities to company performance. While the KM literature boasts a great deal of successful case studies demonstrating best practices in particular companies, there are not that many examining the impact of KM on performance issues in a multitude of firms. Thus demonstrating whether and how engaging in KM enhances organizational performance is an important issue to examine further. Therefore this paper addresses the question of how knowledge management practices impact the financial performance of companies. First, we theoretically argue what KM practices are and how they are likely to impact firm performance. Then we empirically examine the relationship of six types of KM practices on the objective financial performance measures with the dataset of 399 Finnish firms.
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Aino Kianto et al. The model presented in the paper is the first step of a major international research project, where the impact of intellectual capital and knowledge management practices on firm performance is tested in a dataset collected from 8 countries (Finland, Russia, China, Italy, Spain, Portugal, Romania, Serbia).
2. Knowledge management practices as sources of firm performance The significance of knowledge and its management for firm performance has been most sophisticatedly argued within the realm of the knowledge‐based strategy theory. According to the knowledge‐based view of the firm, performance differences between organizations accrue due to their different stocks of knowledge and their differing capabilities in using and developing knowledge (Kogut & Zander, 1992; Grant & Spender, 1996; Grant, 1996). The firm is conceptualized as a social community specializing in speed and efficiency in the creation and transfer of knowledge (Kogut & Zander, 1996, 503). Knowledge is seen to exist in many forms, e.g. tacit, explicit, self‐transcending (Nonaka & Takeuchi, 1995; Scharmer 2001; Smedlund 2008) and embedded in many locations and containers, e.g. in individuals, groups and communities, as well as in documents and practices (Blackler, 1995; Hedlund, 1994; Spender, 1996). It is acknowledged that producing a good or a service typically requires the application of many types of knowledge, and therefore in addition to possessing knowledge resources, the firm has to be able to manage, integrate, and coordinate different types of knowledge (Penrose, 1959; Kogut & Zander, 1992; Grant, 1996; Grant & Baden‐Fuller, 2004). Thus, the knowledge‐based view underlines management practices of knowledge as the key determinant of competitiveness. Taken together, the key assumptions of the knowledge‐based strategy theory entail that the better an organization is able to manage its knowledge, the more likely it is to achieve high performance. Knowledge management practices can be defined as the set of management activities conducted in a firm with the aim of improving the effectiveness and efficiency of organizational knowledge resources (Kianto & Andreeva 2012). They refer to the aspects of the organization that can be manipulated and controlled by conscious and intentional management activities, and can thus be distinguished from knowledge processes (such as knowledge sharing and knowledge creation), which are more generic in nature and likely to take place to some extent in any organization regardless of whether there are any systematic efforts for management control concerning them. KM practices can be divided into six main categories, related with the strategic management of knowledge, structural arrangements, building a knowledge‐friendly culture, information and communication technology practices, learning mechanisms and human resource management practices The strategic management of knowledge can be defined as the strategic planning and implementation activities related to the knowledge‐based assets in the firm (Kianto et al. in press). It entails identifying the key strategic knowledge resources in the organization and building a knowledge‐based strategy, as well as activities for monitoring and measuring knowledge assets in the firm, and their developmental needs in relation to the business environment (Zack, 1999; Skyrme & Amidon 1997; Dalkir 2005; Kianto 2008; McKeen et al. 2005). Strategic KM activities increase organizational performance through the following mechanisms: First, they enable focusing on the most value‐creating activities of the firm, as the intangible assets have been suggested to be the focal sources of competitive advantage (Barney, 1991; Grant, 1996; Conner and Prahalad, 1996). They also enable crafting strategies based on the knowledge‐based advantages compared with competitors (Zack et al., 1999). Furthermore, they enable making strategic decisions of allocation, utilization, expansion and sharing of the company’s knowledge base that follows the overall strategic aims of the company (as suggested by Zack et al., 1999; see also Von Krogh et al., 2001). Organizational structure is another central aspect in implementing KM (Hedlund, 1994; Gold et al, 2001; Quintas et al, 1997, Wong, 2005). KM practices related with organizational structure deal with the division of labour, definition of work roles, formal communication channels and decision making and power relations invested in these. Building intra‐organizational as well as cross‐boundary groups and communities as well as promoting shared leadership and employee‐driven, intrapreneurial activity enhances knowledge‐based operation. Specifically, structural KM practices increase organizational performance through the following mechanisms. They enable providing structures that utilize highly differentiated individual expertise, which makes knowledge‐based work more effective and efficient (Grant, 1996). They also creating physical spaces (also referred to as ba’s), that help to create atmosphere where knowledge can be fluently shared (Nonaka, 1998). Building and empowering communities of practice increases access to relevant knowledge both within
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Aino Kianto et al. the organization as well as with external parties and thereby performance (Brown & Duguid 1998; Lesser & Storck 2001). Empowering experts to make decisions concerning organizing work increases the speed of organizational functions. Empowering experts to build, maintain and organize work around their internal and external networks with task‐related expertise will increase efficiency of knowledge processes (Argote & Ingram 2000). Finally, vertical integration creates a shared language and identity that improves knowledge exchange in an organization (Kogut & Zander 1996) Organizational culture encompasses the shared basic assumptions, values, norms and related artefacts within the firm, which have been created during the life‐span of the organization (Schein 1985). Many studies demonstrate the importance of building a knowledge‐friendly culture for facilitating knowledge processes, and thereby knowledge‐based value creation (e.g. De Long & Fahey 2000; McDermott & O’Dell 2001; Dorothy et al. 2006, Kristen et al. 2004). Cultural KM practices increase organizational performance through building and sustaining a culture where withholding is not accepted and not encouraged (Husted & Michailova 2002) and that can be characterized by a widely disseminated knowledge creating and sharing mindset (Nonaka, 1991). The positive climate of collaboration increases inter‐personal interaction and thereby knowledge sharing and helping behavior and thus leads to higher collective knowledge processes (Von Krogh 1998). Organizational culture where reciprocal knowledge sharing is a norm increases knowledge stocks and organizational performance (Nahapiet & Ghoshal 1998). Practices for utilizing information technology and computer‐supported communication are another important means for improving the leverage of knowledge in a firm (Alavi & Leidner 2001; Davenport & Prusak 1998). ICT practices for KM increase organizational performance through the following mechanisms: increasing access to a wide set of information and timeliness of information flow, as well access to social networks (social media); improved possibilities for knowledge codification (turning tacit knowledge into explicit knowledge) Nonaka & Takeuchi 1995); providing means for knowledge storage and utilization, and thus building organizational memory and efficient re‐use of knowledge. ICT practices can also contribute greatly to systematic knowledge analysis, improve knowledge combination from various sources, as well as allow for location‐independent, seamless access to knowledge and information within the organization and beyond and increase the means and channels for collaboration and interaction between organization’s experts (e.g. Kankanhalli et al., 2003). Finally, they also enable more rapid application of knowledge through workflow automation (Alavi & Leidner 2001). Learning, i.e. improvement and increase of organizational knowledge and competence is a key facet of effective knowledge‐based operation. In the organizational context, learning mostly takes place as workplace learning in the job through learning‐by‐doing or practice‐based learning (Billet 2004; Gherardi, 2001; Lave 2009) or vicarious social learning, i.e. learning from others by observing their behavior and its consequences. Specifically, learning‐related KM practices increase organizational performance through the following mechanisms. By enabling improving access to collegial tacit and explicit knowledge they increase the quality of performance. By legitimizing vicarious learning they increase the motivation to share and create knowledge. Also providing opportunities for mentoring and coaching in the organization and providing opportunities for learning‐by‐doing will help share, build and develop knowledge for organizational benefit. Finally, human resource management practices play a significant role in KM (Hislop, 2003; Scarbrough, 2003; Wong, 2005). HRM is typically defined as the management of the organization’s employees (Foot and Hook, 2008). Usually HRM functions include tasks such as staffing, remuneration, performance evaluation, and training and development. The ultimate goal of HRM is to find and select the best fitting employees, and by appropriate remuneration, training and evaluation mechanisms bring the best out of them. HRM practices increase organizational performance through the following mechanisms. Through paying attention to knowledgeability and social skills in recruitment process, they increase the availability of knowledgeable workforce for producing effective and efficient performance in knowledge‐intensive tasks. Through defining work roles and positions based on competences, they increase the likelihood of matching the person with the best expertise to the right task. Through promoting and rewarding knowledge process activities (knowledge sharing, knowledge creation etc.) they increase the likelihood of employees engaging in such activities. Through acknowledging expertise in career advancement, they increase employee motivation to utilize their knowledge in their work. And finally HRM practices are related with retention of knowledgeable employees within the organization with remuneration, compensation, and other means of acknowledging them (intangible & tangible motivations).
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Aino Kianto et al. Based on the argumentation above, it can be posited that KM practices increase effective and efficient performance of knowledge‐intensive tasks, and thereby financial performance of a firm. Specifically, this hypothesis can be broken to 6 parts, each representing a particular set of KM practices. More formally put, we claim that the more intensively an organization applies a given KM practice, the higher performance it is likely to attain.
3. Methods 3.1 Sample and data collection First, we got 518 responses from a sample of Finnish companies, representing firms from different industries, the common denominator being involvement in international activities. The survey was a part of a large scale customer survey (n = 31398) of a Finnish information directory company. The responses were collected by via a web‐based survey, conducted by an independent research and consulting organization. Some of the companies responded with several people (between 1‐7 responses per company, most firms had only 1 respondent), and altogether the responses were received from 399 different companies. The respondents represented senior or junior level managers, e.g. marketing managers, communications manager, or sales director. In the case of multiple respondents, a mean value was calculated for each KM practice measure for each firm.
3.2 Measures The scales used for measuring KM practices were drawn from the KM Survey project, conducted during 2009‐ 2010 in collaboration by School of Business, Lappeenranta University of Technology, Finland and Graduated School of Management, St. Petersburg State University, Russia. The KM Survey project conducted an extensive literature review on previous KM practices models and metrics and thereby constructed scales for measuring various types of KM practices. The original scales have been previously reported e.g. in Kianto, Andreeva & Shi, 2011, Kianto and Andreeva 2012, and Andeeva, Kianto, Pavlov and Shi, 2011. In this paper we utilize a slightly modified set of these scales to cover full scale of different practices, as described in the following. We measured the KM practices with six multi‐item summated, reflective scales. First, strategic management of knowledge (reliability, measured with Cronbach’s Alpha = 0.92) was measured with nine items related to recognizing knowledge as a key element in firm’s strategic management. Second, organizational structure (reliability 0.84) includes five items related to such structure that facilitate informal interaction and cross‐ functional collaboration. Third, KM‐friendly culture (reliability = 0.93) includes six items related to such an organizational culture that creates the atmosphere and possibilities to share and create knowledge within the organization. Fourth, IT and computer supported communication (reliability = 0.88) includes five items focusing on practices for utilizing information technology, information systems, tools, and computer‐ supported communication in the organization. Fifth, learning measure (reliability = 0.82) includes three items which focus on organizational processes supporting mentoring and learning. Finally, human resource management practices (reliability = 0.93) includes six items related to rewarding, evaluating and other practices that facilitate knowledge sharing through means of HRM. The firm performance was measured by two objective financial metrics obtained from the Amadeus database. We used Return On Equity (ROE) and Return On Asset (ROA) from two years (2010‐2011). The ROE is expressed as a percentage and calculated as Net Income/Shareholder’s Equity and the formula for ROA is Net Income/Total Assets. Both are often utilized measures of objective financial performance, and they reflect the issue from a bit different viewpoints.
4. Results We tested the relationship between different KM practices and firm performance by the means of correlation analysis. Our data was not normally distributed and thus we utilized Spearman’s correlation for the analysis (see Table 1).
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Aino Kianto et al. Table 1: Correlations between KM practices and firm performance Firm performance
Strategic Management of knowledge
Organizational structure
KM‐friendly culture
ROE 2010 ROE 2011 ROA 2010 ROA 2011
0.169** 0.146** 0.140** 0.166**
0.136* 0.136* 0.123* 0.157**
0.166** 0.145** 0.147** 0.150**
IT and computer‐ supported communication 0.092 0.080 0.081 0.058
Learning
HRM practices
0.191** 0.157** 0.140** 0.149**
0.133* 0.129* 0.095 0.051
Notes: ** Correlation is significant at the 0.01 level; * Correlation is significant at the 0.05 level Overall, the results provide consistent support for a positive relationship between different practices and objective performance measures. However, based on our analysis it seems that practices for utilizing information technology and computer‐supported communication do not significantly correlate with neither of the performance measures in any measured period. HRM practices is only related to ROE measure, but non‐ significant in terms of ROA. The other four practices have a statistically significant correlation with the performance during years 2010‐2011 with both performance measures.
5. Discussion This paper examined the impact of knowledge management practices on the financial performance and found that there is a strong relationship with the extent of systematically managing knowledge and obtained performance. Overall, this finding demonstrates the importance of knowledge management as an important managerial tool that can bring significant performance benefits to the firm. The current paper represents the first step to examine the impact of a wide set of knowledge management practices on financial firm performance from a longitudinal perspective. However as the different knowledge management practices might interact with each other, a further step should be to analyze the relationships with a method that enables examining the interactions between the practices and potential combinations of them allowing for maximal performance.
Acknowledgements We wish to express our gratitude to Mr. Pasi Raatikainen and Ms. Anna Tubal of AAC Global for conducting the data collection.
References Alavi, M. & Leidner, D. (2001) “Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues”, MIS Quarterly, Vol. 25, No. 1, pp. 107‐136. Andreeva, T., Kianto, A., Pavlov, Y. & Shi, X. (2011) Knowledge management in peripheral countries: Evidence from China, Finland and Russia. European Group of Organizational Studies (EGOS) colloquium, 7‐9 July, Göteborg, Sweden. Argote, L. & Ingram, P. (2000) “Knowledge transfer: A basis for competitive advantage in firms”, Organizational Behavior and Human Decision Processes, Vol. 82, No. 1, pp 150‐169. Barney, J. (1991) “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17, No. 1, pp 99‐ 120. Barney, J. (1991) “Firm resources and sustained competitive advantage”, Journal of Management, Vol. 17, pp. 99‐120. Blackler, F. (1995) “Knowledge, knowledge work and organizations: An overview and interpretation”, Organization Studies, Vol. 16, No. 6, pp. 1021‐1046. Brown, J. & Duguid, P. (1998) “Organizing knowledge”, California Management Review, Vol. 40, No. 3, pp. 90‐111. Conner, K.R. and Prahalad, C.K. (1996) “A Resource‐Based Theory of the Firm: Knowledge Versus Opportunism”, Organization Science, Vol. 7, No. 5, pp 477‐501. Davenport, T, H & Prusak. L. 1998. Working Knowledge, How Organizations Manage What They Know. Boston: Harvard Business School Press De Long, D. & Fahey, L. (2000) “Diagnosing cultural barriers to knowledge management”, The Academy of Management Excecutive, Vol. 14, No. 4, pp. 113‐127. Grant, R. & Baden‐Fuller, C. (2004) A Knowledge Accessing Theory of Strategic Alliances. Journal of Management Studies January, 41(1), 61‐84 Grant, R.M. (1996). ”Toward a Knowledge‐Based Theory of the Firm”, Strategic Management Journal, Vol. 17, Winter Special Issue, pp 109‐122.
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Creating Banks’ Competitiveness by Proper Identification and Usage of Intangibles – Survey Results Monika Klimontowicz University of Economics, Katowice, Poland mklimontowicz@ue.katowice.pl Abstract: The dynamism of today’s banking market in Poland has motivated banks to focus on exploitation of their internal resources for higher organizational performance. Knowledge and intellectual capital embodied in intangible assets are considered as banks’ primary source of competitiveness. The paper presents the results of the survey focused on determining the role of particular intangible assets in the process of creating bank’s competitiveness and indicating the directions of bank’s intangibles effective usage. A four step methodology was designed to achieve the purposes of research. First step concerned the definition of bank’s intangible assets and their structure. It involved an investigation of the current professional literature, including books and journals, reports, conference proceedings, dissertations and thesis, social media and portals. The next steps were a part of empirical survey targeted to retail banks’ managers and customers. The survey was conducted in the spring of 2012. The purpose of the second step was to establish the role of intangible as customers decisions’ determinants. The third step included the assessment of intangibles’ significance for bank’s competitive advantage’ creation. The forth step was designed in order to estimate bank’s ability to intangibles’ effective usage. Results show that, despite the customer‐oriented basis of competitive strategy that is usually declared by banks in Poland, banks’ managers are quite often wrong about the customers’ decisions determinants. As a result they base their strategies on a wrong foundation. Surprisingly they still consider tangible assets to be more crucial for bank’s competitiveness than intangibles. It is worth to say that the importance of particular intangibles and their hierarchy for customers has being changed what has not been noticed by them. The results’ analysis was the foundation of preparing some proposals for increasing the efficiency of bank intangibles’ usage. Putting consumer needs and expectations at the heart of competitive strategy will require banks’ new skills and competences. Developing them is an inevitability because the customer satisfaction has already become the key to repeated buying and loyalty in Poland. Thus banks in Poland must learn to nurture the loyal core of their customer and develop skills for attracting the new customers. Keywords: bank’s intangibles, bank’s competitiveness, competitive advantage
1. Introduction Since the nineties last century the situation of banking sector in Poland has changed remarkably. Banks have realised that a firm possesses a sustainable competitive advantage when its value‐creating processes and position have not been able to be duplicated or imitated by other firms (Porter 1998). Nowadays the challenge for a bank is not only to understand that the real value of bank, its competitiveness and the customers’ loyalty are based on intangible assets but also to specify components of its structure and find out which of them are the most significant and effective for making customers satisfy and bank’s market performance (Klimontowicz, 2011). In order to understand the role of intangible assets in the process of bank’s competitiveness creation we must first define bank’s intangibles, their structure and their role in gaining sustainable advantage. The main purpose of the research was to determine the role of particular intangible assets in the process of creating bank’s competitive advantage and to indicate the directions of bank’s intangibles effective usage. The three hypotheses were made. First of them assumed that, despite the usually declared customer‐oriented basis of competitive strategy, banks in Poland were quite often wrong about the customers’ decisions determinants. As a result they based their competitive strategies on a wrong foundation. Secondly bank’s managers in Poland still considered tangible assets to be more crucial for bank’s competitiveness than intangibles. The third hypothesis focused on the importance of particular intangibles for customers and assumed that their hierarchy has been changing.
2. Research methodology The research was prepared combining descriptive theoretical and empirical methods. A four step methodology was designed to achieve its purposes. The methodology included following steps:
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Step 1:
Defining bank’s intangible assets and their structure.
Step 2:
Establishing the role of intangible as customers decisions’ determinants.
Step 3: Assessment of intangibles’ significance for bank’s competitive advantage’ creation.
Step 4: Estimating bank’s ability to intangibles’ effective usage.
The first step involved an investigation of the current professional literature, including books and journals, reports, conference proceedings, dissertations and thesis, social media and portals. Among theoretical sources 145 books and 127 published papers have been analysed. This analysis was the foundation for defining bank’s intangible assets and their structure. The next steps were a part of empirical research targeted to retail banks’ managers and customers. The defined structure of banks’ intangible assets was the base for designing the questionnaire. Altogether, 51 statements in the questionnaire dedicated to banks’ managers and 36 statements in the questionnaire dedicated to customers were selected to examine the significance and efficiency of banks’ intangibles. All that statements were summed into five group of assets: human, market, organizational and innovative assets versus financial assets which represent tangible assets. Reliability analysis, measured with Cronbach’s alpha, showed adequate reliability levels for all of the scores (see table 1). Table 1: Scores reliability levels measured with Cronbach’s alpha. Scale Significance of intangible assets (according to banks’ managers). The ability to gain competitive advantage using intangible assets (according to banks’ managers). The efficiency of using banks’ intangibles (according to banks’ managers). Significance of intangible assets (according to customers). The efficiency of using banks’ intangibles (according to customers).
Cronbach’s alpha 0,97 0,96 0,64 0,89 0,72
A seven‐point Likert scale from 0 to 6 was used in the research. The significance of intangible was graded from 0 which meant that the factor is not important at all to 6 which meant the huge importance. When the banks’ managers had decided how important was a factor they were asked to grade if bank is able to use that factor efficiently in the process of gaining competitive advantage. They used the seven‐point scale from 0 which meant desperately low ability to 6 which meant excellent ability. When the customers had graded the significance of a factor they were asked to decide what in their opinion was the grade for that factor in their banks. They also used seven‐point scale (from 0 which meant desperately low grade to 6 which meant excellent grade). The data was collected by two methods – PAPI (personal and pen interviews) and CAWI (computer assisted web interviews). The survey’s target group consisted of banks’ managers and customers. The assets of banks which took part in the survey correspond to 48,4% of polish retail banking sector. 54,5% of them represent domestic capital and 45,5% foreign capital. Taking into account the number of employees and the number of branches that probe was also representative one. 679 customers responded to the questionnaire. All of them use at least one banking or financial product. 61,4% of them have been banks’ client for more than 5 years. They mostly use personal accounts (98,5% of respondents), debit cards (76,7%) and savings accounts (55,7%). The customers’ probe is representative for Polish society in relation to sex, incomes, permanent residence, opinion about their economic situation and their expectations concerning banking services. Taking into account sex, incomes and permanent residence its structure corresponds to statistical data characterizing Polish society. Opinion about their economic situation follows the normal distribution (Gaussian distribution) which is commonly encountered in practice and is used throughout statistics as a simple model for complex phenomena. Presented results are a part of an survey focused on the role of intangible assets in gaining competitive advantage on Polish banking market and have practical implications to banks’ managers in different fields of their competitive strategies.
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3. Results 3.1 Step 1: The definition and structure of bank’s intangibles The term Intangibles has many complex connotations and is often used synonymously with intellectual capital, intellectual property, intellectual assets and knowledge assets. Despite the increasing interest of academics and practitioners there is no generally accepted taxonomy so far. It is defined as (Rogowski 2006, Urbanek 2008):
the sum of all the people of the company know which gives a competitive advantage in the market (T. Steward),
knowledge that can be converted into value (L. Evidson),
knowledge, experience, organizational technology, clients relationship and professional skills which give company a competitive advantage (L. Evidson, M. Malone),
the sum of hidden assets which are not seen in balanced sheets consists of what employees have in their heads and what they leave in a company going home (G. Roos, J. Ross).
Some of researchers say that it is too early to define the term of intellectual capital definitely because it is still being examined and conceptualized from different perspectives. The variety of definitions makes the scientists and managers to classify, order and characterize the components of intangibles individually. The intellectual capital is the link between knowledge, talent, skills, resources’ creativity and innovativeness with resources supporting the productivity such as technology, modern organizational structure and patents. As the result the term of intellectual capital is extended to all intangible assets or narrowed down to few components. Taking into account creation of bank’s competitiveness intangibles are all its strategic resources that enable to create sustainable value, but are not available to a large number of banks. They lead to potential future benefits which cannot be taken by others and are not imitable by competitors, or substitutable using other resources. They are not tradeable or transferable on factor markets due to corporate control. Because of their intangible nature, they are non‐physical, non‐financial, are not included in financial statements and have a finite life. In order to become an intangible asset included in financial statements, these resources need to be clearly linked to a company’s products and services, identifiable from other resources, and become a traceable result of past transactions (Kristandl, Bontis, 2007). Sustainable competitive advantage is achieved by continuously developing existing resources and creating new ones in response to rapidly changing market conditions. Distinctive capabilities need to be supported by an appropriate set of complementary reproducible capabilities to enable a company to sell its distinctive capabilities in the market. Among these resources and capabilities intangible assets are the most important value‐creating assets (see Figure 1). Resources Other bank’s resources
Strategic bank’s resources
Tangible Assets
Structure
Intangible Assets
Financial Assets
Human Assets
Market Assets
Organisational Assets
Innovative Assets
Figure 1: Company resources in achieving competitive advantage
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Monika Klimontowicz Analyzing the internal structure of intangibles it can be noticed that human capital is defined in the same way in all concepts and consists of employees’ experience, knowledge, qualifications and skills combined with their motivation and managers’ skills and abilities. At the contrary structural capital is defined and named in different way. Comparing those concepts it should be stressed that as far as intangibles’ components have been described precisely in the industry, they are rarely examined in banking sector (Klimontowicz, 2011). The structure of bank’s intangibles must reflect its specific character and take into account factors which create its long‐term value. From that perspective two the most important items are human assets and market assets. In banking sector achieving a market success is impossible without proper reputation and clients’ trust. In today’s changing environment the process of increasing bank’s value is undoubtedly connected with process optimization and service technology. That is why the structure of bank’s intangible assets should also include organizational assets and innovative assets (Klimontowicz 2012) ‐ see table 2. Table 2: The structure of bank’s intangible assets Intangibles Human Assets
Market Assets
Organizational Assets
Innovative Assets
Components knowledge and experience professionalism client oriented attitude and an ability of developing relations with clients level of employees’ creativity and innovativeness will to cooperation quality of management image and reputation quality and effectiveness of bank’s marketing activity knowledge of clients’ needs and an ability to match offer with consumers’ needs and expectations and sales strategy ability of developing relations with clients knowledge of competitors and their offers traditional distribution channels modern distribution channels equipment and infrastructure working conditions safe and comfort way of transactions’ authorization TQM system level of service’s modernity R&D and innovativeness budget innovative products/services implementation innovative procedure implementation using the innovative technology in bank’s management new way of providing services
3.2 Step 2: Establishing the role of intangible as customers decisions’ determinants. Owing to increased competition in the banking service industry banks should specify the determinants of competitive advantage. Research continually confirms a significant correlation between satisfaction and repeated buying, brand loyalty and spreading a positive opinion of the product. In the banking sector Loveman (1998) found that higher customer satisfaction leads to increased cross‐selling at the branch level. According to Ittner and Larcker (1998) customer satisfaction is a leading indicator of revenue and growth. The consumer satisfaction category is based on the premise that the profit is made through the process of satisfying consumers’ needs. That is why it very important to find out what factors are taken into account by customers when they are going to choose a bank. Results show that most of the factors which influence customers’ decisions could be classified as intangible (see figure 2). Banks’ customers had not any problems with pointing them during the research. The most important for them are: the access to products and services by internet and mobile, attractive financial conditions of cooperation with bank, branch’s location and trust. Surprisingly it was difficult for banks’ manager. They were not able to indicate definitely what was important for customers and was the determinant of their decisions. A lot of programs concerning consumer satisfaction have already been implemented in banks in Poland. They include activities which are to attract different kind of clients. Unfortunately they have been probably based
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Figure 2: The factors of customers’ decision concerning the selection of a bank.
3.3 Step 3: The significance of bank’s intangibles for competitive advantage – banks’ managers and customers assessment Whereas the important role of intangibles is quite obvious for scientists and researchers Polish banks’ managers still choose the financial assets as the most important for bank’s competitiveness. 66,7% of them decided that they are the most important assets. The second place was granted to human assets (33,3% of respondents). The third place went to organizational and innovative assets but they were pointed only by 11,1% of respondents each. Generally, according to banks’ managers, the average significance of different assets was as follows:
financial assets
‐ 4,9
human assets
‐ 4,6
market assets
‐ 4,6
innovative assets
‐ 4,4
organizational assets ‐ 4,3
The financial assets are definitely less important for customers. The average significance of these assets was 4,4. Similarly they pointed human, organizational and innovative assets as slightly more important ones. The average significance of these assets was 4,5. Surprisingly the less important significance was granted to market assets (average 4,0) – see figure 3.
Figure 3: The significance of bank’s intangible assets
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Monika Klimontowicz After general evaluation respondents were asked to form their opinion of particular intangible assets (see figure 4).
Figure 4: The significance of intangibles’ components Taking into account human assets’ factors both, banks’ managers and customers, have found them to be important ones. Among them for banks’ managers the most important are: a client oriented attitude and an ability to develop relations with clients. Whereas for customers the most important ones are knowledge and experience. Additionally banks’ managers were asked to decide how important are: a level of employees’ innovativeness (mean score – 4,3), a will to cooperation (mean score – 4,4), and a quality of leadership and management (mean score – 4,8). The second group of intangible assets rated by respondents were market assets. They are thought to be one of the most important factors which impact banks’ position on the financial market. Especially the image and reputation seem to be crucial for every bank activity because they are related with people attitudes, feelings and expectations (Jagelavicienie, Stravinskiene, Rutelione, 2006). However for customers among the market assets the most important are the ability to match bank’s offer with consumers’ needs and expectations and developing relations with clients. Surprisingly nowadays the traditional image and reputation factors as brand, logo, advertisement and promotion, an appearance of employees and bank’s departments, a quality of brochures, booklets and other materials, etc. are the least important for customers. Banks’ managers and customers’ opinions on the significance of image, reputation and banks’ marketing activity differ significantly. The last groups of intangible assets were organizational and innovative assets. They are connected with the new technical solutions leading to the improvement of the bank’s operations quality settlement procedures and speeding up the turnover of money. In the last decade, technical solutions, including the development of IT and the Internet, have become one of the key internal factors enabling banks to improve their management systems. In addition they contributed to the development of banking products and their distribution channels. A lot of customers are interested in Internet and telephone banking, as well as in mobile banking, which combines telephone banking with Internet banking. Modern distribution channels are definitely more important for them than traditional ones and they are the most important among all intangible factors. The second one is safe and comfort way of transactions’ authorization (mean score ‐5,0). Both factors are
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Monika Klimontowicz underestimated by banks’ managers. The results of the survey show that they pay too much attention to the factors referring to traditional branches which are less important for customers. Taking into account a web culture which creates a generation of people who live and work differently from previous generations the level of banks’ innovativeness will become more and more significant. Both, banks’ managers and customers, agreed that innovative assets are very important. Mean scores for almost all innovative factors are at the same level. Only the implementation of innovative procedures is underestimated by banks’ managers in the relation to customers’ scores. The survey results show some differences in opinion on the significance of particular banks’ assets in the process of gaining long‐term competitive advantage. Generally the largest difference concerns the role of financial assets. They are more important for banks’ managers than for customers. Taking into account elements of intangibles the customers’ most important factors are: electronic distribution channels (mean score – 5,1) and safe and comfort way of transactions’ authorizations (mean score – 5,0). Banks’ managers declared that the most significant are: an employees’ client‐oriented attitude and an ability to develop relations with client (mean score – 5,0) and an ability to match offer with clients’ needs (mean score – 5,0). As far as above mentioned factors are also important for customers, the other factors of huge importance for customers are underestimated by managers. On the other hand they used to overestimate factors connected with banks’ image, reputation and marketing activity.
3.4 Step 4: Estimating bank’s ability to effective use of its intangibles The next part of the research focused on banks’ ability to use intangible assets in the process of gaining competitive advantage. Banks’ managers were asked to decide if, in their opinion, bank uses intangibles effectively. Generally they thought their banks to be rather effective in using human, organizational and market assets. The grade for innovative assets was in the middle of the scale what meant neither effective nor ineffective. The customers were asked if they are satisfied with bank’s activity in the field of personnel, organization, innovativeness and marketing. They pointed that they were rather satisfied, especially in the field of human and innovation assets, but their grades were a little bit lower than managers’ grades with the exception of innovative assets (see table 3). Table 3: General efficiency of banks’ intangible usage Intangibles Human assets Organizational assets Innovative assets Market assets
Banks’ Managers 4,1 4,2 3,5 4,3
Customers 3,9 3,8 3,9 3,6
After general evaluation respondents were asked to form their opinion of the efficiency of particular intangible assets’ usage in the process of creating competitiveness (see figure 5). According to banks’ managers they are very good in the field of using human assets. Their employees are thought to be very professional, well‐educated, experienced, customer‐oriented and able to develop relations with customers. Unfortunately customers are not as satisfied as they should be taking into account the importance of these factors. Analyzing the data concerning market assets it is easy to notice that the ability to match offer with consumers’ needs and expectations received the lowest score among all market factors graded by customers. At the contrary, according to managers, banks’ ability to use that assets effectively is thought to be very good. Another factors are graded at the same level by both group of respondents. The organizational and innovative factors consist of traditional and modern factors. The traditional ones such as branch network, equipment and infrastructure received lower scores when they were graded by customers. On the other hand the modern ones such as electronic distribution channels, a quality systems and all innovative factors (level of service’s modernity, innovative product/services implementation, innovative procedures’ implementation) and new way of providing services were graded higher by them. A safe and comfort way of transactions’ authorization was graded at the same level by both groups of respondents.
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Figure 5: The efficiency of particular intangible assets’ usage in the process of creating competitiveness
4. Discussion Comparing the significance of intangibles’ factors with the managers and customers’ opinion on banks’ ability to use them in the process of creating competitiveness should be the foundation for indicating the directions of bank’s intangibles effective usage (see figure 7). The smallest distinction between the opinions on intangibles’ significance and efficiency concerns the human and organizational assets. The largest difference in managers and customers’ opinions concerns market assets. Taking into account innovative assets their significance is graded similarly by both groups of respondents but the distinction between the opinions on their efficiency is quite large. Increasing bank’s competitiveness requires finding out what particular intangible assets should be improved to make customers’ satisfaction much better. An analysis of customers’ opinion on human assets shows that:
employees knowledge and experience is much more important for customers than for banks’ managers,
the employees’ commitment and will to cooperate are definitely higher graded by banks’ managers then customers, but they are less important for customers than for managers,
the importance of service quality is at the same level in both group of respondents but it is graded lower by customers,
banks’ managers overestimate the significance of communication skills for customers and the employees ability to use them in the process of building relations with clients.
Taking into account these results bank should:
develop employees’ knowledge on bank and its competitors’ products and services,
increase the commitment with solving customers’ problems and their ability to explain difficult problems,
prepare the programme of skills and competences’ assessment from the perspective of bank’s long‐term value creation,
motivate employees to develop skills and competences which are the most important ones for customers.
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Monika Klimontowicz Significance 5,0
4,5
4,0
3,5
4,0
4,5
Efficiency
5,0
Human Assets Organisational Assets Innovative Assets Market Assets
Banks
Customers
3,5
Figure 6: The general significance and efficiency of bank’s intangibles In the field of organisational assets the survey’s results show that:
traditional distribution channels become to be unimportant for customers,
safe and comfort way of transactions’ authorisation is graded at the same level by both group of respondents and the grade is very good,
the banks’ managers underestimate the significance of banks’ procedures but customers’ opinion on them is better than their opinion,
the speed and punctuality of transactions’ significance is graded at the same level by both group of respondents but managers’ opinion on them is worst than consumers’ opinion.
Summarising the customers’ opinion on particular organisational assets it is even better that the managers’ opinion. Banks should only verify and restructure their distribution channels, especially the location of branches. The next analysed group of banks’ intangibles is innovative assets. The significance of all innovative intangibles is graded at the same level by customers and banks’ managers. All of them are very important in their opinion. The efficiency and standard of them is much better graded by customers. Thus the innovative assets are the only one group of intangibles which does not require any radical changes. However it is necessary to observe the activity of banks’ competitors and to monitor customers’ needs and expectations permanently. The analysis of market assets shows that:
brand, reputation, logo and the branches and employees’ appearance are still very important for banks’ managers but they are becoming the less important factors for customers,
banks’ managers also remarkably overestimate the banks’ ability to built long‐term relations with customers
the significance of attractive offers for loyal customers is considerably underestimated by banks’ managers; this factor has received the lowest grade among all intangible assets,
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the bank’s marketing activity is also overestimated by banks’ managers.
These results prove that the importance of traditional market activity decreases. In the nearest future using market assets in the process of bank’s competitiveness creation will need the reconstruction and the customer relations’ reinforcement. Banks should focus on gathering and analysing information about customers in order to manage customer‐oriented competitive strategy. It might be a challenge for banks because of their size and, sometimes, lack of speed in decision‐making and new ideas implementation. Undoubtedly banks are expected to focus more on customer‐driven solutions.
5. Conclusions In the response to unstable market environment commercial banks have shown a renewed interest in exploitation their internal resources in the process of gaining competitive advantage. Knowledge embodied in intangible assets has become crucial for that activity and in large extent influences banks’ competitiveness and growth. The proposed structure of bank’s intangibles reflects its specific character and take into account factors which create its long‐term value. From that perspective the most important are human assets and market assets. In today’s changing environment the increase of bank’s value is undoubtedly connected with process optimization and service technology. That is why the structure of bank’s intellectual capital should also include organizational assets and innovative assets. The survey results’ show that the factors which influence customers’ decisions on banking market in Poland are mostly intangible. The most important for them are: the access to products and services by internet and mobile, attractive financial conditions of cooperation with bank, branch’s location and trust. Surprisingly banks’ manager have not be able to indicate definitely what was important for customers and was the determinant of their decisions. It may mean that they do not really know what factors are important to their customers and as the result if banks’ market activity is based on right assumptions. Furthermore they still consider tangible assets to be more crucial for bank’s competitiveness than intangibles. The difference between the banks’ managers and customers’ opinion on the significance and efficiency of some intangible factors should make banks to rethink their future policy. It is worth to say that the importance of particular intangibles and their hierarchy for customers has being changed what has not been noticed by them. The analysis of intangibles’ significance and efficiency has been the base for formulating some proposals for increasing the efficiency of bank intangibles’ usage. Generally banks should focus on developing long‐term relations with customers. Research continually confirms the increasing role of intangible assets in the process of satisfying customers and gaining competitive advantage. Undoubtedly there is a significant correlation between satisfaction and repeated buying, brand loyalty and spreading a positive opinion of the product. In order to manage customer‐oriented competitive strategy banks should focus on gathering and analysing information about customers. It might be a challenge for banks because of their size and a lack of flexibility and speed in decision‐making and new ideas implementation. The results of the survey have established the role of particular intangible assets in the process of creating bank’s competitiveness on banking market in Poland and have indicated the directions of bank’s intangibles effective usage. Proposed competitive activities unable banks to be more customer‐oriented institution which implements customer‐driven solutions.
References Ittner, C. and Larcker, D. F. (1998) “Are non‐financial measures leading indicators of financial performance? An analysis of customer satisfaction”, Journal of Accounting Research, No. 2, pp.138–144. Klimontowicz M. (2012) “Banks’ Intangibles in Developing Relationships with Young Customers” Paper read at 13th European Conference on Knowledge Management, ECKM 2012, Universidad Politecnica de Cartagena, Cartagena, Spain Klimontowicz, M. (2011) “The concept of intellectual capital in a bank”, Paper read at European Financial System 2011 Conference of Masaryk University, Brno, Czech Republic, June Kristandl, G., Bontis, N. (2007) “Constructing a definition for intangibles using the resource based view of the firm”, Management Decision, Vol. 45 No. 9, 2007, pp. 1510‐1524 Loveman, G. W. (1998) “Employee satisfaction, customer loyalty and financial performance: An empirical examination of the service profit chain in retail banking”, Journal of Service Research, No. 1, pp. 18–31. Porter, M. E. (1998) On Competition., Harvard Business Review, pp.40‐42. Rogowski, W. (2006) Kapitał intelektualny jako generator nowych czynników konkurencyjnych, [w:] Kasiewicz S., Rogowski W., Kicińska M., Kapitał intelektualny. Spojrzenie z perspektywy interesariuszy, Oficyna Ekonomiczna, Kraków
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Effective Knowledge Sharing Through Social Technologies Jaroslava Kubátová Palacký University, Olomouc, Czech Republic jaroslava.kubatova@upol.cz Abstract: Social technologies available on the current Web 2.0 provide great opportunities for sharing and creating knowledge. Therefore, implementing social technologies within the framework of knowledge work entails one of the most significant activities carried out by companies today. The goal of the paper is to specify the greatest opportunities and also threats brought by the use of social technologies in terms of sharing knowledge and to recommend what kind of changes should the companies implement in order to use social technologies for knowledge sharing effectively. We have also examined if there are regional differences in the use of social technologies and how to deal with them in case of international cooperation. After a short state of the art description the terms knowledge sharing, social technology, social media and social network are defined. To achieve the goal of the paper, we have analyzed and compared four research reports from 2012: global research by the McKinsey Global Institute and three studies focused on different world regions (Europe, North America, the ASEAN countries). To carry out all the regionally focused research projects, the method of directly asking the managers was used. The results of the resultant analyses and comparisons of the research reports are further extended by the findings and predictions published by the Gartner agency at the end of 2012. In the next part of the paper we have determined the areas of company activities for which the use of social technologies is the most prospective. We have also documented to what extent companies use social technologies’ potential and what kind of regional differences exist. We have assessed whether the companies are successful using social technologies and have also determined the most common causes for failure. Finally, we have presented recommendations about how to make the application of social technologies for knowledge sharing more effective. The most important factors are not those of a technological nature, but rather are arguably connected to the ways of managing knowledge workers and the behavior of the managers. Keywords: social technologies, knowledge sharing
1. Knowledge sharing and social technologies Knowledge, in its different forms, has been increasingly recognized as a crucial asset in modern organizations (Bonifacio, Bouquet and Cuel 2002). Knowledge sharing is some of the fundamental means through which employees can contribute to knowledge application, innovation and ultimately a competitive advantage of the organization they work for (Jackson et al. 2006). Knowledge sharing is a deliberate act by which knowledge is made reusable through its transfer from one party to another (Lee, Al‐Hawamdeh 2002). The process of knowledge sharing has been widely studied for several decades and was reflected by many knowledge management experts in their works, for example Drucker (1999), Davenport and Prusak (2000) or Nonaka and Takeuchi (1995). Nevertheless, there is still a continuing debate about the measurement of the volume of shared knowledge, because knowledge sharing can occur in many different forms (written correspondence, face‐to‐face communication, through networking etc.) and also knowledge as such can have various forms. Behrang, Wongthongtham and Hussain (2010) proposed a knowledge sharing measurement model, which is a function of knowledge nature and trust among workers. Fuzzification in this model is possible. Lee (2002) proposed metrics which are well trackable on‐line, such as the number of links per respondent, frequency of advice seeking, the ratio of internal to external links, etc. The use of Internet‐based social technologies for knowledge sharing is a new phenomenon and its reflection in scientific literature is scarce. Present‐day knowledge in this field was published by Frank Leistner (2012) in his book Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media. Social technologies' entering life today was so quick that there was not enough time for a unified terminology connected to this phenomenon to originate. Therefore, let us first define the basic terms related to this topic. Social network is a set of relations formally created by objects (also known as knots), and reflects the relations between these objects. Objects (knots) are individuals, groups or organizations. While speaking about a social network on the Internet, we mean a combination of a webhosting service and a special search engine (Kadushin 2011). Internet social networks originate thanks to the available social media. Social media are interactive Internet platforms on which individuals and groups (users) share, co‐create, discuss and modify the contents (Kietzmann, Hermkens and McCarthy 2011). In the broader sense of the word it is possible to speak about social technologies (Chui et al. 2012, p.13). Social technologies are used by people for the purpose of
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Jaroslava Kubátová social interaction, for joint creating, extending and sharing of the contents. Social media (e.g. LinkedIn, Facebook, or Twitter), Web 2.0 tools (e.g. blogs, wikis, discussion forums, QaA pages) and collaborative tools including shared work environments (e.g. Chatter, Yammer, Work.com) can be included among social technologies defined in this way. For the purpose of this article we consider the term social technologies as the most suitable for general use. For us, social media are particular Internet applications, and the term social network is used to emphasize the importance of interpersonal links and interactions of the users. External social network means a network accessible to the public (e.g. Facebook, LinkedIn, or Google+). Internal social network is a closed company network accessible only to the company's employees. External networks, however, also provide tools which can be used only by a closed group of persons, and, on the contrary, an internal network can be extended in order to have a part accessible to the public.
2. Areas of using social technologies in companies The number of users of social technologies in 2012 exceeded 1.5 billion and social technologies are used by over 70% of companies in the world, out of which 90% declare that using social technologies brings them some benefits (Chui et al. 2012, p.30). We can determine ten particular areas in which the application of social technologies increases the performance of the organization thanks to sharing knowledge both among the company's employees and subjects outside the company.
2.1 Establishing and applying customers' opinions Thanks to social technologies it is possible to get an overview of the customers' opinions of a particular product or brand, competition and other customer needs. These findings can then serve as a source for further decision‐making within the organization. One of the approaches lies in monitoring and analyzing of what the users of social technologies express. This approach is usually denoted as sentiment analysis. Based on the results it is possible to immediately react and improve both the sales of the product and the brand name. Another approach lies in active communication with customers on social networks, discussion forums, etc. This way the company can attain necessary feedback on the product.
2.2 Collaboration on the development of a product By the application of social technologies, companies can include a wider group of people in the development of a product than only their internal employees. One of the ways is to monitor and acquire customers' opinions. Another way is the application of crowdsourcing. This means that the company appeals to a wider group of participants (the crowd) to submit their ideas and proposals. These are then assessed (e.g. by the management, experts or again using crowdsourcing), and the best‐assessed proposal is then realized.
2.3 Monitoring and predicting demand Thanks to information shared on social networks it is possible to react to locally different demand for a product. In this case, information is valuable not only from the customers but also from staff, for example the sales people. Therefore it is appropriate to enable the employees to access the internal social network where they can describe the situation at their branch. Based on this information the company can quickly react in order to satisfy the customers' needs.
2.4 Searching for suppliers Through social media companies can find external suppliers of both physical commodities and external coworkers for solving particular projects or problems. These can be both other companies and independent social technologies' users.
2.5 Marketing communication Marketing communication is an important area of social technologies' application in marketing. Social technologies enable communication with target groups at very low expenses. The company can support the establishment of customer communities, enable their mutual communication, acquire necessary knowledge from this communication and directly influence it.
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2.6 Creating and strengthening sales opportunities Social technologies can support both the B2B and B2C areas. In case of B2B, sales representatives can establish mutual collaboration, find possibilities to do business with each other, acquire references and contacts to new partners. In case of B2C, social technologies' users' information about important events in their lives can be used, and they can be offered appropriate products. Strengthening a company's position on the market is connected to social intelligence, which is a set of activities used by the companies to ascertain strategic information about their competitors, which has been posted on social networks. It is a very complex analysis and synthesis of various information found on social networks, the result of which can be surprisingly detailed and bring an updated picture of the activities and intentions of their competitors (Harryson, Metayer and Sarrazin 2012).
2.7 Social commerce Social commerce lies in the addition of sales functions to the seller's social media, or, on the contrary, in adding social features to the seller's Internet store. In the first case, for example, it can concern a discussion forum on a product created by the seller themselves. The product can be directly ordered from this forum, too. In the second case, for example, the customers can recommend a product they have bought to their friends, or enable their friends on a social network to see what they have purchased. On the contrary, they can see what their friends have bought and if they are satisfied with the product.
2.8 Customer care Customer care can be significantly developed through social technologies in many ways. Social media can, for example, substitute or complement call centers. The questions of the customers and answers to them can be used to create an easy‐to‐use database (FAQ). Social technologies can include product‐use instructions, user recommendations, etc. in various forms, for example demo videos.
2.9 Communication and collaboration within the organization Social technologies can enable easier collaboration and make communication more effective, reduce time necessary for personal meetings, and contribute to sharing knowledge and good practice among employees, teams and whole organizations. Social technologies are very important to companies which have more branches in different places. Using internal social technologies, even remotely located workers can effectively collaborate in real time, create teams and share knowledge. Team members can communicate both synchronously and asynchronously. For synchronous communication they can use voice or written communication, and modify documents together. For asynchronous communication team members can use, for example, joint blogs, wikis or discussion forums, and modify their contents. With an appropriately designed social platform it is possible to attain an effect similar to a personal meeting of the team members.
2.10 Identifying talents and assigning the most suitable tasks to them Social technologies have expanded the area in which companies are able to contact their potential employees. This so‐called social recruitment is a fast‐growing practice these days. Companies browse social networks (e.g. the professional network LinkedIn), and address suitable candidates that have their profiles on the network. The candidates are addressed regardless of the fact that they are actively looking for a job or not. Internal social networks of companies can be used in a similar way. The workers shall state all their knowledge on their profiles, regardless if they use it in their current positions or not, and also state what kind of projects they have worked or currently work on, etc. While creating a team for a new project, even a big company can easily find the most suitable workers. Thanks to collaborative tools that are available on social networks, it is not necessary for team members to work in the same place. The potential of using the workers' knowledge effectively is thus significantly increased. It is obvious that using social technologies can bring the biggest benefit to those companies, whose products are based on intensive application of knowledge. An example can be professional services and consultancy, education, creating software, Internet services, entertainment industry, etc. Making knowledge work more effective represents up to two thirds of the total benefit companies can achieve by the application of social technologies. This effect has been achieved thanks to improved collaboration, coordination and communication. Knowledge workers who must maintain comprehensive interaction with other coworkers and
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Jaroslava Kubátová make independent decisions (e.g. managers, developers, lawyers, sellers and many others), spend approximately 65% of their work hours communicating and collaborating with the others. They spend almost one third of this time writing, reading and answering emails, and another one fifth of this time they gather information necessary for fulfilling their tasks (Chui et al. 2012). Thanks to the application of social networks, the time necessary for handling emails could decrease by more than a quarter, the time used for searching for and gathering information could decrease by more than a third, and internal communication could be up to 35% more effective (thanks to easier identification of knowledge bearers and quick establishment of contacts). According to a different research report from 2011 published by the Fonality company (Webtorials 2011), knowledge workers lose up to 36% of their work hours by trying to contact other persons, searching for information and organizing appointments. If these activities are replaced by social technologies' features, a knowledge worker can devote to their main work activity, which brings value to their organization, as much as two more hours per day. According to an estimate made by the McKinsey Global Institute, total work productivity of knowledge workers can, thanks to the application of social technologies, increase by up to 25%. The most significant areas that can be continuously improved thanks to the application of social technologies, and which are found across every organization, are communication, knowledge sharing and collaboration.
3. The application of social technologies in companies in various parts of the world In the following part of the article we have analyzed and compared the results of three research studies dealing with the application of social technologies by companies in various parts of the world: in selected European countries, in the U.S.A. and in selected ASEAN countries. These three world regions can be seen as the main economic competitors nowadays, however, at the same time international cooperation is strengthening. For this reason we consider regional comparison beneficial. For our purposes a secondary analysis of the available research studies was used. We have chosen research studies containing the latest data, which is important due to extremely rapid development in this area. The results of the research studies are comparable due to the fact that the methodology used in case of all three studies was the same – interviewing the managers. The research methodology is explained in the below‐cited research studies. Nevertheless, these research studies are not representative surveys, but rather case studies from these different world regions.
3.1 The application of social technologies in selected European countries The research was focused on the opinions of particular managers of big and medium enterprises in France, Germany, Italy, the Netherlands, Spain, Sweden, and Great Britain. These countries were selected because they are considered as the most progressive social technologies users in Europe. A total of 2,700 managers were questioned. The research was carried out jointly by the companies Google and MillwardBrown (2012). Google's interest in such research is understandable since this company also offers its social technologies solutions to other companies. In the companies that were subject to the research the application of social technologies is relatively extensive. Three quarters of them use internal social networks and one third of them use also external social media such as Facebook, LinkedIn, Google+ a Twitter in daily work. Among the most common purposes for which companies use social technologies are:
Quick search for persons, knowledge and information
Collaboration and sharing knowledge
Extending personal contacts and building professional relations, creating communities
Replacing email communication
Managers also think that social technologies shall have a significant impact on business strategies of the companies. They will be significant for searching for, acquiring and keeping talented workers. Managers also estimate that the application of social technologies has increased productivity by 20%. Just by decreasing the volume and contents of email communication, faster searching for coworkers and reducing travel to meetings a worker can save two hours per week. The research has also shown that workers who have access to social networks are more satisfied at work than those who cannot use them. Workers who use social networks
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Jaroslava Kubátová appreciate better communication with their colleagues. Collaboration becomes more effective especially in those cases when the synergy of geographically distant workers is necessary. Managers expect even better effects of using social networks in the future. In their opinion, a worker can save more than three hours per week while performing each of the following, up to now traditionally performed – activities:
Reading and writing emails
Traveling to meet clients
Traveling to meetings and to other branches
Internal meetings
General discussions about company problems
Searching for information and persons
Fulfilling work tasks of a knowledge nature
The most common users and supporters of social technologies in European companies are senior managers. By setting their example they help develop the use of social technologies in the whole company. European managers are convinced that social technologies support the development of creativity and innovations, just like they help acquire talented coworkers. Besides that, the speed of the decision‐making process increases too. Managers expect (80% out of those questioned) that in the future the use of social technologies will lead to further development of companies and improvement of team work and sharing knowledge. It will be increasingly easier to use virtual teams of workers. In general, we can expect a further increase in necessary creativity and innovations. One half of the managers also mentioned the fact that companies which do not adopt the application of social technologies, will not stay on the market.
3.2 The application of social technologies in the USA Based on research (Larcker, D.F., Larcker, S.M. and Tayan, B. 2012) in which 184 top managers took part, the most frequent purposes for the application of social technologies in the U.S.A. are:
Communication with customers
Promotion and sale of products
Marketing research
Monitoring competition
Communication with employees and stakeholders
According to the authors of the research many companies are too slow while implementing social technologies or do not use them correctly. This can be substantiated by the fact that only 22% of the managers have stated that they understand the importance of social media for their company very well. A general question whether the companies use social technologies was not included in this research. However, the managers were asked whether they use social media themselves for business purposes. Sixty‐three percent of responders responded positively, with the main purpose was declared to be professional development (reading blogs and forums, watching videos). Based on this we can assume that managers of companies do not develop sharing and creating knowledge through social media. Local companies may realize how important personal contact between workers is, and might prefer hiring a worker directly for their company to creating virtual teams, even if this is connected to higher expenses. Companies such as Google, Facebook and others, which behave like this, probably know that it is beneficial for them. At the same time, this does not mean that they do not use social networks. For example, Facebook employees working on a related task, create groups not only in terms of organization but also as a group on Facebook. Within this group they use its features for communication and sharing knowledge. The groups are associated in a community, which ensures the possibility of more extensive sharing knowledge and communication. Nobody is allowed to create work groups on a different social medium, the reason being protection of company data. In short, not only do programmers create Facebook, but they also actively use it for their work.
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3.3 The application of social technologies in selected ASEAN countries Similar research (Mortensen 2012) was also carried out in the Asia‐Pacific area, in selected ASEAN countries, in which 1,000 companies were researched. This research was supported by Microsoft. More than a half of the companies (56%) use social technologies, another 26% are planning to do so in the nearest future. The most important areas of using social technologies according to the managers are:
Customer care
Communication with partners and customers
Employee education and development
Sharing knowledge
However, when the managers were to answer why using social technologies is important, they also mentioned different areas:
Growth of employee satisfaction
Effective retention of company knowledge
Easier information sharing
More effective problem solution
Improving collaboration
Easier searching for information and experts within their organization
Nevertheless, according to responders, social technologies are not supposed to replace traditional communication means (telephones, emails), but complement them. Almost all the responders have mentioned that the strategies of applying social technologies are in the competence of higher management and top management. Therefore they sometimes get in conflict with their IT departments, especially due to the question of data safety.
3.4 Regional differences in the application of social technologies The results of the individual research studies confirm the estimate of the McKinsey Institute that over 70% of companies use social technologies. However, there exist regional differences in purposes and ways of their application. From the point of sharing and creating knowledge on social networks, Europe is the most progressive region. Here we have noticed a strong inclination to social technologies' replacing traditional ways of communication including emails. Effective application of social technologies is considered a competitive advantage. Companies in the U.S.A. use social media namely as a marketing tool and tool for communication with customers. Not even the managers themselves use social technologies as a tool of collaboration. It can be assumed that the local environment still puts a lot of emphasis on personal meetings among coworkers. Companies in the ASEAN countries are undergoing an era of implementation of social technologies. The application of social technologies here corresponds to cultural characteristics of this area, especially to collectivism. Management of the companies understands the importance of social technologies, and considers the development of their application as their task. However, social technologies in this area, unlike Europe, are supposed to complement and extend traditional ways and tools of communication.
4. Estimated success rate of using social technologies and its factors Implementation of social technologies into company processes differs from all the previous changes connected to new technologies. Thus far used technologies have been implemented, the workers trained how to use them, and this usage was enforceable. Because social technologies serve primarily for communication, sharing and creating knowledge, it is impossible to force anyone to really share their knowledge. Even if implementing social technologies in companies will continue, there is a risk of failure. According to a forecast made by the Gartner agency (2012), 80% of company activities connected to the application of social technologies planned to be realized by 2015 will fail. Two main reasons for this will be mistakes in managing knowledge workers and overestimating the importance of a technological solution at the expense of motivating the users. Companies
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Jaroslava Kubátová also must be aware of the risks connected to the use of social technologies such as revealing strategic information, which could be caused both by intentional and unintentional conduct of employees on social networks. Technically, the implementation of social technologies is relatively easy. To start using social technologies more extensively, a company needs support from the management, namely top management. It is common knowledge that the culture of every organization is significantly influenced by the conduct of its leaders. Implementing social technologies into the work of a company is an important organizational but also cultural change. In order to give the application of social technologies some sense and achieve the desired effects, all the workers must be willing to change the existing ways of working, be willing to use social technologies, openly communicate, share their knowledge and collaborate with colleagues from remote places who they do not know personally, etc. Managers must count on the fact that communication schemes in their companies will be simpler, and that employees will be able to communicate directly with each other without informing their superiors. Such changes can be started only from the top. Implementation of social networks must be endorsed by top management of the company, and the same managers must start using social technologies, as they expect all their employees to. The employees must know how and for what purpose the social technologies selected by their company are to be used, and also must understand what kind of behavior is expected of them, and how it will be supported. This means that changes in the area of motivation, evaluation and remuneration of employees must be considered in advance. The company also has to consider possible risks of using social technologies, and in connection to this, stipulate rules of its employees conduct. Companies that are able to use social technologies effectively can also expect an increased interest of young talented job applicants. For young knowledge workers the possibility to use social technologies is one of the main motivators (PwC 2012). In the future, the most attractive social technologies will be the mobile ones (those that can be used in tablets and smartphones), and will include elements of gamification. These recommendations can be applied in any world region, however, cultural differences must always be considered.
5. Conclusion In this article we have proved that social technologies have, in the short period of their existence, become a phenomenon significantly influencing activities of companies. Our study and conclusions are limited by the research studies used because they are rather regional case studies and not representative surveys. In spite of that, processing these secondary data can give us an idea of the development of using social technologies in today's business world. There are a number of areas where social technologies are put to use, but the most important ones are support of communication and collaboration inside and outside of the companies. Also, the bigger the share of knowledge work on the performance of an organization is, the bigger contribution can effective application of social technologies bring. The application of social technologies is rapidly developing in all the economically significant parts of the world. However, it brings the features of cultural differences, which is important knowledge in case of intercultural collaboration. Because the application of social technologies for knowledge work is completely new, it is connected to a huge risk of failure. This can be avoided if technical solution in companies is not overestimated at the expense of necessary changes in the company culture, and the management motivates knowledge workers through their own behavior to achieve the workers' desired conduct. We consider managerial methods which support sharing and creating knowledge through social technologies as an important part of future research. To evaluate these managerial methods also the models of the measurement of the volume of shared knowledge must be further developed.
References Bonifacio, M., Bouquet, P., and Cuel, R. (2002) “Knowledge Nodes: the Building Blocks of a Distributed Approach to Knowledge Management”, Journal of Universal Computer Science, 8(6), pp 652‐661. Davenport, T. H. and Prusak, L. (2000) Working knowledge: How organizations manage what they know. Harvard Business Press, Harvard. Drucker, P. F. (1999) Management challenges for the 21st century. HarperCollins, New York. Gartner (2012) “Gartner Says 80 Percent of Social Business Efforts Will Not Achieve Intended Benefits Through 2015”, [online], Gartner, www.gartner.com/newsroom/id/2319215. Google & MillwardBrown (2012) “How social technologies drive business success”, [online], Millwardbrown Libraries, www.millwardbrown.com/Libraries/MB_Articles_Downloads/Googe_MillwardBrown_How‐Social‐Technologies‐ Drive‐Business‐Success_201205.sflb.ashx. Harryson, M., Metayer, E. and Sarrazin, H. (2012) “How ´social intelligence´ can guide decisions”, [online], McKinsey Quartly, www.mckinseyquarterly.com/How_social_intelligence_can_guide_decisions_3031.
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Jaroslava Kubátová Hu, C. and Racherla, P. (2008) “Visual representation of knowledge networks: a social network analysis of hospitality research domain”, International Journal of Hospitality Management, 27(2), pp 302–312. Chui, M. et al. (2012) “The social economy: Unlocking value and productivity through social technologies”, [online], McKinsey & Company, www.mckinsey.com/insights/mgi/research/technology_and_innovation/the_social_economy. Jackson, S. E., Chuang, C. H., Harden, E. E. and Jiang, Y. (2006) Toward developing human resource management systems for knowledge‐intensive teamwork. Research in personnel and human resources management, 25, pp. 27‐70. Kadushin, Ch. (2011) Understanding Social Networks: Theories, Concepts and Understandings, Oxford University Press, New York. Kietzmann, J.H., Hermkens, K. and McCarthy, I.P. (2011) “Social Media? Get serious! Understanding the functional building blocks of social media”, Business Horizons 54(3), pp 241‐251. Larcker, D.F., Larcker, S.M. and Tayan, B. (2012) “What Do Corporate Directors and Senior Mangers Know about Social Media”, [online], The Conference Board Trusted Isigihts for Business Wordwide, www.conference‐ board.org/publications/publicationdetail.cfm?publicationid=2332. Lee, C. K. and Al‐Hawamdeh, S. (2002) “Factors impacting knowledge sharing” Journal of Information & Knowledge Management, 1(01), pp. 49‐56. Lee, L. L. (2000) “Knowledge sharing metrics for large organizations” Knowledge management–Classic and Contemporary Works, MIT Press, Cambridge, MA, pp. 403‐419. Leistner, F. (2012) Connecting Organizational Silos: Taking Knowledge Flow Management to the Next Level with Social Media. Wiley, Hoboken. Mortensen, C. (2012) Ready for the Next Level: Enterprise Social in ASEAN (Excluding Singapore), IDC, Singapore. Nonaka, I. and Takeuchi, H. (1995) The knowledge‐creating company: How Japanese companies create the dynamics of innovation. Oxford University Press, New York. PwC (2011) “Millenials at Work”, [online], PwC Managing tomorrov´s people, www.pwc.com/gx/en/managing‐tomorrows‐ people/future‐of‐work/download.jhtml?WT.ac=mtp‐future‐hp‐panel‐2. Webtorials (2011) “Fonality’s 2011 Report on UC and Cloud‐Based Srvices for SMBs”, [online], Fonality Talking Business, http://cdnso.fonality.com/lp/whitepaper/pdf/2011_SMB_UC_Cloud.pdf. ZadJabbari, B., Wongthongtham, P., and Hussain, F. K. (2010) „Ontology based approach in knowledge sharing measurement“ Journal of Universal Computer Science, 16(6), 956‐982.
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The Manufacturer, the Screener, the User, and the Scientist: Producing and Circulating Information and Knowledge About Equipment Monique Lortie1, Angel Alberto Toyos Alvares1, Steve Vezeau1 and Maud Gonella2 1 Université du Québec à Montréal, Montréal, Qc, Canada 2 Institut de Recherche en Santé et Sécurité du Travail, Montréal, Qc, Canada Lortie.monique@uqam.ca angelalbertotoyos@yahoo.com Vezeau.steve@uqam.ca Gonella.maud@irsst.qc.ca Abstract: This paper addresses two equipment‐related issues: the choice of appropriate equipment on the one hand, and the development of equipment that meets end‐user needs on the other. These issued were explored in two very different cases and contexts: expensive equipment ‐ forklifts ‐ in medium‐sized firms ‐ and inexpensive equipment ‐ kneepads ‐ in micro‐sized firms. The study investigated these issues through the catalogues and brochures, seen here as relay tools between the manufacturer and the users. These latters provide good insight on what is understood of the user’ needs and what is integrated from the scientific literature. Two type of users were considerer: the equipment’ screener and the equipment user. The study shed light on the gap between the information provided by manufacturers and what screeners seek, as well as the gap between what is described in the catalogues and what the end‐users seek. It shows also the gap between the screener – as relay agent – and the end‐user. How relay tools and relay agents may play a crucial role in the capture, organisation, and circulation of information is discussed. Keywords: forklift truck, kneepads, purchase, catalogues, tacit knowledge, relay tool, relay agent
1. Introduction The development and selection of adequate work equipment is an important issue in occupational health and safety (OHS). Proper equipment can improve efficacy and efficiency while providing health and safety protection. To do so, the proposed equipment must meet the users’ needs, and the purchasers must make the appropriate choices. On the one hand, manufacturers who want to remain competitive need to produce innovative equipment that stands out from other equipment and meet or even go over needs. This implies putting in place a process that integrates user‐derived information and scientific knowledge, in particular norms and recommendations. On the other hand, to make the best selection, the managers must understand the employees’ needs ‐ involving sometimes different groups of people, with different needs, such as the operators and the maintenance staff ‐, and translate them into technical characteristics. This requires a minimal understanding of work activities, which constitutes the core of research in ergonomics. In fact the network of exchange may be quite complex. As showed in the figure 1, the flow of information between the manufacturers and the users is usually mostly indirect; it usually transits through diverse relays or agents, such as the representatives, the distributors and the screeners, whom by virtue of their position, develop knowledge about the needs, contexts and conditions. They are not professionals in knowledgeable transfer or management – or knowledgeable brokers, or knowledgeable officers ‐ but, through their role and status, they facilitate the capture and the circulation of known information and knowledge (Lortie et al, 2012). They may relay information and knowledge between organisations –the fabricants and the enterprise‐ customers as well as inside the organisations.
The suppliers, purchasers, and manufacturing representatives may be seen as typical relay agent between two organisations, and supervisors as relay agents. In this relay chain, the screener (selectionneur in French) may play a crucial role. In fact, it is usually not an official function but rather a role that may be filled temporarily by someone who is familiar with the equipment to be purchased. That person will screen what is proposed on the market, in order to propose what would be the most appropriate choices to the decision maker. He has to interface between at least three groups: the tool or equipment fabricant (or its representatives), the enterprise users and concerned employees (e.g. maintenance staff) and the management. To play adequately
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Monique Lortie et al. this role, the screener needs to understand and to translate the characteristics offered in terms of “need” and vice versa. In small businesses, the user is of course generally the screener and the decision maker. What is at the heart of the final decision is therefore the capability to connect the needs, the context and the technical characteristics.
Figure 1 Flow of information between the manufacturer/designer and the screener/decision maker and the end user (Toyos, 2013) The suppliers, purchasers, and manufacturing representatives may be seen as typical relay agent between two organisations, and supervisors as relay agents. In this relay chain, the screener (selectionneur in French) may play a crucial role. In fact, it is usually not an official function but rather a role that may be filled temporarily by someone who is familiar with the equipment to be purchased. That person will screen what is proposed on the market, in order to propose what would be the most appropriate choices to the decision maker. He has to interface between at least three groups: the tool or equipment fabricant (or its representatives), the enterprise users and concerned employees (e.g. maintenance staff) and the management. To play adequately this role, the screener needs to understand and to translate the characteristics offered in terms of “need” and vice versa. In small businesses, the user is of course generally the screener and the decision maker. What is at the heart of the final decision is therefore the capability to connect the needs, the context and the technical characteristics. On its side, the fabricant organises and transfers information on its products through catalogues and brochures. They may be seen as interface or relay tools reflecting the manufacturers’ understanding of customers and user needs. Interface design in itself constitutes an important area of research in human factors, but for the most part, it focuses almost essentially on computer and software interfaces, and little on this type of interface. In addition, catalogues and brochures may be seen also as a relay tool between the fabricant and the scientific community: their analysis may help to understand what is integrated from scientific literature, and is the scientific literature concerned by their contain. So, equipment is an area where knowledgeable management and transfer represent an interesting challenge. The brochures and catalogues diffused may be seen as artefacts reflecting the outcome of this management and transfer activity between various relays and groups of interests. They are also quite interesting as they capture in fact tacit knowledge, which is known to be more difficult to capture (Grant, 2012). The goal of our research in this area was to better understand how much the information provided by these relay tools met the users’ and screeners’ needs, what is integrated from the scientific literature and how far the scientific literature cope with the implicit needs reflected through these artefacts. A second aim was to better understand the role of relay agent an their ability to capture and transfer information.
2. The studied sectors and methodology Our interest covers two very different sectors: the very small and average size enterprise which both differ considerably in terms of structure, tools involved, potential relay agents and needs in knowledge management
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Monique Lortie et al. and transfer. In this section, we describe their main characteristics and the contexts in which these studies were conducted.
2.1 Flexible floor layers and kneepads This construction sector is made up of a multitude of very small or even micro enterprises that install linoleum of fixed carpet. The larger ones hire about 30 workers. The owner is systematically a floor layer himself. A floor layer may work with for several small enterprises. The floor layers ‐ around 1 600 are officially registered ‐ are associated in a federation; a prevention mutual group provides information on and training for occupational health and safety issues. At pro rata, they would be 60 000 in USA. They usually choose to work in the commercial or in the residential sectors. Most of the time, the job giver is the merchant. The work is performed 60% of the time in a kneeling position (Jensen and Friche, 2008). Musculoskeletal disorders are important, knee disorders being what is the best documented. Studies show that about one on six suffers arthrosis after fifty years old (Jensen et al, 2000). In USA, 6% of all knee’ injuries are reported by floor layers, which represents 108 times the national average (Tanaka et al, 1982). This sector is having more and more difficulty in recruiting new workers and in retaining older ones, even though the pay may be very interesting. The technology level is low; the main equipment used is the carpet stretcher (including the knee kicker which is activated by knee impact). The main protection equipment is kneepads. The workers usually buy their own equipment. In Montreal area, there is two specialized distributors. The basic aim of this research‐action was to better identify difficulties encountered by the floor layers in order to determine potential changes that would improve their work conditions. An indirect issue raised was to see how we could improve the information flow transversally between the workers and bottom‐up to the distributor and the fabricants. The idea was to develop an assessment tool for the equipment bought in order to favour the flow of information between the workers but also towards fabricants. The kneepad was picked up because of its importance and the variety of models encounter during preliminary field studies. This product has a short lifespan and manufacturers regularly propose new models. The work activity were observed (e.g. knee posture, area of the knee in contact with the floor, displacement on the floor, etc.; 34 workers on 13 building sites) and 31 workers were questioned on their on kneepads (the model chosen, how they chose their kneepad and their appreciation). The descriptions of 44 models proposed by ten fabricants were collected from the Internet and visits to the two specialized stores. The information provided was classified according the technical characteristics (e.g. material used, attach system, form, etc.) and the qualities underlined (e.g., comfort resistance, etc.).
2.2 Forklift truck operators Forklifts are used in a variety of work industries, both inside and outside (e.g., wood courtyard). It is seen as a significant purchase because of its high cost (± $125,000). Its use leads to the development of cumulative trauma disorders, in particular in the back, the two main causes being vibrations and the postures adopted to see better. However, it is above all safety issues that garner most of the attention because of their potential severity (permanent invalidity, amputation, death; Vezeau et al, 2009). The choice of a forklift that properly meets the needs of users and maintenance workers is therefore important. A first field study was conducted to document the interactions between the characteristics of forklifts and their operation and safety (Vezeau et al, 2009). In the following studies the information disseminated by the five main manufacturers on their forklift through 23 catalogues (and 5 web sites) was analysed. The various characteristics of the lift truck were grouped in six subsystems (e.g., controls, cabin, mechanical system), covering 38 elements themselves divided in 74 characteristics in order to be able to compare the proposals. These characteristics were identified from three sources: the literature, the previous field study conducted with the operators, and the catalogues themselves. All written statements were colligated and classified through this grid (visual data were not covered in this analysis). In the next study, nine screeners were interviewed on their selection experience, their use of catalogues, and their understanding of the information proposed; they were asked to assess 37 proposals extracted from these catalogues. Finally, 40 operators were asked to assess the last model purchased; they were also questioned about the importance of a set of forklift characteristics (for more information, see Toyos, 2013).
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3. Results The first section is related on the catalogues and brochures as interface tools between the users and the manufacturers. In the second section, the integration of scientific data in the material diffused is examined.
3.1 Interface between the users and manufacturers: catalogues and brochures 3.1.1 Kneepads Nineteen different materials were mentioned. The worker had the choice between flat or curved, flexible or rigid kneepad. It could be fastened with a simple elastic band or a system of straps (1, 2 or 3) that were equipped or not with various types of cords. Usually, the manufacturer highlighted three qualities (comfort, knee protection, and adaptation to the work), but they usually emphasized one aspect in particular. So, even a piece of equipment not especially sophisticated poses a problem of choice. In Table 1, what floor layers workers sought and what was proposed in brochures is compared. As it can be seen, there is a significant gap between both perspectives. For some items, the fabricant insisted on qualities attributed to their products and the workers, insisted of problems to avoid. For example, the most important comfort issue for the workers was the lack of aeration in the kneepad. Sweat and heat built‐up was a major problem for them. To improve aeration, many used only one strap kneepad, even if it reduced kneepad stability. So strap adjustments’ finesses were never an issue for them. For other items, such as the floor displacement, the worker referred to what they needed to be able to do, and the fabricant to the type of surface. Several fabricants insisted on the capacity of the padding to protect against impacts (the knee tender is activated with the knee). This issue was never raised by any of the 20 workers. In fact, the kneepad is systematically removed when the knee kicker is used (to achieve the accuracy needed). Table 1 Advantages proposed by the manufacturer and what the floor layers seek Item Comfort Strap Movement Postures Protection
Manufacturers Flexible, light, and soft material Keeps kneepad well in place; adjustable Can move on different surfaces (hard, fragile) Permits easy postural changes Against knee kicker impact and cumulative trauma disorders
Floor layer installer Avoid humidity and heat, No compression Allows to walk, slide, pivot, and swing on knee Ditto Against nails
3.1.2 Forklifts The first analyse conducted aimed to verify if the catalogues covered all the characteristics identified, especially those pointed by the forklift operators, and if in the same way. As show in Table 2, altogether, the catalogues covered 80% of the 74 characteristics identified (12 don’t concern the operators; e.g. the maintenance). The 12 characteristics that none of the 23 catalogues mentioned, were pointed by the operators because of their impact on comfort, efficiency, and safety. For example: wheel dimension is seen as important because a wider diameter absorbs shocks better (comfort issue) and allows managing shortcuts through rougher zones (when working outside; efficiency issue). Pedal dimension has an impact on efficiency and comfort: usually, operators prefer bigger pedals because they can be operated more smoothly. Light size has an impact on safety: co‐workers see large lights better. As shown in Table 2, what was treated varied considerably from one manufacturer to another. For example, in the case of electric forklift, less than a sixth of characteristics were covered in one catalogue. In the best case, two thirds of the characteristics were covered. Nevertheless, the amount of information provided is considerable as up to 135 different proposals were collected. Here, two descriptions were considered to be different if they led spontaneously to two different interpretations (e.g., ‘two‐spoke steering wheel’ vs. ‘hydraulic steering’; ‘spacious cabin’ was considered equivalent to ‘roomy driver compartment’). Some catalogues covered extensively a system, others barely. For example, one forklift catalogue provided information on 13 control’ characteristics and another one, none. So the catalogues present a huge quantity of information to manage and it is difficult for a screener to compare the proposals (For more details, see Toyos, 2013).
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Monique Lortie et al. Table 2: Coverage of forklift characteristics (internal combustion and electric) by the manufacturers Refer to
General Cabin Controls Communication Mechanical Syst. Maintenance Total
Internal combustion # of characteristics covered Descriptio ns All Range Media # manuf. n 10 5 to 10 8 28 16 4 to 13 10 38 19 4 to 13 10 37 3 0 to 3 2 6
Electric # of characteristics covered All manuf. 12 16 19 4
Range 7 to 8 0 to 8 0 to 13 0 to 2
Media n 8 5 5 1
Descriptio ns # 48 35 31 7
10
1 to 7
3
16
7
2 to 6
3
9
4 62
0 to 4 23 to 41
2 33
7 132
3 61
0 to 2 10 to 39
2 21
5 135
A second analyse was conducted on 43 proposals (related to 25 characteristics) in order to determine the type of information provided: was it of a general nature (e.g., presence of the characteristic is mentioned), specific (i.e., descriptive data) or qualifying (e.g., good visibility)? One quarter of the proposals were found qualitative (e.g., spacious, good visibility, comfortable) and one quarter, general (e.g., adjustable seat, dimensions respect norms). In those cases, one can assume that the value of the information provided is limited. In about one third of the proposals, the information could be considered as not useful enough to distinguish between two forklifts, mostly because: all forklifts had this item (e.g., an adjustable seat) or the information was too difficult to interpret (e.g., 17.5º right rotation, 20º left rotation). In the next study, nine screeners were questioned on their using of the catalogues (see Table 3). About half the times, they assessed that the information was difficult to find. They almost always found that it taught them little (94%); most of the times, it did not help them to decide (79%). Table 3: Screener’ s assessment of the information provided in the catalogues Sub system
General
Very important n=54 9
Difficult to find n=48* 5
Learned little n=48* 6
Insufficient to decide n=48* 6
Cabin
2
7
7
7
Controls
4
5
8
6
Communication
0
0
8
7
Maintenance
7
6
8
7
Mechanical system
8
0
8
5
Total (%)
30 (63%)
23 (48%)
45 (94%)
38 (79%)
Dominant comment Incomplete: you need to talk with the representative. Visual material is missing. Difficult to interpret: you need to try it; a lot of photos, but lack of descriptions. Difficult to interpret: does not tell if it does the job. Little information, but not an important issue. Incomplete: you need to talk with the representative. No information on service quality and contract terms. Incomplete: no information on reliability; difficult to interpret, too complex; no link with the actual work.
* One participant did not consult the catalogues Also, 44 proposals (related to eight characteristics) were extracted from the catalogues. For each characteristic, the screener was asked to pick the proposal(s) that were meaningful to them, the proposal they would retain, and what more they needed to know. For example, six proposals deal with the steering wheel adjustment: adjustable; over 38°; in height, back, front; column adjustable; with memory; in height with memory. In this case, eight out of nine screeners picked‐up the indication of an adjustable column as meaningful and seven, as their choice. They would however have liked to know its position in relation to the forklift operator. Overall, only 16% of the proposals presented were considered as meaningful by at least four screeners. Finally, for five of these eight characteristics, no proposal was clearly favoured. Overall, all the screeners at some point during the interview, insisted on the importance of the representative in filling in the missing information and helping to provide information pertinent to their context. Representatives were seen as being able to match the
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Monique Lortie et al. screeners’ needs with the manufacturers’ proposed products. In the subsequent study, the operators (n=40) of the same companies were questioned on the last forklift acquired. These forklift were operated in three different contexts: wood yards, shipment and warehouse. Overall, they systematically liked their previous model better than the new one, whatever quality was considered (accuracy, comfort, safety, efficiency, general performance). For 23 characteristics, they were questioned about the quality seek. For example, the operators said they wanted a control that was quickly responsive (87%), has short range of motion (52%), with an easy access (50%), and a low resistance (35%). In fact, the preference varied according to the work context. For example, a short range of motion was said important in wood yards work and a low resistance, an easy location was more important in shipping work. In the great majority of cases, the qualities evoked by the operators were absent from the catalogues. So, there was clearly a gap between the information provided by the catalogues and the need expressed by the operators: several characteristics that are important for the operators are not covered, and when a characteristic is described, it refers to issues other than what is pertinent for the operators.
3.2 Interface between the users and research community 3.2.1 Floor layers Fourteen solutions proposed in the literature or patented were presented to 13 active workers (n=182 answers). They were asked to say if they had already tried the proposed solution and if it was worthwhile retaining it and seeing how it could be improved: 28% of them had tried the proposed solution. The most used one (n=11) was homemade equipment designed to unroll the carpet or lino rolls; the owner of a small floor layer enterprise has conceived it. Ten of them asked to retain this equipment for further improvement. They discarded the other solutions tried three times out of four. Overall, workers were open to try new equipment’s as 62% of the solutions retained were never tried. The most popular solutions were pieces of equipment proposed helping to support the trunk when kneeling (a portable trunk support) or limit the pressure on ankles when redressing (a portable thigh support). Solutions involving wheels to facilitate the displacements were systematically eliminated as too tough on the back (wheels increase the distance between the floor and the back when bended) and the ankles (they must constantly counteract the wheels mobility). So, workers appeared quite capable of inferring what may be interesting or not to keep as potential solutions. Well, it was striking that the solutions retained by the floor layers corresponded mostly to problems little documented in the literature on floor layers. 3.2.2 Forklift For five key cabin‐related characteristics (e.g., seat, pedal position), the link between what is recommended and what is described was analysed. The analyses showed that the manufacturers usually integrated recommendations and figures suggested (e.g., adjustment range, seat back angle). However, some descriptions were little informative because they incorporated recommendations that were too general or incomplete (e.g., presence of lumbar supports and so‐called “ergonomic” seat backs; however, to be effective, such supports must be positioned correctly, spine curvature varying greatly from one person to another). Also, many recommendations integrated were based on studies conducted in the context of car driving, which is quite different from forklift driving. For example, the recommended adjustment ranges (front‐forward: 150 mm) and angles (back reclining: 5°‐15°) are based on experimental data (increasing the trunk‐thigh angle reduces intra‐disk pressure) combined with car driving studies on visibility (seeing the road ahead at three metres) and steering’ control needs. With forklift, the fork ends must be visible at a shorter distance during forklift operation; operating the controls is more demanding than in a car. In addition a seat angle is not recommended for situations involving vibrations and jolts (i.e. maintaining a vertical axis is preferable) which is the case of forklift, which are often not equipped with suspension systems (Verschoore et al, 2003).
4. Discussion Systems involve a complex network of knowledge producers and users (e.g., scientists, designers, maintenance personnel, end‐users), intermediaries (e.g., marketing personnel, suppliers, buyers, users), and transfer interfaces (e.g., handbooks, catalogues, websites). In the knowledgeable management and transfer literature, studies focus more on internal systems and less on the flow between two systems and the various levels and loops involved (manufacturer loop: scientists, designers, marketing staff, engineers, etc.; customer loop: screeners, suppliers, maintenance staff, end‐users, etc.). In these systems, the exchanges also occur at both
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Monique Lortie et al. the organizational and individual (end‐user) levels. For example, organizations consider production costs, maintenance facilities, quality control, and after‐sale services; end‐users focus on the ease of use and performance efficiency in a given task. The goal is to find a way to combine both of these needs; equipment would be a more than appropriate starting place. What appears to be the main difficulty is the translation of dynamic into static information, namely the translation of what is needed in an activity into technical characteristics, and vice versa. In addition, the research highlighted interesting findings about relay agents. Considerable effort is presently being devoted to defining and developing the function of transfer agents (mostly as brokers) or knowledge officers. The relay agent function has been far less covered in the literature, probably because it is a function, a role rather than a professional activity. What relay agents appear to do well is to understand the needs of specific contexts. In the case of forklifts, two types of relay agents stood out. Firstly, the screeners clearly played an important role, even if they were not the ones making the decisions. They represented a crossroad, an interface between the decision‐makers, the purchasing staff, the maintenance staff, the supervisors, and eventually the operators. Their recommendations may have a substantial impact potential, although it would be difficult to quantify it. However, all screeners expressed substantial difficulties in interpreting catalogues and in linking the information with their company context. Although it was not the purpose of this research to address the selection process, one can say that the screeners also had difficulties understanding the forklift operators’ needs. They concentrated their attention on the maintenance needs, which perhaps were easier to decode. In this context, the second type of relay agent identified as important in overcoming these difficulties was the representative. Because their work involves moving from one place to another, they can more easily grasp the differences and associate them with the various models available. Considering the difficulty fitting generic knowledge with contextual needs, this role appeared to be crucial. In the case of the flexible floor layers, the relay chain was short. The distributors we met with did not know why one model was popular or not. Consequently, they could not play a relay role. The best relay agents were in fact small business owners that kept an eye open for everything new and judged it immediately according their needs. Since the floor layers moved from one place to another, the information circulated quite quickly. At the time of the study for example, a kneepad made with gel was presented as innovative; several floor layers had already tried it and rejected the gel filling as being unsuitable for their needs. This information was widely and quickly circulated. However, one manufacturer has since developed a knee protector that presently seems to be well appreciated by floor layers. It offers a new feature that no one would have spoken about a few years ago, namely an ankle support. The innovation was therefore quickly acknowledged. In such cases, a specific assessment tool, as it was intended at the beginning of the study would have miss that feature. This being said, perhaps what is needed more than relay tools is the development of a relay process that captures the information and knowledge needed to improve decision‐making in purchases. In the same manner, two‐way circuits that allow information to flow freely must be put in place. While the Internet offers interesting possibilities, it is not always easy to link all the various networks together.
Acknowledgments Researches funded by the Institut de Recherche Robert‐Sauvé en Santé et Sécurité du Travail du Québec
References Grant, K.E. (2012) Knowledge management, an enduring fashion, In Case studies in knowledge management, Grant, K.A. (ed). Academic Publishing International, U.K. Jensen, L.K. and Friche, C. (2008) “Effects of training to implement new working methods to reduce knee strain in floor layers. A two‐year follow‐up”, Occupational & Environmental Medecine, Vol. 65, pp. 20‐27. Lortie, M., Desmarais, L. and Laroche, É. (2012) “Knowledge Managers and Transfer Agents: Their Role and Integration in th the Development and Implementation of Knowledge Translation Tools”, 13 European Conference on Knowledge Management, Proceedings, 217‐225. Toyos Alvarez, A.A. (2013) Le transfert de connaissances dans un cadre de conception et de choix d’équipement : le cas des chariots élévateurs. Thèse de doctorat, Université du Québec à Montréal, Canada. Tanaka, S., Smith, A.B., Halperin, W.E. and Jensen, R. (1982) “Carpet‐layer’s knee” (Lettersto the editor). N. Engl. J. Med, Vol. 307, pp. 1275‐1276. Verschoore, R., Pieters, J.G. and Pollet, I.V. (2003) “Measurements and simulation on the comfort of forklifts”, Journal of Sound and Vibration, Vol. 226, pp.585‐599. Vezeau, S., Hastey, P., Giguère, D., Gagné, N., Larue, C., Richard, J.G and Denis, D. (2009) Chariots élévateurs ‐ Étude ergonomique et analyse des stratégies de conduite des caristes. Études et recherches / Rapport R‐601, Montréal, IRSST.
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The Importance of Emotional Intelligence in Effective Leadership Skills: The Case of Romanian Software Development Companies Edit Lukacs, Sofia David and Alexandru Capatina Dunarea de Jos University of Galati, Romania elukacs@ugal.ro sdavid@ugal.ro acapatana@ugal.ro Abstract: Emotional Intelligence (EQ) is considered a relevant tool for developing effective leadership skills. The aim of the present paper is to explore the correlations between the leadership styles, considered as independent variables, and the EQ competences, as dependent variables, clustered in four EQ analysis domains: self‐awareness, self‐management, social awareness and relationship management. The study was based on an empirical research undertaken on a representative sample of 80 managers from different hierarchical levels in Romanian software development companies. The research methodology involved a design of a conceptual framework, based on four hypotheses, tested by means of Pearson chi‐ square. The research results emphasize a cultural specific context and some suggestions for future research are provided. Keywords: emotional competence, leadership effectiveness, software industry, transformational leadership
1. Introduction Over the past decade, the emotional intelligence has received an increasing attention from the organizational behavioral researchers. Trying to find what distinguishes the high performer leaders from the low ones, Goleman (1998) found, in a study based on 121 organizations, that 67 percent of the abilities required for effective performance were emotional competencies. Emotional intelligence is defined as “the ability to perceive emotions, to access and generate emotions to assist thought, to understand emotions and emotional knowledge, and to reflectively regulate emotions so as to promote emotional and intellectual growth” (Caruso et al., 2002). Based on Goleman’s emotional competences model and his six leadership types, the present paper tries to support the body of empirical research for the linkage between EI and leadership styles. The article is organized as follows: The paper is then organised as follows: in the first section, dedicated to literature review, we highlighted the issues referring to the dependence between leadership styles and emotional intelligence; the second section is a description of our research methodology and instrumentation; in the third section, we presented the main findings of the correlation study, using the facilities provided by SPSS software; in the last section, we presented the conclusions, the limitations of our study, its practical implications and the directions in the future research agenda.
2. Literature review According to the Encyclopedia of Applied Psychology (2004) there are three major EI models: The Salovey‐ Mayer Model, The Goleman Model, The BarOn Model. The Salovey and Mayer’s ability model divides EI into four branches: (1) perceiving emotions, (2) using emotions to facilitate thought, (3) understanding emotions, and (4) managing emotions in a manner that enhances personal growth and social relations. The model has been improved since its first construction. In the first version of Goleman’s emotional competence model (1998), the emotional intelligence included 25 competencies that were grouped into five categories: (1) Self‐Awareness: emotional awareness, accurate self‐ assessment, self‐confidence; (2) Self‐Regulation: self‐control, trustworthiness, conscientiousness, adaptability, innovation; (3) Motivation: achievement, commitment, initiative, optimism; (4) Empathy: understanding others, developing others, service orientation, leveraging diversity, [socio‐] political awareness; and (5) Social Skills: influence, communication, conflict management, leadership, change catalyst, building bonds, collaboration and cooperation, team capabilities. Later, he defined emotional intelligence using twenty competences that were grouped into four domains that were categorized further into Personal Competence and Social Competence (Goleman et al., 2002).
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Edit Lukacs, Sofia David and Alexandru Capatina Personal Competence includes two domains and their associated competencies: (1) Self‐Awareness: emotional self‐awareness, accurate self‐assessment, self‐confidence; and (2) Self‐Management: emotional self‐control, transparency, adaptability, achievement, initiative, optimism (Goleman et al., 2002). Social Competence includes two domains: (1) Social Awareness: empathy, organizational awareness, service to others; and (2) Relationship Management: inspirational leadership, influence tactics, developing others, change catalyst, conflict management, building bonds, teamwork and collaboration/cooperation (Goleman et al., 2002). Bar‐On (2006) defines emotional intelligence as the “cross section of interrelated emotional and social competencies, skills, and facilitators that determine how effectively people understand and express themselves, understand others, and relate with them, and cope with daily demands”. The Bar‐On emotional quotient model focuses on the emotional‐social traits or patterns that contribute toward effective psychological functioning, and uses five scales of emotional intelligence: (1) intrapersonal; (2) interpersonal; (3) stress management; (4) adaptability; and (5) general mood. In order to prove the effect of emotional intelligence on leadership, the majority of the empirical studies were based on both Goleman’s (1998) competency model and Salovey and Mayer’s (1990) model. There are two main leadership theories: the emotional intelligence based Goleman’s model of leadership (2002) and Bass’s transformational‐transactional leadership theory. According to Bass (1990) and Sivanathan et al. (2002), the transformational leadership is characterized by four factors, named the “four I’s”: (1) idealized influence; (2) inspirational motivation; (3) intellectual stimulation; and (4) individualized consideration. Goleman connected the emotional competences with leadership effectiveness by categorizing the leadership styles in six types: the visionary, affiliative, democratic, coaching styles (as resonant leadership styles) and the commanding and pace‐setting styles (as dissonant leadership styles). According to Goleman et al. (2002), the visionary leader has the emotional competencies of self‐confidence, empathy, change catalyst, and visionary leadership; the affiliative leader is empathic and competent in building relationships and conflict management; the democratic leader is a strong communicator and listener, and encourages teamwork and collaboration; and the coaching leader possesses the emotional competences of empathy and emotionally self‐aware, and ‘developing others’ (Goleman et al., 2002). Elliott (2003) outlined that the Goleman’s first four styles (the visionary, affiliative, democratic, and coaching styles) are the most complicit with transformational theory and the latest two (the commanding and pace‐ setting styles) are the most complicit with the transactional theory (focuses on the role of supervision, organization, and group performance). According to Shika (2012), there is a significant amount of research on leadership, there are few emotional intelligence studies and the assessments of relationships between leadership and emotional intelligence need more supporting research. In a study of 382 team members from 48 self‐managing teams, Wolff, Pescosolido and Druskat (2002) found that empathy is the basis of the cognitions and behaviors that lead to the emergence of leadership and suggest that emotional intelligence, especially empathy, is a dominant factor of the leadership emergence in self‐ managed teams. The results of a field study on the emotional dynamics of 20 self‐managed groups (Pescosolido, 2002) demonstrated a strong relationship between emotional intelligence and performance, the existence of a relationship between emotional intelligence and leadership style, and the need to combine emotional intelligence abilities and competencies with leadership skill. A survey based on 358 managers across the Johnson & Johnson Consumer & Personal Care Group, conducted by Cavallo and Brienza (2000), outlined a strong relationship between superior performing leaders and emotional competence, meaning that emotional intelligence is an important factor in effective leadership. A selective, qualitative review of affect, emotions, and emotional competencies in leadership theory and research published in ten management and organizational psychology journals, book chapters and special
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Edit Lukacs, Sofia David and Alexandru Capatina issues of journals from 1990 to 2010 was provided by Gooty et al. (2010). The authors examined the theory (construct definition and theoretical foundation) and the methods (design, measurement and context) and summarize key findings in three distinct themes: (1) leader affect, follower affect and outcomes, (2) discrete emotions and leadership, and (3) emotional competencies and leadership. Their findings indicated that the study of affect and emotions in leadership fares well with regard to construct definitions across the first two themes, but not in the last theme. The results of a study on 859 employees, working in 55 teams in a South Korean public‐sector organization, highlighted that transformational leadership mediated the relationships between emotional intelligence and leader effectiveness, as well as between emotional intelligence and service climate, although not between emotional intelligence and team effectiveness (Hur et al., 2011). Emery (2012) investigated how different emotional abilities affect the emergence of task and relationship leaders in a group of 41 students. The results suggested that the abilities to perceive and manage emotions facilitate the emergence of relationship leaders and the abilities to use and understand them facilitate the emergence of task leaders. In a study on 134 midlevel managers from a large Brazilian company that operates in the energy sector that investigated the effects of intelligence, personality traits and emotional intelligence on transformational leadership and the effective performance of leaders in the organizational context, Cavazotte et al. (2012) found that emotional intelligence was statistically related to transformational leadership, if considered in isolation. Hamidi and Azizi (2012) found a positive relationship between relationship between emotional intelligence and leadership styles of principals in 42 high schools of Sanandj city in Iran. The study also concluded that there is a significant relationship between emotional intelligence and open leadership style. An exploratory pilot study, where 101 Romanian Public Managers enrolled in the YPS (Young Professionals Scheme) program were assessed in view of exploring the relationship between leadership styles and emotional intelligence, found significant positive correlations between transformational leadership and emotional intelligence and between leadership effectiveness and emotional intelligence (Stanescu and Cicei, 2012). A study conducted Nythia and Rau (2013) shows that software professionals have got less maturity to acquire Emotional Intelligence, and hence they can acquire it, if the organization gives them constant developmental training programs on Emotional Intelligence.
3. Research methodology On the basis of prior studies reflecting the issues related to leadership styles’ influence on emotional intelligence, we developed a conceptual model (Figure 1) and four hypotheses to be tested by means of appropriate statistical methods.
Self‐awareness EQ competences
Leadership style
Social‐awareness EQ competences
Visionary Coaching Affiliative Democratic Pacesetting Commanding
Relationship management EQ competences
Self‐management EQ competences
Figure 1: Conceptual model of the research
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Edit Lukacs, Sofia David and Alexandru Capatina Hypothesis 1: The predominant leadership styles of the managers from the Romanian software companies are positively related to emotional competences grouped in self‐awareness category. Hypothesis 2: The predominant leadership styles of the managers from the Romanian software companies are positively related to emotional competences grouped in self‐management category. Hypothesis 3: The predominant leadership styles of the managers from the Romanian software companies are positively related to emotional competences grouped in social‐awareness category. Hypothesis 4: The predominant leadership styles of the managers from the Romanian software companies are positively related to emotional competences grouped in relationship management category. The target population was represented by managers (top and middle positions) from Romanian software development companies. The main research tool was a questionnaire, structured in three sections. The first section was dedicated to the assessment of the respondents’ predominant leadership style, while the second section aimed at determining the most relevant emotional competences, grouped in four clusters: self‐ awareness, self‐management, social‐awareness and relationship management. The third section was conceived in view to determine the respondents’ segmentation criteria: sex, managerial position (top or middle), managerial experience and companies’ size, reflected by the number of employees. Before the submission of the questionnaire to the target population, it was tested and validated on a small group of five managers from software industry, which were not included in the sample. We sent the questionnaires to a convenience sample formed by 42 software companies, which were filled by 88 managers from different hierarchical levels. Questionnaires were transferred to the selected participants through electronic mail system and included an introductory letter from the authors, in which the research objectives was presented, accompanied by a commitment of the researchers to respect the confidentiality and anonymity of the answers. Each questionnaire’s results were processed by means of an automatic coding scheme in SPSS software, in order to avoid data input errors. Finally, 80 filled questionnaires were stored in a SPSS database, after eliminating the incomplete answers. The distribution of the population from our research sample according to the seegmentation criteria reveal that the majority of respondents are males (71,3%), while the females represent 22,8%; 53,8% from respondents hold middle management positions, while 46,3% are assigned to top management positions; the majority have an experience on managerial positions between 1 and 5 years (33,8%), followed by the interval 5‐10 years (30%); in what concerns their dimension, the number of employees of 33 companies (41,3%) is included in the interval (50 ‐ 250), followed by 28 companies (35%), whose number of employees is included in the interval (10 ‐ 50). The statistical methods that we used in order to test the hypotheses are chi‐square, Pearson's R and Spearman coefficients of correlation. Chi‐square test is applied in view to determine whether there is a significant difference between the expected frequencies and the observed frequencies in one or more categories. The use of chi‐square test involves the design of two hypotheses: the null hypothesis states that there is no significant difference between the expected and observed frequencies, while the alternative hypothesis states they are different. The level of significance (the point at which we can say with 95% confidence that the difference is not due to chance alone) is set at 0,05. The correlation coefficient Pearson's R is a useful descriptor of the degree of linear association between two variables, having two key properties of magnitude and direction. When it is near zero, there is no correlation, but as it approaches ‐1 or +1 there is a strong negative, respectively positive relationship between the variables. The sign of the Spearman correlation indicates the direction of association between the independent variable and the dependent variable. If the dependent variable tends to increase when the independent variable increases, the Spearman correlation coefficient is positive; otherwise, the Spearman correlation coefficient is negative. A Spearman correlation near zero indicates that there is no tendency for the dependent variable to either increase or decrease when the independent variable increases.
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4. Findings and discussions In order to facilitate both descriptive statistics methods and in‐depth analysis of the research results, we designed four contingency tables, reflecting the distribution of the respondents’ answers on each correlation between the six leadership styles and different cluster of Emotional intelligence competences (Self‐awareness, self‐management, social awareness and relationship management). We considered that the most appropriate IT&C tool in this approach was SPSS software. The distribution of research results corresponding to the first hypothesis involves the design of a contingency table with double entry, which allows the classification of the observed frequencies (Table 1). Table 1: Contingency table associated to the first hypothesis
As we can observe from the Table 1, the affiliative style is characteristic to the majority of respondents, followed by the pacesetting style; these results are representative for the software industry, where the goals’ achievement involves teamwork and the reinforcement of the links between teams’ members. In this particular case, self‐confidence is the most relevant emotional competence for both visionary and affiliative styles, while emotional self‐awareness and accurate self‐awareness are strongly linked to the affiliative style. The democratic style has assigned a low level of self‐confidence, the pacesetting and coaching styles are characterized by a balanced mix of all the emotional competences included in self‐awareness cluster, while the commanding style is characterized by a low level of emotional self‐awareness, correlated with a high level of self‐confidence. The results corresponding to the test of the first hypothesis, after the configuration of the cross‐tabulation process using the respondents’ answers stored in SPSS database are revealed in Tables 2 and 3. Table 2: First hypothesis testing by means of chi‐square test
In this case, the value associated to the Asymptotic significance (0,620) is superior to the level of significance (0,05) and the Pearson Chi‐Square value (8,093) is inferior to the Chi‐Square value reflected by Chi Square Distribution Table for Degrees of Freedom (18,3), in the context of ten freedom degrees, the null hypothesis is accepted, so we can state that there is no association between predominant leadership styles of the managers from the Romanian software companies and the emotional competences grouped in self‐awareness category. Table 3: First hypothesis testing by means of Pearson’s R and Spearman correlation
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Edit Lukacs, Sofia David and Alexandru Capatina The results of the first hypothesis testing process are also validated by Pearson’s R and Spearman correlation coefficients, because their values (‐0,043, respectively ‐0,054) are negative, but situated near zero, emphasizing the lack of correlation between the independent variables (leadership styles) and dependent variables (emotional competences grouped in self‐awareness category). The distribution of research results corresponding to the second hypothesis involves the design of a new contingency table with double entry, which allows the classification of the observed frequencies (Table 4). Table 4: Contingency table associated to the second hypothesis
In this particular case, achievement and initiative are the most relevant emotional competences for the affiliative style, while initiative and transparency are strongly linked to the pacesetting style. The coaching style is characterized by a balanced mix of all the emotional competences included in self‐management cluster, while there is a lack of emotional self‐control and transparency in the case of commanding style and, also, a lack of transparency and adaptability in the case of democratic style. The results corresponding to the test of the second hypothesis, after the configuration of the cross‐tabulation process using the respondents’ answers stored in SPSS database are revealed in Tables 5 and 6. Table 5: Second hypothesis testing by means of chi‐square test
In this case, the value associated to the Asymptotic significance (0,424) is superior to the level of significance (0,05) and the Pearson Chi‐Square value (25,703) is inferior to the Chi‐Square value reflected by Chi Square Distribution Table for Degrees of Freedom (37,65), in the context of twenty‐five freedom degrees, the null hypothesis is accepted, so we can state that there is no association between predominant leadership styles of the managers from the Romanian software companies and the emotional competences grouped in self‐ management category. Table 6: Second hypothesis testing by means of Pearson’s R and Spearman correlation
The results of the second hypothesis testing process are also validated by Pearson’s R and Spearman correlation coefficients, because their values (0,165, respectively 0,176) are positive, but situated near zero, emphasizing the lack of correlation between the independent variables (leadership styles) and dependent variables (emotional competences grouped in self‐management category).
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Edit Lukacs, Sofia David and Alexandru Capatina The distribution of research results corresponding to the third hypothesis involves the design of a new contingency table with double entry, which allows the classification of the observed frequencies (Table 7). Table 7: Contingency table associated to the third hypothesis
In this particular case, empathy is the most relevant emotional competence for the pacesetting styles, and it is strongly linked to the affiliative style. The visionary, democratic and pacesetting styles have assigned a low level of service orientation; the coaching style is characterized by a balanced mix of all the emotional competences included in social‐awareness cluster, while the commanding style is characterized by a lack of organizational awareness. The results corresponding to the test of the third hypothesis, after the configuration of the cross‐tabulation process using the respondents’ answers stored in SPSS database are revealed in Tables 8 and 9. Table 8: Third hypothesis testing by means of chi‐square test
In this case, the value associated to the Asymptotic significance (0,511) is superior to the level of significance (0,05) and the Pearson Chi‐Square value (9,226) is inferior to the Chi‐Square value reflected by Chi Square Distribution Table for Degrees of Freedom (18,3), in the context of ten freedom degrees, the null hypothesis is accepted, so we can state that there is no association between predominant leadership styles of the managers from the Romanian software companies and the emotional competences grouped in social‐awareness category. Table 9: Third hypothesis testing by means of Pearson’s R and Spearman correlation
The results of the third hypothesis testing process are also validated by Pearson’s R and Spearman correlation coefficients, because their values (‐0,074, respectively ‐0,084) are negative, but situated near zero, emphasizing the lack of correlation between the independent variables (leadership styles) and dependent variables (emotional intelligence skills grouped in social‐awareness category). The distribution of research results corresponding to the fourth hypothesis involves the design of a new contingency table with double entry, which allows the classification of the observed frequencies (Table 10).
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Edit Lukacs, Sofia David and Alexandru Capatina Table 10: Contingency table associated to the fourth hypothesis
In this particular case, influence is the most relevant emotional competence for the affiliative style, which is a really surprising finding, if we take into account Goleman' model. Developing others and teamwork spirit are strongly linked to the coaching style, while inspirational leadership and teamwork spirit are representative emotional competences for the pacesetting style. We can observe a lack of conflict management in the case of visionary style and, also, a lack of change catalyst competence in the case of the affiliative style. The results corresponding to the test of the fourth hypothesis, after the configuration of the cross‐tabulation process using the respondents’ answers stored in SPSS database are revealed in Figures 11 and 12. Table 11: Fourth hypothesis testing by means of chi‐square test
In this case, the value associated to the Asymptotic significance (0,390) is superior to the level of significance (0,05) and the Pearson Chi‐Square value (26,340) is inferior to the Chi‐Square value reflected by Chi Square Distribution Table for Degrees of Freedom (37,65), in the context of twenty‐five freedom degrees, the null hypothesis is accepted, so we can state that there is no association between predominant leadership styles of the managers from the Romanian software companies and the emotional competences grouped in relationship management category. Table 12: Fourth hypothesis testing by means of Pearson’s R and Spearman correlation
The results of the fourth hypothesis testing process are also validated by Pearson’s R and Spearman correlation coefficients, because their values (‐0,060, respectively ‐0,092) are negative, but situated near zero, emphasizing the lack of correlation between the independent variables (leadership styles) and dependent variables (emotional competences grouped in relationship management category).
5. Conclusions, practical implications, limitations and future research agenda The realities and challenges inherent to the actual state of the Romanian software industry outline the features of a hyper‐competitive and dynamic environment. In this context, managers need to acknowledge the approach focused on a balanced use of both competitive and emotional intelligence competences, taking into account the fact that software industry can be perceived of as an “industry of the mind”, where knowledge, intelligence and technological expertise are the main inputs, and talents are therefore the most relevant assets. In this context, our paper investigated the correlations between different leadership styles and emotional intelligence competences which are specific to the managers from a sample of Romanian software
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Edit Lukacs, Sofia David and Alexandru Capatina firms. Empathy, self‐confidence, achievement, inspirational leadership and teamwork spirit are shown to be the most relevant emotional competences, while the affiliative style seems to be appropriate to the managers of software development companies. By making sure team members feel connected to each other, this kind of leader is an adept of building teams, in which the talents must be adequately motivated and rewarded, as they represent the most valuable intellectual capital assets of the software companies. Affiliative leaders’ positive feedback for task accomplishment gives subordinates a great sense of having been recognized, which is an excellent motivation for even greater achievements. Besides the correlations between the six leadership styles and Emotional intelligence competences related to the managers included in the research sample, which at first sight seem contradictory rather than complementary, another finding from the in‐depth content analysis developed within the contingency tables emphasizes the role of effective leader in software industry: the one who delegates tasks and shares authority with his team, provides technical IT expertise and background for effective leadership. Understanding precisely how emotional competences relate to effective leadership styles has practical implications for the management bodies of the software companies, particularly in the areas of strategic planning of highly‐skilled employees’ selection, training and motivation. Leaders from this technology‐ intensive industry need more than just technical and traditional managerial skills; they must be able to adapt their leadership style in particular situations, fact which require appropriate emotional competences. Our findings support the idea that organizations from Romanian software industry should select people who are characterized by an optimal mix of emotional competences, because they will have the potential to become effective leaders. Overall, the results contribute to the understanding of the mediating effect of leadership styles on emotional competences and provide opportunities for developing training programs oriented to the development of certain emotional competences in order to be tailored to a specific leadership style. The main limitations of our research were represented by the fact that we carried out the survey on a convenience sample from a single industry, which limited the number of respondents, on the one hand, and we didn’t assess qualitative aspects regarding the correlations between leadership styles and Emotional intelligence competences, as aspects of human behaviour were also involved. Since we have conducted our correlation study in the Romanian software industry context only, we cannot generalize from these findings to other industries. Another limitation is related to the fact that our study does not consider the dynamic nature of emotional competences in the particular case of Romanian software industry because we did not collect longitudinal data; in this way, a follow‐up survey based on a qualitative approach should be a priority in the future research agenda. We consider that training programs can be developed for software professionals in order to make them to be aware with the concept of Emotional Intelligence and to make them to know the importance of Emotional Intelligence competences and leadership style on their job performance, according to their position within the companies. The necessity of building long‐term relationships among software development teams is a good example for building networks inside software companies, which are seeking to strengthen their leaders’ effectiveness using the appropriate Emotional Intelligence competences. The optimal balance between different styles of leadership and emotional competences might differ in other cultural contexts other than software industry. Future researches in this field might benefit from an extended research sample, by adopting a similar exploratory approach, in which we will be able to test the correlations leadership styles and emotional competences in the case of different sectors of Romanian economy. Moreover, a cross‐cultural survey focused on the gap analysis of the emotional competences and leadership styles in the case of software companies from different countries, based on the integration of Cultural intelligence skills in the conceptual model, will be a highly challenging task to carry out in the future.
References Bar‐On, R. (2006) “The Bar‐On model of emotional‐social intelligence (ESI)”, Psicothema, vol. 18(suppl.), pp. 13‐25. Bass, B. M. (1990) Bass & Stogdill's Handbook of Leadership: Theory, Research, and Managerial Applications (3rd ed.), New York: The Free Press. Cavallo, K., and Brienza, D. (2000) Emotional Competence and Leadership Excellence at Johnson & Johnson: The Emotional Intelligence and Leadership Study. Paper presented at the Meeting of the Consortium for Research on Emotional Intelligence in Organizations, Cambridge, Massachusetts, 3th of November.
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Edit Lukacs, Sofia David and Alexandru Capatina Cavazotte, F, Moreno, V. and Hickmann, M. (2012) “Effects of leader intelligence, personality and emotional intelligence on transformational leadership and managerial performance”, The Leadership Quarterly, vol. 23, pp. 443–455. Hamish G. H. Elliott (2003), Emotional Intelligence‐Based Leadership, The Graduate Management Review, http://www.business.otago.ac.nz/mgmt/publications/omgr/2003 /03elliott.pdf. Emery, C. (2012) “Uncovering the role of emotional abilities in leadership emergence. A Longitudinal analysis of leadership networks”, Social Networks, vol. 34, pp. 429– 437. Hamidi, F. and Azizi, F. (2012) “Relationship between emotional intelligence and leadership styles of principals in high schools”, International Journal of Vocational and Technical Education, Vol. 4, No. 4, pp. 60‐67, November, http://www.academicjournals.org/ijvte/PDF/Pdf2012/November/Hamidi%20and%20Azizi.pdf. Goleman, D., Boyatzis, R. and McKee, A., (2002) Primal Leadership: Learning to Lead with Emotional Intelligence, Harvard Business School Press. Gooty, J., Connelly, S., Griffith, J. and Gupta, A. (2010) “Leadership, affect and emotions: A state of the science review”, The Leadership Quarterly, vol. 21, pp. 979–1004. Hur, Y, van den Berg, P. and Wilderom, C. (2011) “Transformational leadership as a mediator between emotional intelligence and team outcomes”, The Leadership Quarterly, 22, pp. 501‐ 603. Nithya, S. and Rau, S. (2013), “A Study on Level of Emotional Intelligence of Software Professionals orking in Software Companies, Proceedings of International Conference on Technology and Business Management, Dubai, March 18‐20, 2013, pp. 362‐367. Pescosolido, A. T. (2002) “Emergent Leaders as Managers of Group Emotion”, The Leadership Quarterly, vol. 13, pp. 583‐ 599. Shikha (2012) “Leadership style and emotional intelligence and its Impact on organizational performance”, International Journal of Research in Economics & Social Sciences, Vol. 2, No. 2, February, http://www.euroasiapub.org/IJRESS/Feb2012/8.pdf. Sivanathan, N. and Fekken, G. C. (2002), “Emotional Intelligence, Moral Reasoning and Transformational Leadership”, Leadership & Organization Development Journal, vol. 23, No. 4, pp. 198‐204. Stanescu, D.F. and Cicei, C.C. (2012) “Leadership Styles and Emotional Intelligence of Romanian Public Managers. Evidences from an Exploratory Pilot Study”, Review of Research and Social Intervention, vol. 38, pp. 107 – 121 Wolff, S. B., Pescosolido, A. T. and Druskat, V. U. (2002) “Emotional Intelligence as the Basis of Leadership Emergence in Self‐Managing Teams”, The Leadership Quarterly, vol. 13, pp. 505‐522.
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Information Technology: An Enabler for Trust‐Building, Knowledge Sharing and Knowledge Transfer to Enhance Absorptive Capacity Athar Mahmood Ahmed Qureshi and Nina Evans University of South Australia, Adelaide, Australia Athar.Qureshi@unisa.edu.au Nina.Evans@unisa.edu.au Abstract: Information and communication technologies (ICT) are evolving so fast that their impact on organisations is very high in terms of culture, environment and how businesses are managed today. This challenge demand organisations to adopt or adapt technologies that enable them to enhance their absorptive capacity, i.e. the ability to acquire, assimilate, transform and exploit knowledge, to create a trust culture, achieve their goals and sustain their competitive advantage among rivals. In particular, information technology plays an important role as an enabler for trust‐building, knowledge sharing and knowledge transfer practices, and as such, for influencing the absorptive capacity of organisations. Although information technology has been extensively studied as a tool and medium for a variety of organisational practices, the role of information technology as an enabler of trust‐building for knowledge sharing, knowledge transfer and knowledge absorption practices has not yet been studied. This research seeks to fill this gap. A qualitative research methodology is used, specifically through exploratory case studies and semi‐structured interviews, to answer the research question. A framework is proposed to understand the role of information technology as an enabler for trust‐building, knowledge sharing, knowledge transfer and knowledge absorption processes. The final version of the framework will guide organisations to deploy adequate information technology and ‐infrastructure to facilitate trust‐building environment and to enable the pathway to innovation, improved performance and competitive advantage. The paper represents research in progress. The final model will be validated in the Healthcare industry in Australia. Keywords: information technology, trust, absorptive capacity, knowledge sharing, knowledge transfer
1. Introduction Knowledge management (KM) has been an established discipline since 1991 (Nonaka 2007) and refers to technology that offers to take care of the issues like finding‐, classifying‐, ensuring quality of‐, storing‐, maintaining‐, using‐ and motivating people to contribute knowledge as knowledge is often not documented (Gu & Warren 2004; Liebowitz 1999; Turban & Aronson 2001). Knowledge management is therefore a “set of techniques and practices that facilitate the flow of knowledge into and within the firm” (Birkinshaw 2001). Organisations that are “knowledge management proficient” are capable of more innovative way of performing their daily routines and will perform competitively (Esterhuizen, Schutte & du Toit 2011). Knowledge management literature suggests that among the capabilities that enable organisations to improve performance and gain a sustainable competitive advantage is absorptive capacity (AC), which refers to the ability of an organisation to acquire knowledge, to assimilate the acquired knowledge, to transform the assimilated knowledge and to exploit the transformed knowledge that is gained from external sources (Cohen & Levinthal 1990). Furthermore, Von Krogh (2000) asserted that merely gaining the knowledge is not a benefit for the organisation, unless it is shared among individuals, groups, functions or systems in that organisation. Knowledge sharing is therefore like a back‐bone of knowledge creation mechanisms. It leverages organisational knowledge (Mishra & Bhaskar 2011) and enables knowledge transfer among the employees (McNeish & Mann 2010) toward optimum performance and competitive advantage (McNeish & Mann 2010; Mishra & Bhaskar 2011). Moreover, knowledge management literature has identified trust as an essential factor that can enable knowledge sharing (Huotari & Iivonen 2004) and knowledge transfer mechanisms within an organisation. Trust has been asserted as a “tacit foundation for relationships” and has been widely discussed in organisational context and included in ethical agreements (Baumard 1999). Information technology and information systems play vital roles in knowledge management (Alavi & Leidner 2001; Edwards 2011; Leavitt 1964) by facilitating the four established themes of knowledge management, namely creation, sharing, upgrading and retention of knowledge (Mishra & Bhaskar 2011). Information systems research has investigated organisations, understanding of people’s interests and attitudes, workflows, community and social behaviour with respect to change and challenges (Lee 1989; Orlikowski & Baroudi 1991). Information systems research has also studied the information and communication technologies and their challenges (Whitman 2004).
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Athar Mahmood Ahmed Qureshi and Nina Evans Knowledge management literature is lacking accounts on how to make a set of knowledge credible, relevant and trustworthy, so that it can be used across time, contexts and organisations (Ellingsen 2003). This paper draws from the knowledge management literature and proposes a positive relationship between information technology as an enabler for building a trust‐culture that enable knowledge sharing and knowledge transfer to enhance absorptive capacity.
2. Literature review 2.1 Absorptive capacity Absorptive capacity is a well‐established capability (construct) of an organisation to identify, assimilate, and exploit external knowledge (Cohen & Levinthal 1990; Zahra & George 2002). Based on these three crucial components, it is the capacity of an organisation to recognise external knowledge and its value for the organisation. It is a capacity to integrate that external knowledge (assimilation), and, it is a capacity of applying that knowledge to commercial ends (Van den Bosch, Wijk & Volberda 2003). Similarly, it is an ability to “exploit less commercially focused knowledge such as basic scientific research or new IT solutions” (Francalanci & Morabito 2008). Therefore, organisational performance is directly influenced by absorptive capacity (Francalanci & Morabito 2008), which means, it is an ability of an organisation to grow its innovativeness and competitive advantage. Numerous investigations have been performed to study this construct (theoretically) during the last two decades (Noblet, Simon & Parent 2011). However, few attempts were made to study how information technology can enable trust‐building culture for knowledge sharing and transfer mechanisms in organisations to enhance absorptive capacity operationalisation.
2.2 Trust Trust has been established as a diverse field of research between 1995 and 2006 and have been discussed in two often cited books (Bachmann & Zaheer 2006; Kramer 2006). Literature uses a number of terms that directly or indirectly refer to trust (e.g. cooperation, confidence, and predictability). These terms complicate the phenomenon of trust (Mayer, Davis & Schoorman 1995). Trust “is not a behaviour (e.g. cooperation) or a choice (e.g. taking a risk) but an underlying psychological condition that can cause or result from such actions” (Sitkin, Rousseau, Burt et al 1998). The importance of corporate or organisational trust has been significantly increased among the corporate personnel (Mayer, Davis & Schoorman 1995). In their seminal paper Mayer, Davis and Schoorman (1995) defined trust as “the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party”. Furthermore, Rosanas (2009) defined organisational trust as the “relationship between two people where one takes an action making him vulnerable to the other”. Being vulnerable is risk‐taking, where “trust is not taking risk per se, but rather it is a willingness to take risk” (Mayer, Davis & Schoorman 1995). Trust is asserted as an antecedent as well as a consequence in many of the investigations performed by the knowledge management researchers and practitioners (e.g. Dale 2012; Huotari & Iivonen 2004; Kharabsheh 2007; Lin 2011; Mayer, Davis & Schoorman 1995; McNeish & Mann 2010; Parra, Nalda & Perles 2011; Politis 2003a, 2003b; Spraggon & Bodolica 2012) and specifically in the context of absorptive capacity (e.g. Kharabsheh 2007; McNeish & Mann 2010; Noblet, Simon & Parent 2011). There are many properties and traits of trust that influence the establishment of trust‐culture. Contemporary scholars (Parra, Nalda & Perles 2011; Schoorman, Mayer & Davis 2007) acknowledge the three antecedents of trust identified by Mayer, Davis and Schoorman (1995), namely ability (i.e. skills, competencies, traits and characteristics that are essential to influence a specific domain), benevolence (i.e. the degree or level to which the first person believes the second person wants to do good to the first person) and integrity (i.e. the valuation that the first person do to judge whether or not the second person will adhere to acceptable principles) (Evans & Wensley 2009; Mayer, Davis & Schoorman 1995). Trust is an established antecedent to knowledge sharing mechanisms that, along with other enablers, enable knowledge sharing and knowledge transfer mechanisms to achieve competitive advantage (Kharabsheh 2007; McNeish & Mann 2010; Qureshi & Evans 2013a). As a consequence, trust influences the level of absorptive capacity in organisations (Qureshi & Evans 2013a). Organisations that have a trust‐culture and are more trust‐
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Athar Mahmood Ahmed Qureshi and Nina Evans focused will have higher level of absorptive capacity (Qureshi & Evans 2013a; Ratten 2004). In this paper we seek to investigate how information technology infrastructure can enable trust‐building culture in both intra‐ and inter‐organisation settings and develop linkage between trust‐culture, knowledge sharing and knowledge transfer mechanisms to enhance absorptive capacity. Henceforth, we propose a framework to investigate such a relationship.
2.3 Knowledge sharing Organisations incorporate new knowledge into their existing knowledge from external or internal sources. Knowledge sharing refers to the capacity (or capability) of an organisation to create new knowledge, disseminating it, and embodying it in its services and systems (Nonaka & Takeuchi 1995). Furthermore, in organisations, this creation of knowledge depends on the understanding of the organisation of how it learns (Mishra & Bhaskar 2011; Schon 1975). Moreover, merely gaining knowledge through externalisation or internalisation is of no benefit to organisations, unless it is shared among individuals, groups, functions or systems of the organisation (Von Krogh 2000). Knowledge sharing is the back‐bone of knowledge creation. It leverages organisational knowledge (Mishra & Bhaskar 2011), enables knowledge transfer among the employees (McNeish & Mann 2010) and drives to optimum performance and competitive advantage (McNeish & Mann 2010; Mishra & Bhaskar 2011). Information technology with its current maturity can accommodate fast, reliable and efficient knowledge sharing infrastructure in organisations. Various research studies established that information technology infrastructure is one of the core knowledge sharing enablers (Bechina & Bommen 2006; Kharabsheh 2007) for organisations, yet few attempts have been made to study how information technology can mediate in creating trust‐culture for knowledge sharing and transfer mechanisms in organisations, and help enhance absorptive capacity. Information technology is not the only enabler for knowledge sharing and transfer mechanisms. It requires trust‐culture i.e. that people gain trust in each other (interpersonal‐trust) and in their management (organisational‐trust). Therefore, this research seeks to investigate how trust influences the uptake of information technology to enable knowledge sharing and transfer mechanisms to enhance absorptive capacity.
3. Knowledge transfer Knowledge transfer is one of the distinct mechanisms in organisations that influence the level of absorptive capacity (Cohen & Levinthal 1990) in a unit‐to‐unit, or department‐to‐department setting, or between the external environment and the organisation, or between an internal network and an external network (Van den Bosch, Volberda & de Boer 1999). Knowledge transfer mechanisms are usually bidirectional, enabling in‐bound knowledge transfer (i.e. enriching organisation from external sources) or out‐bound knowledge transfer (i.e. enriching external networks with self‐knowledge) (Kharabsheh 2007). Furthermore, knowledge transfer mechanisms are challenged when we evaluate the two types of knowledge (i.e. explicit and tacit) to be transferred. Explicit knowledge can be represented by various means, for example numbers and words, and it can be easily communicated through agreed upon principles and codified routines (Kharabsheh 2007). Literature refer to examples of explicit knowledge, such as chemical formulae, codes, or sets of rules (Nonaka & Takeuchi 1995). Explicit knowledge can therefore easily be recorded into books, manuals, blueprints et cetera. The best practice to transfer this kind of knowledge is through the “impersonal communication of technological transfer method” (Kharabsheh 2007; Rebentisch & Ferretti 1995). In contrast, tacit knowledge such as instincts, premonitions, individual’s experience, expertise actions, reactions, values or emotions (Nonaka & Takeuchi 1995; Silke & Alan 2000) is very hard to formalise and communicate, “at least not via impersonal communication methods” (Kharabsheh 2007), because it is very personal and also very challenging. Tacit knowledge can be transferred through socialisation mechanisms (Nonaka 1994) which means in a social network setting where source and the recipient work alongside (Kharabsheh 2007). Therefore, success of knowledge transfer is exaggerated and is affected by some critical factors, e.g. the absorptive capacity of the source and the recipient, previous experiences and related knowledge (Volberda, Foss & Lyles 2010). The twin terms; knowledge sharing and knowledge transfer are often used one after another in knowledge management literature (Kharabsheh 2007; Volberda, Foss & Lyles 2010). However, few, attempts have been made to distinguish them as an antecedent and a consequence (e.g. McNeish & Mann 2010). In this study we
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Athar Mahmood Ahmed Qureshi and Nina Evans regard knowledge sharing as an antecedent that triggers knowledge transfer mechanisms (McNeish & Mann 2010). Therefore, we seek to investigate the linkage between trust, knowledge sharing and knowledge transfer that is enabled by the information technology to enhance absorptive capacity.
4. Social integration mechanisms Socialisation, unlike formalisation (Volberda, Foss & Lyles 2010) and social integration mechanisms are terms that are frequently used in the knowledge management literature to refer to the potential vehicle to be used for knowledge sharing and transfer activities (Armstrong 2006; Esterhuizen, Schutte & du Toit 2011; Kharabsheh 2007; Todorova & Durisin 2007; Volberda, Foss & Lyles 2010; Zahra & George 2002). However, a clear definition, scope and explanation other than a general humanistic understanding has not yet coined. This research will adopt social networks as the potential vehicle (Armstrong 2006), that enable socialisation activities (e.g. sharing and transfer of knowledge in a social network setting). Social interactions in organisations are dynamic and fluid in nature, and embody social aspects as well as network aspects (Obembe 2006). From the review of the literature, it is established that social networks facilitates the creation of knowledge (Griffith, Sawyer & Neale 2003; Nonaka & Takeuchi 1995) and therefore, it is through these informal social networks that an individual’s explicit and tacit knowledge transforms and build upon each another. Social networks will leverage the social‐ and organisation‐level knowledge (Chou 2005), and hence, influences the absorptive capacity operationalisation. Information technology enabled social networks (through the use of social media) is an online media where people are talking, participating, sharing, bookmarking and networking through accelerated conversations. It is a set of tools and infrastructure that enables people to share their experiences in an online environment, among an online community. In this context, community is a group of people who connect with one another through information technology channels to work, organise, learn and play, and hence, socialisation takes place. Community may vary in size. It may be a local (small) community or may be a global community connecting through this “technoculture” milieu. Apart from technological benefits, social media is mostly a multimedia by nature (that includes video, audio, text, podcasts etc.) (Ruzic 2011). In this research we therefore seek to identify how information technology‐enabled social networks facilitate the linkage between trust‐building, knowledge sharing and knowledge transfer mechanisms in organisations to enhance absorptive capacity.
5. Proposed research framework In this study we aim to offer a holistic approach for studying how information technology can enable trust‐ building culture and mediate knowledge sharing and knowledge transfer mechanisms in organisations to enhance absorptive capacity. Trust is asserted as an antecedent as well as a consequence of knowledge sharing and knowledge transfer (Kharabsheh 2007; McNeish & Mann 2010; Noblet, Simon & Parent 2011) to enhance absorptive capacity. Knowledge sharing is investigated to be an antecedent to knowledge transfer (McNeish & Mann 2010). Knowledge transfer enables an organisation to increase the level of absorptive capacity. The literature does not provide a full picture of these sequential growth mechanisms. The research is therefore seeking to establish this link through information technology as one of the enablers. The study will therefore address the following research question: “How do information technology‐ enabled social networks enable trust‐building culture in organisations to activate knowledge sharing and knowledge transfer mechanisms to enhance absorptive capacity?” To achieve this linkage, a qualitative approach has been adopted to review literature and an empirical investigation is followed in four major Healthcare organisations by conducting semi‐structured interviews. Furthermore, in order to study these linkages, their implications and the role of information technology, our research is built upon the theory of absorptive capacity, original by Cohen and Levinthal (1990), reconceptualised model of the theory of absorptive capacity by Zahra and George (2002), a refined model by Todorova and Durisin (2007), the original model of trust by Mayer, Davis and Schoorman (1995), a reviewed version by Schoorman, Mayer and Davis (2007), a revised model of trust by Parra, Nalda and Perles (2011), the model of antecedents of knowledge sharing by Kharabsheh (2007) and the model of trust and knowledge sharing by McNeish and Mann (2010), as shown in Figure 1.
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Athar Mahmood Ahmed Qureshi and Nina Evans Enhanced Absorptive Capacity
Innovation
Improved Performance
Success
Competitive Advantage
Enhanced Organisational
Model of Trust (Mayer, Davis & Schoorman 1995)
Models of Knowledge Sharing (Kharabsheh 2007; McNeish & Mann 2010)
Model of Knowledge Transfer
Models of Absorptive Capacity (Todorova & Durisin 2007)
(McNeish & Mann 2010; Zahra & George 2002)
Figure 1: Research framework – adapted from Qureshi and Evans (2013b)
6. Conclusion In the 21st century, every organisation is seeking to attain competitive advantage and to retain its competitive knowledge assets. For this, they have to go through diverse challenges and face dynamic changes in their cultures, environments and the way they do their businesses and the way they design their strategies to achieve their goals and success. Absorptive capacity is the construct that enable organisations to achieve success, improved performance, efficiency and competitive advantage. Therefore, it is important to reconceptualise this construct and to study how other constructs (e.g. trust) can influence absorptive capacity through enablers like information technology. The rapid growth in information and communication technologies pose severe challenges that attract organisations to adopt or adapt adequate information technology infrastructure to facilitate trust‐building culture and also to facilitate knowledge sharing and knowledge transfer activities to achieve their objectives. This research is contributing to the body of knowledge by extending the literature on knowledge management adding value to the current understanding of the aforementioned dimensions, constructs and linkages. The final framework (Qureshi & Evans 2013a) is being validated in the Healthcare industry in Australia.
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Applying a Technology Acceptance Model to Test Business e‐Loyalty Towards Online Banking Transactions 1 Eva Martinez‐Caro1, Gabriel Cepeda‐Carrión2, and Juan‐Gabriel Cegarra‐Navarro1 Universidad Politécnica de Cartagena, Spain 2 Universidad de Sevilla, Spain
1
eva.martinez@upct.es gabi@us.es juan.cegarra@upct.es Abstract: This paper examines the relative importance and significance of the four technology enablers introduced by Venkatesh et al. (1989) (performance expectancy, effort expectancy, social influence, and facilitating conditions) for value on banking transactions. In this research, an extended model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) is developed to test business e‐loyalty towards online banking services from a sample of 87 companies who used an automated communication channel (called Editran) broadly utilized in Spain to transmit files and send and receive orders, using standard formats. The results obtained suggest that the core constructs of UTAUT significantly affect companies’ e‐loyalty. In summary, although the proposed model follows UTAUT and explains the intention towards the actual use of the Editran tool by postulating three significant determinants (i.e. performance expectancy, social influence, and facilitating conditions), our results also support that in order to implement the Editran tool, these factors matter more than effort expectancy to implement the Editran tool. The implications of the findings are discussed and useful insights are provided on what policy to follow to establish the appropriate conditions to build companies’ e‐loyalty. Keywords: UTAUT model, banking sector, e‐loyalty, performance expectancy, effort expectancy, social influence
1. Introduction The rapid growth of Internet usage has led to a revolution implying a dynamically changing environment in all sectors, and the banking sector could not keep out of it. This sector has undergone important changes, particularly in the development of new online services providing an alternative channel for serving the customers. Online banking services provide offers many benefits to banks as well to customers. Online banking enables customers to perform transactions and other activities from any place and at anytime. In addition, online banking helps banks to keep their existing customers, win new ones, improve customer satisfaction, increase banks’ market share, reduce administrative and operational cost and more importantly may lead to improve banks’ competitive positions (Al‐Somali et al., 2009; Pikkarainen et al., 2004). However, those improvements are possible only if customers use those services regularly, by integrating them into their daily activities. If their use of the services is discontinued, banks would be wasting their resources. Although millions of dollars have been spent on building online banking systems, reports on online banking show that potential users may not be using the systems, despite their availability (Luarn & Lin, 2005). Thus, research is needed to identify the factors determining users' acceptance. According to Bhattacherjee (2001), the initial acceptance of a technology is an important first step; however, the eventual success of the technology depends on its continued use. Hence, companies’ electronic loyalty (hereafter eLoyalty) is the key for online banking services success. According to the marketing literature, loyalty is present when favorable attitudes for a brand are manifested in repeat buying behavior (Keller, 1993). Adapting that definition to the banking sector, eLoyalty can be defined as the favorable attitude of the customers towards an online banking service that results in repeated use behavior. Since the success of the online services is dependent on their adoption rate, a better understanding of which factors influence customers’ adoption is needed (AbuShanab et al., 2010). While there is a rich body of literature on online banking services and their adoption, little is known about how to keep customers loyal to those services (Floh & Treiblmaier, 2006). Furthermore, previous studies about online banking are focused on individual consumers. For example, Pikkarainen et al. (2004) used a sample of 1
The dates of this research were taken from a research program supported by the Spanish Ministry of Education (REF: ECO2011‐28641‐ C02‐02), the R&D Project for Excellence. Andalusian Ministry of Education (REF: SEJ‐6081), and the research program supported by the Agencia de Ciencia y Tecnología Región de Murcia (F Séneca 18709/EE/12).
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268 Finnish consumers who filled a questionnaire in three different places (university classes, two barber shops, and at a medium sized retail company) and was representative of the population. In the Al‐Somali et al.’s (2009) research participants were bank customers selected randomly from universities, companies, Internet cafés and businessmen from private and public sectors, representing the Saudi community. Polatoglu and Ekin (2001) analysed a sample of 30 randomly selected customers of one of the five largest commercial banks in Turkey.
The aim of this paper is to focus on business customers. To achieve this goal we developed a research in the Spanish banking sector, and specifically, in the context of the use of the Editran tool. Editran is a platform for communications over data networks and the internet to create advanced solutions that enable direct connectivity between IT applications in different computers and operating systems, in a heterogeneous environment of business activity, entities and public bodies. Its capacity to integrate with different operating systems, the dynamic configuration of its operating mode and simultaneous multiple exchanges with various remote centres and various network protocols have made Editran the de facto standard in electronic information exchange processes in the Spanish banking sector. Editran allows the communication of business with banks for the sending and receiving of salary payments, balances and transactions. The benefits of Editran are: Centralisation of external or internal file exchanges, use of a single platform for transmissions with all Spanish financial entities, reduction of the payment and collection periods, automation of the processes prior and subsequent to the data exchange, or delivery confidentiality and guarantee. In our research we use the core concepts of the UTAUT acceptance model to study the relationship between Editran acceptance and companies’ eLoyalty towards the services provides by their banks. A model is developed and tested by using the Structural Equation Modelling (SEM) approach. In the following section we investigate the development of hypotheses as to how the UTAUT’s core variables contribute to companies’ e‐ loyalty. The methodology employed to construct the questionnaire and the details of the sample are presented in Section 3, whilst the results from the hypothesis tests follow in Section 4. Finally, the results are discussed in Section 5.
2. Conceptual framework The banking business is very complex and requires intensive use of technology tools to competitively operate in the market and satisfy its customer needs. Like other service providers, banking institutions need ways of accepting new technologies (Ali & Ahmad, 2006). Customer e‐loyalty plays an important, if not a critical role in a bank’s success. Loyal customers provide banks a consistent source of revenue (repeat and increased use of services) and for cost reduction (less promotional expenses), thus increasing profitability (Li & Green, 2010). In the opinion of Reichheld & Schefter (2000) the increase of 5 % loyalty rate supposes an increase of 40 to 60 % business performance. Therefore, e‐loyalty can help banks understand target market needs and, ultimately, recover the investment that has been made to obtain and maintain technologies (Zviran & Erlich 2003). Among all the agents with which a company has relationships, one of the most important agents are banks because of their direct relationship with financial performance and long‐term survival (Ali & Ahmad, 2006). Clearly companies provide a bank with direct revenue through the purchase of products or services. In addition, the acquisition of knowledge about the company, the fostering of long‐term relationships and the using of the Editran tool creates value through the creation of trust, reputation and an ability to better respond to present and future company needs (Curado, 2008). However, despite the espoused and observed positive effects of the Editran tool, issues remain on how companies facilitate e‐loyalty through technology tools (Hafizi & Nor Hayati, 2006). It has been found that users’ attitude towards the acceptance of a new information system has a critical impact on its success (Al‐Somali et al., 2009; Venkatesh & Davis, 1996; Davis et al., 1989). The acceptance of technology systems may increase productivity and improve individual and organisational performance. The initial stages of the implementation of technology systems can be difficult, but considering that most technical obstacles are gradually eliminated, the question that arises is whether people are willing to use these new technological achievements (Aggelidis & Chatzoglou, 2009). Acceptance of information technology by users is deemed a necessary condition for its success and researchers have been trying to find factors that influence individual’s acceptance of information technology (Al‐Somali et al., 2009). Researchers have developed several models with the aim of improving the theoretical understanding of technology acceptance. Ventakesh et al. (2003) proposed a Unified Theory of Acceptance and Use of
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Technology (UTAUT) developed through a review and consolidation of the constructs of the eight models (Theory of Reasoned Action (TRA), Technology Acceptance Model (TAM), Motivational Model, Theory of Planned Behavior (TPB), C‐TAM‐TPB, Model of PC Utilization (MPCU), Innovation Diffusion Theory (IDT) and Social Cognitive Theory (SCT)) that earlier research had employed to explain technology usage behaviour. Because UTAUT captures the essential elements of the different previous models, this study chooses UTAUT as a theoretical foundation to develop the hypotheses. The UTAUT model examined the determinants of user behavioral intention and usage behavior (performance expectancy, effort expectancy, social influence, and facilitating conditions) and found that all contribute to usage behavior either directly or through behavior intentions. These relationships were found to be moderated by gender, age, experience, and whether or not use is voluntary. Based on Ventakesh et al. (2003), in this study performance expectancy is defined as the degree to which an individual believes that using Editran will help him or her to attain gains in job performance); effort expectancy is defined as the degree of ease associate with the use of Editran; social influence is defined as the degree to which an individual perceives that important others believe he or she should use the Editran; and facilitating conditions are defined as the degree to which an individual believes that an organizational and technical infrastructure exits to support use of Editran. The UTAUT model specifies the causal relationships between performance expectancy, effort expectancy, social influence, facilitating condition, behavioral intention and use intention. Therefore, based on Venkatesh et al. (2003), we frame the following hypotheses: H1: Performance expectancy will have a significantly positive influence on behavorial intention to use Editran. H2: Effort expectation will have a significantly positive influence on behavorial intention to use Editran. H3: Social influence will have a significantly positive influence on behavorial intention to use Editran. H4: Facilitating conditions will have a significantly positive influence on behavior of using Editran. H5: Behavioral intention will have a significantly positive influence on behavior of using Editran. According to Fishbein and Ajzen (1975), behavioral intention is an indication of an individual's readiness to perform a given behavior. Ajzen (1991) argued that behavioral intention reflects how hard a person is willing to try, and how motivated he or she is, to perform the behavior. TRA states that behavioral intention constitutes the most immediate determinant of behavior (Fishbein & Ajzen, 1975). Davis et al. (1989) found that behavioral intention to use the system is significantly correlated with usage, and that behavioral intention is a major determinant of user behavior. Therefore, customer intention to use a service provided by a bank (e.g. Editran) should be an acceptable predictor of continuance intention. On the other hand, loyalty occurs based on a positive behavior toward a particular service (Caruana, 2002). It can be considered that by using Editran companies should find several benefits such as time and cost savings and freedom from place, than could lead to a positive behavior of using this service. Hence, behavior of using Editran should be also an antecedent of e‐loyalty. Following those reasoning, we hypothesize: H6: Behavioral intention to use Editran significantly affects companies’ e‐loyalty. H7: Behavior of using Editran significantly affects companies’ e‐loyalty. Figure 1 provides a synopsis of the arguments above. Performance expectancy
Companies’ e-loyalty H1
Effort expectancy
H3
H7
H6
H2
Behavioral intention
H5
Actual use
Social influence H4 Facilitating conditions
Figure 1: Research model
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3. Method Data collection The population used in this study consists of Spanish organizations with more than 100 employees and companies that used the Editran tool to have close financial relationships to their banks. Like other studies on the topic, this study was designed to cover a wide range of industries, but excluding the agricultural and construction sectors. 360 companies were identified from the SABI 2 (Sistema de Análisis de Balances Ibéricos) database and invited to participate in the study. 121 companies agreed. They were also informed by telephone of the work objectives and they were assured of its strictly scientific and confidential character as well as the global and anonymous treatment of the data. The unit of analysis of the study was defined as business customers. We paid particular attention to the identification of the most appropriate person to complete the questionnaire. To ensure reliability of the gathered data, we selected the ICT executive or the person with direct responsibility in the firms’ ICT investment. We adopted the Huber and Power (1985) approach that suggests that a single key informant should be interviewed in order to minimize the potential for systematic and random sources of error. In addition, as the data for the constructs present in this study were obtained from one single respondent through a self‐report questionnaire, common method variance could have been a concern. Such a problem could have inflated the relationship among the constructs of the study, especially if respondents had been aware of the relationships under analysis. In order to avoid such problem, the research project was labeled as a broad overview of management practices adoption. Therefore no explicit reference to the intention to test antecedents of innovation was evident. Thus, respondents’ attention was not drawn to the relationships being targeted in this study (Podsakoff et al., 2003). Surveying took place over a period of 2 months, from October 2012 to November 2012. A total of 112 valid and completed questionnaires were collected. Of these 112 companies, 87 reported that used Editran during the year 2012. Consequently, we had 87 complete surveys giving a response rate of 24.16% of the total number of companies invited to participate, with a factor of error of 9.1% for p=q=50% and a reliability level of 95.5%. This is within the 10 to 25 percent range which is the average response rate for surveys involving senior management (Menon et al., 1996). Responding companies were compared with those that did not respond in terms of size and performance. No significant differences were found between those two groups, suggesting no response bias. Measures A questionnaire was developed to be the instrument for data collection. All items were measured using a seven‐point Likert‐type scale with anchors from “Strongly disagree” to “Strongly agree”, except two items from the use behavior scale (see Table 1). Performance expectancy, effort expectancy, social influence, facilitating conditions, behavioral intention and use behavior scales were based on Venkatesh et al. (2003). The companies’ e‐loyalty scale uses five items adapted from Taylor and Baker (1994), Oliver (1980) and Zeithaml et al. (1996).
4. Results Smart PLS 2.0 (Ringle et al., 2005) was used in the study, which involves a two‐stage approach (Barclay et al., 1995): the first step requires the assessment of the measurement model. This allows the relationships between the observable variables and theoretical concepts to be specified. This analysis is performed in relation to the attributes of the individual item of reliability, construct reliability, average variance extracted (AVE), and the discriminant validity of the indicators of latent variables. In the second step, the structural model is evaluated. The objective of this evaluation is to test the extent to which the causal relationships specified in the proposed model are consistent with the available data. For hypothesis testing, we used the bootstrapping procedure recommended by Chin (1998). We adopted the latent model perspective to analyse the relationships between the different constructs and their indicators, in which the latent variable is understood to be the cause of the indicators. We therefore refer to reflective indicators. All constructs in the 2
This database contains financial information for 520,000 companies (480,000 from Spain and 40,000 from Portugal), and includes public and private, Spanish and Portuguese companies, with up to 10 years of data. It is updated daily.
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model were operationalized as reflective. With regard to the measurement model, we began by assessing the individual item reliability (Table 2). The indicators were above the accepted threshold of 0.707 for each factor loading (Carmines & Zeller, 1979). Table 1: Summary of scale items
From an examination of the results shown in Table 2, we can state that all of the constructs are reliable. Their Cronbach’s alpha coefficients are good and they have a composite reliability of over 0.7, which is required in the early stages of research, and above the stricter value of 0.8 required for basic research (Nunnally, 1978). The AVE should be greater than 0.5, such that it accounts for at least 50% of the variance of the indicators (Fornell & Larcker, 1981). All the constructs of our model meet this condition (Table 3). For discriminant validity, we compared the square root of the AVE (i.e., the diagonals in Table 3) with the correlations between constructs (i.e., the non‐diagonal elements in Table 3). On average, each construct related more strongly to its own measures than to others. The structural model resulting from the PLS analysis that is summarised in Figure 2 shows the explained 2 variance of endogenous variables (R ) and the standardised path coefficients (β). As can be seen, all the hypothesized relationships are significant, and therefore, all the hypotheses are supported except H3. Since PLS makes no distributional assumptions in its parameter estimation, traditional parameter‐based techniques for significance testing and modelling were used (Chin, 1998). As a consequence of the comparison between covariance structure analysis modelling approaches and PLS, no proper overall goodness‐of‐fit measures exist for the PLS models (Hulland, 1999). The structural model is evaluated by examining the R2 values and the size of the structural path coefficients.
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The stability of the estimates is examined by using the t‐statistics obtained from a bootstrap test with 500 resamples. Table 4 sets out the model statistics, the path coefficients and the t values observed with the level of significance achieved from the bootstrap test. Finally, we performed the Stone‐Geisser test for predictive relevance to assess the fit of the model in the PLS analysis (Geisser, 1975; Stone, 1974). When q‐squared is greater than zero, the model has predictive relevance. In our model, q‐squared was 0.48. Table 2: Factor Loadings of reflective constructs
Table 3: Descriptive statistics and correlation matrix
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Figure 2: Results of PLS Table 4: Model statistics
5. Discussion Relevant literature in the bank industry has emphasized the fact that companies which use technology tools will benefit from the services and consequently be encouraged to adopt technology tools as a regular method of accessing and interacting with bank services. Therefore, the first contribution of this research is to question the existing models which relate to technology and customer loyalty in online bank services. This paper supports or goes in the same direction of previous studies in identifying the value of UTAUT in the implementation of new technology systems in the banking sector. The data indicates that the three constructs (Performance expectancy, effort expectancy, and social influence) contribute to usage behavior, which implies that the main aspects of UTAUT apply to this context of using Editran as well. According to the results, facilitating conditions do not influence use. It can be explained because the participants in this research could have enough familiarity with Editran, thus reducing their dependence on support. On the other hand, issues related to the facilitating conditions construct could be captured within the effort expectancy construct (Venkatesh et al., 203). In addition, performance expectancy was found to be the most significant effect on behavioral intention, which suggests that a customer’s belief in usefulness is a decisive antecedent of behavioral variables (i.e. usage behaviour). This is consistent with previous research which found that performance expectancy construct is the strongest predictor of intention (e.g. Davis et al., 1992; Taylor and Todd, 1995; Ventakesh & Davis, 1996). These findings support the view of Ventakesh et al. (2003), that perceived usefulness has positive and significant effects on users’ continual usage intentions towards electronic services. If the utility of the Editran tool is understood, then mechanisms can be developed for allowing electronic transactions to occur in a controlled and constructive way. The second contribution is to extend the UTAUT towards the postcedents by adding the variable e‐loyalty. Modeling online banking services acceptance is very useful to financial institutions but understanding why customers build e‐loyalty towards them is crucial. The research model tested provides deeper insights into the process of customers’ loyalty build‐up. E‐Loyalty was included in the model as a result of both behavioral
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intention and usage behavior. Findings support that a positive intention towards the use of Editran leads to customers’ e‐loyalty. Hence, it is very important to strive to get the highest positive attitude in users by enhancing effort expectancy, social influence and, mainly, performance expectancy. This way, banks will enlarge their customers’ e‐loyalty encouraging them to continue using their services. Put it another way, the result of a successful customer loyalty strategy leads to customer retention. In addition, this is an important finding as loyalty is not an aim by itself, but a way to improve profitability. The third contribution of this research is to test the research model in a business‐to‐business (B2B) context. Business customers’ loyalty is very important because loyal business customers are more likely to focus on long‐term benefits and engage in cooperative actions beneficial to both partners in a relationship, than enhancing the competitiveness of both partners (Lam et al., 2004). Previous research on online banking services has mainly been conducted in individual customers. Individual customers respondents are free to form their own beliefs, attitudes, and intentions while in a workplace setting people’s attitudes, intentions, and behaviors, as well as their interrelationships are likely to be shaped by formal authority and directives (Lanseng & Andreassen 2007), as the theoretical foundation of the UTAUT assumes (Ventakesh et al., 2003). Thus, the results contribute to the general validity of the model. From a managerial point of view, these findings suggest that online banking services managers should focus on the following issues: Since performance expectancy is the most important antecedent of behavioural intention, managers should increase customers’ e‐loyalty by improving their beliefs of how Editran can offer advantages in their jobs. Informative actions (guides, promotional tasks, etc.) must focus on the usefulness of using Editran services. On the other hand, training programs and disseminations of user guide could also promote self‐efficacy. This work found that employees were significant influenced by their superiors to use Editran. Hence, banks are suggested to develop promotional campaigns to publicize the Editran services between the senior management of potentially business customers. These individuals could be utilized as important change agents because they could increase the use of Editran among their employees leading to the company’s loyalty. This research has several limitations. First, as UTAUT model proposes, other variables (such as age, gender, experience or voluntariness) may affect the results. In futures studies, the research model proposed in this paper could be extended by incorporating these variables. In addition, other external variables such as organizational factors (e.g. trust or resistance to change) or technological factors (e.g. system customisation or cost), could be analyzed. In this way, the model’s predictive power could be improved. Secondly, the research model was tested with a specific tool: Editran. Caution is necessary when generalizing the findings in relation to other online banking services. Finally, because the study was conducted Spain, applying the conclusions to other countries should be further examined in future research.
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Knowledge Management for Organizational Innovation: A Multinational Corporations Perspective Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz and Raquel Sanz‐Valle University of Murcia, Murcia, Spain mili@um.es danieljj@um.es raquel@um.es Abstract: Multinational companies require from mechanisms to capture and apply new knowledge that could be used in their current operations in order to be competitive. One of the objectives of this knowledge is the generation of innovations. In this paper, we try to show how the degree of internationalization is related to the generation of innovations. For this purpose, many companies demand knowledge management processes that capture and apply information from local and international markets. This transferred knowledge could be combined with the internal and external knowledge from their social capital structure. Our results show that this process of learning fosters the generation of innovations on the local headquarters. Keywords: internationalization, knowledge management, social capital, knowledge transfer, MNCs and innovation
1. Introduction Knowledge management is frequently considered as a source of competitive advantage for companies in turbulent markets. For multinational corporations (MNCs) knowledge management is even more important since they have to face a more intense competence and a higher number of changes in the different countries they operate in. However, MNCs are also considered to have better opportunities to acquire and exploit knowledge than domestic organizations because they are in contact with different sources of knowledge in different countries (foreign suppliers, customers, competences, institutions…). In today’s knowledge‐based economy, innovation and learning are vital for value creation in a firm (Kang et al., 2007). There is growing recognition that speed of innovation is important for a firm to create and sustain competitive advantage amidst rapidly changing business environments (Kessler and Chakrabarti, 1996). For this reason, an organization’s ability to innovate is closely tied to its intellectual capital, or its ability to use its knowledge resources (Subramaniam and Youndt, 2005). Furthermore, employee knowledge, skills, and abilities have been considered key resources for the improvement of existing products and services and for the generation of new ones (Lopez‐Cabrales et al., 2009). Recent findings, however, suggest that MNCs do not necessarily exploit such locational advantages of developing countries, but instead increasingly standardize and coordinate environmental practices at the global level – going beyond local environmental requirements – to gain cost and reputational benefits (Pinkse et al., 2010). In the international business literature, MNCs have been viewed as networks of spatially dispersed knowledge for which learning is one of the most important capabilities adding value (Kogut and Zander, 1992, Kogut and Zander, 1993). This study focuses on the knowledge management processes that increase the generation of organizational innovations in MNCs. First, companies should promote the acquisition of knowledge from their international subsidiaries, local markets or internal employees. Then, they could use this knowledge for the generation of new products, improve their current operation processes or make changes in their current organizational and commercialization practices. Using structural equation model with a sample of 104 MNCs, this paper analyses the relationship between the above‐mentioned variables.
2. Theoretical framework Organizational innovation is viewed as the adoption of an idea or behaviour pertaining to a product, service, device, system, policy or programme that is new to the adopting organization (Damanpour and Gopalakrishnan, 2001). Literature underlines that innovation captures the newness of an idea that attempts to improve organizational performance. Furthermore, innovation is a central mechanism for strategic change and growth whereby organizations exploit, explore, and reposition themselves in changing internal and external
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz and Raquel Sanz‐Valle conditions (Dittrich and Duysters, 2007, Kim et al., 2012). The discussion on open innovation suggests that the ability to absorb external knowledge has become a major driver for competitive advantage (Spithoven et al., 2010). MNCs have the opportunity to acquire knowledge for innovation for multiple international and local sources.
2.1 Internationalization and innovation It is generally assumed that innovation development and the subsequent intra‐corporate transfer will positively affect the business activities of recipient units located elsewhere. Previous studies have demonstrated that the development of innovations for international markets may allow economies of scale and cross‐subsidization. Therefore, the development and diffusion of innovation are key strategic challenges for MNEs in the globalised business environment (Li et al., 2013). Furthermore, MNCs can operate as a distributed innovation network that generates, assimilates and integrates knowledge on a worldwide basis. While geographically dispersed subsidiaries can tap into specialized clusters of expertise dispersed worldwide, formal and informal intra‐firm mechanisms can help achieve cross‐regional integration in order to make the dispersed knowledge available throughout the firm (Kogut and Zander, 1993). The reverse knowledge transfer (RKT) could be understood as the knowledge transfer from foreign subsidiaries to local headquarters. This knowledge from a foreign subsidiary could be used by a local headquarter as a source of knowledge or capability (Yamin and Andersson, 2011). Hence, MNC subsidiaries have access to more international knowledge than strictly domestic firms (de Faria and Sofka, 2010). Intensive collaboration between headquarters and subsidiaries as well as between peer subsidiaries provides a social basis for knowledge exchange (Galunic and Rodan, 1998) and supports knowledge sharing processes within the organization (Hakanson and Nobel, 2001, Szulanski, 1996, Almeida and Phene, 2004). Some studies (e.g. Birkinshaw and Morrison, 1995) have found, on examining communication between subsidiaries and parent companies, that the most integrated subsidiaries (those with a higher degree of communication and socialization) developed more knowledge than those that simply implemented innovations. Thus, the literature highlights the importance of foreign subsidiaries' abilities to create, develop and integrate knowledge through both their internal and external networks (Andersson et al., 2002, Phene and Almeida, 2008) and also to generate innovations. Thus, we propose that: H1. MNCs’ internationalization positively influences reverse knowledge transfer from subsidiaries to local headquarters. H2. MNCs’ internationalization positively influences local headquarters’ innovation.
2.2 Knowledge transfer in MNCs MNCs have also the possibility to transfer and share knowledge within their different locations around the world. Knowledge transfer is a process of systematically organized exchange of information and skills between entities (Wang et al., 2004). Successful knowledge transfer promotes that the MNCs locations absorb new knowledge developed in any other location and use it for developing innovations (Andersson, 2003). International management literature highlights the importance of foreign subsidiaries' abilities to create, develop and integrate knowledge through both their internal and external networks (Andersson et al., 2002, Phene and Almeida, 2008). Given their access to the existing knowledge pool in the local environment, foreign subsidiaries play a prominent role in MNE innovation and they can directly enhance the MNE's strategic competitive advantage (Ambos et al., 2006). This recent trend is in line with the broader recognition that foreign subsidiaries can serve as sources of innovations (Birkinshaw et al., 1998, Pearce and Papanastassiou, 1999) that can be transferred to and used by parent companies. What is more, some results show how local headquarters increase their innovative skills and capabilities benefit from the use of knowledge transferred from foreign subsidiaries (Rabbiosi and Santangelo, 2013). In this case, subsidiaries that develop R&D abroad are more likely to develop innovations that can be transferred to the headquarters (Borini et al., 2012), and not just for the local market (Boehe, 2008). In conclusion, the transfer of knowledge from foreign subsidiaries will generate innovation in the local headquarters. Thus, we propose that:
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz, and Raquel Sanz‐Valle H3. Reverse knowledge transfer from subsidiaries to local headquarters positively influences local headquarters’ innovation.
2.3 Social capital The data, information and knowledge that contribute to innovation processes may be fostered by the firm´s social capital. Social capital is understood as the networks, norms, and trust that enable participants to act together more effectively to pursue shared objectives (Putnam, 1993). The generation of internal knowledge for innovation depends on the existence of internal and external social capital. Thus, internal social capital enhances the ability of members within a firm to know who to contact with to acquire relevant knowledge (Lesser, 2000). Regarding external social capital, what enables the company to gain resources from its environment and discover new opportunities are its external networks (customers, suppliers,…) (Aldrich and Zimmer, 1986). Thus, social capital facilitates the development of innovations through the acquisition of updated knowledge from internal and external networks. Kostova and Roth (2003) appoints that social capital is about networks that provide value or benefits. Coleman (1988) states that the focus of social capital is on building and maintaining advantageous ties and contacts. According to Inkpen and Tsang (2005), social capital represents the ability of firms to secure benefits from networks. These benefits can include access to knowledge, resources, technologies, markets, and business opportunities. The behaviour of a collective actor, such as a firm is influenced by its external linkages to other firms and institutions and by the fabric of its internal linkages (Adler and Kwon, 2002), is essential for generating new knowledge and learning. In this sense, it seems clear the fact that social capital is related to a knowledge management processes for generating new knowledge. Social capital theory argues that specific elements of external and internal social relationships provide valuable learning resources (Adler and Kwon, 2002). According to Nahapiet and Ghoshal (1998), social capital is the aggregate of resources embedded in, available through and resulting from the network of relationships held by a firm. Several scholars propose that social capital facilitates the development of a distinctive knowledge base, thereby providing a basis for the creation of organizational advantage (Yli‐Renko et al., 2002). In the same line, Hoffman et al. (2005) state that social capital can enhance the entire knowledge management process because it makes collective action more efficient, because it becomes a substitute for the formal contracts, incentives and monitoring mechanisms that are necessary in systems with no social capital among the organizational members, what in the language of economics, it can reduce transaction costs. Consequently, it can be argued that the new knowledge generated from both external and internal social capital would be a powerful tool for generating innovations in the company. Hence, we state that: H 4. Internal social capital positively influences local headquarters’ innovation. H5. External social capital positively influences local headquarters’ innovation.
3. 3. Methodology 3.1 Population, data collection and sample The sample for this research includes Spanish MNCs with more than 100 employees, tenure of more than 5 years, and having at least one subsidiary in a foreign country. According to the Amadeus database, the number of MNCs fulfilling these requirements in Spain is 1.397. The data was collected using a structured questionnaire through phone interviews. A specialized market research company managed the process. Different steps were followed to carry out the data collection. We contacted the CEO or innovation executive of each organization. The market research company then tracked completion of the questionnaire and helped organizations to complete it. All the processes were supervised and the quality of this activity was tested by contacting a randomly selected sample of firms that had answered the questionnaire. The authors monitored the performance of the companies that had completed the survey. No problems were found. The unit of analysis for this study was the company. Of the 1397 companies invited to participate, a total of 104 usable questionnaires were received (a response rate of 7,44%). The responding companies belong to different sectors of the economy, which allows for a good
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz and Raquel Sanz‐Valle representation of companies in general. The food and beverage industry, the furniture industry and metal production have the highest representation in the sample. A routine check for industry bias indicated no significant differences in the mean responses on any construct across firms from different industries. In addition, Chi‐square distribution analysis revealed no significant differences between the sample and the population, which was drawn from in terms of industry distribution, the number of employees and sales volume.
3.2 Measures The key variables in this study were measured using 5‐point Likert scales based on previous literature. Internationalization It has been measured as a formative scale from three items (we calculated the mean of them) related to the number of international subsidiaries, the numbers of years from the creation of the first international subsidiary and the number of different countries that counts with a subsidiary (Bausch and Krist, 2007, Duarte‐López and Vidal‐Suárez, 2011, Pedersen et al., 2003). They were recoded to 1‐5 Likert scales. The construct used for measuring external social capital was composed by 4 items and based in Perrez‐Luño et al. (2011), Maurer and Ebers (2006), and Inkpen and Tsang (2005). They are related to the degree and quality of the cooperation of the organization with other companies. Internal social capital was measured with 4 items based in Yii, Renko et al. (2002). There are related to cooperation, teamwork, variety of jobs, and jobs rotation of the employees on their jobs. Reverse knowledge transfer was measured by asking the respondent the degree to which the knowledge they had acquired from their subsidiaries was useful in improving a list of tasks. We adapted the Rabbiosi (2011)’ scale. After the scale depuration process through CFA, the scale includes 6 items. Organizational innovation measure includes four items, each referring to one of the four types of innovation (OCDE, 2005): innovations in product, process, commercialization and management. One item was eliminated in the process of scale purification.
3.3 Validity and reliability check Both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted on the multi‐ item reflective measures (internal social capital, external social capital, reverse knowledge transfer and innovation). EFA with varimax rotation was performed on 22 variables yielded four factors with eigenvalues greater than one (five items were erased) and explaining 70.4 per cent of the total variance. To assess the single dimensionality of each construct, a confirmatory factor analysis of the four constructs was conducted (Anderson and Gerbing, 1988). The results of the confirmatory factor analysis (CFA) to test the validation of the measures (χ2(84)= 122.196 CFI=.945 IFI=.947 BNNFI=.931 RMSEA=.073 SRMR=.060) indicate a good fit for the model. Reliability of the measures was calculated with Bagozzi and Yi’s (1998) Composite Reliability Index and with Fornell and Lacker’s (1981) Average Variance Extracted Index. Discriminant validity is indicated first since the confidence interval (± 2 S.E.) around the correlation estimate between any two latent indicators never includes 1.0 (Anderson and Gerbing, 1988). Secondly, discriminant validity was tested second by comparing the square root of the AVEs for a particular construct to its correlation with the other constructs (Fornell and Larcker, 1981). The results of these tests provided strong evidence for the reliability and discriminant validity among the constructs. Table 1 provides an overview of the means and standard deviations of the constructs. The results show that there is no multi‐collinearity. In addition, the table shows basic information about each factor.
4. Results We conducted our analyses with structural equation modelling (SEM) using the statistical program EQS 6.1 for Windows (Bentler, 1995). After satisfying the requirements discussed above, we tested the structural model,
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz, and Raquel Sanz‐Valle which summarizes the three proposed hypotheses. Conventional maximum likelihood estimation techniques were used to test the model (Jöreskog and Sörbom, 1996). The fit of the model is satisfactory, thereby suggesting that the nomological network of relations fits the data. This is another indicator that supports the validity of these scales (Churchill, 1979). Table 1: Reliability, validity and measurement model Lowest Cronbach SCRa AVEb t‐value alpha Internationalization 2.928 1.285 ‐ ‐ ‐ ‐ Internal social capital 3.984 .719 5.448 .734 .783 .547 External social capital 3.776 .888 9.225 .895 .901 .754 Reverse knowledge transfer 2.897 1.058 7.580 .910 .916 .646 Innovation 3.721 .743 4.629 .732 .787 .553 Age 4.312 1.108 ‐ ‐ ‐ ‐ Size 1.115 .596 ‐ ‐ ‐ ‐ CFA Goodness of Fit: χ2(84)= 122.196 CFI=.945 IFI=.947 BNNFI=.931 RMSEA=.073 SRMR=.060; a Scale composite reliability (qc=(Aki)2 var (n)/[(Aki)2 var (n) +Ahii]; (Bagozzi and Yi 1988); b Average variance extracted (qc=(Aki)2 var (n)/[(Aki)2 var (n) +Ahii]; (Fornell and Larcker 1981) Constructs
Mean
SD
Internal social capital
β
=0. 3
15*
*
β =0.384**
External social capital
β
* 1* .3 0 =0
Size
Age
β =0.138
β =0.107 Innovation
R2=0.472
Reverse knowledge transfer
β =0.333***
R2=0.111
β =-0.058 Rate of internalization
Figure 1: Structural model We do not found support for supporting hypothesis H1 concerning the relationship between MNCs internationalization and organizational innovation (table 2). The degree of internationalization does not guarantee that these companies c innovate (β = ‐0.052; p>0,10) when we included the mediation variable (reverse knowledge transfer) on the model. However, our findings support H2. In this case, we have observed a positive relationship between the degree of internationalization and RKT (H2; β = .333***). Thus, a higher degree internationalization promotes that headquarter could acquire new knowledge from the foreign subsidiaries. Table 2: Construct structural model relationships Main relationships
Coefficient
td
‐.058 .315** .384** .301** .333***
.477 1.999 2.543 2.271 2.997
0.107 0.138
.947 1.183
.100*
1.853
Main paths Internationalization → Innovation Internal social capital → Innovation External social capital → Innovation RKT → Innovation Internationalization → RKT Control variables Age → Innovation Size → Innovation Indirect effects Internationalization → Innovation 2 (121)
Goodness of Fit from the model with mediator variable χ
= 164.854 CFI=.936 IFI=.939 BNNFI=.919 RMSEA=.065
Finally, we found support for the rest of hypotheses as sources of new knowledge for generating innovation. As table 2 shows, there is a positive relationship between RKT and organizational innovation (H3; β = .301;
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz and Raquel Sanz‐Valle p<0,10), what reinforces the idea that knowledge from overseas promotes the innovation process. Also, innovation is also enhanced by the internal social capital (H4; β = .355; p<0.05). The internal relationships among different members or an organization facilitates the creation of relevant knowledge that could be used for innovation. Finally, external social capital is also related to organizational innovation (H5; β = .384***), since the relationship of the headquarter with their customers, suppliers and competence provide also relevant information for generating new products, processes or changes in management and marketing. Additional results show how, although we have not found a direct relationship, the degree of internationalization influences organizational innovation through promoting RKT (κ=0.100, p<0.10). Thus it, internationalization contributes to generate innovation if headquarter have the possibility of acquiring the knowledge from their foreign subsidiaries.
5. Conclusions Organizational innovation is broadly considered as a source of competitive advantage (Lieberman and Montgomery, 1998, Schumpeter, 1942, Utterback, 1994). Especially, MNCs require of the generation of innovation in order to be competitive and adapt for each market in which they operate. However, organizational innovations demand of the generation of new knowledge, what is a particularly relevant in MNCs. They control knowledge‐based resources and capabilities across borders (Bartlett and Ghoshal, 1989, Kogut and Zander, 1992) and engage in different types of knowledge transfers (Rabbiosi and Santangelo, 2013). In this paper we have focused on the reverse knowledge transfers from subsidiaries to parent companies (Ambos et al., 2006). RKT provides potential opportunities for headquarters to develop new products through the combination of existing and different complementary skills (Kotabe et al., 2011). Consequently, subsidiaries’ resources and capabilities can be transferred trough the headquarters for generating new knowledge and innovations (Bartlett and Ghoshal, 1989). The main contributions are based on this topic. First, headquarters’ innovation is determined by the organizational capacity to management the new knowledge that is acquired from different sources. As other companies, the headquarters could generate new knowledge from the relations among their employees. We have found a positive effect of internal social capital on organizational innovation. In this case, the internal generation of knowledge is crucial for developing new products or introduces others changes on the organization. Also, the headquarters could foster innovation trough the acquisition of new knowledge from their relationships with suppliers, customers, competence and others institutions from their local markets. This is supported since we have found evidence of the relationship between external social capital and innovation. Finally, other source of acquisition of knowledge that is particular of the MNCs is the RKT. The knowledge transferred from subsidiaries that operates on international markets provide of a rich source of knowledge that is not available on local markets and that could show the difference with the local competence. Secondly, our findings provide evidence about that the degree of internationalization (numbers of years on international markets, number of international subsidiaries and numbers of countries in which MNCs operate) is positively related to the utility of their knowledge transferred. In this case, internationalization provides an important source of managing knowledge. However, we have not found evidence about that the degree of internationalization fosters the generation of innovations directly. We only have found indirect evidence about internationalization could be derived on organizational innovation if MNCs allow the transference of knowledge from foreign subsidiaries and the headquarters, which suggest that RKT could play a mediator role. In conclusion, MNCs that are characterized by working in different countries are going to generate innovations if they promote knowledge management initiatives inside and outside of the organization and also with their subsidiaries. Thus, internationalization does not generate organizational innovation alone, but companies need to interchange knowledge and generate learning among subsidiaries to attain this target. This study has also implications for practitioners. On the one hand, like previous research, our data show that in order to generate innovations, companies should foster their knowledge management processes through their social capital and the relationships between subsidiaries and headquarters. In this case, companies should promote the relationships among internal employees, external agents and international subsidiaries. Despite the contributions of this paper, its results should not be interpreted without recognizing its potential limitations. The most important one is its cross‐ sectional design, which may constrain both the observation of multiple long‐term effects of each variable and the elucidation of causal relationships between the variables. This limitation could be avoided by employing a longitudinal study design. Other recommendations for future research on the relationship between RKT and innovation emerge from the present study. Since the premise that RKT is based on the transmission of knowledge, it would be necessary to analyse how this knowledge is distributed. Two main ideas to examine are
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Micaela Martínez‐Costa, Daniel Jimenéz‐Jimenéz, and Raquel Sanz‐Valle the use of expatriates (Minbaeva, 2008) and the role the knowledge management strategies (Edvardsson, 2008, Hansen et al., 1999). This could help to understand how this knowledge could be easily transmitted to the headquarters.
Acknowledgements The authors acknowledge the funding received from the Spanish Ministry of Science and Technology (research project ECO2009‐12825) to undertake this research
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Expatriates’ Influence on Knowledge Sharing: An Empirical Study With International Portuguese Companies Dora Martins Superior School of Industrial and Management Studies, Polytechnic of Porto, Vila do Conde, Portugal doramartins@eu.ipp.pt Abstract: Despite the abundant literature in knowledge management, few empirical studies have explored knowledge management in connection with international assignees. This phenomenon has a special relevance in the Portuguese context, since (a) there are no empirical studies concerning this issue that involves international Portuguese companies; (b) the national business reality is incipient as far as internationalisation is concerned, and; (c) the organisational and national culture presents characteristics that are distinctive from the most highly studied contexts (e.g., Asia, USA, Scandinavian countries, Spain, France, The Netherlands, Germany, England and Russia). We examine the role of expatriates in transfer and knowledge sharing within the Portuguese companies with operations abroad. We focus specifically on expatriates’ role on knowledge sharing connected to international Portuguese companies and our findings take into account organizational representatives’ and expatriates’ perspectives. Using a comparative case study approach, we examine how three main dimensions influence the role of expatriates in knowledge sharing among headquarters and their subsidiaries (types of international assignment, reasons for using expatriation and international assignment characteristics). Data were collected using semi‐structured interviews to 30 Portuguese repatriates and 14 organizational representatives from seven Portuguese companies. The findings suggest that the reasons that lead Portuguese companies to expatriating employees are connected to: (1) business expansion needs; (2) control of international operations and; (3) transfer and knowledge sharing. Our study also shows that Portuguese companies use international assignments in order to positively respond to the increasingly decaying domestic market in the economic areas in which they operate. Evidence also reveals that expatriation is seen as a strategy to fulfill main organizational objectives through their expatriates (e.g., business internationalization, improvement of the coordination and control level of the units/subsidiaries abroad, replication of aspects of the home base, development and incorporation of new organizational techniques and processes). We also conclude that Portuguese companies have developed an International Human Resources Management strategy, based on an ethnocentric approach, typically associated with companies in early stages of internationalization, i.e., the authority and decision making are centered in the home base. Expatriates have a central role in transmitting culture and technical knowledge from company’s headquarters to the company’s branches. Based on the findings, the article will discuss in detail the main theoretical and managerial implications. Suggestions for further research will also be presented. Keywords: international Portuguese companies, expatriates, knowledge sharing, knowledge transfer, international assignments
1. Introduction The internationalization of business, the globalization of the economies and the free circulation of people and goods at a global scale have contributed to the increase in expatriation (Baruch et al., 2002; Scullion and Brewster, 2001). An expatriate is an employee sent by a company to another company of the group, to work in another country for a defined period of time, which can last from six months to several years (Avril and Magnini, 2007). Previous research (e.g. Brookfield GRS, 2010; Harzing, 2001) indicates that the proportion of expatriates in multinational companies has been growing in recent years. In this context, expatriates have a fundamental role on knowledge transference between headquarters and their subsidiaries (Lazarova and Tarique, 2005) and can help company to understand the business opportunities in relation to other parts of the world, because they have knowledge about these particular cultural contexts and specific market and customer information (Lazarova and Caligiuri, 2001). The role of expatriates as vehicles for disseminating knowledge across multinational corporation (MNC) units has emerged as a new area in the international human resource management (IHRM) literature (Minbaeva and Michailova, 2004). Some studies (e.g. Bonache and Brewster, 2001; Tsang, 1999) show that MNCs are interested in using expatriates as knowledge transfer agents. Despite the importance of this theme in literature, empirical studies (e.g., Baruch et al., 2002; Caligiuri and Colakoglu, 2007) focus mainly on companies based in the USA, the United Kingdom, Finland, Germany, Australia, and studies of a similar nature in companies based in Portugal are unknown. Therefore, this research intends to continue the studies already conducted in other countries. It is the aim of the present research to
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Dora Martins identify the expatriates’ role in the process of growth of Portuguese companies. Although the main focus of this research refers to a specific geographic area (i.e., Portugal), the data from this study will provide a basis for comparative analysis within an international context. We have chosen Portuguese companies as a sample because the number of Portuguese expatriates has increased in recent years. However, the experience of Portuguese Companies relating to this issue is scarce. On the other hand, research on knowledge management in MNCs has generally focused on subsidiaries. Only a few studies have explored knowledge management in connection with international assignees. Thus, our research questions are: How do the types and other characteristics of international assignment and reasons for adopting expatriation help us to understand the role of expatriates in knowledge sharing? How is the degree of knowledge transfer among headquarters and their subsidiaries enhanced? This paper is structured in the following way: in the next section, the literature on the role of expatriates in transfer and knowledge sharing will be reviewed; afterwards, the methodology used in the empirical research and the presentation of the main results will be presented. Finally, the paper shall be concluded with a discussion on the key findings and future research directions.
2. Theory 2.1 Expatriates as control and learning agents and as diffusers of knowledge International assignments continue to have an essential role in maintaining and generating high business value (Brookfield GRS, 2010). In general, expatriates are professionals entrusted with this responsibility. Generally, they are considered to be transfer, learning and dissemination of knowledge agents (Minbaeva and Michailova, 2004), due to:
Acting as transfer agents when they transfer routines, information, knowledge (explicit and implicit), values/culture from headquarters to subsidiaries. This happens when, for example, they teach the natives the headquarters’ typical actions or base their decision‐making on "adequate" knowledge, expertise and guidance;
Acting as learning agents when, for instance, (i) they learn new ways of operating in the host country, (ii) they enhance decision‐making mechanisms adjusted to that particular country, (iii) they acquire knowledge about the foreign culture; (iv) they create interpersonal relationship networks; (v) they understand the legal, social, political and economic environment of the host country;
Acting as agents of knowledge diffusion when they transfer to headquarters (and/or to other company subsidiaries) the knowledge acquired throughout their international experience. Such diffusion occurs when expatriates share and disseminate their knowledge.
The literature (e.g., Minbaeva and Michailova, 2004) suggests that the expatriate’s role is to disseminate knowledge amongst the different multinational subsidiaries. This necessity is greater when the duration of the international assignment is longer. Therefore, there is ground to believe that, besides facilitating communication, expatriates transfer knowledge and experience among the different subsidiaries and headquarters. Moreover, they are better equipped to more consistently manage work according to the company’s overall interests. When good management is observed, expatriates are assumed as the responsible agents for expatriation success.
2.2 Types of international assignment The literature (e.g., Lazarova and Caligiuri, 2001; Harzing, 2001) proposes four different types of international assignments:
Technical international assignment. Its main objective is to ensure that the expatriate performs technical work and returns to his/her current position in the home company. The employee is not required to develop intercultural skills in order to be successful in the international assignment;
Tactical or functional international assignment. The expatriate goes on an international assignment to do a specific job and returns to his/her current job in the home company. In general, the experience of the international assignment is similar to the acquired experience in the home company;
Developmental international assignment. The reason behind this international assignment is the developing of high‐potential talent based on the development of overall management skills. Typically, the
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Dora Martins recipients of this type of assignment are leaders, to whom Caligiuri (2006) recommends an internal rotation program after returning to the home company, so as to develop leadership skills;
Executive or strategic international assignment is targeted at executives with nuclear positions in the company. This type of assignment helps to acquire the skills required for the general development of intra‐organizational career plans. According to Caligiuri (2006), this type of mission requires an added concern after returning to the home company so as to ensure a new job that allows implementing the new global competencies developed, which, in turn, are assumed as critical to the executive worker and the home company.
2.3 Reasons for adopting expatriation practices Various literature references (e.g., Bonache et al., 2001; Minbaeva and Michailova, 2004) suggest that this diversity of organizational reasons may require expatriates to transfer knowledge and experience among the branches (and among themselves and the home office), to coordinate units globally interdependent and to carry out the local adaptations without affecting the global company, namely:
Initiating operations in foreign countries and transfer knowledge and competencies (Bonache et al., 2001; Minbaeva and Michailova, 2004). This reason is linked to the need to send teams or employees to promote the transfer, control and dissemination of knowledge through all the multinational business units. In addition to this, they are also provided with cross‐cultural skills to facilitate communication and cooperation between headquarters and branch offices;
Transmission of the national image and representation of corporate home office (Bonache et al., 2001). This reason is linked to the multinational company in the initial phase of development that tends to assign national employees to positions of greater trust in branches in third countries. This decision aims to ensure the success and development of the home office’s new businesses established in new international markets;
Control and coordination of global activities (Bonache et al., 2001; Harvey and Novicevic, 2001). This reason is directly linked to the interest in the global integration of the company’s trans‐national activities. Through the expatriates, they seek to replicate the values and objectives of the home office in the culture of the branch where the international assignment is taking place;
Career development for executive positions (Bonache et al., 2001; Harzing, 2001). This reason is used by companies that include a career development plan of their executive managers on an international assignment as an essential condition;
Development of a global mentality in the organization (Bonache et al., 2001; Harzing, 2001). This reason is based on the fact that international companies intend to develop an integrated perspective of the organization, share new ideas, strategies and action among the different business units of the organization, regardless of their country of origin;
Lack of local talent (Baruch et al., 2002; Harzing, 2001; Minbaeva and Michailova, 2004). This reason is explained by the need from companies to send employees equipped with distinctive technical, inter‐ personal and management competencies to branches in other countries lacking in local candidates qualified for the available job post. The expatriate’s individual competencies can be improved without the incidence of a great disparity in experience between the work performed before and during the international assignment.
3. Methods 3.1 Case selection We opted for a qualitative case study methodology to gain a comprehensive, in‐depth understanding the role of expatriate to improve knowledge sharing. In order to do so, three criteria were adopted to choose the cases for analysis. Firstly, the companies should be located in Portugal. Secondly, they should conform to a formal HRM structure. Thirdly, they should have expatriation experience (i.e. have expatriates and repatriates). Given that Yin (2003) suggests that a multiple case‐study should present between 4 and 10 cases, we have a theoretical and intentional sample (Creswell, 1998) seven companies, which have been interviewed. All companies were private and based in the North of Portugal: three comprised the industrial sector (ICA, IEE, IMC), two of them were integrated in the commerce and distribution sector (CDA and CDS), two belonged to
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Dora Martins the services sector (SFA and SSA). Three companies had had expatriation experience more than ten years before, and four of them had had this experience less than five years before. The majority (57,2%) has less than one thousand workers and thirty‐five months had been the average period of the international assignment. These companies have subsidiaries in different countries (e.g. Angola, Brazil, China and Germany). Table 1 summarizes the main characteristics of the companies included in the study. Table 1: Characteristics of companies studied Company
Business Sector
Number of workers
Number of expatriates
Duration of expatriation (average in months)
CDA
Commerce/ distribution
960
66
47
CDS
Commerce/distribution
35000
90
40
ICA IEE IMC SFA SSA
Industry Industry Industry Services Services
1800 4500 932 295 598
258 160 10 6 23
16 48 27 51 16,5
Fourteen organizational representatives (eight males; aged 39 in average) have participated in this study. Six performed technical functions related to the HR department (a lawyer, two operational managers and three technical coordinators) and eight belong to direction boards (seven Human Resources Directors and a CEO). The majority possessed a university degree (n=12), one had a Masters’ course and another had the twelfth grade. Thirty repatriates (25 males; aged 43 in average) were interviewed. The vast majority of repatriates (n= 16) possessed a university degree, five of them had post‐graduated qualifications (MBA and a Masters’ Degree) three had a BA, five had finished twelfth grade, and one had finished ninth grade. As for their marital status, 7 were single, 20 were married and three were divorced.
3.2 Data collection and coding Semi‐structured interviews were made to organizational representatives (two per company) and to repatriates (four or five per company) between October 2009 and March 2010. A total of forty‐four interviews were made (fourteen to organizational representatives, thirty to repatriates after completing the expatriation assignment). All interviewees were native Portuguese and all interviews were conducted in Portuguese, by the same researcher. Particular attention was paid to the data collection about the types of international assignments; reasons for expatriation and role of this repatriates on international assignments. The average duration of each interview was 70 minutes. They were tape‐recorded, data were transcribed and categorized based on ‘commonalities and differences’ across emerging themes and then frequencies for each category were determined (Ghauri and Gronhaug 2002). To ensure anonymity identification codes were assigned to each company: CDA; CDS; ICA; IEE; IMC; SFA; SSA. In each company, repatriates called REPAT and organizational representatives called REPORG. Confidentiality was granted to interviewees and to the companies, as well.
4. Results 4.1 Types of assignment Expatriate roles during the international assignment are related to the type of international assignment. We have found three types of international assignments in the companies studied (cf. summary in table 2). Table 2: Repatriates’ distribution by company and type of assignment Companies Type of assignment CDA CDS ICA IEE IMC SFA SSA Total Technical 3 1 4 2 1 1 3 15 Tactical or functional 1 1 1 0 2 1 1 7 Strategic/executive 1 2 0 2 1 2 0 8
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Dora Martins Technical international assignments All companies use expatriates to perform technical responsibilities. The ICA is a company that encourages the use of expatriates for international assignments of this type (n = 4) as opposed to CDS, SFA, IMC (n = 1 in each company). Most expatriates go on an international assignment in order to give their contribution to support technical activities which are determinant of the success of the foreign subsidiaries and of their return to the home company. These expatriates carried out specific projects and, once they were finished, they had returned to their headquarters. Tactical or functional international assignments The tactical or functional type of international assignments has been adopted by these Portuguese companies as well. Its use is more recurrent in IMC (n = 2). This type of international assignment is not implemented by the IEE company. The companies that adopt this type of international assignment instruct expatriates so as to ensure the support of important but not critical maintenance activities of the foreign branches. The expatriate’s assignment is to perform specific tasks allowing him/her to develop skills. Strategic/executive international assignments The companies adopt this type of international assignment instructing expatriates to be fully responsible for foreign subsidiaries. Such assignments are aimed at executive expatriates who have high levels of responsibility within the company. This type of assignment has been adopted by in 5 companies (IMC, SFA, IEE, CDA, CDS). In this type of international assignment, expatriates’ tasks include controlling international operations or transferring organizational culture from headquarters to foreign subsidiaries. To sum up, the results have suggested that there were different roles assigned to expatriates which, per se, determine different types of international assignments. The assignments of a technical type were the most common. Although it was observed in all companies, the CDS and the SFA have shown a greater tendency to adopt assignments of a strategic/executive type.
4.2 Organizational reasons for expatriation Two of the main reasons why companies revert to expatriation were identified: i) control of international operations (n=8) and; ii) business needs (n=6). Table 3 summarizes the organizational reasons identified by organizational representatives of companies included in the study. Table 3: Organizational reasons, per company CDA CDS ICA IEE IMC SFA SSA Total Organizational reasons Control of international operations 0 2 1 1 2 2 0 8 Business needs 2 0 1 1 0 0 2 6
Control of international operations The companies (CDS, IEE, IMC, ICA, SFA) refer that one of the main reasons for deciding to expatriate executives is connected to the need to control international operations while the subsidiaries do not become autonomous (n=8, this is referred to by both organizational representatives of CDS, IMC and SFA and, by one organizational representative from the companies ICA and IEE). Sending trustworthy people with knowledge of the culture and business helps improving the home company and its subsidiaries institutional representation in the foreign country. Besides, it also facilitates the diffusion of the know‐how from the home company to the subsidiaries. These arguments are explained in the following words: … when opening a branch abroad, Portuguese workers are sent abroad (...) these have already a perfect knowledge of the organization, where they are going to start working. And those kinds of people, who belong to the company’s permanent staff, are the ones we acknowledge to be able to represent the organization abroad.... (REPORG 1, ICA) Once subsidiaries are set up in other markets, some of these companies (CDS, IEE) defend the need to maintain national collaborators in top management positions, so that national cultural and business values can be replicated in these other foreign structures. This argument is clearly illustrated in the following arguments:
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Dora Martins … typically, what IEE does is to place at the head of the business in a subsidiary, either the CEO or, whenever possible, the CFO… we want to control the business, and the best way to control it is either through the CEO or through the CFO… Although we respect the local culture, we like to add value to it (by hiring, teaching and training local workers) we wish, above all, to continue and take our values, our culture, our mission, our way of life, our business ethics to the markets where we are. In short, everything that characterizes the culture of IEE in Portugal ...we try to replicate it in the selected target‐markets. (REPORG 1, IEE) Business needs The national market is showing signs of decline, thus the companies studied feel the need to reorient their expansion strategies internationally so as not to lose business. The need for business growth through internationalization is another main reason, especially for the companies CDA, ICA, IEE, SSA (n=6, this is referred to by both organizational representatives of the companies CDA and SSA and by one of the organizational representatives of the companies ICA and IEE), as illustrated in the following statements: The principle of necessity is in the basis [of expatriation] … there really is a strong investment at that level [the expatriation of highly competent staff, with great potential from CDA headquarters].This happens because about 70% of the Group's cost‐effectiveness is in the international area in the next 10 years. (REPORG 2, CDA)
5. Discussion and conclusion On the one hand, the results of this study indicate that there is a group of companies (CDA, IEE, SSA and IMC) that generally share the same organizational reasons for expatriation. That is to say, they assume the international assignments according to the need of finding alternatives to the increasingly decaying domestic market in the economic areas in which they operate. On the other hand, evidence reveals that expatriation is assumed as a strategy to fulfill some of the main organizational objectives (e.g., business internationalization, improvement of the coordination and control level of the units/subsidiaries abroad, replication of the home base aspects, development and incorporation of new organizational techniques and processes). The organizational reasons for expatriation found in these companies are congruent with the majority of the literature reviewed (e.g., Bonache et al., 2001). However, comparing the results found to those recently obtained by Tungli and Peiperl (2009), Portuguese companies tend to resemble companies in the United Kingdom and Japan (i.e., using expatriation to create a new operation) more than the U.S. companies (i.e., to fill competency gaps). Companies in the early stages of international development tend to draw more attention to expatriations of a technical or functional type (Caligiuri and Colakoglu, 2007).This can help us to understand the reason why expatriations of a functional and technical type predominate in Portuguese companies over expatriations of a developmental and strategic type. Additionally, the management of expatriates in these companies seems to be in congruency with the opinion of Mayrhofer and Brewster (1996) and of Perlmutter (1969) who state that the majority of European companies organize and maintain an IHRM according to an ethnocentric approach. In other words, the authority and the decision making are centered in the home base. This type of IHRM strategy is characteristic of companies in the early stages of internationalization, whose occupation of the core positions in the branches is attributed to home base expatriates. The expatriates have a leading role in the culture and technical knowledge transfer of the home base to the international branches. The companies with an ethnocentric management of their HR tend to consider the home base expatriates better and more trustworthy than the native collaborators from countries where the branches are located. This evidence helps to understand why the expatriates’ competence development is not one of the organizational reasons referred to by these Portuguese companies. Similar to the conclusions of Scullion and Brewster (2001), the results of this research seem to demonstrate that, from an organizational perspective, the expatriate’s role is linked to the need to improve knowledge sharing, which confirms the strategic importance of expatriates in these Portuguese companies. Our findings show that expatriates have also long been regarded as part of a knowledge network in international companies (Reiche et al., 2011). They also have shown how the expatriates acquire the knowledge that they can subsequently disseminate to the wider organization. Our research additionally suggests that if expatriates develop links and share values with the host company staff, they will be more likely to acquire company‐
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Dora Martins specific knowledge that they will potentially be able to disseminate and/or facilitate ongoing learning and knowledge sharing further in the home company upon completion of their assignments (Reiche et al., 2011). Some of the benefits of the expatriates’ influence on knowledge sharing/transfer are the contributions that they may give to the subsidiaries’ performance improvement through their individual and corporative knowledge. Furthermore, through knowledge transfer, the subsidiaries’ global knowledge can be enhanced so as to better understand international company networks, namely when expatriates are sent to different organisation areas. According to Crowne (2009), expatriates can be very important when it comes to a better understanding of local market, knowledge about foreign culture, understanding of the macro‐economic environment and/or infrastructure distribution. Typically, expatriates have extended experience within the home companies when chosen for international assignments. Thence, they usually show to have a solid knowledge on corporative objectives and strategies. Consequently, they are an important vehicle to the success of knowledge transfer and dissemination between the home company and the subsidiary (Minbaeva and Michailova, 2004). Finally, the expatriates’ role is also significant on both knowledge dissemination and absorption, especially when home company knowledge needs to be transferred to foreign subsidiaries because of host country markets differences (Li and Scullion, 2010). As for the problems that may arise from the expatriates’ influence on knowledge transfer, we can say that it might not be always beneficial for the subsidiaries. For example, when expatriates show insufficient knowledge on the host country culture and local business operators (Fang et al., 2010), the local workers are in advantage. Finally, there is also the possibility of both expatriates and local workers knowing little about each other’s knowledge. This can be also a problem to knowledge sharing among expatriates and local workers (Li and Scullion, 2010). Research implications also emerge from this theoretical discussion. Firstly, it expands previous research on expatriates’ role in the Portuguese context. Secondly, the results confirm previous studies (e.g. Bonache and Brewster, 2001; Reiche et al., 2011, Tsang, 1999) by providing empirical evidence on the type of assignment and organizational reasons for expatriation and how expatriates from headquarters can make a contribution to knowledge sharing and transfer. Our study shows that improving knowledge transfer is more important than improving knowledge sharing. Our results might suggest managerial implications as well, especially in terms of how to develop the capacity to improve knowledge transfer and sharing between headquarters and their subsidiaries. Finally, our study has some limitations that should be considered when interpreting the findings and should be considered when pursuing further research. First of all, we have analysed a specific context. These companies were all Portuguese, and it may not be possible to generalize these results to other companies, especially in other countries with different characteristics. Future research may opt for distinct methods of data collection (e.g., questionnaire surveys) addressed to a broader universe (not just the number of cases, but also in the diversity of respondents) in order to obtain information and to analyze the broader Portuguese organizational context. It is important that future studies do continue this approach, with a larger sample of both the companies and the repatriates so as to allow comparisons. To sum up, this study encourages investigation paths so that future researchers can enhance and deepen knowledge on the subject and help the emergent internationalization process of Portuguese companies.
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Intellectual Capital: A Valuable Resource for University Technology Commercialisation? Kristel Miller1 Sandra Moffett2, Rodney McAdam2 and Michael Brennan2 1 Queens University Management School, Queens University Belfast, UK 2 Ulster Business School, University of Ulster, UK kristel.miller@qub.ac.uk sm.moffett@ulster.ac.uk r.mcadam@ulster.ac.uk m.brennan@ulster.ac.uk Abstract: With the emergence of the knowledge‐based economy, intellectual capital (IC) has gained prominence in literature. In a knowledge‐based society, knowledge is recognised as the driver of productivity and growth (OECD, 2011) thus this intangible asset is regarded as the hidden value of an organisation. Parallel to this development, universities role in society has changed whereby they are expected to contribute directly to economic development through technology transfer. University technology transfer (referred to from here onwards as UTT) is an uncertain and risky process whereby multiple stakeholders interact to commercialise knowledge residing within universities. Thus, it is a knowledge intensive process where competitive advantage is often based on intangible assets, namely lC. IC and knowledge management are closely intertwined with both concepts being linked to superior innovation performance. However, very little research has looked at this vital intangible side related to knowledge transfer and exchange within UTT (Lockett et al., 2003; Miller et al., 2011). This paper attempts to help fill this gap by exploring IC within a UTT context, with the aim of unravelling its importance for knowledge transfer and sharing. A qualitative methodology of one university was undertaken to explore this under‐researched area. Various factors attributed to IC were found to both enhance and hinder knowledge sharing during university technology commercialisation processes. These factors are broken up into human capital factors which comprised of networking capability, learning orientation and attitudes; relational capital factors which comprised of relationship building, trust and synergy and structural capital factors which comprised of procedures and social integration mechanisms. This research found that the three key components of IC play a key role in affecting knowledge transfer and sharing; and consequently impact UTT activities. Research on IC is still in its infancy and more empirical studies are needed to explore the managerial issues related to IC (Dumay and Garanina, 2013); thus this research will give UTT practitioners and University stakeholders an insight of the importance of valuing and managing their intangible assets to aid the entrepreneurial mission of universities. Keywords: intellectual capital, university technology transfer, human capital, relational capital, structural capital, knowledge transfer
1. Introduction With the emergence of the knowledge‐based economy, intellectual capital (IC) has gained prominence in literature. In a knowledge‐based society, knowledge is recognised as the driver of productivity and growth (OECD, 2011) thus this intangible asset is regarded as the hidden value of an organisation. Nahapiet and Ghoshal (1998) identify that IC represents a “valuable resource and capability for action based in knowledge and knowing” (pg. 345). Whilst IC is emergent in regards its development in literature, it is growing at an accelerated rate as organisations realise the importance of their intangible assets when competing in a knowledge economy (Yitmen, 2011; Bontis, 2001). Parallel to the emergence of the knowledge‐based economy, universities role in society has changed. Traditionally universities were involved in teaching, research and the dissemination of knowledge across both th academic and student communities (Lu and Etzkowitz, 2008). However, the early 20 Century witnessed a shift in the role of the scientific community whereby universities had to take on a ‘third mission’ and contribute directly to society through technology transfer (Rosenberg and Nelson; 1994).This evolution was due to a combination of globalisation and regionalisation in economic development (McAdam et al., 2012) and the increased pressure from government on universities to take a more proactive role in regional and societal development (Rothaermel et al., 2007). The increasing decentralisation of university funding means that there is increasing pressure on universities ability to leverage their IC and manage knowledge in order to gain a competitive advantage (Ramirez et al., 2007). However, technology transfer from universities does not exist in a silo (McAdam et al., 2012). It is a knowledge intensive process and requires interaction between the university, government, industry and other technology transfer stakeholders to increase the chances of commercialisation and consequently enhance regional development (Lu and Etzkowitz, 2008). Thus intangibles
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Kristel Miller et al. and IC is of strategic importance not only for academics but is a major issue of interest for policy makers and practitioners who are interested in value creation and competitive advantage (Seleim and Khalil, 2011). To date, very little research has looked at the vital intangible side related to knowledge transfer and exchange within UTT (Lockett et al., 2003; Miller et al., 2011).Thus this paper attempts to help fill this gap by exploring IC in a university technology commercialisation context, with the aim of unravelling its importance for knowledge transfer and sharing. This paper will begin by looking at the theoretical background to the study, namely IC and knowledge transfer within UTT. The methodology will then be outlined and then a discussion of the findings will be given. The paper will be concluded by identifying the key contributions of this research.
2. Theoretical background The concept of IC has been around since the 1960’s however, the transition from the industrial to the knowledge economy brought the term to the forefront in early 1990’s (Bontis, 1998). IC has origins in the resource‐based view of the firm (Edvinsson and Malone, 1997) whereby it can be viewed as an asset which is difficult to imitate. Cabrita and Bontis (2008) identify that IC is strategically linked to an organisations ability to create and apply knowledge; thus in a knowledge economy, IC is an important resource. Various researchers and policy makers have explored IC without a consensus on its definition (Edvinsson and Malone 1999). Definitions within literature vary depending on the disciplines they relate to. Stewart (1997) defines IC as “intellectual material – knowledge, information, intellectual property and experience that can be put to use to create wealth”. Whereas, Williams and Bukowitz (2001) state that IC encapsulates all forms of knowledge, from the more abstract tacit knowledge (i.e. knowledge skills, culture, norms, group dynamics) to the more concrete explicit knowledge (e.g. documents, processes). In general, most definitions of IC are in agreement that it is made up of three core premises, namely: it can be a source of competitive advantage, its intangible and it can be retained and traded by a firm (Guthrie, 2012). The intangible nature of IC poses multiple problems in relation to its management, value and measurement (Petty and Guthrie, 2000). Whilst a vast array of studies focused on measuring and valuing IC come from an accounting and financial perspective (Guthrie 2012); there has been a lack of studies exploring IC from a business and management perspective (Dumay and Garanina, 2013). Despite variances in definitions, most IC models classify IC into three categories namely relational capital, structural capital and human capital (Bontis, 1998; Petty and Guthrie, 2000). While each component of IC is important in its own right, Freeling (2004) identifies that a firm is not only a bundle of resources but needs to possess and develop unique and difficult to imitate capabilities. The basic premise of IC is that value is created when organisation’s human resources, organisational processes and mechanisms for knowledge sharing and transfer are aligned to enhance knowledge creation and exploitation (Yitmen, 2011). Indeed, it is widely accepted that an organisations capability to innovate is closely tied to its IC (Wu et al., 2008). Organisational knowledge is embodied in IC and thus these intangible assets can be converted into a competitive advantage. Whilst previous research has looked at the individual components of IC; Mention (2012) identifies that few empirical studies have concentrated on the impact of IC as a whole on innovation from a processes perspective.
3. Leveraging IC to aid knowledge transfer and exchange within UTT (Lu and Etzkowitz, 2008). The academic, referred as the principal investigator (PI) is at the centre of the UTT process and thus is the most important actor in the process (Lockett et al., 2003). However, the PI’s involved with commercialisation activities are often reliant upon collaboration and knowledge transfer between government, universities, industry and other UTT stakeholders. Thus ensuring efficient knowledge management processes is important to aid commercialisation success (McAdam et al., 2009). Seleim and Kahil (2011) stress that IC and knowledge management are interlinked; they both encompass a whole range of knowledge processes from knowledge creation to knowledge transformation. They both facilitate organisational learning and both concepts are reliant upon each other. Thus, whilst their relationship is evident, much remains to be known about how organizations actually create and accumulate their IC by dynamically managing their knowledge (Seleim and Kahil, 2011). When looking at the individual components of IC, it is clear the important role they each play in respect of the various stages of commercialisation (Ramirez et al., 2007). The human capital of the PI is a key factor in the development of embryonic technologies and their success in the marketplace; since they are the instigator and
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Kristel Miller et al. driver of the whole process of UTT (Lockett et al., 2003). However, not all academics possess the required human capital needed to successful commercialise their technologies. Thus, engaging and building up relationships with stakeholders such as the technology transfer office (TTO), government and industry is essential to facilitate knowledge transfer to overcome this ‘knowledge gap’ and enhance commercialisation activities (Rothermel et al., 2007). However, even engaging with stakeholders to facilitate knowledge transfer and exchange requires human capital and relational capital in order to be able to recognise the value of new knowledge from these external sources, acquire that knowledge, internalise it and exploit it; which is termed an individual’s absorptive capacity (Cohen and Levinthal, 1990). In addition, the social norms, organisational structure and internal processes and mechanisms within a university can impact knowledge transfer and exchange and thus impact on UTT efforts (Bercovitz and Feldman, 2008).Yitmen, (2011) identifies that IC helps provide a bridge for exploring the link between the static notion (i.e. current knowledge stocks) and the dynamic notion (i.e. activities used to leverage this stock of knowledge) of a firm. This research takes a dynamic view of IC to try understand the knowledge flows within university technology transfer so that interventions can be implemented to promote knowledge transfer and exchange.
4. Methodology To explore IC within UTT, a qualitative instrument of one intrinsic case study of a University was undertaken. A qualitative methodology is deemed appropriate when develop an understanding of a phenomenon and consequently build theory (Straus and Corbin, 1998). The university chosen has an established Office of Innovation and a dedicated TTO which facilitates the commercialisation of knowledge residing within the university. In addition, The university has over 750 research active staff thus, was thought to be a rich case within which to conduct this research. The research was exploratory with the aim of building theory inductively in an under‐researched area. Due to the multi‐dimensional nature of IC, data was collected in three stages. Firstly, in‐depth semi‐structured interviews were carried out with multiple stakeholders, namely TTO staff (n=6; 2 top management, 1 middle management and 3 operational staff), PI’s (n=23) and enterprise co‐ordinators (n=5). Next the researchers engaged in observational analysis of six technology transfer meetings. The technology transfer meetings were held in one of the four campus’ of the case university and consisted of strategic, managerial and operational staff members of the technology transfer team meeting up in order to discuss all activities related to UTT. The researcher engaged in observational research over the period of May 2009 – November 2009 adding a longitudinal element to the research. Lastly, the researchers carried out repeat interviews with a selection of respondents who either had time constraints in the first interview or who covered issues which needed further probing (n=10 PI’s, 1 enterprise co‐ordinator and 4 TTO staff). Since the focus of the study was to explore the impact IC has on knowledge transfer and sharing, Zahra and Georges (2002) dimensions of absorptive capacity were followed as a basis of questioning. Therefore interviewees were asked various questions relating to how they acquire, assimilate, transform and exploit knowledge during UTT commercialisation. Each interview was recorded via Dictaphone and lasted on average 1 hour for the interviews in stage one. Repeat interviews lasted between 30‐40 minutes each. The observational research was recorded by means of detailed notes which were then developed into learning logs. A method of open inductive coding was then followed (Strauss and Corbin, 1998) both manually and through the use of NVivo 8. These open codes were then grouped into themes and sub themes through an iterative process of theoretical coding (Strauss and Corbin, 1998). These themes and subthemes can be seen in figure 1. The findings will be presented in narrative form and where relevant direct quotes from the interviews will be given.
5. Findings Various factors which can be attributed to IC were found to impact knowledge transfer and sharing during university technology commercialisation processes. These factors were categorised against the dimensions of IC. Figure 1 provides a diagrammatic representation of the key findings of the research. Each element of IC will be discussed in turn.
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Figure 1: Key findings of the research
5.1 Human capital factors The empirical research unravelled that networking capability, learning orientation and attitudes all had an impact on knowledge sharing and transfer during UTT activities. Networks were recognised as sources of new knowledge, as vehicles for accessing other knowledge and also as potential future technology transfer partners. The networking ability of the PI was highlighted by both the TTO staff and enterprise co‐ordinators as being influential in UTT success. “What I do would be impossible without my networks of people”. PIs were expected to actively engage in networking however, actual levels varied from PI to PI. This variation in networking levels was thought to be due to individual attitudes towards networking, with some academics expressing their dislike of engaging in networking activities. Individual skills and experience was also thought to affect PIs’ networking capabilities; as demonstrated in the following response: “It’s a personal thing. Everyone have their own personal mechanisms for networking. I don’t think there is anything that can be done”. A lot of PIs appeared to be lacking the confidence and skills to effectively engage with key industry players; concurring with past research, which stresses that a lack of expertise in effective networking can impact UTT activities (Miller 2011). Learning orientation was an important factor as it indicates how new knowledge and skills were acquired. The willingness to learn is essential for knowledge sharing. In addition, learning is cumulative and path dependent so it aids the understanding and internalisation of new knowledge (Zahra and George, 2002) thus is a key factor of human capital. The PIs learning orientation was found to be reliant upon constant knowledge acquisition and problem solving methodologies. The majority of PIs indicated that they are actively seeking new knowledge all the time by engaging with others and making the effort to attend events as they arise. However, it was stated that there was not a particular method employed but instead it was about being open to attending new events and being proactive in looking for new opportunities. The engagement with diverse knowledge was thought to be when opportunities will arise. The attitudes of the PIs were particularly important in relation to their willingness to engage in UTT activities. These attitudes were broken into motivation and being opportunistic. Personal aspirations and interests emerged as the most important motivators when undertaking technology transfer activities. It was found that an interest or love of research was the main reason why engaged in technology commercialisation. This finding relates to past research on technology transfer which identifies that the motivation of the founder positively influences UTT commercialisation success (Lockett et al., 2003). Being self‐motivated and taking advantage of opportunities as they arise was a key antecedent for UTT activities; it is also a typical trait for entrepreneurs. An enterprise co‐ordinator highlighted that PIs need to be self‐motivated to make their own opportunities. It was identified that opportunities often arise out of daily every day activities. “It’s not a conscious premeditated activity, it’s more just sort of opportunism, you run across people... and you make a point of talking”. All this suggests that having the ability to not only recognise opportunities when they present themselves, but to actively seek out opportunities is a key trait that those engaging in technology transfer should have. Being opportunistic could consequently aid knowledge acquisition and help with technology exploitation (Inkpin, 2005).
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5.2 Structural capital factors It was evident during the interviews that structural factors played a key role in facilitating knowledge absorption, sharing and transfer between the various stakeholders. Previous literature on technology transfer recognises the importance of the university structure in facilitating innovation and technology transfer (McAdam et al., 2009). In addition, past literature on knowledge transfer and absorptive capacity (see Van den Bosch et al., 1999; Yeoh, 2009) recognise the moderating role organisational processes and mechanisms have for knowledge absorption, sharing, transfer and exploitation. Organisational factors were found to affect PIs’ engagement with UTT commercialisation activities and also were found to facilitate and hinder UTT activities. Throughout the course of the interviews it was clear that organisational mechanisms and procedures had the potential to both facilitate and hinder knowledge sharing and transfer both internally within the university and between UTT stakeholders. Based on the interview data, in some respects there appeared to be a lack of internal procedures and mechanisms that facilitated knowledge sharing and transfer. It was also reported that some PI’s were not aware of expertise that existed within the university. While the Office of Innovation staff were there to sign post people and part of the TTOs role was to act like a broker (Easterby‐Smith et al., 2008), better internal communication mechanisms throughout the various faculties and campuses could have enhanced knowledge sharing and creativity. Despite PI’s not being aware of expertise within the university, they did appear to have two‐way communication with the TTO and their networks, which aided the assimilation, transformation and exploitation of external tacit knowledge. Due to the tacit nature of knowledge which was most often sought when engaging in UTT activities; these two‐way communication channels helped knowledge transfer and sharing.
5.3 Relational capital factors The ability to build relationships with external actors was also a key issue. PI’s need to build relationships with network members to help with knowledge acquisition, assimilation, transformation and exploitation stages (Miller et al., 2011). For instance, building relationships with networks and stakeholders was found to be essential to gain access to large companies; which concurs with previous literature which states that inter‐ organisational relationships increase familiarity which in turn increases knowledge transfer and organisational absorptive capacity (Lichtenthaler, 2009). The interviewees recognised the value of creating and maintaining relationships which could be cultivated in the future, “Ultimately never burn bridges and give people your information because you never know perhaps 2 or 3 years down the line those people might have an answer or query”. Thus, building relationships and actively maintaining those relationships was said to allow them to reap benefits in the future (Miller, 2011). The willingness and motivation to build relationships with network members was found to be reliant upon two conditions, 1) trust and 2) synergy. One PI stressed, that developing trust was the most important factor when engaging in knowledge transfer “because that is a partnership and that high level of engagement, ongoing engagement is very reliant on the development of trust”. It was found that a lack of trust could potentially hinder knowledge sharing and transfer within technology transfer activities since it prevents knowledge openness (Szulanski, 1996). Synergy was found to be equally as important as trust when forming relationships with people. Synergy within the context of technology transfer consisted of complementary skills and interests with a potential partner. Synergistic partnerships, based upon a balance of knowledge similarity and dissimilarity have been associated with positive alliance outcomes such as innovation (Lane and Lubatkin, 1998). A summary of the key findings is provided in table 1.
6. Discussion and conclusions The changing role of universities in the knowledge economy has placed greater emphasis on the importance of managing and enhancing their IC (OECD, 2011). In the knowledge economy sustainable competitive advantages are mainly based on intangibles (Yitmen, 2011; Bontis, 2001). Thus an organisation’s intellectual capital is said to be a source of competitive advantage and there is evidence that business success can be partly explained by its intellectual capital (Hamzah and Ismail, 2011).
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Kristel Miller et al. Table 1: Summary of key findings
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Kristel Miller et al. This research unravelled that all three components of IC and various corresponding factors played a key role in affecting knowledge transfer and sharing between UTT stakeholders and consequently impacted on commercialisation activities. Thus it was evident that university IC plays an important role in the development of embryonic technologies (Ramirez et al., 2007) since human capital, relational capital and structural capital underpinned knowledge transfer and exchange between university technology transfer stakeholders. It was found that there is a need to balance the skills of employees and the environment which promote innovation through knowledge sharing and transfer. Whilst the importance of human capital has been heavily documented in literature, this research confirms and extends theory by looking at an under‐researched context (Dumay and Garanina, 2013). The emerging ‘entrepreneurial role’ of the university requires a huge shift in mindset for academics to be enticed into engaging in UTT. Decter, (2007) identifies that engaging in commercialisation activities does not mean academics cannot publish, however, RAE and internal promotion is often focused on publications. O’Gorman et al., (2008) highlights that modifications to the traditional university reward systems may help to incentivise more academics to engage in UTT commercialisation activities. PI’s who are the key stakeholder for UTT were often lacking the time and skills to network with industry; consequently were often lacking business experiential and market related knowledge (Rothaermel et al., 2007). Thus whilst in many respects the PI needs to play a key role in helping develop their own knowledge and networking with industry, this research presents evidence that the university could do more to help develop PIs’ business‐related knowledge; enhancing their human capital. Whilst TTO staff were seen to make an efforts to connect to industry and market the technologies residing from the university, there could be more of a focus on helping PIs develop their exposure to external industry networks. In addition, the university remit was found to impact on the resources that PIs had to engage in networking with industry. However, many universities now have implemented industry engagement in their vision and strategy therefore, it is suggested that there should be more support and pressure at a faculty level to motivate academics to engage with industry which may enhance commercialisation opportunities in the future. This may require more interventions at a policy level to aid universities with resource constraints. The findings highlighted that a lack of social integration mechanisms internally can significantly impact knowledge transfer, sharing and learning from peers. Wu et al., (2008) identify that firms which have strong structural capital will create favourable conditions in which to utilise human capital, allow it to realise its fullest potential and consequently enhance innovation levels. Therefore, it is suggested that the case university implement effective knowledge management processes and enhance their social integration mechanisms to aid knowledge sharing and transfer internally. Lastly, it was stressed that the need to build up strong relationships facilitated knowledge access. However, again resources hindered some PI’s ability to develop and maintain relationships so that they could be cultivated in the future (Lichtenthaler, 2009).In addition, issues surrounding trust often prevented the sharing of knowledge and ideas. It is reported that to build and maintain a healthy innovation ecosystem a high level of transparency and trust between industry, higher education institutions and government is needed to ensure clarity and balance the various roles and interests of stakeholders (Bramwell et al., 2012). Thus, relational capital can be considered to be a key antecedent of an innovating region stressing the need to encourage investments in relationship building and to create a knowledge sharing culture (Capello and Faggian, 2005). Recent policies at a European, national and regional levels stress the need to not only focus on innovation but on enhancing intangible skills, namely intellectual capital due to their mutual interdependence for national competitiveness (DTI, 2007). However, it has been identified by a recent report by CM International (2012) that the relationship between universities and government has become similar to a client relationship which is in contrast to the strategic partnership needed to develop an innovating region. Universities are a key player of regional competitiveness in a knowledge economy thus even with the decentralisation of university funding, efforts from researchers, policy makers and UTT practitioners need to be aligned in managing and developing the intangible assets of universities to enhance economic development. Knowledge assets underpin the core competencies of any organisation and consequently determines organisational competitiveness and performance (Marr et al., 2004). Thus, it is important that universities consciously value and manage their IC to fulfil their role in society (Rowley, 2000).
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Kristel Miller et al. In sum, it was found that the various dimensions of IC may affect commercialisation success or failure which consequently can impact upon regional development and national wealth (Seleim and Khalil, 2011). It has been reported that internationally, thriving industries with high productivity are those that in which human, structural and relational capital interact in a synergic way (Kamukama et al., 2010). However, the strategic management of intellectual capital within universities is a fundamental task due to its intangible nature (Dumay and Garanina, 2013). Indeed, it is only recently that organisations have recognised the importance of valuing their IC however, there are still problems with the identification and measurement of IC within organisations (Petty and Guthrie, 2000). This research helps further knowledge in this area by unravelling the different elements of intellectual capital from a business and management perspective so that researchers, policy makers and practitioners can start to understand this complex concept and begin to implement interventions to contribute to future IC management (Dumay and Garanina, 2013). Research on IC is still in its infancy and more empirical studies are needed to explore the managerial issues related to IC (Dumay and Garanina, 2013). Further research should focus on how it can be developed and managed within a wide range of contexts. thus this research gives UTT practitioners and University stakeholders an insight of the importance of valuing and managing their intangible assets to aid the entrepreneurial mission of universities. In addition, whilst there has been a decentralisation of university funding, policy makers still need to help provide mechanisms to support universities in leveraging their IC.
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Reconceptualising knowledge transfer practices in the South African public sector Peter L Mkhize University of South Africa, Pretoria, South Africa mkhizpl@unisa.ac.za
Abstract: In the knowledge economy, organisations are shifting their investment focus from natural resources to intellectual capital, in order to sustain a competitive advantage in the global marketplace. Organisational survival is increasingly dependent on the organisationâ&#x20AC;&#x2122;s ability to create knowledge that contributes to performance improvement. The purpose of this article is to qualitatively evaluate knowledge acquisition practices in the South African public sector. The researcher applied grounded theory analysis techniques to extract themes that could provide insight into knowledge acquisition that takes place in the South Africa public sector, even though these practices are not documented as knowledge transfer practices. Findings revealed that informal sharing of knowledge take place in discussion forums within communities of practice. These communities of practice are widespread throughout the public sector, and are established with the purpose of soliciting expert knowledge from those who have been using open source software successfully. Keywords: public sector, knowledge acquisition, communities of practice, social network, knowledge management, discussion forum
1. Introduction Innovation and change in an organisation bring about a need to up-skill employees, in order to keep up with new organisational demands. In the knowledge economy, a businessâ&#x20AC;&#x2122;s competitive advantage is dependent on the organisation's ability to adapt to rapid technological changes. According to Acton and Golden (2003), organisations need to improve their knowledge acquisition strategy, because skills and knowledge become obsolete quickly. Jarrar (2002) suggests that knowledge is increasingly becoming a crucial asset for organisations, unlike in the industrial age, where machinery was the most important asset. According to Pacharapha (2012), knowledge resides with individuals in the organisation, that becomes an instrument for business process improvement, thereby gaining a competitive advantage. Knowledge kept in the individual's mind does not contribute to organisational success if it is not given through to, and shared by, the entire organisation. In this paper, the researcher investigates the knowledge transfer practice in the South African public sector, in relation to the problem described below.
2. Rationale of the study The South African public sector is arguably the largest employer in the country. The South African parliament made a decision to adopt 'open source' as the information systems' platform of choice in all the government departments. However, the migration has application of knowledge implications, as open source software evolves rapidly. The reported skills shortage could be an indication that existing skills training mechanisms are either not being used optimally, or are failing altogether (Statistics South Africa 2010). However, some individuals in the workforce may possess knowledge that could be useful in improving service delivery. The challenge is the transfer of skills from the individuals who have such skills, to other employees organisation wide. Individualised knowledge does not help the public sector, because it could be lost if such individuals retire or resign. In addition to that, social media is growing at a fast pace in South Africa and other African countries (World Wide Worx 2012). The South African population has widely adopted social media for social interaction. It is important to investigate the possibility of promoting knowledge sharing and transfer through social media, even though such a practice is not formally instituted in the public sector. Understanding knowledge sharing and transfer in the public sector would enable the researcher to construct a guiding framework for future development of the knowledge transfer mechanism in the public sector.
3. Literature review In the knowledge economy, organisations depend on the ability to acquire and transfer knowledge, in order to gain a competitive advantage. In the organisation there could be individuals who possess valuable knowledge; however, individual knowledge is not a competitive advantage for the organisation if it is not shared by other
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Peter L Mkhize relevant members in the organisation. According to Alavi and Leidner (1999), knowledge sharing enables an entire organisation to gain competitive knowledge and productivity improvement. Knowledge transfer takes place between individuals and teams. It could be technical knowledge that is important for functional departments instead of for the entire organisation, despite the fact that each ounce of knowledge that could improve business performance is critical, whether it is in the possession of individuals or teams in departments. Organisations that want to facilitate knowledge transfer between individuals and teams, have to take into cognisance the type of knowledge involved. Polanyi (1966) elaborates on the conversion of knowledge, and characteristics of tacit knowledge as non-codified knowledge, which is difficult to articulate to others in the organisation. Tacit knowledge is usually acquired through years of experience, and cannot be expressed in a step-by-step process for the next person to decode. On the other hand, explicit knowledge is the easiest of the two types knowledge to codify and express in easyto-understand information. According to Nonaka (1994), this type of knowledge can be expressed through traditional learning methods. However, the challenge is creation of knowledge through the interplay between tacit knowledge and explicit knowledge.
4. Knowledge creation Nonaka (1994) proposes the Socialization, Externalization, Combination and Internalization (SECI) modes of knowledge creation, underpinned by socialisation, externalisation, internalisation and combination. Knowledge creation is critical for both the public and private sectors in South Africa, in light of the brain drain and skills shortage reported in the popular media. Jarrar (2002) posits that intellectual capital is replacing finance, commodities and natural resources, in terms of importance in the knowledge economy. Organisations have to invest in knowledge creation, in order to sustain a competitive edge. In line with the SECI modes of knowledge creation, the public sector needs to create an environment that enables interplay between individuals in the organisations, sharing tacit knowledge through mechanisms such as observation and imitation (Lottering and Dick 2012). In this mode, sharing of information would not serve any purpose, as experience is difficult to articulate; therefore, the learning individual has to shadow the expert. This may imply that both parties build and manage an emotional relationship. Meanwhile, explicit knowledge can be transferred to others in the organisation through a social medium. Explicit knowledge is articulated and can be transferred in electronic media. Meetings and traditional workshops can be used to reconfigure and reconceptualise existing knowledge in the combination mode (Mahomed 2012). Externalisation enables conversion of tacit knowledge to explicit knowledge, where individuals involved in the creation of knowledge have to spend extensive time having mutual interaction, whereas internalisation relates to conversion of explicit knowledge into tacit knowledge.
5. Communities of practice Balcaen and Hirtz (2007) argue that an online-based knowledge sharing promotes critical thinking. Employees participating in online communities have the advantage of engaging the subject of interest critically, especially when they are encouraged to learn independently, and work interdependently, to support each other. Kanuka and Garrison (2004) claim that collaborative, yet reflective, learning has great potential for facilitating critical thinking, which, in turn, would enable a learning organisation to facilitate the transfer and creation of skills and knowledge. Critical thinking is encouraged within communities of practice, as major players in the industry would be able to share insight with employees who also aspire to be experts in their field of interest (Balcaen and Hirtz 2007). Within the community of practice, knowledge is socially constructed by the group of participants who weigh each contribution to add value to the discussion (Salmon 2002). Each participant in the community of practice is free to make a contribution towards a solution to the problem, or to a subject of concern among members of the community. Contributors to the discussion and debate become absorbed into the debate until consensus is reached, and the agreed solution remains tentative until a better solution comes along (Wenger and Snyder 2000). The facilitator would be there to ensure that the discussions are not diverted towards the wrong direction, and to redirect the discussions, if necessary (Levinsen 2006). In order to realise the success of a community of practice, the sponsor of an online community takes into account the participantsâ&#x20AC;&#x2122; demographic characteristics such as culture and economic background. This will give an insight into the inclination and preference of each participant, so that they can customise knowledge sharing in order to achieve success.
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6. Research questions Research questions will provide guidelines for the research process as the researcher attempts to answer these questions using appropriate research methodology. The following questions were formulated after the researcher gained theoretical sensitivity from the literature review: ď&#x201A;§
What are the key concepts that have to be considered in the facilitation of knowledge transfer in the South African public sector?
ď&#x201A;§
How do these key concepts interrelate in the design of a knowledge transfer mechanism in the SA public sector?
7. Research methodology, data analysis and ethics In order to answer the research questions for this study, the researcher chose a qualitative approach within the social constructivist paradigm, so that he could gain an in-depth understanding of the skills problem in the workplace. The aim thereby was to co-create or co-develop a model with the research participants, that could provide a solution to some aspects of the problem, if not to the entire problem. Due to the scarcity of literature and theories that specifically address online knowledge acquisition in the South African context, the researcher will apply the grounded theory analysis method within a case study design (Glaser and Strauss 1967). Grounded theory analysis principles will be applied in a case study, in order to generate a theory in relation to the above rationale. According to Charmaz (2006), grounded theory principles are not prescriptive, but provide guidelines for the detailed analysis of qualitative data and the generation of theory. In applying grounded theory, the researcher will be preparing to conduct data collection and analysis concurrently, because subsequent interview probing is dependent on the analysis results of the previous interview (Corbin and Strauss 1997). The researcher has developed a case study protocol, including an interview schedule, based on the research questions of the study (Remenyi et al. 1998). Questions in the interview schedule could change slightly from one interview to another as the researcher becomes more theoretically sensitive. He will then apply theoretical sampling to find prospective participants who are more likely to give further information or clarity to the questions which might not have been answered by the initial sample (McCallin 2003). All interviews will be transcribed by a qualified transcriber, then uploaded into AtlasTI, a qualitative data analysis software. Grounded theory analysis techniques will be applied by conducting open coding to identify codes as they emerge from data. A bracketing technique will be used to suppress the researcherâ&#x20AC;&#x2122;s preconceived ideas about the researched subject (McGhee et al. 2007). A second step will be Axial coding that will allow for categorising codes into families in AtlasTI, and the next step will be to conduct the following interview with new categories in mind. This process will be repeated until data saturation. Thirdly, there will be selective coding, where codes and family networks will be formed to determine relationships and create a story.
8. Collaborative learning Collaborations are gaining popularity both in business and academic institutions, where collaborators sharing resources, or working on the same project, can exchange information and ideas, in order to co-create solutions to eminent problems, and also knowledge. Sharing of information and ideas could be an interaction between individuals within a community of practice, or outside the community (Mkhize et al. 2011). Figure 1 shows the network of codes that represent activities involved in the development of collaborative experience. Some collaborations are informal, and others are coordinated, depending on the objectives and resources allocated for the learning community participating in the collaborative learning (Allan and Lawless 2005).
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Figure1: Network showing collaborative engagement in the SA public sector. Membership of SITA’s collaborative forum is by invitation to the qualifying prospective participants, who are expected to make a meaningful contribution to the learning group. An administrator makes a judgement decision by qualifying prospective participants, and then allows them to join the group discussing a specific topic regarding a new open source platform. P4: you might be able to invite external people but then you would qualify them, so in that government-wide collaboration we on the administrator, so I set it up I need to say who’s in and who’s out and then they would do the same with that The SITA’s collaborating group sometimes outsources subject expertise from other discussion forums, by going out of the official government discussion group to find those who may make a great contribution in the current issues of concern. The administrator would even go to the extent of scouting in the social networks, to find bloggers who might be experts in a specific subject. P4: say I was a local developer in SA I would do 1 of 2 things I would either see if there’s existing forums linked in groups specific groups that are discussing that specific topic, it is possible that those groups won’t be focused enough or there might …but you’ve got specific needs, what I’ll do then is I’ll create my own group I’ll choose a certain media like I would say I’m going on Facebook or I’m going on this, I would find something that’s more like a super cool the kind of personalities that use that,... I would find something that is suited to my community, having more technical or whatever and then I would start extending that network ...the thinkers in that area and I would extend an invite to that somebody that writing a blog that’s...or start talking to that network and say who are the real experts in open source migration Inviting renowned experts in a certain field, allows the administrator to create a ripple effect by attracting the experts’ followers into their discussion forum. Although collaborating groups would need outside expert contributions to the discussions and debates about issues of concern, it is still important to maintain confidentiality. P4: think it’s just about the confidentiality of the information, say you are in government you typically want to control whoever joins cause you might discuss strategies, communication strategies, things that you want to first vet with different stakeholders before you bring them to the public so in that case you will firstly have the private network
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Peter L Mkhize As a result, administrators have to be careful in their selection of the joining members, and ensure that confidential information is not openly discussed in the forums. This is to avoid exposure of government’s open source strategies and operations. Participant #5 suggests that a collaborative forum should apply the same model as was applied by early collaborators in government, but now with the guidance of an expert to facilitate engagement and debate about topical issues in open source migration. Through engagement, collaborators would be able to deduce meaning from, or come to agreement about, new solutions – which could be an extension of the existing knowledge. In setting up collaboration, instructional designers can explore the application of technology in facilitating online collaboration. Participant #4 points out that Moodle is an effective and efficient collaborative tool for the SITA collaboration group. P4: within Moodle there are some kinds of collaboration or that kind of functionality that you can use and we kinda put them into our project Moodle is an open source application that can be acquired free of charge – which could mean easy access and affordability for instructional designers and collaborators. Besides, Moodle incorporates even extended pedagogical features that can be used for administration and management of the knowledge exchange process. Instructional designers are facing the task of converting pure collaborative activities to a knowledge transfer mechanism, and enabling an environment where knowledge transfer practice can be modelled around the existing collaborative instructional strategy. In doing so, it can ease tensions between management and learners/employees regarding the use of social networks in the office, because a formalised collaborative instructional strategy could be institutionalised, and then form part of institutional policy.
9. Learn by discovery within a community Some of the participants quoted in the discussion above, also mentioned or implied communities of practice (CoP). Figure 2 shows the CoP theme: the researcher will discuss a concept that seems to be prominent in the transcript, which is directly related to communities of practice – that is, learning by discovery. This concept is not foreign to the field of education, as the researcher has noticed the continuous emergence of learning by discovery, after reading literature on learning theories. collaboration: social networks {1-4} collaboration: managing group dynamics {1-4}
collaboration: peer to peer learning {1-5}
is property of
is property of collaboration: informal learning through discusion forums {2-6}
is associated with
collaboration: interconnection of communities {1-3}
collaboration: collaboration of expertise {5-6} is part of
is part of CF:Learning through discovery support collaboration: sharing ideas {1-4} is part of instructional design: sharing experiences {2-6}
is associated with
instructional design: co-creation of knowledge {1-9} collaboration: communities of practice {1-5}
Figure 2: Network showing learning through discovery within communities.
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Peter L Mkhize Learning by discovery in a community, starts with the creation of the community where learners/employees who are sharing a common interest, converge to discuss critical issues on a specific topic. Case studies revealed that topics of interest revolve around the optimised usage of an open source platform. Participant #4, who administrates the collaboration forum for government collaboration groups, suggests that collaboration should be designed for free social platforms such as Google or any other Web2.0 platform where an instructional designer can create a group that can share text or video files. SITA’s collaborative forum is secured, because of the security and confidentiality requirement. Some of the information shared is sensitive in nature, and then high security measures should take priority over functionality. However, free social networks can be used where security is not a sensitive issue. P4: start to building that functionality into the e-learning tool so whether you in the design of the course or whether you want students to interact you need to build the social media the social learning at stake as facilitating the process of learning either by using that functionality in the application you use such as Google or just signing up to any free collaboration tool, create a group then you collaborate so most of these tools they have a model where you can use those functionality for free and those functionalities you can connect with people …which is making sure that if you doing a course for the military then there’s specific requirements around security confidentiality, so that’s what SITA is doing in this project, we could use social networks or social tools that are on the Internet but because of that requirement we need to have something that can secure on our firewall and the access of control is very strict Once the security requirements have been established in order to create parameters for collaboration forum membership, instructional designers have to consider instructional strategy that is appropriate for the target audience. In line with collaborative strategy for government's open source training, a collaborative environment has to be created within a community of practice. Participant #5 thinks that those social networks represent the most effective platform for collaborative learning within a specialised group, called a community of practice. Interaction within the community can be standardised into specific time intervals, or openness and flexibility. P5: community of practice would see people who share common interest in a particular field something, they will be able to seat and collaborate, discuss, move forward and look at the development, to me community those are groups ... they seat every week or every month or people collaborate through that social platform they are all related and they’ll say they also contribute to the management of knowledge and knowledge gathering that can be preserved In these communities, members get to share their experiences, and learn from those who have been through the learning curve. That way, members of the community don’t have to repeat the same mistakes made by those who have become experts over the years. Less experienced collaborators in the community can learn best practices, with regard to a specific trade, from more experienced community members, without going through trial and error. Sharing of information and knowledge enables all concerned to learn new skills to solve persisting problems. P4: think the main thing about collaboration in government is the culture is pretty much …so everybody is busy with their own stuff, fighting their own battles and not knowing that another department has maybe kinda a step further in a particular area and they basically got a better solution, so collaboration for us is about creating the tool that can connect these people so that they can form groups, networks of interests and can become aware of other projects, other best practices, other people that have gone through the learning curve, that have got skills A collaborative environment allows for co-creation of knowledge, based on the collective and agreed interpretation of the studied phenomenon. As members of the community of practice engage one another in a collaborative environment, different forms of expertise interplay into development of new models that emerge from the convergence of ideas. This is eminent where communities are interlinked in order to engage in issues of common interest, even though communicating individuals might belong to separate communities. P4: collaboration in terms of the different roles, to …, and that what’s exciting us, getting together to work out a solution for the government we’ve had architects, we’ve had business analysts, we’ve had the now the content developers as where I’m coming from, we’ve got the technology architects for government and then we’ve got change managers who are also involved from beginning to end although they are observing what is coming up first more than anything
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Peter L Mkhize Members of SITA’s collaboration group are not restricted to one community of practice: they can join multiple communities of practice. In that way, one can find communities of practice interlinked by dual membership. Those members with dual membership can source some input from peers of the other community, where specialised expertise is required to solve a specialised problem – such as that of anti-corruption. P2: more of the discussion forum and semi-informal course that is being run, the course is called anti-corruption, so it’s just more of a discussion forum, we calling in experts from time to time to give more information on how to deal with corruption and so on A collaborative environment encourages exchange of ideas and knowledge among learners/employees within a community of practice, which enables learners/employees to learn through discovery. Participants in the knowledge exchange don’t have to enrol for a formal classroom course, and then expect the lecturer to present learning material to them while they become passive recipients of knowledge. They actively engage each other on important issues or concepts relating to the current problem, that makes it easy to find direct and relevant solutions.
10. Proposed framework Figure 3 shows a proposed framework that could provide conceptual guidelines for the design and development of a knowledge transfer mechanism in the public sector. The knowledge transfer process takes place within the social constructivist paradigm, where knowledge is created through social interaction, and everybody involved is an equal contributor to the creation of knowledge.
Figure 3: Conceptual framework knowledge transfer in SA public sector. The creation and transfer of knowledge in the public sector is supported by collaboration that takes place within communities of practice. A subject of interest is proposed to the communities for discussion, and then members of the communities apply a collaborative strategy to openly discuss, analyse and evaluate issues of interest to the community. The process enables learning through discovery as they discover new meanings to current problems. The definition of 'new meaning' is the product of social engagement between the novices and expert employees who openly share knowledge and ideas for the purpose of knowledge development and institutional performance improvement. Knowledge agents in the public sector are already operating within the social constructivist paradigm to allow for social engagement between all parties involved in the knowledge transfer process. They go on to open debate for extension of the current knowledge as new perspectives emerge from new employees, and both novices and experts learn from one another.
11. Conclusion This study set out to determine key concepts that have to be considered in the facilitation of a knowledge transfer mechanism in the public sector, and also to identify relationships. Results of the case study revealed that the public sector is engaged in un-institutionalised knowledge acquisition initiatives. Among other themes that emerged from grounded theory analysis, are: collaborative engagement, communities of practice, learning through discovery, and co-creation of meaning. Some of these themes are sub-themes embedded in the themes discussed above. Despite the existence of comprehensive knowledge transfer initiations, it is important to formulate guidelines for knowledge transfer that can be replicated or adapted by different stakeholders in the public sector, in the time of need for knowledge transfer. The qualitative research approach does not allow for generalisation of results to the entire population. It does, however, allow for transferability of results to different departments. The framework guidelines can be transferred to other departments in the public sector that have similar characteristics, or can even be adapted to suit another department.
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Peter L Mkhize Knowledge transfer has been a public sector challenge, as it is engulfed by a skills shortage where some individuals possess critical skills that could be used to sustain productivity in the departments. Skilled individuals alone cannot improve department performance; they need support from their peers – which can happen if everybody involved has somewhat the same skill levels. All participants mentioned that knowledge transfer thrives within communities of practice.
References Acton, T. and Golden, W. (2003) “Training the knowledge worker: a descriptive study of training practices in Irish software companies”, Journal of European Industrial Training, Vol. 27, No. 2/3/4, pp. 137-146. Alavi, M. and Leidner, D.E. (1999) “Knowledge Management Systems: Issues, Challenges, and Benefits”, Communications of AIS, Vol. 1, No. 7, Allan, J. and Lawless, N. (2005) “Learning through online collaboration by SME staff: a scoping investigation into likely team-role stressors”, Education Training, Vol. 47, No. 9, pp. 653-664. Balcaen, P. and Hirtz, J. (2007) "Developing critically thoughtful e-Learning communities of practice", Proceedings of the 2nd international conference on e-learning, Academic Conferences Limited, , pp. 11. Charmaz, K. (2006) Constructing grounded theory: A practical guide through qualitative analysis, Sage Publications. Glaser, B.G. and Strauss, A.L (1967) The discovery of grounded theory: strategies for qualitative research, Aldine de Gruyter. Jarrar, Y.F. (2002) “Knowledge management: learning for organisational experience”, Managerial Auditing Journal, Vol. 17, no. 6, pp. 322-328. Kanuka, H. and Garrison, D.R. 2004, "Cognitive presence in online learning", Journal of Computing in Higher Education, Vol. 15, No. 2, pp. 21-39. Levinsen, K. (2006) "Collaborative on-line teaching: The inevitable path to deep learning and knowledge sharing", Electronic journal of e-learning, Vol. 4, No. 1, pp. 41-48. Lottering, F. and Dick, A.L., 2012, ‘Integrating knowledge seeking into knowledge management models and frameworks’, South African Journal of Information Management, Vol.14, No. 1, http://dx.doi.org/10.4102/ sajim.v14i1.515. McCallin, A.M. (2003) "Designing a grounded theory study: some practicalities", Nursing in critical care, Vol. 8, No. 5, pp. 203-208. McGhee, G., Marland, G.R. and Atkinson, J. (2007) "Grounded theory research: literature reviewing and reflexivity", Journal of advanced nursing, Vol. 60, No. 3, pp. 334-342. Mkhize, P.L. Huisman, M. and Lubbe, S. (2011) "Analysis of Collaborative Learning Experience in Government Training Practices ", 10th European Conference on e-Learning, 10-11 November 2011. Mohamed A. C. (2012) "Knowledge management: a personal knowledge network perspective", Journal of Knowledge Management, Vol. 16, No. 5, pp. 829 – 844. Nonaka, I. (1994) “A Dynamic Theory of Organizational Knowledge Creation”, Organizational Science, Vol. 5, No. 1, pp. 14 37. Pacharapha, T. (2012) Knowledge acquisition: the roles of perceived values of knowledge content and source, Journal of Knowledge Management, Vol. 16, No. 5, pp. 724 – 739. Polanyi, M. 1966, The Tacit Dimension, Routledge and Kegan, London. Remenyi, D. and Williams, B. (1998) Doing research in business and management: an introduction to process and method, Sage Publications. Salmon, G. (2002) E-tivities: The key to active online learning, Routledge Falmer. Statistics South Africa, (2010) “Quarterly Labour Force Survey: quarter 1, 2010”, Stats SA Library Cataloguing-in-Publication (CIP) Data. Strauss, A.L. and Corbin, J.M. (1997) Grounded theory in practice, Sage Publications. World Wide Worx, (2012) Social Media breaks barriers in SA, viewed 25 November 2012, http://www.worldwideworx.com/socialmedia2012/
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Knowledge Worker From the Perspective of Their Managers Ludmila Mládková University of Economics Prague, Prague, Czech Republic mladkova@vse.cz Abstract: This paper investigates whether managers understand the specifics of knowledge workers and their management. Knowledge workers represent a special group of highly qualified employees. The specifics of their work and management reflect the intangibility of their major tool and resource, knowledge. Knowledge consists of two dimensions, explicit and tacit. The explicit dimension is easy to code and share, by language, pictures and notes. The tacit dimension is related to practical activity; it is highly personal, partly or fully subconscious. It cannot be separated from its human owner. Due to tacit knowledge, knowledge as a whole is intangible. The intangibility of knowledge makes knowledge workers special and difficult to manage. The most important part of the work of knowledge workers happens in their heads even though the final result may be material. It cannot be observed and controlled, and it is not linear. Many knowledge workers report that their best ideas and solutions were invented outside their organisation when they were relaxing, not officially working. Even more, the results of the work of knowledge workers may differ from the short and long‐term perspectives, which causes problems with standards, measurement and evaluation. Knowledge workers are usually well educated or trained and able and willing to make their decisions independently. The growing importance of knowledge workers changes power relationships in organisations. Managers used to be the people who had more knowledge, more decision‐ making rights and the right to control their subordinates. When knowledge workers are involved, power shifts from managers to subordinates. They have more knowledge and they often understand what they are doing better than their managers. Many of them make the final control of their product or service themselves. Recent research shows that knowledge workers want their managers to adjust their managerial style to these specifics. They want the manager to be the one who serves more as an agent than a manager; who provides a knowledge worker with the means necessary for his work (including knowledge and contacts), helps him to synchronise his objectives with corporate objectives and supervises his personal development. Based on the empirical research done among managers of knowledge workers, this paper is trying to answer questions on how managers see their knowledge workers and how they manage them. The research was designed to discover who managers understand as knowledge workers, if they understand their specifics and are aware of their importance, which managerial styles they prefer managing knowledge workers and how they eliminate resistance. As such the paper focuses on the problems of knowledge workers and their management from the point of view of their managers. It enables managers to confront the requirements of knowledge workers from the standpoint of the manager. Keywords: knowledge workers, management of knowledge workers, knowledge, style of management
1. The research on knowledge workers and their management The research on knowledge workers and their management started in the autumn of 2010 and it still continues. The objective of the research is to identify important aspects of the work of knowledge workers and their management. The main hypothesis of the research is that managing knowledge workers in the traditional manner is contra‐productive. We think that knowledge workers prefer a different style of management. The research consists of two parts. The main part of the research examines the specifics of knowledge work, and the specifics of the management of knowledge workers from the point of view of knowledge workers. We interviewed 592 respondents ‐ knowledge workers and asked for their opinion. The second part examines the problems of knowledge workers and their management from the point of view of the managers of knowledge workers. The total number of respondents is 97. This article discusses the results of the second part of the research. Managers were asked questions on who they perceive as knowledge workers, which style of management they prefer, how they execute control and which type of organisational structure they like. Respondents of the research are distant students of the University of Economics, Prague, the Police University of the Czech Republic and the Armed Forces Academy, Liptovský Mikuláš, Slovakia. We decided on them because most of them work in knowledge intensive jobs, e.g., it is possible to anticipate that they and their subordinates are knowledge workers. To be sure, certain questions in the first part of the questionnaire allow us to verify that the respondent is a knowledge worker. The professions of respondents are different. Respondents interviewed at the University of Economics in Prague work mostly in business and finance; respondents of the Police University of the Czech Republic work
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Ludmila Mládková, in security services as policemen, firemen, soldiers and in public administration. Most of the respondents of the Armed Forced Academy in Liptovský Mikuláš, Slovakia were soldiers. The majority of our respondents can be classified as lifelong learning position knowledge workers (Reboul 2006).
2. Methodology of the research The research consists of theoretical research (review of existing literature) and empirical research. The methodology used for the review of the literature was as usual for this type of theoretical research. We collected described and evaluated different approaches and different ideas on knowledge workers and their management and other related topics. The data used are secondary data collected from traditional and electronic media. The article pays attention to both historical approaches and the latest approaches in the field. Methods used for the review of the literature include typical methods of theoretical work, e.g., methods that allow interlinking separated pieces of knowledge like analysis and synthesis, comparison, induction, deduction, abstraction, generalisation and critical thinking. The theoretical part of the article offers different options on how to understand knowledge workers and the problems of their management. As for the methodology of the empiric research, the research is a quantitative research and is based on a questionnaire. The questionnaire provides answers to important questions concerning knowledge workers. It helps us to separate respondents who are non‐knowledge workers from respondents who are knowledge workers, gives answers on the role of tacit knowledge in knowledge work and on how knowledge workers develop their knowledge (this part is not addressed by this article). It also helps us to identify important aspects of the management of knowledge workers. Questions are constructed as closed questions. Respondents choose from given options or evaluate given options on the Likert 1‐5 scale. The Likert scale options are as follows: 1 ‐ factor is poor, 2 ‐ factor is under average, 3 ‐ factor is average, 4 ‐ factor is over average and 5 ‐ factor is excellent. Some of the closed questions offer the option of commentary. Respondents complete the questionnaire without the supervision of researchers. Questions were constructed so that they did not indicate what may be a “correct answer”.
3. Theoretical background of the research The limited space of this article does not give us a chance to cover the theoretical background of the research in all details. The topic of knowledge workers and their management is multidisciplinary so when working on the theoretical background of the research we had to cover different topics. The theoretical work started with a review of the literature in the field of knowledge workers and their management. As knowledge is an extremely important factor that influences the work, performance and management of knowledge workers, we also undertook a review on knowledge and knowledge management. We then made a choice and decided on definitions and concepts that we would use as the theoretical background for our research. Due to the limited space we decided not to present the part of the literature review concerning knowledge and knowledge management in this article. Anyway, it is important to say that this part of the research resulted in the choice of the definition and concept of knowledge. We understand knowledge as a changing system with interactions among experience, skills, facts, relationships, values, thinking processes and meanings (Veber 2000) for our research. Knowing well that our managers do not have time to learn and work with complex theoretical concepts we decided to use the simplest possible concept of knowledge. In our research we work only with explicit and tacit knowledge (Nonaka, Takeuchi 1995). The literature review on knowledge workers offers three basic approaches to this term (Brinkley, Fauth, Mahdon, Theodoropoulou 2009); conceptual approaches, data (industry) driven approaches, and job content approaches. Conceptual approaches explain the term knowledge worker from the point of view of employees’ importance for an organisation, and his style of work with knowledge. Authors who can be classified to conceptual approaches are P. Drucker (1954), J. Vinson (Vinson 2009), G.S. Lowe (2002), T. Davenport (2005), C. Reboul (2006). Data driven approaches see knowledge workers as all those who work in particular organisations or in particular sectors or institutions. Representatives of this approach are for example K. E. Sveiby (1997), M. Alvesson (2002).
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Ludmila Mládková Job content approaches see knowledge workers as people who do a certain type of job. This approach can be identified in the works of A. Toffler (1990), R. Reich (1992), A. Kidd (1994), G. E. Nomikos (1989). Literature provides some but not many ideas on how to manage knowledge workers (Drucker 1954, Newell 2000, Harman, Brelade 2000, Roffey Park Institute 2000, Suff, Reilly 2005, Buckingham, Coffman 2005, Kelemen et al 2010, Mládková 2012). Many of the mentioned authors examine the management of knowledge workers from the point of view of the HR field; many ideas on knowledge workers are perceived as generally true but not the subject of research (the importance of tacit knowledge for knowledge workers, specifics concerning decision making, style of management addressing knowledge workers’ needs, etc.) and the literature review showed that there is lot of space for future research in this field. As our research is based on the management of knowledge workers and the way they work with knowledge we decided to base it on the conceptual approach. This approach explains the term knowledge worker from the point of view of an employee’s importance for an organisation, and his style of work with knowledge, and perfectly fits our purposes.
4. Results of the research This article covers only that part of the research focused on the management of knowledge workers as seen by their managers. All interviewed managers were classified as knowledge workers and managed subordinates working in knowledge intensive jobs, e.g., knowledge workers. Our questions were answered by 97 respondents – managers. If the summation of responses is not equal to 97, respondents chose more possibilities (it was possible) or did not answer the question at all. Percentages are rounded off. The author of this article does not provide any statistical analysis due to the way the questionnaire was constructed; it has no relevant meaning. Table 1: Characteristics of respondents Age Sex Education Profession
Number
Under 25 26‐45 46‐65 66‐75 76 and older Female Male
3 82 8 0 0 13 77
Only primary Vocational Secondary University Scientific title Pedagogical title Soldiers Policemen Other profession Not specified
0 0 35 56 0 0 32 28 15 22
% 3 85 8 0 0 13 79 0 0 36 58 0 0 33 29 15 23
There were a total of 97 respondents. 85% of these respondents belong to the age group 26‐45 years, and 79% of the respondents are male. 58% of the respondents have a university degree. As for the profession, the majority of interviewed managers were soldiers; 33%. There were 29% of policemen. 23% of the respondents did not disclose their profession. 15% of respondents are of different professions than soldiers and policemen and cannot be simply classified to one professional group. They work, for example as firemen, managers of security organisations, logisticians, managers in catering, entrepreneurs and public administration officers. Table 2: Knowledge compatibility between the manager and his subordinates Are you an expert in the same field as your subordinates?
Yes
Number 90
No No answer
5 2
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% 93 5 2
Ludmila Mládková, Historically, managers used to be the people who had more knowledge, more decision‐making rights and the right to control their subordinates. The growing importance of knowledge and the growing share of knowledge work changes power relations in organisations. As opposed to non‐knowledge work, the most important part of knowledge work happens in the heads of employees. It cannot be observed and controlled, and it is not linear. Due to the sample of our respondents it is no surprise that 93% of our respondents are experts in the same field as their subordinates. A manager may benefit from being from the same field as his subordinates as he has similar knowledge to them and knows how to use it. If that is not the case, managers are recommended to become agents more than classical managers (Drucker 1954) and create a proper environment for their knowledge workers. Table 3: Style of management I prefer to
Manage by orders and control (autocratic style) Delegate, and I let subordinates work and decide independently but I control them (delegation style). Let subordinates work independently and concentrate on the creation of a proper working environment (liberal style) I use a different style
Number 22 58
% 23 60
15 15 1
1
Due to the intangible character of tacit knowledge, knowledge work is difficult to control. It happens in the heads of subordinates. Even managers with expertise in the same field as their subordinates cannot follow the process of knowledge work, how an employee uses knowledge, makes decisions, how he is doing certain things and why he is doing them. An autocratic style of management based on orders and control has limited applicability on knowledge workers; it even may be contra‐productive (Mládková 2012, McGregor 1960). We were interested in whether managers are aware of the shift in managerial style or if they still insist on autocratic style typical for our region. The research shows that 60% of respondents prefer delegation style of management, e.g., they let their subordinates work independently but try to control them. A liberal style is preferred by 15% of respondents, 23% of respondents prefer an autocratic style. The results show that the majority of interviewed managers understand the limits of an autocratic style in management of knowledge workers. The name of the style was not written in the questionnaire so as not to mislead managers. Table 4: Relationships of managers to delegation, control and 3S I prefer to
Number 44
Delegate Strictly control subordinates use an ordinary daily control on subordinates Let subordinates work on the 3S principle (self‐ management, self‐organisation, self‐control)
21 26 44
% 45 22 27 45
The next question further explored the preferences of managers concerning control, delegation and the independent work of employees. Answers correspond with the answers to managerial style. 45% of respondents delegate, 26% allow ordinary daily control on subordinates, 45% of managers are not afraid to let their subordinates manage, organise and control themselves and only 22% of respondents insist on a strict control of subordinates. Table 5: Resistance How do you address resistance of your subordinates?
By orders and sanctions. It’s never happened to me. Differently (not autocratically)
Number 35 27 29
% 36 28 30
Resistance, especially quiet resistance, is a big problem in the Czech and Slovak republics. Historical consequences made Czech people experts in this field. Orders and sanctions are the worst ways to address resistance (Senge 1990). An aggressive responce to resistance leads to escalation of the problem, pretended consent and the misbehaviour of subordinates. There are many stories about quiet resistance in Czech organisations that were discovered after causing harm to the organisation or the manager who was
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Ludmila Mládková responsible. Resistance is a very sensitive problem in our region. We were curious whether interviewed managers understand that resisting knowledge workers must be treated sensitively. 28% of managers never experienced resistance of their subordinates, and 29% of managers prefer a different way than autocracy. It indicates that they understand the problem with resistance. 36% of managers still think that orders and sanctions can treat resistance, which is a naive and dangerous assumption. Table 6: Preferred type of organisational structure I prefer an organisational structure where
Decision making and control are centralised in the hands of top management Decision making and control are decentralised and are in the hands of employees Other types of organisational structure
Number 35
% 36
54 56 4
4
Organisational structure is the backbone of the organisation and predetermines the way knowledge is shared and knowledge workers are managed (Nonaka, Takeuchi, 1995, Mládková, 2012). 56% of respondents preferred decentralised decision making and control, which corresponds with the results on preferred style of management (60% of respondents prefer a delegation style of management) and the relationship of respondents to management and control (45% of respondents prefer to delegate). Table 7: Who are knowledge workers? Who is in your opinion a knowledge worker?
Highly qualified expert
Number 52
Person with great experience. Person with excellent performance Everyone these days Nobody
76 17 3 0
% 54 78 18 3 0
78% of our respondents, suggest great experience makes a knowledge worker. This result indicates that the interviewed managers understand the importance of experience (tacit knowledge) for knowledge workers. 54% of respondents see knowledge workers as a highly qualified expert. 18% of respondents link knowledge workers with excellent performers and 3% of respondents think that everyone is a knowledge worker these days. Table 8: Are your subordinates knowledge workers? Are your subordinates a knowledge workers
Yes No
Number 68 23
% 70 24
70% of respondents see their subordinates as knowledge workers, 24% of respondents do not see their subordinates as knowledge workers. As we know that subordinates of our respondents were people working in knowledge professions where great experience and high qualification is required we think that the number of managers who do not perceive their subordinates knowledge workers is quite high. Table 9: How many knowledge workers do I manage? Out of all my subordinates approximately .....% are knowledge workers
100% 75%
Number 6 39
50% 25% and less
22 24
450
% 6 40 23 25
Ludmila Mládková, The results of this table show that approximately half of interviewed managers understand their subordinates as knowledge workers. 6% of those interviewed stated that all of their subordinates are knowledge workers; 40% say that 75% of their subordinates are knowledge workers; 23% say that 50% of their employees are knowledge workers and 25% say that they manage 25% or less knowledge workers.
5. In conclusion The intangibility of knowledge makes knowledge workers difficult to manage. The most important part of the work of knowledge workers happens in their heads even though the final result of their work may be material. It cannot be observed and controlled, and it is not linear. The results of the work of knowledge workers may differ from the short and long‐term perspective. The growing importance of knowledge workers changes power relationships in organisations. When knowledge workers are involved, power shifts from managers to subordinates. They have more knowledge and they often understand what they are doing much more than their managers. Many of them make the final control of their product or service themselves. Researches of the Gallup Organisation on motivation and management of so called talented employees (the term fully corresponds with the term knowledge worker and is how it is understood in this paper) focused on employees’ performance and loyalty to their organisations identified that whatever the corporate policy and rules are, the behaviour and performance of knowledge workers influences the person who is above them, their direct manager (Buckingham, Coffman, 2005, Kelemen, 2010). Recent research shows that knowledge workers want the manager to be the one who serves more as an agent than a manager; who provides the knowledge worker with the means necessary for his work (including knowledge and contacts), helps him to synchronise his objectives with corporate objectives and supervises his personal development. Our research on knowledge workers interviewed 97 managers of knowledge workers. 93% of our respondents were experts in the same field as their subordinates, so they understand the knowledge their subordinates are using when working. 75% of our respondents prefer non‐directive styles of management (60% delegation style, 15% liberal style); only 23% decided for the autocratic style. 45% of respondents like to delegate, 45% even prefer subordinates to work on the 3S principle; only 22% of respondents prefer strict control. 56% of respondents like decentralised organisational structures, with 36% preferring traditional centralised structures. When asked who they think that a knowledge worker is, 78% of respondents decided for a person with great experience and 54% of respondents for a highly qualified expert. This result indicates that the interviewed managers understand the importance of experience for the creation of knowledge. 70% of managers admitted that their subordinates are knowledge workers. When asked to guess how many knowledge workers are between people they manage, 40% of respondents decided on 75%, 23% of respondents think that about 50%. 25% of respondents think that 25% or less (two respondents suggested none). The research sample is too small and to specific to allow us to generalise the results we received. However, it shows that with the exception of approximately ¼ of our respondents, interviewed managers understand that knowledge workers require a different management style than the traditional autocratic style of management. They also understand the shift in the role of a manager. And they understand importance of experience and education for their knowledge workers.
References Alvesson, M. (2002). Management of Knowledge Intensive Companies. 1995. De Gruyter. Bair, J. H. and O’Connor, E. (1998) The state of the product in knowledge management, Journal Knowledge Management, Vol. 2 (2), p. 20–27. Brinkley, I. and Fauth, R. and Mahdon, M. and Theodoropoulou, S. (2009) Knowledge Workers and Knowledge Work. [online] A Knowledge Economy Programme Report. http://www.theworkfoundation.com/Assets/Docs/Knowledge%20Workers‐March%202009.pdf, 20.3.2009. 11.7.2011 14:16. Buckingham, M. and Coffman, C. (2005) First, Break All the Rules, London: Simon&Schuster UK. ISBN 1‐4165‐0266‐1. Davenport, T. (2005). Thinking for Living. HVB School Publishing. ISBN 1‐59139‐423‐6.
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Ludmila Mládková Drucker, P. F. (1954) Landmarks of Tomorrow. A Report on the New ‘Post‐Modern’World. Transaction Publisher London. ISBN 1‐56000‐622‐6. Harman, C. and Brelade, S. (2000) Knowledge Management and the Role of HR. Financial Times‐Prentice Hall. Kelemen J. et al. (2010) Knowledge in Context. Iura Edition. SR. 2010. pg. 139‐172. Kidd, A. (1994). The Marks are on the Knowledge Worker. Human Factors in Computing Systems, CHI94. Boston. Lowe, G.S. (2002). Leveraging the skills of Knowledge Workers. Isuma, Spring. McGregor, D. (1960). The Human Side of Enterprise, New York, McGrawHill Mládková L. (2012) Management of Knowledge Workers, Iura Edition, SR, ISBN 978‐80‐8078‐463‐8. Nonaka I., Takeuchi, H. (1995) The Knowledge Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press. UK. ISBN 0‐19‐509269. Newell, D. (2000) How to Retain Technical Professional. People Management. 8 June 2000. Nomikos G.E. (1989) Managing Knowledge Workers for Productivity. National Productivity Review, 8(2). 1989. Reboul, C. et al. (2006) Managing Knowledge Workers: The KWP Matrix. Conference Proceedings MOMAN 06, Prague 2.2.2006. ISBN 80‐86596‐74‐5. Reich, R. B. (1992). The Work of Nations. New York: Vintage Books. Roffey Park Institute (2000) Developing the Knowledge Creating Culture. Horsham. Suff, P. and Reilly, P. (2005) In the Know: Reward and Performance Management of Knowledge Workers. [online] Institute of Employment Studies. 2005. http://www.employment‐studies.co.uk/pdflibrary/mp47.pdf. 12.7.2011 10:34. Sveiby, K. E. (1997) The New Organisational Wealth: Managing and Measuring Knowledge‐Based Assests. 1997. Berrett‐ Koehler. Toffler, A. (1990). Powershift: Knowledge, Wealth and Violence at the Edge of the 21st Century. 1990. Bantam Books. ISBN 0‐553‐29215‐3. Veber, J. (2000) Management, Basics, Prosperity, Globalization, Management Press. Praha. ISBN 80‐7261‐029‐5 pg. Vinson, J. (2009) www.vinson.com. [online] 5.5.2009, 16:45
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Strategies for KM Implementation: UK Case Study Perspectives Sandra Moffett University of Ulster, Londonderry, Northern Ireland sm.moffett@ulster.ac.uk
Abstract: Within the United Kingdom the MeCTIP model and supporting ‘Benchmarking KM’ assessment tool (Moffett et al., 2000) provide a framework for organisations to identify Knowledge Management (KM) implementation opportunities, gaps and limitations. Based on the MeCTIP concept, following a large-scale empirical study undertaken in 2009 with 588 UK organisations from various organisations types, sizes and sectors, a knowledge taxonomy was created based on success of KM implementation. Each of the 588 participant organisations were classified across a KM continuum, six categories existed namely beginners, laggards, non-viewers, emergers, progressors and achievers. Categorisation focused on the implementation approach that each organisation adopted from non-viewer, ad-hoc implementation to those that focused on KM elements, such as cultural aspects or technical approaches, to those that had a strong combination of people, process and technology for successful KM initiatives. From each category a number of companies were selected for further in-depth qualitative review. Case study research was conducted to obtain a deep, qualitative analysis of KM implementation processes. A total of eight organisations were selected for multi-level analysis, gaining in-depth views of strategic and operational KM from a range of employees. This paper presents the findings of this ‘KM in Action’ approach, identifying KM implementation strategies. Qualitative findings are applied to support current literature, anecdotal quotations provide insight into the views of those involved in the KM implementation journey.This paper contributes to the 'Knowledge in Action' track as it uncovers some interesting insights as to how and why UK organisations have chosen to adopt KM initiatives and the pitfalls/benefits they have found on the implementation journey. Audience participants will be able to critically assess the approaches undertaken to cherry pick any useful techniques for their own organisations (practitioner perspective) or to enhance their own research agenda. Keywords: MeCTIP model, implementation, case studies, UK
1. Introduction The future of KM relies on level of acceptance on a par to other business improvement concepts. In 2000, Beijerse stated that to achieve total acceptance as a concept more comprehensive studies relating to KM implementation in organisations of different sizes and types was needed. A similar view was expressed during the European Conference of Knowledge Management (ECKM) in 2011, especially in the keynote addresses of Klaus Tochtermann and Ronald Maier. In 2012, a very successful ‘Knowledge in Action’ track was included in ECKM conference with 16 papers selected, following peer review, to present in this theme. During this session the author presented the results of an empirical study undertaken in 2009 with 588 UK organisations, employing the MeCTIP Knowledge Management model and the ‘Benchmarking KM’ assessment tool. The findings indicated key factors for successful KM implementation strategies. This paper takes the empirical research findings a stage further by identifying examples of KM activity within eight UK companies.
2. The MeCTIP Knowledge Management Model Current KM literature outlines a number of aspects which contribute to KM implementation, these are summarised in table 1: Table 1: Key contributors to KM Title Macroenvironment
Theme Economic, technical and social agents of change
Internal organisational development
Culture and organisation climate
Content Includes globalisation and the recession, emergence of new technology such as the Internet, market orientations Includes organisational structure, strategy, goals, culture, employee emancipation, change management and business improvement initiatives
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References Johnston, (2009) Obeng and Crainer, (1996) Ward, (1994) Vorakulpipat and Rezgui, (2008) Moffett et al., (2003) Davenport and Prusak, (1998) Lank, (1997)
Sandra Moffett Overall management approach
Link between strategy and operations
Customer focus
Interface between internal operations and customer /client TQM, Business Process Reengineering, production improvement KM concepts, tools and applications, implementation, knowledge drivers of change Internal technical climate, technical contributors to change
Quality focus
Knowledge focus
Technical focus
Informational Contributors
Creating, storing, disseminating and using information
Personal Contributors
Human Resource Management, people and working practices
Includes business improvement initiatives (TQM, the Learning Organisation, Business Process Reengineering), continuous improvement, leadership and facilitiation, knowledgeorientated direction Includes satisfaction, loyalty, customer relationship management
Fernandez et al., (2006) Moffett et al., (2003) Normann, (2001) Davenport and Prusak, (1998) Powell, (1995)
Includes production and manufacturing processes, service delivery, outsourcing, partnerships and alliances, new product design, research and development
Johnston, (2009) Johnston and Clark, (2001) Liljander and Strandvik, (1997) Fernandez et al., (2006) Moffett et al., (2003) Kurland, (1992) Crosby, (1979)
Includes tacit and explicit knowledge, knowledge roles, knowledge-based systems, information management, employee emancipation
Borges Tiago et al., (2007) Dunford, (2000) Davenport and Prusak, (1998) Quintas et al., (1997)
Includes technological infrastructure, response to technical change, system standardisation and compatibility, technical usability, technological tools and software applications Includes information fatique, infofamine, infoglut, knowledge silos and power-bases and information auditing Includes knowledge roles and skills, motivation and self-reflection, empowerment, learning networks and communities of practice, dialogue, collaboration and innovation
Jennex, (2005) Davenport and Prusak, (1998) Shenk, (1997) Ajmal and Koskinen, (2008) Borghoff and Pareschi, (1999) Offsey, (1997) Sarros et al., (2008) Lustri et al., (2007) Scarborough et al., (1999) Zuboff, (1998) Peters, (1992)
Moffett et al., (2002; 2003) have grouped these into five key categories that can either support or hinder KM implementation, forming the basis of the MeCTIP model (shown in figure 1). MeCTIP is an acronym of model components, namely, Me C T I P
Macro Environment Culture Technology Information People
Organisations must be aware of external, macro-environmental factors that will have an impact on organisational climate/culture and technical climate/ infrastructure, both of which further impinge on technical, informational and personal processes internally. A successful knowledge-orientated organisation is one which has strong information practices and technical resources to support employees in decision making processes.
3. Research methodology The MeCTIP model informed the development of an on-line survey based measurement instrument, known as the â&#x20AC;&#x2DC;Benchmarking KMâ&#x20AC;&#x2122; tool, available at http://www.business.ulster.ac.uk/questionnaires/moffett/ (last accessed 08/05/2013). Quantitative research was undertaken with 588 UK organisations and used for organisation size comparison (Moffett et al., 2011) and organisation sector comparison (Moffett et al., 2009), details of the statistical analysis process and results can be obtained from Moffett et al., (2009, 2010).
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Figure 1: The MeCTIP model For each respondent organisation, a total score for KM was derived based on cultural, technological and informational scores. Organisations were classified as either poor (three low scores, or two low and one medium score), developing (two medium and one low score, or three medium) or potential (one or more high score in any category). When grouped according to these classifications 27% of respondent organisations are deemed poor at KM, 15% have developed some KM initiatives, though the approaches were ad-hoc and not part of a strategic KM plan (more by chance than with vision) and 57% exhibited KM potential, where at least one category scored highly showing success at KM activity. Taking this a stage further participant organisations were re-classified on a knowledge taxonomy basis. Depending on the activity undertaken, strategic and operational vision, and success to date organisations were categorised as beginners, laggards, non-viewers, emergers, progressors and achievers. Figure 2 shows the results of this categorisation.
Frequency
KM Categories 400 350 300 250 200 150 100 50 0 Beginner
Laggard Non-viewer Emerger
Progesser Achiever
Category
Figure 2: Knowledge Taxonomy The results of the knowledge taxonomy classification indicate that: • 2% of repondents are ‘beginners’ with little KM implementation • 14% are deemed to be ‘laggards’, they have low focus on at least two of the three elements necessary (technology, information and people) for KM implementation. • 11% have a key driver for KM implementation, receiving a high score in one element, but are not seeing the bigger picture ‘non-viewers’ which requires focus on all three elements
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• •
59% scored medium on either two or three of the elements showing that some form of KM implementation was in motion ‘emergers’, this activity needs to be nurtured to move towards progresser/achiever status 13% are organisations with high KM activity in two of the elements ‘progressors’. While these organisations will see benefit to KM implementation the third element in which they are lacking needs attention. 2% are deemed ‘achievers’ received a high factor score in all three elements. These organisations should be exemplars of KM implementation and practice.
4. KM in cases Further support for quantitative findings was derived from qualitative cases. As part of the quantitative data collection organisations were asked to express an interest in participating in further research identifying a contact person as gatekeeper. From the 588 organisations employed in the empirical study 53% expressed an interest in further research, from these eight were selected as they represent organisations at various stages of KM implementation, ranging from those who claim to have limited KM in place (poor) to those deemed successful (achiever) equally merging people, process, information and technological applications. Contact was made with the gatekeeper to arrange visits, he/she was asked to nominate up to 6 people in the organisation most knowledgeable in KM. A total of 33 managers, those with KM responsibility in areas such as HR, IT, operations, business intelligence and general management were involved in the qualitative process, as shown in table 2. Table 2: Case Study Participants Case No 1 2 3 4 5 6 7 8
Sector Engineering Engineering/Manufacturing Financial Services Engineering Higher Education Health Inspection Financial Services Aerospace Manufacturer
KSM Implementation Stage Poor Emerger Emerger Emerger Progressor Progressor Progressor Achiever
No of interviewees 5 – coded A1 to A5 6 – coded B1 to B6 1 – coded C1 3 – coded D1 to D3 4 – coded E1 to E4 5 – coded F1 to F5 5 – coded G1 to G5 4 – coded H1 to H4
In keeping with the theme of this paper, components of the KM MeCTIP model will now be discussed from a qualitative viewpoint.
4.1 Macro-Environment (Me) Organisations are not ‘black boxes’ so attention must be paid to the external environment and changes therein. One factor that is having extreme effect on organisations at present is the recession. As interviewee B1 states, ‘The trouble comes in a recession, when you have £150 million of fleet, depreciating at £15million per year, sitting in a yard not being used’. While the recession can be an inspiration for some to seek new business/contracts as outlined by A2 ‘For quite a small company, we are out there trying to get business’, the push to drum up business is not welcomed by all, as commented by A1 ‘I don’t see the point in going all out for Sales, we don’t have the capacity to deliver, in the current market we should just focus on the work we have got’. Sustainability is a consideration for most UK companies in the current business climate, as G1 outlines ‘When there’s less capacity in the market, you need to be able to change more, and start going back up the cycle. So I guess our plan right now is hold tight, pull back on the stuff that is ‘dangerous’, the highly risky stuff, and be ready to expand into the market when it (improvement) happens again’. Interviewee F1 comments on efficiency as being key in the current climate, ‘increasingly we are looking at our spend, we must at all times demonstrate that what we do spend is value for money. We are trying to work smarter and cheaper’. However, the recession is not viewed by all as having a negative impact, C1 looks positively towards the current economic situation, ‘It has been a difficult period over the last 12 to 18 months. We have ridden that quite well, and I think that there are opportunities that will come out of that’. C1 contributes being ‘able to ride the storm’ to conservatism ‘that steady hand has now paid off’ while H1 contributes their success to innovation, ‘What did we need to do to become more innovative? Knowledge Management was identified as an enabler, now it is one of our core themes’. Within the same organisation, H2 adds ‘We started looking at what other people do, what might be out there, what we really need, and we add detail to those. We have a plan now for future innovation’.
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Sandra Moffett Application of KM should lead to a well-designed/managed change programme, responsive to environmental changes external to the organisation. Aspects for development include sustainability, cost reduction and efficiencies, conservatism, ability to work smarter, and innovation.
4.2 Organisational Climate (OC) Within organisations conflict exists regarding external pressures, reflected on internal organisation climate (OC). On one hand, OC is viewed as positive, expressed in flexible working practices, employee loyalty, low staff turnover, etc. while on the other, it is viewed as static and stale, stifling creativity and innovation. While one staff member may describe OC as ‘interesting’ another refers to it as ‘cynical’. One way to reduce such varied approaches is via company strategy/mission statement. The need for strategic positioning is raised in the qualitative cases. B2 states, ‘everyone is aware of the mission statement and organisation values. We (board members) come up with a three year plan once a year’. While this is useful for strategic direction, B4 states, ‘When speed is of the essence, sometimes not all procedures are followed’. Therefore flexibility is key when environments are turbulent. Interviewee A3 comments on issues surrounding lack of strategy, stating ‘That is a hot topic at the moment. There isn’t a set strategy in place, we have been led by XXX (founder of the business), but we realise this is something we need to focus on’. Within the same organisation, A1 outlines, ‘We know what our strategy is – to survive, to grow, build up the business, make money ... the question is whether we need to put that down on paper’. C1 also comments on the need for a more formal strategic position, ‘There hasn’t been a coherent strategy across the group that you would put your finger on and say that’s our strategy. However it has been identified that we need to refocus on what is our strategy. We all consciously know that, but I think it has never been defined clearly, so we are going through a period of work where we are doing that. We are having sessions about things like missions and values. I think it will give everybody a bit more of a focus on where we want to get to, because there is some debate about whether we are a reactionary organisation, where we see opportunities and move for them, or do we go out and find them’. Communication is identified as a key issue to develop positive organisational climate. C1 highlights the need to be in touch with colleagues, outlining ‘We did a staff survey recently. It provided a few surprises, but for a lot of it you could have predicted some of the answers. It give us a bit of focus on some development areas for the business, things like communication. With it being a small business you assume everyone knows what is going on. That is an assumption that was not right. There was not enough communication and we were not conscious that that was the case. Little things like that have come out, and we have rectified them. We consciously made an effort to be visible in doing these things, and it has really helped.’ This quotation also highlights the need for transparency within organisations.
4.3 Technical Climate (TC) In smaller organisations codification of tacit knowledge can takes place in meetings, conversations, notes, etc. so the need for technological aids is not as crucial as in larger organisations. A5 comments on this point, ‘Technology is poor, we don’t even have a website. IT systems is one area where we need much more, we really need a system (in manufacturing) to capture all our system data to enable us to use it better, you know, identify trends, streamline processes, etc.’ Within the same company, A2 outlines the downside to lack of technical climate, ‘Most of our communication takes place by phone or face-to-face. The downside to this is that we don’t have a record of what is happening, decisions can be made between two people but that is not communicated to the rest of the team, if they (the person with the tacit knowledge) don’t pass it on no-one else knows’. Embedding technical climate into organisations is challenging, E1 declares, ‘There seems to be initial excitement and then organisations become complacent’. However E3 claims this should be the case, ‘What I like here is that we don’t talk about IT. It really annoys my colleagues but I feel it shouldn’t be mentioned, it should just work. It’s like your care; it’s supposed to start every morning and take you somewhere. You don’t think your car, it’s just a given. But when it breaks you realise how much you depend on it. For me, that is IT’. Overall, technical climate is key for promoting KM. Scalability tends to depend on organisation size, while smaller organisations focus on information storage and communication, larger organisations are seeking robust, integrated systems that can be utilised globally for information storage, share and application.
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4.4 Technology Technological tools for KM can be classified into three categories, namely, intelligent tools, support tools and web-based tools. Not surprisingly the four most popular tools are those which organisations provide most training in. For KM to be successful organisations must select tools which are not only familiar to the employees but of use. The KM arena has suffered in recent years with the re-branding of traditional tools (such as office automation systems) as KM systems. Organisations need to look at their information needs, choosing technology systems and applications to further advance the knowledge agenda. ICT systems are used for information capture, storage and use, to obtain expertise into and within the organisation. G2 comments on knowledge acquisition, ‘Building the information into an industry-level discipline is a challenge. The information is out there. In some markets, it is just built into their DNA to use information, it is not yet like that in the commercial market that we are in. A lot of the market is based on tacit knowledge. There is a lot of knowledge which cannot be codified, which is actually quite valuable. IT professionals need to use technologies that will capture that tacit knowledge, no matter how limited that may be, providing information that makes sense, processed in a way that is currently possible’. Another main reason is communication, ‘Email is accessed from the internet, which provides the opportunity for connection from any location’ (E2) and ‘email is the main driver of communication’ (G3). Security of technological systems/tools is a problem which many organisations face. As H4 states, ‘We don’t want a walled garden or a silo, but a controlled membrane surrounding the whole organisation, so that you know with confidence that information can be quite safely circulated to the audience to engage the maximum degree of expertise, but not go out to your competitors. This is starting to be a problem’. Security can have a detrimental effect on knowledge sharing if it is too controlled. Other technology challenges include location-based access to systems, single sign-on, better internet access and use in terms of content filtering, searching and semantic labelling, system access to areas that are offlimits, and reduction of corporate knowledge silos. However on a positive note most organisations interviewed found that ‘employees are willing to accept new technological implementations’ (G4) ‘if provided with tools that make it easy for them’ (B2) and are willing to ‘actually relinquish some of what they perceive as control over the information and at least allow people to see it’ (H3). Business Intelligence is the goal for many organisations to fully understand company ‘knowledge nuggets’. Technology tools such as Internet and email enhance communication channels while information systems encourage content management, knowledge sharing and information accessibility. Security needs to be high yet flexible to encourage knowledge sharing and technological use.
4.5 Information Information should flow easily around the organisation ensuring that people have access to ‘the right knowledge in the right format at the right time’ (Davenport and Prusak, 1998). Systems to facilitate the capture and dissemination of information throughout the organisation facilitate information capture from both internal and external sources. One element to be considered in ensuring accurate information systems is that of content management. Responsibility must be taken to ensure that information sources are up-to-date and relevant preventing databases and other storage mechanisms from becoming static repositories of obsolete data (Davenport and Prusak, 1998). H5 comments on the vastness of the task in organising information content for user accessibility, ‘We are currently looking at all unstructured data, stored in electronic information such as emails, Word, Excel, Powerpoint, information in image format, etc. Anything that is held in databases in structured format does not come under the remit of content management: it is already searchable and available to users, hence content management is a challenge for most organisations, ‘how do you bring all this together, ideally in one central place, so that users can get access to all of that information that is in there? How do you secure it so that only the right people can see the right information? How do you version control it so that obsolete information is superseded and that key, relevant, up-to-date information is always available at the front-end?’ (H1). Reflecting on the need for an information strategy Company E is an example of good practice as they have awarded considerable time and effort to creating an information strategy. E4 outlines, ‘We wrote our information strategy about three or four years ago – we took a year writing it, going backwards and forwards, working out what we wanted to do – and it’s a real, living document and strategy. And we are doing what it says we are going to do. And for me, that is really important’.
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Sandra Moffett Information overload is a challenge for individuals in everyday life. E4 outlines one way they attempt to reduce overload, claiming, ‘We have identified who the lead owner is for pieces of information. What that means is the person who own it knows they shouldn’t throw it away, and everybody else knows they can. One of the issues I have, especially in a small institution, you feel you have to remember everything all the time. And you can’t. What is important to me is I know what I need to keep, and what someone else knows and so I don’t have to worry about any more, we can integrate things better, so we don’t operate in silos but in a genuinely joined-up way, but no one individual needs to know all the joined up bits’. While G5 appreciates information overload within the organisation, he states ‘people are used to this in their personal life, there is data smog everywhere’. Information overload seems to be a sign of the times.
4.6 People Knowledge-oriented organisations respect employee emancipation and welfare, evidenced by informal interactions and practice (Haas and Hansen, 2007). G5 outlines some welfare benefits offered, ‘All benefits are better than the norm. The organisation offer staff childcare vouchers, private medical insurance for members and their families, very good life insurance policy. There are also little things in the building, for example the company provides free fruit daily and a masseuse comes in once a month. People are well looked after though they may take it all for granted. The company is considering benefit statements, as way of reminding people of all they get in addition to salary and bonuses. Family friendly policies and flexible working hours are also the norm’. Providing such strong welfare practices results in low staff turnover, ‘People see us as a good employer, absolutely. I think our pay rates are quite competitive. People say ‘if I get into Company H I’m going to stay there forever’. We have plenty of guys who have been here 20+ years. That’s the way it’s always been. I’m certainly going to work here as long as I possibly can’. Views on flexible working practices seem to differ within participant organisations. For example, G3 states, ‘home working is accepted but not encouraged. Too many home workers might lead to fragmentation. The view is that you are better at your job when you talk to people’. H2 states ‘I do work from home quite a bit. Rather than stay at work longer, I go home early, sort out the family, then do a bit more. A lot of managers subsidise their hours in-house’. Consistent with the literature (see Davenport and Prusak, 1998) much KM work takes place in teams. This is the case in company H where ‘in a given programme there will be a team selected based on their function, role, knowledge and expertise’. Senior management tend to lead by example, creating an atmosphere where new employees soon feel settled and ready to participate in flexible work practices. C1 states, ‘during induction we encourage new staff to sit with the other teams in the business for an hour or so, just to get an overview of what they do, how the whole thing hangs together’. H4 outlines flexibility as key to helping new staff fit in, ‘I have an open door policy, I am glad to take the time to sort out issues with new staff, a fresh pair of eyes can be very useful’. Interviewee F1 also comments on leading by example, ‘we have really improved in that area. It is very important. It’s like a love or hate at first sight. I spent an hour yesterday just talking about the office environment, as a manager I have to devote time to staff issues, make sure I do it properly’. Succession planning is one KM initiative most organisations are considering. F5 outlines the exit process, claiming ‘Well I certainly believe that we are in a much stronger position: if I were to go tomorrow, I think that we now have strategies and plans in place, a person who met the job description could easily move in and say ‘oh, that’s what they were doing’. However, some organisations have not yet considered knowledge capture for future use, A2 states, ‘No, we have nothing in place to do that. We simply wish them all the best, for whatever reason they are leaving, and then recruit someone in their place and start to train them up all over again’. Interviewee B5 also comments on lack of succession planning, ‘When staff are retiring, you are aware that they are taking their knowledge. We currently have a few people approaching retirement age, and potentially they could all leave at the same time, causing a large gap’. People issues are the most stretching for organisations to adopt. Changing individual perspectives, gaining staff buy-in for change, and implementing change consistently across all levels of the organisation is challenging.
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5. Strategies for KM implementation Current KM literature outlines a number of strategic approaches, for example Hansen et al., (1999) consider codification versus personalisation, Robertson, (2005) introduces a top-down and bottom-up approach and Choi and Lee, (2002) link strategy to the knowledge creation process, to name but a few. With no intention of re-inventing the wheel, this paper has identified a number of factors for KM implementation strategies, these are displayed in the following word tag (figure 3).
Figure 3: KM strategies tag
6. Conclusion While an increasing number of organisations are realising the benefits of active knowledge management they are also discovering the difficulty of KM implementation (Birkinshaw, 2001). Results from an empirical study conducted in early 2009 with 588 UK companies, applying the MeCTIP model and ‘Benchmarking KM’ online survey tool, provide insight into key elements which organisations must focus on for KM success. Two of these relate to the infrastructure of the organisation in terms of culture and technical infrastructure while three relate to process orientated activity for information, technology application and human expertise. The effective measurement of KM enables organisations to have a more upstream, predictor focus on business performance (Zack et al. 2009). As the creation of new knowledge and its embodiment within the organisation is likely to lead to new product/service development (Johnston and Clark, 2008), the measurement of knowledge activity within the organisation, resulting in increased business intelligence and sustainable competitive advantage (Tochtermann, 2011), will facilitate UK companies’ sustainability, growth and maturity ‘riding the storms’ of the current economic climate.
References Beijerse, R. P. (2000), Knowledge management in small and medium-sized companies: knowledge management for entrepreneurs, Journal of Knowledge Management, Vol. 4, No. 2, pp. 162-177 Birkinshaw, J. (2001), Why Knowledge Management is difficult?, Business Strategy Review, Vol. 12, Issue 1, pp. 11-18 Choi, B. and Lee, H. (2002) Knowledge management strategy and its link to knowledge creation process, Expert Systems with Applications, Vol 23, pp. 173-187 Corso, M., Martini, A., Paolucci, E. and Pellegrini, L. (2003), Knowledge management, Vol. 14, No. 1, pp. 46-56 Davenport, T. and Prusak, L. (1998), Working Knowledge - How Organisations Manage What They Know, Harvard Business School Press, Boston Demerest, M. (1997), Understand Knowledge Management, Journal of Long Range Planning, Vol. 30, No. 3, pp. 374-384 Haas, M.R. and Hansen, M.T. (2007), Different Knowledge, Different Benefits: Towards a Productivity Perspective on Knowledge Sharing in Organisations, http://knowledge.wharton.upenn.edu/papers/1346.pdf (last accessed 08/05/2013) Hansen, M.T., Nohria, N. and Tierney, T. (1999), What’s Your Strategy for Managing Knowledge?, Harvard Business Review, March-April 1999 Johnston, R and Clark, G. (2008), Service Operations Management, Prentice Hall, Third Edition, ISBN 9781405847322
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Maier, R. (2011), Re-focusing knowledge management: concepts of knowledge maturing, Keynote address 12 European Conference of Knowledge Management, University of Passau, Germany, 1-2 September Moffett, S. McAdam, R. and Parkinson, S. (2002), The inter-relationship of cultural and technological factors in Knowledge th Management: An empirical analysis, 7 International Conference on ISO 9000 & TQM, Melbourne, Australia, 2-4 April Moffett, S. McAdam, R. and Parkinson, S. (2003), An empirical analysis of knowledge management application, Journal of Knowledge Management, Vol. 7, No. 3, MCB University Press Ltd, ISSN 1367-3270, pp. 6 â&#x20AC;&#x201C; 26 Moffett, S. and McAdam, R. (2009), Knowledge Management: a factor analysis of sector effects, Journal of Knowledge Management, Vol. 13, No. 3, pp. 44-59 Moffett, Sandra and Hinds, Anne (2010) Assessing the impact of KM on organisational practice: applying the MeCTIP model to UK organizations. Electronic Journal of Knowledge Management (EJKM), Vol. 8, Issue 1, pp. 103-118 Moffett, Sandra, McAdam, Rodney and Humphreys, Paul (2011) Knowledge Management Implementation in the UK â&#x20AC;&#x201C; Does Size Matter? In: In Proceedings of 12th European Conference on Knowledge Management, University of Passau, Germany, Academic Conferences International. 9 pp. Offsey, S, (1997), Knowledge Management: Linking People to Knowledge for Bottom Line Results, Journal of Knowledge Management, Vol. 1, Issue 2, pp. 113-122 Robertson, James, (2005), Developing a knowledge management strategy, Step Two Designs Pty Ltd, http://www.steptwo.com.au/files/kmc_kmstrategy.pdf (last accessed 08/05/2013) Tochtermann, K. (2011), 10 Years of Knowledge Management th - Will another 10 Years follow?, Keynote address 12 European Conference of Knowledge Management, University of Passau, Germany, 1-2 September Zack, M., McKeen, J. and Singh, S. (2009) "Knowledge management and organizational performance: an exploratory analysis", Journal of Knowledge Management, Vol. 13 Issue 6, pp.392 - 409
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Motivating key Employees Towards Knowledge Sharing ‐ Research Findings and Suggested Solutions Mieczysław Morawski Faculty of Economics, Management and Tourism, Department of Business Administration, Wroclaw University of Economics, Poland mmorawski@ae.jgora.pl Abstract: One of the most important problems of human capital management, especially in relation to knowledge management, is motivating key employees to share their knowledge with colleagues presenting lower competences. Key personnel represent top‐class professionals. They include top managers, senior executives of long‐term employment in a company and specialists presenting unique knowledge and skills. Key personnel of an organization frequently have no reasons to be generous and share their knowledge with colleagues. The Author presents research findings based on questionnaire surveys made up of a sample consisting of fifty companies operating in Poland. The responses provided during interviews by both mangers and key employees, representing the surveyed companies, have been analyzed. Research findings resulted in presenting the Author’s model of the working environment facilitating knowledge sharing by key employees. The model is embedded in the selected type of organizational culture and approach to human capital management. The paper discusses qualities of organizational culture and human resources management which are positively related to motivating key employees towards knowledge sharing. Keywords: key employee, knowledge sharing, key employees motivating, human capital
1. Introduction In present conditions competitive advantage is obtained through the ability to create new values. An organization physical property is less important, however, what it knows and is capable of accomplishing in the knowledge‐based economy is of much greater significance. Visible assets do not present the object of special interest in a modern organization, but rather its invisible resources including mainly knowledge based on human capital. In consequence, in case of companies subject to strong competition, an appropriate approach to managing people gains special meaning. The best HR practices are always focused on knowledge management. In recent years Knowledge Management has emerged as one of the prime concerns related to human resources management. In HRM context Knowledge Management stands for the creation, distribution and utilization of knowledge in case of both an individual employee and a group, at an organizational level, for the benefit of employees affected by it aiming at their improvement and advancement. The hereby paper discusses the emerging trends in Knowledge Management faced by HR area (Martin, Whiting, Jackson 2010). Furthermore, recent research indicates that intellectual assets and resources can be utilised much more efficiently and effectively if organizations apply knowledge management techniques for leveraging their human resources and enhancing their personnel management (Soliman, Spooner 2000). The central concern of human resources management, especially in relation to organizational learning, is both recruitment and retention of valuable employees (Davenport 2000). The significant problem influencing the effectiveness of innovative processes is the transfer and dissemination of knowledge in a company. One of the challenges – conceptual and practical – is to encourage key employees to share their knowledge (experience, skills, good practices, ideas) with other company workers. Modern human resources management is necessary for this purpose, defined as human capital management and referring to methods of knowledge management. It is particularly important to gain knowledge from the best valued employees presenting core competences. Their knowledge constitutes the perfect basis on which the knowledge of other individual employees and the entire company organizational knowledge can be constructed. The process of sharing knowledge serves this particular purpose. While CEOs of large organizations tend to think of valued employees as senior management layer (the “top 200,” for example), our experience suggests that the focus should be much wider. In fact, we think of valued employees as meeting one or more of three key criteria (regardless of their level). Either they have critical skills (such as IT or product development), or they are high performers, or they are “high potentials,” which would include those who may be central to helping the organization meet its diversity objectives. The challenge for HR, then, is how to help the line to stimulate the maximum possible investment from valued employees. (The Future of the HR Profession 2002)
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Mieczysław Morawski An outstanding expert, attempting to be the key employee for an organization hiring them is a specialist with high, master competences, an innovator – a person introducing breakthrough changes, independently or in cooperation with other creative employees, a leader – capable of building and leading a team of specialists and a mentor – promoting and monitoring career of other employees presenting big potential (Morawski 2011). In Poland, new solutions that combine knowledge management and governance arise recently in traditional industries. The paper is to present legal, organizational and technological determinants at the electronic scrap market in Poland. From such perspective the Author discusses the situation of the new market player – “Legnica” Copper Smelter. (Bakowska‐Morawska 2013).
2. Research questions and methods The research was conducted in the years 2011 and 2012 and was based on a sample consisting of 50 enterprises. The target group covered enterprises seated in western and south‐western Poland. The two largest groups, comprising the studied sample of enterprises, represent companies included in a broadly understood automotive industry, as well as enterprises functioning in the sector of tourist services. The selection of type of operations performed by these enterprises resulted from the importance of cars and their spare parts manufacturing, as well as tourism and leisure oriented services, for the development of Polish economy and their significant share in GDP (gross domestic product) creation. Additionally, both automotive industry and services in tourism are the example of economic and organizational success. Enterprises representing these sectors earn large income and frequently implement modern technical and managerial solutions. Two research tools were applied in the underlying analyses, i.e.: survey questionnaire addressed to entrepreneurs and managers and an interview questionnaire addressed to key employees. The survey questionnaire applied in the study included 18 questions divided into 3 thematic blocks: company management, key employee profile and key workers involved in the knowledge sharing process. The questions were mostly of closed type ones. Company owners or top managers were the questionnaire respondents. An interview consisted of open questions and its purpose was to provoke key employees for presenting deeper reflections and their own, personal opinions. The Author was mainly focused on finding out the real motives underlying knowledge sharing, as well as specifying situations in which knowledge sharing takes place and what factors encourage this group of workers to share their knowledge with others. The tab. 8 presents five selected questions from interviews, frequently repeated responses and the Author’s comments.
3. Results As the answers provided by the respondents (tab.1) confirm flexible work division is typical for the majority of studied enterprises and their employees participate in regular meetings organized by their supervisors. Additionally, the management strategy followed is characterized by employees’ active and personal participation in different processes. Table 1: Which of the listed qualities are characteristic for your enterprise?(an unlimited number of qualities can be indicated)
Ordinal number 1. 2. 3. 4. 5. 6.
Qualities ongoing and current, objectives focused, work division (tasks, authorization, responsibility) low level of formality (measured by the number, detailed and rigorous nature of regulations) changeable organizational roles (the same roles played by different employees: manager, specialist, consultant, executor, depending on the task type) rotation at work positions: employees change their positions depending on specified rules flexible work time flat organization structure (small number of management levels, extensive spread of management)
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Qualities low level of decisions centralization (many decisions are made at lower management levels, lower level management is authorized to solve problems individually) the majority of workers are appointed for periodical work in different temporary projects implementation or in expert teams, etc. the majority of workers participate personally in different processes (contacts with institutions in their environment, customer service, organization of internal trainings, negotiations with suppliers, etc. supervisors organize regular meetings with employees regarding key issues (e.g. product advancement, quality improvement) supervisors organize regular meetings with employees regarding current issues and problems informal meetings (other than in working hours, workplace, without any initiative by the supervisor) of employee groups representing a particular company unit and discussing current professional issues and problems informal meetings of employee groups representing different organizational units of an enterprise and discussing current professional issues and problems
7. 8. 9. 10. 11. 12. 13.
Table 2: Please evaluate, in the scale from 0 to 5, the activities undertaken in your enterprise (an unlimited number of qualities can be indicated)
Ordinal number 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.
Activities motivating (bonuses, awards, other) employees to share their knowledge with others acquiring knowledge (opinions, assessments, suggestions) from clients motivating staff towards creative thinking, solving organizational problems encouragement for cooperation and open communication in teams ongoing learning of all personnel at their job positions by cooperation and exchange of experiences (e.g. informal meetings before work, during breaks at work) creating organizational base for knowledge exchange and dissemination between personnel (e.g. meetings, workshops, presentations) the estimation of company intangible value components (e.g. human capital, company brand, customers loyalty value estimation) undertaking activities aimed at upgrading company intangible components value encouraging staff towards creating innovations establishing organizational culture focused on cooperation, reliability and partnership managers’ willingness and actual activities for staff knowledge upgrading (support in unusual situations, suggesting best possible solutions, answering questions) the reduction of mid‐level management positions appointing different teams, e.g. focused on implementing projects, solving problems, undertaking initiatives creating special programmes for talented employees support for continuing education and upgrading qualifications by workers making best managers responsible for taking care of certain employees’ career assessing and motivating staff for developing qualifications they already have and learning the new ones
In the next question (tab.2) respondents are requested to evaluate activities which are crucial from the perspective of managing broadly understood material resources (e.g. intellectual capital, knowledge,
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Mieczysław Morawski innovation, talent, etc. management), i.e. to what extent modern management methods are applied by the company. As the responses indicate, the majority of respondents confirm obtaining knowledge from clients, but at the same time point to the motivation oriented activities implementation which stimulate knowledge sharing, creative thinking, cooperation and open communication. The support provided by companies regarding continuing education and upgrading qualifications, including the crucial role played by managers for the benefit of personnel development, is also emphasized. Table 3: If there are key workers in your company, what requirements do they have to meet to be included in this category of workers? (Please, mark 5 responses max.)
Ordinal number 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.
Qualities university graduate university graduate in the field of study related to the performed job received many prizes and awards presents many years of experience in the particular sector of professional activity has extensive contacts among suppliers, business partners, other organizations, specialists, clients, etc obtains above average work results publishes his/her papers in professional journals prepares rationalization oriented applications, presents new ideas, registers his/her patents works in an important, strategic unit/team for the entire enterprise is a trustworthy person presents management skills worked as team leader in the past currently works as a manager holds an important position in an enterprise wins new clients maintains good relations with important company clients is well known by the majority of company staff
According to respondents’ opinions (tab.3) key workers in their enterprises are mainly characterized by the following qualities: trustworthy, present many years of professional experience, achieve above average work results. Table 4: If there are any key workers in your enterprise, how is their special status emphasized?
Ordinal number 1. 2. 3. 4.
Qualities they are not distinguished in any way comparing to other employees they are employed based on individual work contacts (employment agreement, other forms) they are individually remunerated, according to separate criteria and rules they receive additional financial benefits covered by an enterprise (medical, leisure services, holiday trips, additional insurance, etc.
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Mieczysław Morawski Ordinal number 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
Qualities they have more opportunities of business trips than other employees: conferences, fairs, exhibitions, shows, etc. they receive higher than the remaining staff financial resources for the participation in: trainings, courses, post‐graduate studies they participate in company profits based on individual agreements with an enterprise their professional career path has been planned they belong to a special group of workers covered by such programmes as e.g. leaders creation, talent management, managerial positions successors they have access to strategic knowledge of an enterprise (technologies, development plans, technical and construction parameters of products they are invited to participate in management board, supervisory board and other company management meetings as consultants, experts, advisors, etc. they are appointed to work in permanently or temporarily functioning groups of experts playing the role of company management consultants they work as managers of specially appointed commissions, teams for solving particular company problems other …………………………………………………………………………………
Following the respondents’ opinions (tab.4), the most important way to emphasize key employees’ exceptional status, in their companies, is offering them individual and separately agreed remuneration. Additionally, their special position is also recognized by inviting them to top management team meetings as consultants or experts. Another important factor confirming their special position takes the form of extensive opportunities for participating in business trips to conferences, fairs, exhibitions held for their sector, etc. A group of key workers also has access to enterprises strategic knowledge. Table 5: What personal incentives – in your opinion – underlie sharing knowledge – acquired through years of experience – by the key workers with their younger and less experienced colleagues in an enterprise?
Ordinal number
Incentives
1. 2. 3.
the desire to receive additional remuneration (or a special bonus) offered by an enterprise hoping for promotion (higher periodical assessment) for assistance offered to other colleagues emphasizing the position of a master, an unquestionable authority in a particular domain
4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.
gaining recognition, admiration for the obtained professional knowledge imposing an individual point of view, ideas, assessments, observations on other colleagues concerns related to poorer quality of tasks carried out by less experienced colleagues striving for obtaining planned results by the team (entire enterprise) focus on higher efficiency of the results planned by the team (entire enterprise) the willingness to pay back the resources spent by an enterprise on upgrading individual qualifications the sense of strong emotional bond with an enterprise, pride and loyalty towards an organization the sense of obligation and a well‐conceived work ethics in a particular profession (at a given position) the sense of responsibility for the development of less experienced, younger colleagues preparing one’s successors at a given position (for a particular function) the desire to pass over one’s professional output to others and preserve it in time
It turns out, as the respondents’ answers illustrate (tab. 5), that the key employees are assigned certain motivating factors confirming great responsibility of this group for the result of company performance. It is also very important for them to win or maintain both recognition and respect of their company colleagues.
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Mieczysław Morawski Table 6: Please rank, in the scale from 1 – the most important to 12 – the least important, which listed below factors, in your opinion, have impact on knowledge sharing in a relation: key workers – the remaining company employees
Ranking 3. 7. 6. 10. 11. 12. 4. 5. 1. 2. 8. 9.
Factors human capital management strategy organizational structure organizational culture data communication tools office equipment offices arrangement and topography management methods knowledge sharing methods key worker’s professional competencies key worker’s interpersonal competencies key workers’ motivating competencies of the knowledge sharing process addressee
Regarding the question concerning the most important factors influencing knowledge sharing efficiency between key employees and the remaining company personnel (tab.6), the majority of respondents pointed to factors related to professional, substantive and interpersonal competencies presented by key employees. The other responses in this ranking were: human resources management strategy, management methods and organizational culture. What is surprising, in the answers provided, is the low relevance assigned to the significance of key employees’ motivation. Probably the respondents are of the opinion that key employees present strong inner sense of responsibility for the results of company performance which, in consequence, initiates attitudes and behaviours oriented towards cooperation and providing support for less qualified colleagues. Such conclusion underlies the types of response choices made by respondents to the previous question. It also offers an idea of a certain track of thought followed by the respondents if, at this point, answers to question 3 are reminded. Probably an assumption is made that trustworthy, competent and having many years of experience employees present such strong sense of responsibility, accompanied by strong inner motivation underlying their actions strengthened by company objectives realization, that sharing knowledge with others is perceived by them as a natural component of professional activity. Having assumed such way of respondents’ thinking it is well understood that marginal significance is assigned to the organizational structure or ICT tools in the knowledge sharing process which involves key employees. In general, the respondents indicate (tab.7) that determinants encouraging for knowledge sharing, in their enterprise, represent operational factors related to more extensive independence in carrying out tasks, flexible work time or unlimited access to information and supervisors, also these at the top management positions. The sense of enjoying professional stability is also highly valued by key employees, i.e.: permanent work agreement, high remuneration. On the other hand, the need for applying adequate financial solutions is often mentioned. The respondents probably assume that it could function as an additional factor to strengthen motivation for knowledge sharing. Based on information included in the table, which synthetically presents responses provided by key employees, a conclusion can be drawn that they do not expect any extraordinary or outstanding incentives for knowledge sharing. Additionally, they value the sense of stability more and expect mainly organizational support from enterprise management, i.e.: opportunities for performing different functions, managing different teams, participation in formal and informal meetings. Therefore, it is necessary to offer key employees higher autonomy in performing their duties, in making choices about forms of activity and types of carried out projects.
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Mieczysław Morawski Table 7: What kind of motivation incentives are applied in your enterprise encouraging key workers to share their knowledge with colleagues and what kind of incentives, in your opinion, should be applied?
Ordinal number Motivation incentives
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25.
higher percentage of base salary special permanent financial remuneration for participating in the process of co‐workers education high special bonuses sharing awards received by co‐workers with whom knowledge was shared sharing awards received by a team made up of employees with whom knowledge was shared commission for higher knowledge productivity (e.g. faster knowledge transfer to those who need it) appointing for work in the group of company experts with higher remuneration to follow shares ownership in company equity additional benefits and perks /privileges, e.g. extra equipment at workplace/ detailed plan of professional development attractive trainings participation in conferences external internships promotion to a higher managerial position possibility of a project team leadership choice of a new or additional function, organizational role, e.g. of a mentor higher independence in carrying out the so far performed tasks employment contract for an indefinite period flexible work time unlimited access to company database unlimited access to supervisors including top company management influence on some personnel decisions, e.g. regarding new staff employment at vacant positions, types of trainings for workers influence on the decision regarding the choice of a particular successor influence on the talent management programme other …………….
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encouraging for knowledge sharing SHOULD BE APPLIED
encouraging for knowledge sharing APPLIED
Mieczysław Morawski Table 8: The summary of responses provided by key employees during interviews: Question Are you aware of being the key employee?
Core idea of the response high awareness of one’s own strong points apparent, subdued self‐ confidence and confidence in one’s own beliefs
What were the core milestones in your career in the enterprise?
advantages for the company from the implemented projects as an idea provider and their executor – team leader managing a new department obtaining new knowledge and skills which the other employees do not present team work taking care of a new employee in his/her induction period playing the role of an internal coach explaining current issues instruction at workplace providing consultancy in new situations
In what situations does knowledge sharing process occur most frequently?
What kinds of factors enhance knowledge sharing?
the sense of security and stability in an enterprise
Are there any special or additional motivating incentives necessary for the process of knowledge sharing to occur?
work organization enhancing the exchange of knowledge frequent formal and informal meetings individual participation in different project
Comment The questioned employees are fully aware of being key employees, but they do not manifest it in their behaviour or show arrogance and overconfidence. The questioned employees frequently come forward with initiatives for work organization processes or the other employees’ competencies improvement.
The questioned employees were performing different roles and functions in an enterprise, both managerial and executive. They were in the past or currently are functioning as management board proxies, managers of departments, leaders of temporary teams, auditors, recognized specialists. The questioned employs have usually been employed in their company for a long time, longer than 7‐8 years. The questioned employees usually do not expect any special motivating financial means for sharing their knowledge with other colleagues.
4. Discussion Knowledge represents a dynamic rather than static category. If it is left to itself without any imposed discipline it, just like water or air, spreads freely in a given space, both inside and outside an enterprise. If it is assumed that knowledge results from cognitive processes initiated and modelled by observing environment, experimenting, acquiring information, obtaining skills, participation in the actually occurring processes – then the majority of these activities require interpersonal contacts. In the course of social interactions with another person or a group of people an exchange of thoughts takes place, as well as the confrontation of opinions, enriching one’s own professional position, creative development of ideas, new proposals and suggestions are offered, which often happens as the result of a different outlook taken at a given problem by a person after he/she has acquired new knowledge. The significance of social contacts network keeps growing in the circumstances in which intense, frequent, indirect, informal communication between specialists is important owing to unusual, complex, multi‐layered problems, unique projects, radical changes they experience in their professional operations. Mutual consultations, discussions, disputes, exchange of information, knowledge sharing turn out indispensable. The importance of social contacts between employees is particularly evident in the tourism industry. These results were obtained in earlier studies (Morawski 2012). Answering the question: “What kind of motivation incentives are applied in your enterprise encouraging key workers to share their knowledge with colleagues and what kind of incentives, in your opinion, should be applied?” respondents in the tourism industry generally responded as follows: special permanent financial remuneration for participating in the process of co‐workers education, sharing awards received by co‐workers with whom knowledge was shared, sharing awards received by a team made up of employees with whom knowledge was shared.
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Mieczysław Morawski Relations oriented nature of knowledge requires the occurrence of relations based approach towards personnel management in an organization. Therefore a new attitude towards staff management in an organization has to be identified with focusing on mutual relations between employees, understood in their broad context. These relations take the form of different types and levels of involvement, loyalty, trust, integration. It is necessary to have an overall idea of knowledge oriented enterprise management. It is required to establish strong correlation between company values ingrained in its organizational culture, its vision and strategy, its business model and personnel policy, especially regarding these key employees attracting and retaining who create its competitive advantage. It is indispensable to combine the concept and the implementation of personnel functions with the selected components (processes, tools) for knowledge management. Both human resources management and knowledge management have to be directly related to an overall business management model in a particular company. The presented set of guidelines if implemented in an enterprise allows for the establishment of key employees environment which enhances knowledge sharing. The four basic areas and the distinguished detailed factors it covers are based on the Author’s research and his analytical considerations.
DIRECT MOTIVATION • Bonus for time spent on providing consultations and opinions • Participation in awards obtained by employees and teams with whom knowledge was shared • Share in profits earned as the result of knowledge applied
ORGANIZATIONAL CULTURE • • • • •
PROFESSIONAL DEVELOPMENT • Long-term employment in the company • Multistage career path • Intense activity at work place • Searching for challenges • Recognizing problems and offering their solutions • Opportunities for one’s own projects implementation
Key employee needs
Earning recognition and respect The cult of competencies and efficiency Responsibility for others Assistance and support Partnership management styles
• • • • • •
WORK ORGANIZATION Flexible work time Individual nature of tasks Work in different teams Work autonomy Changeability of roles played in an organization Project management
PERSONNEL STRATEGY
ENTERPRISE BUSINESS STRATEGY
Source: own study Figure 1: The key employees’ work environment
5. Conclusions The problems of knowledge sharing by key employees, their inner incentives, as well as the \\underlying motivating factors created by enterprise management, require an ongoing anexploration. The problem, therefore, has to be approached in a complex manner. It is absolutely obvious that in cannot be studied as a unilateral case by pointing to the decisive importance of just one group of factors. In the Author’s opinion it is indispensable to create the concept of an adequate and versatile work environment for this particular group of employees. In the discussed model oriented perspective financial incentives are not at all of primary significance. They constitute just one of many components. A key employee expects organizational comfort, which provides him/her with extensive independence and opportunities for professional skills advancement. A
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Mieczysław Morawski key employee also values organizational culture in which competencies and knowledge are respected and have impact on the entire company personnel attitudes and behaviour.
References Bakowska‐Morawska U.(2013), Commercialization Smelter "X" ‐ Key Aspects of Change, 22nd International Conference on Metallurgy and Materials, Conferences Proceedings METAL 2013 Davenport T. (2000) Human Capital: What it is and why people invest in it. San Francisco: Jossey‐Bass. Martin M., Whiting F., Jackson T. (2010) Human Resource Practice, Fifth ed. London : Chartered Institute of Personnel and Development Morawski M. (2012), The Conditions, Motives and Methods of Sharing Knowledge with the participation of key personnel in th enterprises, Proceedings of the 13 European Conference on Knowledge Management, Universidad Politecnica de Cartagena, Spain 6‐7 September 2012, Edited by J.G. Cegarra, Cartagena, Spain, pp. 802‐808. Morawski M. (2011) Conditions of sharing knowledge in companies, Contemporary Management Challenges in the Transition Period. The Perspectives of Poland and Spain, Scentific Editors P. Buła, H.Łyszczarz, A.M. Ramirez, J. Teczke, Wyd. Cracow University of Economics, Cracow ‐ Granada, pp. 367‐380 Soliman F.,Spooner K. (2000) "Strategies for implementing knowledge management: role of human resources management", Journal of Knowledge Management, Vol. 4 Iss: 4, pp.337 – 345. The Future of the HR Profession (2002) Eight Leading Consulting Firms Share Their Visions for the Future of Human Resources. Society for Human Resource Management, p.2.
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Santarém, Portugal
The 15th European Conference on Knowledge Management Escola Superior de Gestão e Tecnologia, Instituto Politécnico de Santarém, Portugal 4-5 September 2014
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