Pproceedings of the 8th European Conference on Innovation and Entrepreneurship -ECIE 2013-volume 1 by ACPIL

Proceedings of the 8th European Conference on Innovation and Entrepreneurship Hogeschool-Universiteit Brussel Brussels Belgium Volume One 19-20 September 2013

Edited Edi d by b Dr Peter Teirlinck and Stijn Kelchtermans Hogeschool-Universiteit Brussel, Belgium and Filip de Beule Th Thomas More M Antwerpen, A t Antwerp A t Belgium A conference managed by ACPI, UK www.academic-conferences.org

The Proceedings of the 8th European Conference on Innovation and Entrepreneurship ECIE 2013 Volume One Hogeschool‐Universiteit Brussel (HUBrussel) Brussels, Belgium 19‐20 September 2013

Edited by Dr Peter Teirlinck and Stijn Kelchtermans Hogeschool‐Universiteit Brussel, Belgium and Filip de Beule Thomas More Antwerpen, Antwerp Belgium

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 yearâ&#x20AC;&#x2122;s proceedings can be purchased from http://academicbookshop.com E-Book ISBN: 978-1-909507-61-6 E-Book ISSN: 2049-1069 Book version ISBN: 978-1-909507-59-3 Book Version ISSN: 2049-1050 CD Version ISBN: 978-1-909507-62-3 CD Version ISSN: 2049-1077 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

Volume One Examining Determinants of Innovation Culture in Egyptian Organizations

Hadia Abdel Aziz and Sandra Marcos

Rethinking Employee Contribution: A Framework for Promoting Employee-Driven Innovation

Tuomo Alasoini

Environmental Innovation and Financial Performance: The Moderating Effect of Motives and Firm Size

Petra Andries and Ute Stephan

Organizational Innovation as Leverage for Open Innovation Practices: A Business Model Perspective

Paula Anzola Román, Cristina Bayona-Sáez and Teresa García-Marco

Spin-Up: A Comprehensive Program Aimed to Accelerate University Spin-Off Growth

Manuel Au-Yong Oliveira, João José Pinto Ferreira, Qing Ye and Marina van Geenhuizen

Entrepreneurship Versus Self-Employment in the Context of Social Changes in Romania: Individual and Contextual Factors

Alina Badulescu and Roxana Hatos

Environmental Obstacles and Support Factors of Social Entrepreneurship

Alina Badulescu, Sebastian Sipos-Gug and Adriana Borza

Narrative Analysis of a Highly Creative Entrepreneur Pursuant to Scientific Evaluation Criteria

Zuhal Baltas and Handan Odaman

A Comparative Study of the Entrepreneurial Potential of Economics Students of the University of Oradea, Romania and Adnan Menderes University, Turkey

Olimpia Ban, Esin Sayin, Dorin Coita and Ali Eleren

Key Factors Affecting Strategy-Minded Decision Makers in Their Innovations Choices

Fernando Barbosa and Fernando Romero

Business Strategies in Contexts of High Uncertainty: A Case Study on the Innovation and Internationalization Processes of a Technological Portuguese SME

Fernando Barbosa and Fernando Romero

Co-Ownership of Intellectual Property: Exploring the Value Appropriation and Value Creation Implications of Co-Patenting With Different Partners

Rene Belderbos, Bruno Cassiman, Dries Faems, Bart Leten and Bart Van Looy

Organizational Innovations – Constituents and Determinants Within Underdeveloped and Immature Markets

Muamer Bezdroband Aziz Šunje

105

Paper Title

Author(s)

Page No.

How Organizational Creativity Influence Firm’s Profitability: The Moderating Role of Corporate Entrepreneurship

Katarzyna Bratnicka, Bartłomiej Gabryś and Mariusz Bratnicki

118

Innovation and Entrepreneurship Assessment Initiatives: A Critical View

Cagri Bulut, Eda Evla Mutlu and Murat Nazli

126

Innovation Through Offset Agreements: An Empirical Study in the Brazilian Defence Industry

Alex Carlos and Regina Leite

136

Individual and Mandatory Innovation in Automotive Industry: A Case Study

Cristian Chiru, Versavia Ancusa, Razvan Bogdan and Bogdan Suta

145

Costs as a Decision-Making Criteria in the Planning of Innovation Processes

Piotr Chwastyk

154

Platform Strategies for Open Government Innovation

Brian Cleland, Brendan Galbraith, Barry Quinn and Paul Humphreys

162

Small and Medium Enterprises (SME) and Competitiveness: An Empirical Study

Teresa Costa and Luísa Carvalho

173

Innovation in Energy Sector – a Comparative Study in Brazil and Portugal

Teresa Costa, Luísa Carvalho, Geciane Porto and Priscila Rezende da Costa

180

Innovation and Entrepreneurship by Academic Spin-Offs: The UNITI Business Case

Renata Paola Dameri, Federico Fontana and Roberto Garelli

189

Students’ Gains in Entrepreneurial Self-Efficacy: A Comparison of ‘Learning-By-Doing’ Versus Lecture-Based Courses

Luc De Grez and Dirk Van Lindt

198

Rewards Work? Researching the Relation Between Monetary Reward and Employee Innovativeness

Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem

Significant Competitiveness Factors of Companies in the Czech Part of the Euroregion Neisse-NisaNysa

Jaroslava Dědková and Denisa Skrbková

212

Towards Sustainable Business Models: Necessity, Opportunity or Challenge?

Nikolay Dentchev and Jan Jonker

221

Standardization- the Source of Innovation and Sustainable Development of Companies in Romania

Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka

228

Employee-Driven Innovation in a Higher Educational Institution: Organisational and Cultural Influences

Smile Dzisi, Joshua Ofori-Amanfo and Benjamin Kwofie

235

Firm Capabilities, Complementarities and Innovation in the Latin American Coffee Sector

Luis Figueroa

243

Intellectual Capital Between Innovation and Innovative Adaptation- Opportunities to Obtain Performance

Nicoleta Valentina Florea and Mihaela Badea

252

SMEs’ Internationalisation Through Strategic Alliances: A Qualitative Study

Mário Franco, Heiko Haase and Sandra Figueiredo

261

204

Paper Title

Author(s)

Page No.

The Business Model of the Entrepreneurial University

Olaf Gaus and Matthias Raith

268

National Innovation System and Public Innovation Policy: Theory and Practice Problems

Oleg Golichenko and Svetlana Samovoleva

278

Involving Students in Ideas Generation – a Bulgarian Case

Elissaveta Gourova, Tzvetelina Teneva and Tsvetoslava Kyoseva

287

Emancipatory Māori Entrepreneurship in Screen Production: Theory and Application

Ella Henry

296

Research on the Trust Governance in the Venture Capital Syndication

Heyin Hou and Weixing Qu

303

Employee-Driven Innovation (EDI): Toward an Extended Concept of Innovation

Steen Høyrup

313

Innovative Approach in Managing the Process of Manufacturing Removable Partial Dentures

Danut Iorga, Alexandru Ghiban and Cezar Scarlat

322

Entrepreneurial behavior and interactivity of Sri Lankan farmer groups

Chandana Jayawardena and Madushi Abeyrathne

333

Business Modeling for Sustainability: Identifying Five Modeling Principles and Demonstrating Their Role and Function in an Explorative Case Study

Jan Jonker and Nikolay Dentchev

340

Innovation Process Planning: Aim, Scope and Constraints

Magdalena Jurczyk – Bunkowska

347

Higher-Order Learning in Entrepreneurship: A key-Issue for Lifelong Learning and Career Counselling?

Alexandros Kakouris, , Niki Perdikaki and Panagiotis Georgiadis

355

Innovation Capital as a Driver of Eco-Innovations: A Case of European Enterprises

Tomasz Kijek

363

Employee Driven Innovation: Bridging Open and Close Innovation Management Practices

Eric Michael Laviolette, Renaud RedienCollot and Ann-Charlotte Teglborg

370

Social Capital, Knowledge Strategy, and new Venture Performance: Evidence From Graduate Entrepreneurial Ventures in China

Jun Li and Weihe Gao

378

For Strategic Environmental Sustainability not to be Lost in Translation(s) Anymore

Sophie Liénart and Annick Castiaux

384

Social Responsibility Like aim of Innovation Activity in Information and Communication Industry: The Spanish Case

María Jesús Luengo, Teresa Areitio and María Obeso

392

State Parenting Entrepreneurship - the Process of Seizing Opportunities – a Case of a Chinese Entrepreneur

Sabrina Luthfa Karim and Hanjun Huang

401

The Impact of the Economic Downturn on Innovative Performance in Poland

Anna Matras-Bolibok

409

iii

Paper Title

Author(s)

Page No.

Céline Maximin-Tieu

417

Failing to Succeed: A Network Theoretic Comparison of Global Accelerators

Patrick McHugh, Chris Whipple and Xiaoyang Yang

425

Sustainability Among Tourism and Hospitality Industry’s Ventures: From Awareness to Specific Practices

Ioana Mester and Daniel Badulescu

434

Innovation, Design and Competitiveness: Results From a Portuguese Online Questionnaire

José Monteiro-Barata

442

Using Strategic Alliances to Facilitate Community Based new Venture Creation

Peter Moroz, Bob Kayseas and Robert Anderson

454

Senior- & Juniorpreneurship: An Intergenerational Approach in Engineering and Entrepreneurship for Value Creation

Bernd Neutschel, Olaf Gaus, Matthias Raith and Sándor Vajna

463

Cooperation Activities for Innovation: An Empirical Analysis Applied to Iberian Countries

Sandra Nunes, Teresa Costa and Luísa Carvalho

471

Organizational Innovation – can job Enrichment Enhance Employee?

Morena Paulišić, Tea Golja and Barbara Unković

482

The Institutions of Social Entrepreneurship in the USA, UK and Germany Within a Context of Market-Based vs. Bank-Based Systems

Ruslan Pavlov

490

Collaborative Strategies for Innovation CapacityBuilding: A Study of MIT’s International Partnerships

Sebastian Pfotenhauer, Dan Roos, and Dava Newman

498

The Internationalization Process of German HighTech SMEs: An Empirical Analysis

Andreas Pinkwart and Dorian Proksch

507

Entrepreneurship - Successes and Failures of Start-Up SMEs on Regional and International Markets

Aneta Ptak-ChmielewskaI

515

Entrepreneurship Education: A View Across Outcome Expectations and Antecedents in Students of Higher Education

Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati

525

Institutional Support Program for Entrepreneurship: The Experience of the University of Minho

Cristina Rodrigues and Filipa Vieira

533

Factors Influencing Innovation and Competitiveness – a Comparative Analysis of Selected Economies

Anna Sacio – Szymańska

543

Experiential Entrepreneurship Education in Canada – new Venture Creation While Earning a Masters Degree

Tarek Sadek and Rafik Loutfy

555

How to Conciliate Best Enemies? The Case of Competitive Chemical Industries in Ecofriendly Cultures Volume Two

Paper Title

Author(s)

Page No.

Knowledge Sharing, Innovation Networks, and Innovation Capability: The Case of Uruguayan Software Firms

Josune Sáenz and Andrea Pérez-Bouvier

564

IS Resilience in SMEs in Post-Earthquake Christchurch

Amitrajit Sarkar and Stephen Wingreen

573

The Institutional Support as a Factor for Technology Internationalization From Developing Countries

Viktor Stojmanovski, Velimir Stojkovski, Mijalce Santa and Beti Kostadinovska Dimitrovska

581

How SMEs Mitigate Risks When Embarking in Open Innovation Projects

Adrian Dumitru Tanţău and Eliza Laura Paicu (Coraş)

588

How Planguage Measurement Metrics: Shapes System Quality

Man-Chie Tse and Ravinder Singh Kahlon

597

A Study of Customer Feedback and Employee Driven Innovation

Jiro Usugami

605

Space Technology Transfer: A Systematic Literature Review

Karen Venturini and Chiara Verbano

613

The Evolution of Resources in Research-Based Spinoffs: Learning from a Case Study

Chiara Verbano, Karen Venturini and Avi Wasser

623

Companies’ Innovativeness Influenced by Organizational Structures

Annika Vesterinen and Kalle Elfvengren

633

Structuring the Unstructured: Service Innovation in a UK Small Business Services Firm

Vessela Warren and Barry Davies

641

Student Entrepreneurial Intentions: Two Perspectives

Doan Winkel, Jeff Vanevenhoven, Mark James and Eric Liguori

649

Complex Technology Assessment as a Determinant for Marketing Activities in Innovation Commercialisation

Urszula Wnuk and Ludmiła Łopacińska

661

Disruptive Innovation in Public Service Sectors: Ambidexterity and the Role of Incumbents

Danielle Wood, Sebastian Pfotenhauer, Wiljeana Glover and Dava Newman

669

Entrepreneurial Attitudes and Entrepreneurship’s Potential in East Timor

Tomas Xavier, Filipa Vieira and Cristina Rodrigues

677

PHD Papers

687

Marketing Support of Innovative Projects

Gulnara Chernobaeva

689

Public and Private Sector Approaches to SMME Development in the Ethekwini Municipality

Anneline Chetty

698

Factors Influencing an Upscaling Process of Grassroots Innovations: Preliminary Evidence From India

Ann De Keersmaecker, Prabhu Kandachar, Vikram Parmar, Koen Vandenbempt and Chris Baelus

705

Collective Entrepreneurship, a Solution to Conflicting Institutional Logics in the Entrepreneurship Process?

Frédéric Dufays

715

Innovations, Standards and Quality Management Systems: Analysis of Interrelation

Raimonda Liepiņa, Inga Lapiņa, Jolanta Janauska and Jānis Mazais

723

Paper Title

Author(s)

Page No.

Achieving Performance of Organization by Developing a Model of Innovation Management

Andreea Maier, Marieta Olaru, Dorin Maier and Mihai Marinescu

731

Integrating Concepts of Creativity and Innovation - a key to Business Excellence

Dorin Maier, Marieta Olaru and Andreea Maier

739

Entrepreneurs’ Access to Public Finance as a Gendered Structure Case Finland

Petra Merenheimo

747

Firms’ Response to Peer Behaviour

Daniel Neicu, Stijn Kelchtermans and Peter Teirlinck

755

Firm Structure and Problems of Governance in the Italian SMEs

Adalberto Rangone

762

Understanding Entrepreneurial Performance in a Networked Social Environment

Carla Riverola and Francesc Miralles

773

Performance Measurement and Management in SMEs

Ted Sarmiento and David Devins

782

Effects of Technological Innovation on Knowledge Acquisition Inside the Organization: A Case Study

Dorotéa Silva, Fernando Romero and Filipa Vieira

791

Measuring the Validity of a Text Based Indicator for Exploration and Exploitation Activities

Nazlihan Ugur

797

Non Academic Papers

808

Incubators as Enablers for Academic Entrepreneurship

Frank Gielen, Sven De Cleyn and Jan Coppens

809

Applying the Disruptive Israeli Innovation Model to Re-Inventing Corporate Education

Janet Lea Sernack

818

Work in Progress Papers

825

Entrepreneurship as Future Career for PostGraduate Business Students: A Realistic Option?

Daniel Badulescu and Mariana Vancea

827

How Strategic and Social Entrepreneurship can Create Sustainable Economic and Social Value: A Proposed Model for the Cooperative Sector

Vítor Figueiredo and Mário Franco

831

Exploring the Social Dimension of Entrepreneurial Resourcefulness: A Case Study Among Family Business Entrepreneurs

Bart Henssen

835

Dragging One's Feet Along the way: How (In)Congruent Motives Influence Entrepreneurial Performance

Julie Hermans

838

Finding New Competitive Intelligence: Using Structured and Unstructured Data

Ravinder Singh Kahlon and Man-Chie Tse

842

Implications of an Emerging Model for Product Ideation, Design and Development Using Bridging Enterprises and Open Communities of Practice

Karla Phlypo

847

Internationalisation by SMEs as a Strategy to Cope With Weakness in the Domestic Market : The Case of Spain, Ireland and France

Angela Poulakidas, Robert Hisrich and Claudine Kearney

851

Preface These proceedings represent the work of contributors to the 8th European Conference on Entrepreneurship and Innovation (ECIE 2013), hosted this year by Hogeschool-Universiteit Brussel (HUBrussel) in Belgium.The Conference Chair is Dr Peter Teirlinck from HUBrussel(KU Leuven) and the Programme Co-Chairs are Dr Stijn Kelchtermans from HUBrussel(KU Leuven) and Dr Filip de Beule from Thomas More Antwerpen (KU Leuven). Keynote presentations are given by Katrien Mondt, Director-General at Innoviris, Brussels Institute for Science and Innovation on the topic “Regional Innovation Policy: the case of the Brussels Capital Region”. Cornelis J.J. Eldering from the European Space Agency, Noordwijk, The Netherlands will address the topic “Technology Transfer at the European Space Agency” and Prof. Dr. Ir. Koenraad Debackere, KU Leuven, Belgium will talk about “Smart entrepreneurship in the Triple Helix”. ECIE continues to develop and evolve. Now in its 7th year the key aim remains the opportunity for participants to share ideas and meet the people who hold them. The scope of papers will ensure an interesting two days. The subjects covered illustrate the wide range of topics that fall into this important and growing area of research. With an initial submission of 244 abstracts, after the double blind, peer review process there are 79 academic papers, 14 PhD papers, 2 non academic papers and 7 work-in-progress papers published in these Conference Proceedings. These papers represent research from Belgium, Bosnia and Herzegovina, Bulgaria, Canada, Croatia, Czech Republic, Denmark, Deutschland, Egypt, Finland, France, Germany, Ghana, Greece, Israel, Italy, Japan, Köln, Latvia, Macedonia, México, Morocco, New Zealand, People's Republic of China, Poland, Portugal, Republic of San Marino, Romania, Russia, South Africa, Spain, Sweden, Turkey, UK, and the USA. We hope that you enjoy reading these Proceedings. Stijn Kelchtermans and Filip de Beule Co-Programme Chairs September 2013

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Conference Executive Professor Peter Teirlinck Hogeschool-Universiteit Brussel, Belgium Professor Stijn Kelchtermans Hogeschool-Universiteit Brussel, Belgium Bart Leten Catholic University of Leuven, Belgium Mini Track Chairs Doan Winkel Illinois State University, USA Dr Alexandros Kakouris, University of Athens, Greece Dr Ella Henry Auckland University of Technology, New Zealand Dr Filip De Beule Lessius University College, Antwerp, Belgium Milan Todorovic Union Nikola Tesla University in Belgrade, Serbia Dr Yipeng Liu University of Kent, UK Dr Jun Li University of Essex, UK Prof Dr Alina Badulescu University of Oradea, Romania Dr Ann-Charlotte Teglborg Novancia, Business School Paris, France Dr Liang Guo Rouen Business School, France Dr Ke Rong Bournemouth University, UK Committee Members The 2013 conference programme committee consists of key people in the entrepreneurship and innovation community, both from the UK and overseas. The following people have confirmed their participation: Kamarulzaman Ab. Aziz (Multimedia University, Malaysia); Assoc.Prof.Dr. Zafer Acar (Okan University, Istanbul, Turkey); Dr. Bulent Acma (Anadolu University, Turkey); Dr Hassanali Aghajani (University of Mazandaran(UMZ), Iran, ); Jaione Aguirre (Tekniker technological centre, Spain,); Prof. Ruth Alas(Estonian Business School, Estonia); Dr Laurice Alexandre Leclaire (Sorbonne Paris Cité University, France); Dr. Saleh Al-Jufout (Tafila Technical University, Jordan); Prof. Khedidja Allia (University of Science and Technology, Algiers, Algeria); Dr. Hanadi AlMubaraki (Kuwait University, Kuwait,); Dr. Rumen Andreev (Bulgarian Academy of Sciences, Sofia, Bulgaria); Dr. Zacharoula Andreopoulou (Aristotle University of Thessaloniki, Greece); Dr Christos Apostolakis (Bournemouth University, UK); Erik Arntsen (University of Agder, Kristiansand, Norway); Omid Askarzadeh (Polad Saab Shargh, Tehran, Iran); Samantha Aspinall (University of Leeds, UK); Dr. Claire Auplat (Imperial College Business School, London, UK); Prof. Miroslav Baca(University of Zagreb, Varaždin, Croatia); Prof Alina Badulescu (University of Oradea, Romania); Susan Bagwell (London Metropolitan University, UK);Prof.Dr. Mihai Berinde (University of Oradea, Faculty of Economic Sciences, Romania,); Prof. Cristin Bigan (Ecological University of Bucharest, Romania);Prof. Dr. Ferrucio Bilich (University of Aveiro, Portugal); Dr. Adam Jay Bock (University of Edinburgh, United Kingdom,); Prof. Dr. Dietmar Boenke(Reutlingen University, Germany); Ana Maria Bojica (University of Granada, Spain); Prof Raymond Boyle (University of Glasgow, UK); Tina Bratkovic(University of Primorska, Slovenia); Dr. Alexander Brem (University of Erlangen-Nuremberg, , Germany); Fraser Bruce (University of Dundee, UK); Dr. Cagri Bulut (Yasar University, Izmir, Turkey); Dr Cagri Bulut (Yasar University, Turkey); Jeffrey Burke (National Pollution Prevention Roundtable, Washington DC, USA); Kevin Burt (University of Lincoln, UK); Prof Luisa Carvalho (Institute Polytechnic of Setubal, Portugal, Portugal); Dr. Toly Chen (Feng Chia University, Taichung, Taiwan); Ph.D. Kuo-Sheng Cheng (National Cheng Kung University/Institute of Biomedical Engineering, Taiwan); Prof Chuang-Chun Chiou (Dayeh University, Changhua, Taiwan); Dr. Nick Clifton (Cardiff Metropolitan University, UK); Prof. Costas N. Costa (Cyprus University of Technology, Lemesos, Cyprus); Prof. Teresa Costa (Instituto Polit cino de Set bal | Escola Superior de Ci ncias Empresariais, Portugal); Dr. Fengzhi Dai (Tianjin University of Science and Technology, , China); Dr Leo-Paul Dana (University of Canterbury, Christchurch, New Zealand); Dr Filip De Beule (Thomas More Antwerpen, Antwerp,, Belgium); Prof. Rogerio Atem De Carvalho (Instituto Federal Fluminense, Campos, Brazil); Sven H. de Cleyn (University of Antwerp, Antwerp, , Belgium); Dr. Luc De Grez (Hogeschool Universiteit Brussel, Belgium); Prof. Armando Carlos de Pina Filho (Federal University of Rio de Janeiro , Brazil); Carine Desleee (University of Lille 2- IMMD,France); Maria Chiara Demartini (University of Pavia, Italy); Dr Izabela Dembińska (University of Szczecin, Poland); Charles Despres (Conservatoire des Arts et Metiers, Paris, France); Prof. Dr. Anca Dodescu (University of Oradea, Romania); Prof. Dr. Michael Doellinger (University Hospital Erlangen, Germany); Prof. Salah Doma (Sinai University, El-Arish, Egypt); Dr. Nelson Duarte (Porto Politechnic - School of Management and Technology, Portugal,); Dr Smile Dzisi (Koforidua Polytechnic, Ghana); Prof Vasco Eiriz (University of

viii

Minho, , Portugal); Dr Hatem El-Gohary (Birmingham City University, UK,); Dr Scott Erickson (Ithaca College, USA); Prof. Engin Deniz Eris (Dokuz Eylul University, Turkey); Dr. Mahtab Farshchi (London South Bank University, UK); Professor Luis Fé De Pinho (Universidade Lusíada de Lisboa, Portugal,); Burca Felekoglu(University of Cambridge, Turkey); Professor Paula Odete Fernandes (Polytechnic Institute of Bragança, Portugal,); Prof. João Ferreira (University of Beira Interior, Covilhã, Portugal); Prof Maria Joao Ferreira (Universidade Portucalense, Porto, Portugal); Dr Heather Fulford (Aberdeen Business School, UK); Dr Erdei Gábor (University of Debrecen, Hungary); Brendan Galbraith (University of Ulster, UK); Dr. Laura Galloway (Heriott-Watt University, Edinburgh, UK);Dr Cephas Gbande (Nasarawa State University, Nigeria,); Prof Panagiotis Georgiadis (University of Athens, Greece); Prof. Alan Gillies (Hope Street Centre, UK); Ass. Prof. Dr. Andriana Giurgiu (University of Oradea, Romania); Dr Andrew Goh (University of South Australia, Australia); Dr Sayed Mahdi Golestan Hashemi (Iranian Research Center for Creatology, TRIZ & Innovation Management, Iran); Prof Oleg Golichenko (Central Economics and Mathematics Institute of Russian Academy of Science, Russia,); Dr. Mario Gomez Aguirre (Universidad Michoacana de San Nicolas de Hidalgo, Mexico,);Dr. Elissaveta Gourova (Sofia University "St. Kliment Ohridski", Bulgaria,); Dr Izold Guihur (Université de Moncton, Canada); Dr Ebru Gunlu (Dokuz Eylul University Faculty of Business, Turkey); Dr Liang Guo (Rouen Business School, Mont Saint Aignan, France); Prof Jukka Hallikas (Lappeenranta University of Technology, Finland); Kaled Hameide (Montclair State university in New Jersey, USA); Prof Wafa Hammedi (University of Namur (FUNDP), Belgium); Dr Saskia Harkema (The Hague University of Applied Sciences, The Netherlands); Dr Jennifer Harrison (Southern Cross University, Australia,); Takashi Hirao(Tokyo University of Science, Suwa, Japan); John Howard (Public Health and Clinical Sciences, UK); Dr Amy Hsiao (Memorial University of Newfoundland, St John’s, Canada); Dr. Dil Hussain (Aalborg University, Denmark); Dr Harri Jalonen (Turku University of Applied Sciences, Finland,); Paul Jones(University of Plymouth, UK); Dr Magdalena Jurczyk-Bunkowska (Opole University of Technology, Poland); Dr Alexandros Kakouris (University of Athens, Greece); Dr. Yusniza Kamarulzaman (University of Malaya, Kuala Lumpur, Malaysia); Dr Mira Kartiwi (International Islamic University Malaysia, Malaysia);Prof stijn Kelchtermans (Hogeschool-Universiteit Brussel, Belgium); Professor Panayiotis Ketikidis (CITY College - International Faculty of the University of Sheffield, Greece); Dr Marko Kolakovic (Faculty of Economics & Business, Croatia); Sam Kongwa (Walter Sisulu University, Mthatha, South Africa); Prof Kothandaraman Kumar (Indian Institute of Management Bangalore, India); Dr Stefan Lagrosen (University West, Sweden); Prof Brent Lane (Kenan-Flager Business School, University of North Carolina, USA); DR Jonathan Lean (University of Plymouth Business School, UK); Kiefer Lee (Sheffield Hallam University, UK); Prof. Dr. Joao Leitao (University of Beira Interior, Portugal); Dr. Jun Li (University of Essex, UK); Yipeng Liu (University of Mannheim, Germany); Prof Ilidio Lopes (Polythenic Institute of Santarém, Portugal); Dr Angeline Low (University of Technology Sydney, Mosman, Australia); Prof Sam Lubbe (University of South Africa, South Africa); Dr Fernando Lucas (Polytechnic Institute of Santarém, Portugal); Phd María Jesús Luengo(University of Basque Country, Spain); Dr. Randa Mahasneh (The Hashemite University, Jordan); Anneli Manninen (Laurea University of Applied Sciencies, Finland,); Dr Maria Markatou (Technological Education Institute of Larissa, Greece,); Prof Carla Marques (University of Trás-osMontes Alto Douro (UTAD), Portugal,); Dr. Florinda Matos (ICAA - Intellectual Capital Association Accreditation, Portugal,); Philip McClenaghan (Augsburg University, Germany); Prof.Luis Mendes (Beira Interior University, Portugal,); Zoran Mitrovic (University of Western Cape, South Africa); Asst. Prof. José Monteiro-Barata (ISEG, UTL, Lisbon, Portugal); Isabel Mota (Universidade do Porto, Porto. , Portugal); Maurice Mulvenna (University of Ulster, Newtownabbey, UK); Dr Jan Nab(Utrecht University, The Netherlands); Professor Desai Narasimhalu (Singapore Management University, Singapore); Dr. Artie Ng (School of International Business, Seneca College of Applied Arts and Technology, Toronto, Canada); The Hong Kong Polytechnic University, Hong Kong); Prof. Alcina Nunes(Polytechnic Institute of Bragança, Portugal,); Ass.Prof. Birgit Oberer (Kadir Has University, Turkey); Dr Maria Obeso (University of Cantabria, Spain); Alex Obuh (Delta State University, Nigeria); Professor Jukka Ojasalo (Laurea University of Applied Sciences, Espoo, Finland); Dr. Noreen O'Shea (Novancia Business school, France,); Professor Mohand-Said Oukil (King Fahd University of Petroleum and Minerals, Dhahran,, Saudi Arabia); Dr Shaun Pather (e-Innovation Academy, Cape Peninsula University of Technology, Cape Town, South Africa); Ruslan Pavlov (Central Economics and Mathematics Institute, Russia); Prof. Dr. Ige Pirnar (Yasar University, Turkey); Dr. Nataša Pomazalová (University of Defence, Brno, Czech Republic); DR. Malgorzata Porada-Rochon (University of Szczecin, Poland,); Dr Jean-Michel Quentier (ESC-Bretange, Brest, France); Sudhanshu Rai (Copenhagen Business School, Frederiksberg, Denmark); Dr Catarina Ramalho (University of Lisbon, Portugal); Prof.Dr Ganesan Ramaswamy (Asia-Pacific Institute of Management, New Delhi, India); Prof. Ricardo Rodrigues (NECE / University of Beira Interior, Portugal); Prof Cristina Rodrigues (University of Minho, Portugal); Dr Jose Carlos Rodriguez (Economic and Business Research Institute - Instituto de Investigaciones Economicas y Empresariales, Mexico,); Prof Cristhian Rodriguez Schneider (Catholic University of Temuco, Chili); Fernando Romero (University of Minho, Portugal); Jonas Rundquist (Halmsted University, Sweden);

Prof Paulo Rupino Cunha (University of Coimbra, Portugal); Dr. Balasundaram Sadhu Ramakrishnan (National Institute of Technology, Tiruchirappalli, India); Prof Rui Pimenta (ESTSP- Instituto Politécnico Porto, Portugal); Amitrajit Sarkar (Christchurch Polytechnic Institute of Technology, New Zealand); Dr Ousanee Sawagvudcharee (Centre for the Creation of Coherent Change and Knowledge, Liverpool John Moores University, UK); Simone Scagnelli (University of Turin, Torino, Italy); Professor Dr. Cezar Scarlat (University "Politehnica" of Bucharest, Romania); Mark Schatten (University of Zagreb,Varaždin, Croatia); Prof. Jeanne Schreurs (Hasselt University, Diepenbeek, Belgium); Dr. Maria Theresia Semmelrock-Picej (Klagenfurt University Biztec, Austria); Dr Nima Shahidi (Islamic Azad University- Noorabad mamasani Branch, Iran,); Dr. Armin Shams (University College Cork, National University of Ireland, Ireland); Dr. Namchul Shin (Pace University, New York, USA); Eric Shiu (The University of Birmingham, UK); Prof Sandra Silva(Faculdade de Economia da Universidade do Porto, Portugal,); Carmen Sirbu (Danubius University, Romania); Prof Aelita Skarzauskiene (Department of Social Informatics, Mykolas Romeris University , Lithuania); Dr Dorotea Slimani (Innventia AB, Sweden); Professor David Smith (Nottingham Trent University, UK); Cristina Sousa (ISCTE-IUL, Portugal); Dr André Spithoven (Belgian Science Policy Office, Belgium); Dr Ludmila Striukova (University College London, UK); Prof Peter Teirlinck (Hogeschool-Universiteit Brussel, Belgium); Dr Aurora Teixeira (Faculdade de Economia, Universidade do Porto, Portugal,); Dr Mangaleswaran Thampoe (Vauniya Campus of the University of Jaffna, Sri Lanka); Prof Milan Todorovic (University Union Nikola Tesla, Serbia); Ana Trevino (ITESM, Mexico); Dr Marios Trigkas (Technological Educational Institute of Larissa, Greece,); Prof. Dr. Lorraine Uhlaner (EDHEC Business School , France); Armando Luis Vieira (Universidade de Aveiro, Portugal); Prof Filipa Vieira (Universidade do Minho – DPS,Portugal); Dr Marcia Villasana (Tecnologico de Monterrey, Mexico);Dr Carla Vivas (Polytechnic Institute of Santarém, Portugal); Bernard Vollmar (Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany); Dr Catherine Wang (Royal Holloway University of London , UK); Dr Ismail Wekke (State College of Sorong, Indonesia, ); Dr Wioletta Wereda (Siedlce University of Natural Sciences and Humanities, Poland); Dr. Doan Winkel (Illinois State University, USA); Catherine Wright (Heriot Watt University, UK,); Fabiola Wust Zibetti (University of Sao Paulo, Brazil); Aziz Yahya (Universiti Teknikal Malaysia Melaka, Malaysia); Prof Shaker Zahra (University of Minnesota, USA); Dr Krzysztof Zieba (Gdansk University of Technology, Poland,); Dr Malgorzata Zieba(Gdansk University of Technology, Poland); Ph.D. Afonso Zinga (University of Coimbra, School of Economics, Portugal);

Biographies Conference Chair Dr Peter Teirlinck is Programme Director of the Bachelor and Master of Business Administration at Hogeschool-Universiteit Brussel. He is professor in Innovation Management. His main research interest areas include: Innovation in SMEs; Impact assessment of public funding for RTDI; The internationalisation of business research; Innovation and regional development. Peter Teirlinck also is policy adviser for the Belgian Science Policy Office and has been a detached national expert at the European Commission (DG Research). He obtained a Ph.D. in Applied Economics at the Universiteit Antwerpen in 2009 on the topic "Location of (FDI in) R&D and networking in innovation: analysis and policy making for the business enterprise sector"

Programme Co-Chairs Dr Stijn Kelchtermans (Ph.D. KULeuven, 2007) is Professor at Hogeschool-Universiteit Brussel (HUBrussel) and affiliated researcher at the department of Managerial Economics, Strategy & Innovation at the KULeuven. At HUBrussel he teaches Master-courses Innovation & Technology Management, R&D Management and Open Innovation. He is also Faculty Coordinator for the learning track Technology & Innovation in the Commercial Engineering program. His research interests include the economics of science and education (productivity analysis, demand estimation) as well as innovation, mainly focusing on industry-science links. His research has been published in international journals like the Journal of Applied Econometrics, Journal of Public Economics and CESIfo Economic Studies. Dr Filip de Beule is Assistant Professor of International Business at the Lessius University College, Antwerp, Belgium. He holds a BA and MA in Economics, and an MBA from the University of Antwerp Management School (UAMS). He got his PhD from the University of Antwerp on Belgian subsidiary management in the Peopleâ&#x20AC;&#x2122;s Republic of China: Strategic evolution, host country impact and policy. Prof. De Beule has lectured as Visiting Professor at the University of Antwerp and the Catholic University of Leuven. Dr. De Beule is board member of the European International Business Academy, where he serves as national representative for Belgium. He is an affiliate researcher at the LICOS Centre for Institutions and Economic Performance at the Catholic University of Leuven, where he focuses his research on multinational companies and emerging economies. Filip is also affiliated with Thomas More Antwerpen, Antwerp, Belgium.

Keynote Speakers Prof. Dr. Ir. Koenraad Debackere obtained his Ph.D. in Management with an ICMfellowship at the University of Gent after stays as an ICM-fellow and an ICRMOT research assistant at MIT Sloan School of Management. He was a Fulbright-Hays postdoctoral fellow at MIT in 1991-1992. Since 1992, he was for two years an assistant professor at Erasmus University Rotterdam before becoming an NFWO-Post-Doctoral Researcher in 1993. In 1995, he became professor at KU Leuven where he teaches Technology and Innovation Management. In 1999, he became the managing director of KU Leuven Research & Development, the technology transfer office of KU Leuven. He has been a promotor and recipient of various research grants by IWT (Flanders), FWO (Belgium & Flanders), DWTC (Belgium), EC (European Commission) and OECD in the areas of innovation management and policy. He is promotercoordinatorspokesperson of the Interuniversity Centre for R&D Monitoring of the Flemish government based at KU Leuven. He is also actively engaged in technology transfer activities as managing director of KU Leuven Research & Development and Chairman of the Gemma Frisius Fonds (the venture fund) of the KU Leuven. He is the cofounder and chairman of Leuven.Inc, the innovation network of Leuven high-tech entrepreneurs. He is a board member of IWT-Vlaanderen, the Flemish government agency that supports science and technology development in Flemish industry. Since 2005, he is the general manager of KU Leuven.

Cornelis (Niels) Eldering is Technology Transfer Officer at the Technology Transfer Programme Office of the European Space Agency (ESA). His main responsibility is the ESA Business Incubation Centre (ESA BIC) programme. The primary aim of an ESA BIC is to provide support to entrepreneurs who wish to exploit space-based solutions into nonspace markets. ESA has Business Incubation Centers in the UK, the Netherlands, Belgium, Germany, and Italy. Niels holds a Master of Science in Business Administration from the Rotterdam School of Management, is living in the Netherlands and working at ESTEC, the European Space Research and Technology Centre in Noordwijk. Passionately engaged in the challenging process from exploration to exploitation of science & technology, he regularly provides presentations and international guest lectures such as to the CEMS international Master of Management. The main mission of the Technology Transfer Programme is to strengthen the competitiveness of European Industry and to demonstrate the benefit of the European Space Programme to European citizens via the transferring of space technologies to non-space applications. The Technology Transfer Programme Office is responsible for defining the overall approach and strategy for the transfer of space technologies applications and systems, including the incubation of start up companies and a related venture fund. Katrien Mondt After an academic career in the field of medicines, Katrien has been involved in the development of research policy in the field of Education for the Flemish Community. Since January 2013 she is Director-General at Innoviris, the Brussels Institute for Science and Innovation

Mini Track Chairs Dr Alina Badulescu is Professor of Economics and Economics of Tourism at the University of Oradea, Romania. She graduated from the Bucharest University of Economics and has a PhD in Economics from the Babes-Bolyai University in Cluj-Napoca. She has written numerous journal articles and books and supervised PhD theses in Economics. Her research interests include economics of entrepreneurship, sustainable entrepreneurship, and tourism policy and development. Dr Liang Guo is assistant professor of management and BNP-KPMG Research chair of "business model and entrepreneurial innovation". He has published several articles in international journals including one in the Journal of Product & Innovation Management. His research focuses on business model, innovation, entrepreneurship and venture capital. Dr Ella Henry is a Māori woman, one of the indigenous people of New Zealand, and a Senior Lecturer in Māori Development and Māori Media in Te Ara Poutama, the Faculty of Māori Development at Auckland University of Technology. She has an academic background in Sociology, Māori Studies and Management Studies. Her Masters' thesis focused on Māori women in management. In 2012 Ella completed a PhD which explored Māori entrepreneurship in screen production. Alongside her academic career Ella has been actively involved as a practitioner and activist in the development of the Māori screen industry in New Zealand. Dr Alexandros Kakouris is a part time lecturer in entrepreneurship and innovation at the University of Athens. He holds a Ph.D. in Physics and a M.Sc. in Adult Education. He has been involved in entrepreneurship research since 2006, involved mainly with educational issues. His special interest concerns fostering of entrepreneurship and innovation to science graduates and support of youth entrepreneurship through counselling. He also specialises in nascent entrepreneurship and virtual business planning. Dr Jun Li is a senior lecturer in Entrepreneurship at University of Essex. His research interests on entrepreneurship and innovation in emerging economies. Dr. Li has published in leading entrepreneurship journals, e.g. Entrepreneurship and Regional Development, and edited several special issues on entrepreneurship in emerging economies. Dr. Li is co-editor of Journal of Chinese Entrepreneurship.

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Dr Yipeng Liu is a lecturer in Entrepreneurship at University of Kent. His research interests centre on entrepreneurship and institutions, global talent management and business sustainability with a focus on emerging economies. Dr. Liu has published in Thunderbird International Business Review, Promethus: Critical Studies in Innovation, among others. Dr Ke Rong is a lecturer in strategy at the business School of Bournemouth University. Ke got the PhD degree from University of Cambridge and obtained Bachelor degree in Tsinghua University. His research interests include business ecosystems, frugal innovation, and emerging industries and economies.

Ann-Charlotte Teglborg is a research professor at Novancia, Paris Business School. She is an early and active member of the European Employee driven innovation Research Network: EDI-Europe. She is also administrator of the French professional association Innovacteurs dedicated to employee driven innovation in French private and public sector. Milan Todorovic is a Professor of Entrepreneurship and Innovation, Corporate Entrepreneurship and Organisational Changes at Union Nikola Tesla University in Belgrade, Serbia. He holds a MBA from Melbourne Business School and has extensive international experience across diverse industries and government enterprises encompassing lecturing, management consulting, business development, directorships and successful management of global, mission critical business systems for leading international companies. During his career he has combined his significant professional experience and leadership skills with excellent knowledge of business strategy to conduct consulting assignments and deliver strategic projects worldwide. Currently, he is involved in several research projects including how public policies impact on innovation and entrepreneurship. Doan Winkel is an Assistant Professor of Entrepreneurship at Illinois State University and Associate Director of Programs at The George R. and Martha Means Center for Entrepreneurial Studies. His research has been published in the New England Journal of Entrepreneurship, the Journal of Entrepreneurship Education, the Journal of Occupational and Organizational Psychology, Human Resource Management, and the Journal of Business Ethics. He is co-founder of SproutEcon, LLC and One Virtual Business Coach, Inc

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Biographies of Presenting Authors Dr. Hadia H. Abdel Aziz is an Assistant Professor of Entrepreneurship and Innovation Management at the German University in Cairo. She has vast practical experience in the areas of SME financing, financial innovation and entrepreneurship which also constitute her main research interests. Dr. Tuomo Alasoini coordinates workplace innovation and development activities in Tekes (the Finnish Funding Agency for Technology and Innovation). He is Adjunct Professor of Sociology at the University of Helsinki and director of Tekes programme “Liideri – Business, Productivity and Joy at Work”. He is an active member of the European Workplace Innovation Network EUWIN. 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. Robert B. Anderson is a Professor of entrepreneurship with the University of Regina. He has authored or coauthored more than 150 peer-reviewed articles (more than 40 of these refereed journal articles) on economic development and entrepreneurship, two books on the subject and co-authored of a third, and co-edited of a handbook research on indigenous entrepreneurship. Petra Andries (petra.andries@kuleuven.be) is a senior researcher at the Centre for R&D Monitoring (KU Leuven). Her research interests are in innovation management and entrepreneurship in general, with a particular interest in new venture development, collaborative innovation and knowledge management. Paula Anzola Román, BA, MBA is a Researcher/contributor at the Department of Business Administration at Public University of Navarra. Her research has been focused in Open Innovation and Business Models. María Teresa Areitio, PhD is University Professor at Department of Industrial Economics at the University of Basque Country, Spain. She has managed some research projects and she has contributed to scholar area with articles and books. Her current work focuses on knowledge management, TICs and innovation in the EHEA and international economy. Manuel Luís Au-Yong Oliveira earned a distinction for his PhD degree in Industrial Engineering and Management from the University of Porto and is currently a part-time lecturer both at the University of Aveiro and at the University of Porto. Manuel is affiliated to INESC TEC. Alina Badulescu is Professor of Economics and PhD coordinator at the Faculty of Economics and Doctoral School in Social Sciences of the University of Oradea, Romania. She graduated Bucharest University of Economics and since she has authored and co-authored numerous journal articles and books. Her interests include economics, but promoting young researchers’ activity as well. Daniel Badulescu graduated Bucharest University of Economic Studies and has a PhD in Economics. He is Associate Professor in Business Economics and Business Financing at the Department of Economics, University of Oradea, Romania. His current research interests include economics, business economics and business finance. Olimpia-Iuliana Ban Ph.D. in Marketing, West University of Timisoara, Romania, 2005. Now is associate professor and Head of Economy Departament at University of Oradea. Fernando Barbosa is an invited lecturer in the Department of Production and Systems Engineering at the Engineering School of the University of Minho. He holds a B.Sc. in Management from Portucalense University, and an M.Sc. in Industrial Engineering from the University of Minho. He is a Business Consultant and Trainer in several organizations. Bartłomiej J.Gabryś is Assistant Professor at Chair in Entrepreneurship at the University of Economics in Katowice, Poland. He received his Ph.D. in corporate entrepreneurship. His present research focuses in the area

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of corporate entrepreneurship and growth. His research were presented at EURAM, BAM, AOM, ISBE, RENT conferences or published by Wolters/Kluver and Routledge. Muamer Bezdrob is a cofounder and director of the PING ltd. Sarajevo. He graduated at the Faculty of Electrical Engineering in Sarajevo, where he was an assistant professor. He earned his MSc and his PhD at the School of Economics and Business in Sarajevo. Muamer lives in Sarajevo with his wife and their son. 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. Katarzyna Bratnicka, is Ph.D. student at the University of Economics in Katowice, Poland. She received her Master degree in human resources management. Her present research focuses in the area of corporate entrepreneurship and creativity. Her research was presented at EURAM, BAM, AOM and ISBE conferences. Mariusz Bratnicki, is a Professor in management and holds the position of head of Chair in Entrepreneurship at the University of Economics in Katowice, Poland. His present research focuses on the area of corporate entrepreneurship, creativity and organizational performance. His research were presented at EURAM, BAM, AOM, ISBE, RENT conferences or published by Routledge. Dorotéa Bueno da Silva is Ph.D. Student in Industrial and Systems Engineering at the Production and Systems Department, School of Engineering, University of Minho, Portugal. She obtained a Master degree in Industrial Engineering at the Production Engineering Pos-Graduate Department, Paraíba Federal University, Brazil after graduating in Psychology at the Paulistana University, Brazil. The theme of her doctoral research is evaluation of innovation programs for SME, with a special focus on the evaluation of their indirect effects. Cagri Bulut is Associate Professor of Management, Ambassador of ENT-Division, of Academy of Management to Turkey, and Chair of Department of Business Administration, Faculty of EAS, Yasar University, Turkey. Alex Lôbo Carlos is a Brazilian Navy Officer, born in Rio de Janeiro in 1974. He graduates in Nautical Sciences and postgraduates in economics. Currently he is completing a Master in Management at the University of Minho, Portugal. Luísa Carvalho: Professor of Economics, Entrepreneurship and Innovation. Department of Economics and Management, Business School – Setúbal Polytechnic Institute – Portugal since 1999. Researcher in CEFAGE – University of Évora- Portugal. PhD in management, McS in economics. Author of several publications in national and international journals and book chapters. Pr. Annick Castiaux holds a PhD in Physics from the University of Namur and teaches innovation and technology management. Her research considers a systemic approach of innovation, trying to detect paradoxes that can lead to emergent technologies or business models. She focuses on agent-based simulations, to realise in silico experiments helping to understand innovation strategies. Paula Castro is a Undergraduate Student, University of Sao Paulo, Brazil. Develop a international internship in Business School – Setúbal Polytechnic Institute during 1st semester of 2013. Gulnara Chernobaeva is an Associate Professor and Post-doctoral Fellow at the Department of Innovation and Project Management, Omsk State University, Russia. She teaches several marketing courses. Her main research interest is marketing communications. Currently, she investigates marketing project support. Gulnara additionally has extensive experience of working as Head of Marketing at leading Omsk companies. Dr Anneline Chetty completed a Masters in Town & Regional Planning and a PH.D with a focus on Public and Private sector approaches towards the provision of Business Development services for SMMEs in the eThekwini Municipality. Authored the book: Promoting entrepreneurship in South Africa. Excellent understanding of Economic development issues globally.

Piotr Chwastyk is a researcher and lecturer at The Opole University of Technology. His field of research are innovation processes especially cost estimation in processes planning of innovation. He received PhD title in 2006. He is a member of the Polish Society of Production Management, and since 2006 a member of the board. Brian Cleland is a PhD candidate with the Ulster Business School, University of Ulster, where he is researching "Open Innovation Practices in the European Public Sector". He has over 20 years experience of working in the IT sector, and has recently been working as a researcher in the area of e-participation. He also acts as an advisor to SMEs, specialising in innovation and internet technologies. Dorin Cristian Coita Ph.D in Marketing at Academy of Economic Sciences, Bucharest, Romania. Currently is associate professor and Head of Management and Marketing Department at University of Oradea. (Foto) Jan Coppens obtained his Ph.D. in computer science engineering from Ghent University. He continued his research in network technology at Alcatel-Lucent Bell Labs. End 2007, he left Bell Labs to Join the Business Technology Office of McKinsey & Company. Currently, Jan is responsible for marketing and business development at the iMinds Incubation & Entrepreneurship program. Eliza Laura Coraş field of work is credit risk management but during her eight year experience in the banking industry she has accumulated extensive knowledge on all banking processes and risks. She is currently advancing her business risk knowledge and intrapreneuring experience by attending a PhD programme at the Academy of Economic Studies in Bucharest. Her research is focused in risks in the innovation process and her practical studies are aimed to open innovation practices. Teresa Costa Professor of Management, Innovation and Entrepreneurship, Department of Economics and Management, Business School – Setúbal Polytechnic Institute – Portugal s since 2001. Researcher in CITIS – University of Lusíada- Portugal. Phd in Management. McS in Management. Author of several publications in international and national journals and book chapters. Renata Paola Dameri is professor in Accounting and in Information Systems at Faculty of Economics, University of Genova, Italy. She is visiting professor in IT governance at the University of Paris-Dauphine. She is also member of the research Unit “Information Systems” at Bocconi School of Management. Sven H. De Cleyn is Incubation Programs manager at iMinds, where he supports new start-ups. He received a PhD in Applied Economics at University of Antwerp on the early development of academic spin-offs. He’s also lecturer in entrepreneurship at Karel de Grote University College and post-doc researcher on high-tech entrepreneurship at University of Antwerp. Ann De Keersmaecker is PhD student with a background in product development and industrial engineering. She is affiliated with the University of Antwerp, Belgium, and the Delft University of Technology, the Netherlands. Her research interest lays in innovating in developing countries and inclusive design. Moreover, she coaches students and combines this job with consulting activities. Stan De Spiegelaere is a researcher at the HIVA – KULeuven (Research Institute for Work and Society). In this function he studies topics in innovative employee behavior, employee-driven innovation, labour regulation and industrial relations. He is also linked to the VIGOR innovation research group and is currently preparing a phd thesis on labour regulation and innovative behaviour of employees. Edward Debelka - Educated at University of Oradea Faculty of Electrical Engineering and Computer Science in 1997.graduated from 3 courses. Worked in S.C. Unicert International Group, Oradea in 2005 as General Manager. Jaroslava Dědková, Ph.D is a lecturer at the Faculty of Economics, Technical University of Liberec. She gives lectures in Marketing, Consumer behaviour and Strategic marketing. She supervises baccalaureate and diploma works and acts as an opposer of diploma and baccalaureate works. In her scientific work, she deals with the competitiveness of companies located in the Euroregion Nisa.

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Nikolay A. Dentchev is an Assistant Professor of Entrepreneurship and Corporate Social Responsibility at the University of Brussels (VUB) and at HUBrussels. Currently, his research interests are related to sustainable business models, sustainable innovations, instrumental stakeholder management theory and the implementation of CSR strategies. Biagio Di Franco is a Phd Student, Politehnica University, Faculty of Management in Production and Transportation, Romania. Master Degree in Management of Innovations Polytechnics of Mons, Belgium . Master Degree in Management of Transports University of Brussels, Belgium. Master Degree in International Trade University of Brussels, Belgium. Degree in Sciences of Management - Catholic University of Mons, Belgium. Maier Dorin PhD student at The Bucharest University of Economic Studies, Bucharest, Romania. Maier hastwo BSc on engineering, an MSc degree in management and a PhD in Civil Engineering. Maier researches are oriented towards innovation and integrated management systems. Frédéric Dufays is a PhD-student at the Centre for Social Economy of HEC-ULg Management School in Liege (Belgium). His research interests are social entrepreneurship and collective entrepreneurship, which he analyses through social network and institutional theory lenses. Dan Constantin Dumitrescu 1969- “Politehnica” University of Timisoara. 1999 – PhD. Internships in universities: 1991- Koln, 1992 - Siegen, 1997 - Tennessee . Own field of specialization: Quality Manufacturing Systems. Smile Dzisi (PhD) is a Senior Lecturer in the School of Business and Management Studies at Koforidua Polytechnic. She is also the Managing Editor of the International Journal of Technology and Management Research. Her research and teaching interests are in Entrepreneurship, Innovation and Organizational Management. Dr. Kalle Elfvengren is an associate professor in the School of Industrial Engineering and Management at Lappeenranta University of Technology, Finland. His research topics include technology management, decision support systems (e.g. group support systems), decision analysis and creative group work methods. Vítor Figueiredo is a Full PhD Student of Management at the University of Beira Interior, Department of Management and Economics, Portugal. He studied Tourism Management and received his MSc in Tourism Management and Development, from the Aveiro University in 2010. He is an enterprise Consultant and President of the Moledo Community Council, Portugal. Luis Rafael Figueroa is an economist and a PhD student in Entrepreneurship and Innovation of the University of Essex, United Kingdom. His research interests and working experience are focused on business clusters and innovation in the case of SMEs in the agribusiness, tourism and textile-apparel activities in Latin America. Rebecca Fill Giordano studied Psychology at the University of Vienna. As expert for occupational aptitude assessments she advises universities and business organisations on psychological assessment. Her team developes online tools for analyses and feedback for different target groups. Her doctoral thesis (in progress) concerns self regulated learning in adults. Mário Franco is an Assistant Professor of Entrepreneurship and SME Administration at the Department of Management and Economics, Beira Interior University, Portugal. He received his PhD in Management from Beira Interior University in 2002. His research focuses on strategic alliances, business networks and entrepreneurship. He is a member of the NECE-Research Unit in Business Sciences of the Beira Interior University. Brendan Galbraith is a member of the European Network of Living Labs, University of Ulster Business and Management Research Institute, Connected Health Ulster and is Book Reviews Editor at Technology Analysis and Strategic Management Journal. Brendan has led several large-scale EC funded innovation and technology transfer projects and is a consultant to a number of SMEs. Olaf Gaus a Research Associate in Entrepreneurship at the Faculty of Economics and Management, Otto-vonGuericke-University, Magdeburg, Germany, I am interested in the transferability of business models on public

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institutions. I am working on this subject as a member of a research project entitled "Universities as Enterprises", funded by the German Federal Ministry of Education and Research. Frank Gielen is Director Incubation & Entrepreneurship at iMinds, where he is responsible for all Incubation & Entrepreneurship activities. He holds a PhD in computer science from the Free University of Brussels. He is Professor at Ghent University, where he is teaching courses on software and technology entrepreneurship, and has entrepreneurial experience through several ventures. Patrick Gilbert is a professor at the Sorbonne Graduate Business School. He holds a PhD in Management and is an accredited research supervisor in management and psychology. He also serves as a scientific advisor to national and international organizations. Oleg Golichenko has a degree of Doctor of Economic Sciences. He is a chief research associate at the Central Economics and Mathematics Institute of the RAS. He is also a professor at the National Research University Higher School of Economics and the Moscow Physics and Technique Institute in Moscow, Russia. His research interests are related to investigation of innovation development processes on micro-macro economic levels and design of social economic and innovation policy. He is an author of more than 200 scientific publications. Tea Golja, PhD Juraj Dobrila University of Pula, Department of Economics and Tourism “Dr,Mijo Mirković” . Tea Golja is holding a position of the Assistant Lecturer at Juraj Dobrila University of Pula. Major field of interest: management, corporate social responsibility, quality management, tourism and sustainable development. In 2012 she successfully finished an IRCA course for total quality management - Lead auditor for ISO 9001:2008 by the Bureau Veritas in Croatia. Dr. Gourova is Associate Professor at Sofia University and New Bulgarian University. She has professional experience at Ministry of Transport and Communications, DG JRC –IPTS, and in expert groups at European Commission, EUTELSAT, Council of Europe. Her research is cross-disciplinary focused on Knowledge management and open innovation, as well as on e-skills, e-Learning, mobility and career of researchers. Roxana Hatos is a Ph.D. student at the Faculty of Economics Sciences, University of Oradea, working as junior researcher within the Center of Adult Education. She has BA in Sociology and Economics and MA in Regional Development and she has been involved in several research projects. Bart Henssen received his PhD in Applied Economics from Hasselt University, Belgium, and a PhD in Economics and Business Administration from Jyväskylä University, Finland. He is Research Manager at the University College Brussels and affiliated with the KIZOK Center for Entrepreneurship and Innovation of Hasselt University. His research interests include entrepreneurial processes in family businesses. Julie Hermans holds a Degree in Management Engineering from the University of Namur where she also pursued her Ph.D. Her research interests are in University-industry collaborations, Innovation networks and ambitious entrepreneurship. She recently became a postdoctoral researcher for the Belgian Science Policy Office in collaboration with the University of Antwerp, Tilburg University and the Eindhoven University of Technology. Heyin Hou is an associate professor at the School of Economics and Management, Southeast University, China. Heyin got the Ph. D from Antai College of Economics & Management, Shanghai Jiao Tong University, China at 2004. And main research interests at present include: Venture Capital, Entrepreneurship, Technology Business Incubator(TBI), Technovation. Danut Iorga is PhD student at Doctoral School of Entrepreneurship, Business Engineering and Management, UPB, Romania. He earned a bachelor’s degree in Avionics, Aeronautics Faculty, UPB, Romania. ASQ senior member, Danut Iorga is certified as Six Sigma Black Belt, with more than 200 Improvement and Design Projects in companies such as NCH Group and Accenture. Mark James, Ph.D. is an assistant professor of management a United International College in Zhuhai, China. He received his Ph.D. in organizational behavior from the University of Wisconsin – Milwaukee. His research focuses on issues relating to diversity and fairness in the workplace, and global perspectives on entrepreneurship.

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Chandana Jayawardena - BSc (Hons), MBA. is presently a doctoral researcher attached to the Department of Management and Marketing, Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic. His research interests focus on Career Development, Managerial Competencies, and Employees Behaviour at work. He is an academic staff member of the University of Peradeniya, Sri Lanka Jan Jonker is a Professor of Corporate Sustainability at the Nijmegen School of Management of the Radboud University Nijmegen (The Netherlands). His research interest are in sustainable strategy development, (new) business models and transition thinking. 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. Ravinder Singh Kahlon is a PhD student at Ulster University. His research interest surrounds KM Strategies and Systems, especially in performance measurement metrics and critical success factors implementing KM within organisations. He works with IT consultancies that specialises in top-quality innovative IT Solutions, to enable KM within organisations. Tomasz Kijek, PhD in Economics conducts teaching and research activities in the Department of Economics and Management at the University of Life Sciences in Lublin, Poland. His research interests focus on innovation, innovation capital, knowledge and a firmâ&#x20AC;&#x2122;s competitiveness. He is the author and co-author of several scientific publications, including chapters of monographs and articles. Beti Kostadinovska Dimitrovska, a Ph.D. student at the Faculty of Economics-Skopje, works as a Project officer in the European Information and Innovation Centre in Macedonia within the Ss. Cyril and Methodius University in Skopje. Beti is responsible for the research and innovative component providing innovative, R&D and IPR services to SMEs and academia sector. Eric Michael Laviolette Associate Professor of Strategy and Entrepreneurship at Novancia Business School, Paris with a doctoral degree in Management at University of Lyon. His research builds on organizational and management theories to analyse entrepreneurial processes within innovation systems. He has published several papers on spin-offs, incubators, entrepreneurial skills & leadership development and international entrepreneurship. Regina Leite is an Assistant Professor in organizational behaviour and HRM in the School of Economics and Management at the University of Minho. She received the PhD degree in management from de University of Minho. Her current research interests include work and non-work spheres, organizational commitment, privacy issues, sexual harassment, change and innovation. Bart Leten is Assistant Professor in Innovation Management at the Vlerick Business School and the KU Leuven (MSI department). His research focuses on corporate innovation and international business strategies, and deals with various topics such as open innovation, IP strategies, industry-science links, R&D internationalization and organizing for innovation. Sophie LiĂŠnart is a 4th year PhD student in Management Science from the University of Namur, Belgium. Under the supervision of Pr. Dr. Annick Castiaux, she is researching the integration of energy efficiency requirements into the innovation process of information technology products and services, and its impact on business strategy. Raimonda LiepiĹ&#x2020;a, Mg.oec., Lecturer of Riga Technical University, Faculty of Engineering Economics and Management, Department of Quality Technologies. Almost 10 year experience as Head of Conformity Assessment Coordination Division in the Internal Market Department of the Ministry of Economics of the Republic of Latvia. Area of research interests: conformity assessment, among them standardization, accreditation, metrology.

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Eric Liguori is an assistant professor in the department of management at California State University – Fresno. He received his Ph.D. in entrepreneurship from Louisiana State University. His primary teaching interests are entrepreneurship and taking an experiential approach to his classroom. His research focuses on small business, family business, and entrepreneurship Dr Jun Li is Senior Lecturer at the Essex Business School of University of Essex, UK. He was President of Chinese Economic Association (UK/Europe) during 2011-2012 and is Co-Editor of Journal of Chinese Entrepreneurship. His recent publication includes China’s Economic Dynamics (Routledge, 2013). María Jesus Luengo PhD is Associate Professor at Department of Management Evaluation and Business Innovation, at the University Of País Vasco Spain. She has managed some research projects and she has contributed to scholar area with articles and books. Her current work focuses on knowledge management, intellectual capital and innovation in the regional areas and political quality in the EHEA. And organizational behaviour. Sabrina Luthfa Karim is a doctoral candidate in University of Halmstad, Sweden. Her research interest is to investigate how multinational firms manage business relationships with their partners. She has completed her MSc. in International Business from Gothenburg University, Sweden and BSc. in Industrial Marketing from University of Skövde, Sweden. Andreea Maier is PhD student in the Research Center for Engineering and Management of Innovation (RESIN), Department of Engineering Design and Robotics, Faculty of Mechanical Engineering, Technical University of Cluj Napoca. She has two BSc, engineering and economics, and a MSc degree in management. As member of RESIN, her researches are oriented towards innovation management systems. Anna Matras-Bolibok holds PhD in Economics and she conducts teaching and research activities in the Department of Economics and Management at the University of Life Sciences in Lublin, Poland. Her research interests focus on innovations, determinants of innovativeness of enterprises and economies and the role of innovation in regional development Céline Maximin-Tieu is awarded with a PhD in Economics (University Paris 1 Panthéon-Sorbonne), Céline Marie Maximin-Tieu is currently an academic teacher at ISTEC Paris business school, in charge of research linking sustainable development and industrial organization. Author of several chapters in books on this subject, she studies the feasibility of these features through her teaching and research. Patrick McHugh is Director of the IE Brown EMBA program and lecturer in entrepreneurship at Brown University. He has 25 years of industry experience and degrees in engineering from Columbia University, an M.B.A. from Harvard, and a Ph.D. from Bentley University. His research interests are in the areas of innovation, entrepreneurship, and social networks. Petra Merenheimo is doctoral student at the University of Lapland, Finland. Her doctoral thesis is about entrepreneurship at the Finnish social services sector. She has done research about and development work with female entrepreneurs both in Finland and Germany. Ioana Teodora Meşter is Ph.D. in Economics - Cybernetics, Statistics and Economic Informatics. Member of the Department of Economics, Faculty of Economic Sciences, University of Oradea, Romania. Specialist in Statistics, Econometrics and Economic modelling. Interest domains: quantitative methods applied in business administration. José M. Monteiro-Barata is an Assistant Professor of Economics, R&D Management and Industrial Organization at the School of Economics and Management of the Technical University of Lisbon, (ISEG/UTL). PhD in Economics (1996) from the UTL. Former Vice-President of ISEG/UTL. Coordinator of Graduate and PostGraduate courses at the Portuguese School of Bank Management (APB). Peter W. Moroz, Ph.D., MPA, B.A. Primarily teaches entrepreneurship and economics related courses. Research interests include process theory in entrepreneurship, regional and economic development, technology transfer and social enterprise creation. Peter currently holds a SSHRC grant that focuses on strategic alliances

among corporations and Indigenous communities and how they may be used to facilitate the creation of joint and wholly owned new ventures by Indigenous peoples. Eda Evla Mutlu is a PhD Candidate and Research Assistant in Faculty of EAS of Yasar University, İzmir, Turkey. Murat Nazlı is a PhD Candidate and Part-time Lecturer in Faculty of EAS of Yasar University, Turkey. Daniel Neicu is currently a doctoral student in Business Economics at KU Leuven and HU Brussels. His general research interests are behavioural economics, game theory, and innovation economics, while focusing on more specific issues such as clustering of young innovative companies and the competitive behaviour of innovative firms. Sandra Nunes: President of Department of Economics and Management, Business School of Setúbal Polytechnic Institute, Portugal. Professor of Analysis of Statistical Data; Statistic; Quantitative Methods and Mathematics. Professor in Setúbal Polytechnic Institute since 1995. Researcher in CMA – Faculty of Sciences and Technology, New University of Lisbon, Portugal. PhD in Mathematics - Statistics, McS in Actuarial Sciences. Author of several publications in national and international journals. María Obeso, PhD, is Assistant Professor at Department of Business Administration at the University of Cantabria, Spain. She has been Visiting Scholar in Business School at the University of Bedfordshire, UK. Her current work focuses on knowledge management Handan Odaman, M.A. graduated from Boğaziçi University, Department of Psychology with a High Honor degree and specialized in Cognitive Psychology. She attended national and international meetings with various research projects. She works as academic executive assistant in Baltaş Group and she is responsible from academic studies. Odaman is a member of Turkish Psychological Association. Iuliana Olimpia. Ph.D. in Marketing, West University of Timisoara, Romania, 2005. Now is associate professor and Head of Economy Departament at University of Oradea. Morena Paulišić is a senior assistant at the University of Pula. She holds a PhD degree in organization and management. Her research interests include organization and management especially factors as structural components, business processes and strategies that have influence on organizational behavior. She is also a member of IMSS - research network of business schools. Ruslan Pavlov is a senior researcher at the Central Economics and Mathematics Institute, and post graduated from the same institution. His research interests include the diversification of business within a context of the long waves theory; institutions of social entrepreneurship as factors of social innovations. Steen Høyrup Pedersen is Associate Professor and member of the Research Programme ‘Organisation and Learning’ in the Department of Education, Aarhus University, Campus Copenhagen, Denmark. He is engaged in the management of the EDI-network: The European network of Employee-Driven Innovation and workplace learning. Research interests include employee-driven innovation, competence development and reflection and learning. Andreas Pinkwart was a Member of the German Bundestag (2002 - 2005) and Minister for Innovation, Science, Research and Technology as well as Deputy Prime Minister of the state of North Rhine-Westphalia (2005 - 2010). Since 2011 Professor Pinkwart is the Dean at HHL Leipzig Graduate School of Management and holds the Stiftungsfonds Deutsche Bank Chair for Innovation Management and Entrepreneurship. Dr. Sebastian Pfotenhauer is a researcher at the MIT Technology Policy Program, the MIT Portugal Program, and the Program Science, Technology and Society at the Harvard Kennedy School. His research focuses on strategies for capacity building in science, innovation, and higher education; international university collaborations and start-up universities, and the governance of complex socio-technical systems. Karla Phlypo- Walden University-President of PK & Associates Inc.expertise is social innovation. Integrating a background in knowledge management, her research has led to models for Open Communities of Practice

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(OCoP) and for-profit ‘bridging organizations’. As Global Knowledge Manager for GM Engineering, she contributed to a culture of sharing and innovation through collaboration. Karla is active in the international KM professional community. Adalberto Rangone in 2010, he graduated with a Master's degree from the University of Oradea (Romania) at the Faculty of Economics Science in International Economic Relations and now he is a PhD Student in Economics at the University “G.D'Annunzio” of Chieti-Pescara (Italy) and at the University of Oradea (Romania). Pia Mulvad Reksten, Union Advisor, industrial, innovation & research policy, LO (Danish Confederation of Trade Unions). Elaborates innovation policy recommendations ensuring that national og regional innovation policies take into account the role of non-academic employees (employee-driven innovation) and a more practical form of innovation, where companies draw one inputs from the markets, customers, users – and employees. Andreas Pinkwart was a Member of the German Bundestag (2002 - 2005) and Minister for Innovation, Science, Research and Technology as well as Deputy Prime Minister of the state of North Rhine-Westphalia (2005 - 2010). Since 2011 Professor Pinkwart is the Dean at HHL Leipzig Graduate School of Management and holds the Stiftungsfonds Deutsche Bank Chair for Innovation Management and Entrepreneurship. Dr. Angela Poulakidas is an Assistant Professor of international business development and entrepreneurship at Novancia Business School Paris. Dr. Poulakidas’ professional publications include articles related to marketing, international business and entrepreneurship. Her research interests include corporate reputation, international shipping, entrepreneurship and strategies for effective teaching. Dorian Proksch has joined HHL Leipzig Graduate School of Management as a research associate at the Chair of Innovation Management and Entrepreneurship in 2011, where he is currently writing his doctoral thesis in the area of early stage venture capital funds. His research interests include Internationalization of startup companies and risk management in new venture financing. Aneta Ptak-Chmielewska is Associate Professor at the Institute of Statistics and Demography at Warsaw School of Economy. Her main research fields include applied statistics, event history methods and models, multivariate statistics and advanced statistics application in economy and life sciences. She has been a member of the Network of Excellence RECWOWE project. She has published in high-quality national journals. Nathalie Raulet-Croset is Associate Professor in organizational theory at the IAE, University Paris 1-Sorbonne. She is also researcher at the PREG-CRG of the Ecole Polytechnique. Her research interests are on interorganizational collective work, on the emergence of actor's practices, on territories and spaces considering their impact on collective work and organizations. Carla Riverola is a PhD candidate at La Salle Innova Institute – Ramon Llull University. She holds a Computer Science Degree and Master of Science in IT Management from La Salle – Ramon Llull University in Barcelona. Her research interests are mainly focused on studying the role that ICT may play on Innovation and Entrepreneurship. Augusto Rocha "Master in Entrepreneurship and Business Creation at the University of Beira Interior, Portugal. Graduated in Business Processes from the University of Uberaba (Brazil) and in Computer Science from the Federal University of Uberlandia (Brazil). My research focuses on business innovation, entrepreneurship education and corporate entrepreneurship in technology-based companies." Cristina Rodrigues holds a Ph.D. in Industrial and Systems Engineering. Assistant Professor in the Department of Production and Systems, School of Engineering at the University of Minho and is responsible for disciplines of applied statistics in undergraduate and master engineering courses. She is also a researcher fellow at Algoritmi R&D Centre. Fernando Romero holds a Ph.D. in Science and Technology Studies from the University of Manchester. He is at the Production and Systems Engineering Department, and at the Centre for Research in Industrial and Tech-

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nology Management, in the University of Minho. He publishes regularly in the area of Industrial Innovation, Innovation Systems and innovation management. Tarek Sadek, MASc. is the Enterprise Development Manager at Xerox Centre for Engineering Entrepreneurship & Innovation (XCEEi) at McMaster University. His job responsibilities include supporting the students in their new venture creation and establishing XCEEi as an entrepreneurship hub in the region. Josune Sáenz is PhD in Economics and Business Administration and Vice Dean of Research at Deusto Business School (DBS). Her publications mainly focus on measurement of intangibles, intellectual capital, knowledge management and innovation. She has also carried out research into the link between emotions, expectations and behaviour in change processes. Svetlana Samovoleva graduated from the Economics Faculty of Moscow State University and received PhD in the Central Economics and Mathematics Institute of the RAS where she is a senior research associate. During the last 10 years her research is organized around a set of issues associated with frameworks of national innovation system, risks of innovation activities, innovation policy at state and enterprise levels. Mijalce Santa is a Teaching Assistant at the Ss. Cyril and Methodius University, Faculty of Economics-Skopje and a PhD student at University Paris 1 - Pantheon – Sorbonne. His research interest is in the area of ebusiness, transformation, learning organizations, innovation and change. Amitrajit Sarkar is a lecturer of Software Engineering and Information Systems at Christchurch Polytechnic Institute of Technology, New Zealand. Beside IS resilience, his research interests include Innovation and Entrepreneurship in IS, E-Commerce implementation in SMEs, E-Commerce trust, Big Data, and ERP implementation. Ted Sarmiento is Senior Lecturer at the Business School of Leeds Metropolitan University, Leeds, England and is currently researching small business performance management as part of a DBA programme. As keen amateur cyclist taking part in Cyclo-Cross, Time Trial and Sportive events Ted also has a small business interest in a holiday let in Northumberland. NicoletaTrandafir Scurt, phd-s of Faculty of Management in Production and Transportation. Research areas: industrial engineering. Diplomas: Engineer of “Politehnica” University of Timişoara, (1986) and Economist University of Craiova (1994). Books written: 3,Articles published: 32, Research contracts, including grants: 4. Janet L Sernack After 30 years of consulting experience to the manufacturing, retailing, finance and telecommunications businesses to Australia’s and Israel’s top 100 companies as Compass Learning Pty Ltd, Janet relocated to Israel, where she joined the Start-Up revolution, and founded ImagineNation, an imaginative, generative and provocative global learning company that develops innovative and entrepreneurial leaders. Denisa Skrbková is a student student at the Technical University of Liberec – Economical Faculty - Business Economics. Last year, she finished the Bachelor degree at the University of Huddersfield in the frame of oneyear exchange programme and than she retain the title at the Technical University of Liberec - Economical Faculty - Management of international Trade. Aziz Šunje, PhD. in Business is Full Professor at School of Economics and Business, University of Sarajevo and Chair of Department of Management and Organization, lecturing different courses in the country and abroad. Dr. Šunje has published as author and co-author five books, and a lot of scientific papers in academic journals and conference proceedings. Dr Anna Sacio Szymanska A senior research scientist at Innovation Strategies Department of the Institute for Sustainable Technologies – NRI, Radom, Poland. Interested in long-term strategic thinking; analysing the relationships between innovation, strategy and foresight; designing foresight methodologies; evaluating and putting foresight results into practice. Ann-Charlotte Teglborg is research professor at Novancia, Paris Business School. She is an early and active member of the European Employee driven innovation Research Network: EDI-Europe. She is also administrator

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of the French professional association Innovacteurs dedicated to employee driven innovation in French private and public sector. Ioana Teodora Meşter is Ph.D. in Economics - Cybernetics, Statistics and Economic Informatics. Member of the Department of Economics, Faculty of Economic Sciences, University of Oradea, Romania. Specialist in Statistics, Econometrics and Economic modelling. Interest domains: quantitative methods applied in business administration. Man-Chie Tse is a PhD student. Her research focus surrounds engineering methods for analysis of intangible modelling properties in personal KM, strategic organisational design and development. Besides her research work, she is involved with exploring the practical application of new processes, methods, tools and techniques in organisations to achieve innovation and transformational change. Nazlihan Ugur enrolled University of Leuven, Managerial Economics, Strategy and Innovation (MSI) in 2011 as a full time PhD student and she is writing her PhD thesis on ‘Ambidextrous Organizations: Temporal and structural balances between exploitation and exploration’ under the supervision of Prof. Rene Belderbos and Prof Bart Leten. Barbara Unković, joined the University team after working for international companies such as Deloitte, covering Human Capital Advisory Services; also with experience as Branch Manager at Adecco employment agency; Won a master’s degree in international trade and the field of her research interest considers human resources, services, visual learning tools and international research projects. Jiro Usugami is a Professor of Management at Aoyama Gakuin University, Japan. He received his Ph.D from the George Washington University, USA. He teaches international business and management at Aoyama Gakuin University. Florea Nicoleta Valentina is a PhD Lecturer at Management-Marketing Department, Valahia University of Targoviste, Romania, with an experience over 15 years in HR. She obtained her PhD title in HRM, she published over 30 articles and two books in the same domain. She is a member of Management-Marketing Research Center from VUT. Dirk Van Lindt (PhD in Business Statistics) is professor at the University College in Brussels and coordinator Quality Management in the faculty Business Administration. His main research expertise is in learning and teaching entrepreneurial skills, learning in social networks and gaming as educational tool. Jeff Vanevenhoven, Ph.D, is an Assistant Professor in Management and the coordinator of the entrepreneurship major at the University of Wisconsin-Whitewater. He received his Ph.D (Strategy), a M.S. (eBusiness), and B.S. (Archaeology) from the University of Wisconsin - Milwaukee. His work has appeared or is forthcoming in journals such as: Strategic Management Journal, Journal of Small Business Management. Karen Venturini is an Assistant Professor at the Department of Economics and Technology of the San Marino University. She is teaching at the undergraduate degree course in Industrial Design. She has a PhD in Engineering Management and her research area of interest is diffusion of technologies into various settings, innovation management and R&D management. Filipa D. Vieira holds a Ph.D. in Industrial and Systems Engineering. Assistant Professor at the Production and Systems Department, School of Engineering, University of Minho, since 2007. Lecturing activities on Innovation and Economics Engineering, at undergraduate and post-graduate courses. Researcher fellow at CGIT (Production and Systems Department Research Centre). Author of several research papers on innovation and entrepreneurship. Vessela Warren is a Doctoral Candidate and Research Associate at the University of Gloucestershire, UK. She holds a BSc in Economics from the University of Bologna, Italy and MBA from UWE, UK. She has several years’ experience in business start up, strategy and internationalization. Her main research focus is in innovation, SMEs and knowledge transfer.

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Christopher Whipple is a robotics engineer with a B.S. Robotics Engineering, minor in Computer Engineering, from Worcester Polytechnic Institute and an M.S. PRIME, Brown University. Interests include industrial robotics, mobile robotics, and automation with a focus in digital electronics. Projects include robots for fire-fighting, excavation, and unmanned aerial vehicles for rural search and rescue. Doan Winkel received his Ph.D. in Management from the University of Wisconsin â&#x20AC;&#x201C; Milwaukee. He currently teaches entrepreneurship at Illinois State University, where he is also the Associate Director of Programs at The George R. and Martha Means Center for Entrepreneurial Studies. His research focuses on improving entrepreneurial education. Urszula Wnuk - a young researcher at the Institute for Sustainable Technologies â&#x20AC;&#x201C; National Research Institute in Radom, Poland working for the Innovative Strategies Department. Participated in the realisation of the sectoral foresight project and the strategic programme in the field of mechanisms and structures supporting innovation commercialisation. Author and co-author of several reports and articles. Dr. Danielle Wood is a researcher and systems engineer in Johns Hopkins University. Dr. Woodâ&#x20AC;&#x2122;s research combines tools from technology, management and policy. She extensively studies the management of satellite programs in developing countries. Dr. Wood holds graduate degrees in Engineering Systems, Aerospace Engineering and Technology Policy from the Massachusetts Institute of Technology. Tomas Xavier is an engineering professor in the National University of East Timor. He is currently at University of Minho, Portugal, completing a master in Industrial Engineering. His research interests are engineering and entrepreneurship.

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Examining Determinants of Innovation Culture in Egyptian Organizations Hadia Abdel Aziz and Sandra Marcos Innovation Management Department, Faculty of Management Technology German University in Cairo, Egypt Hadia.hamdy@guc.edu.eg Marcos.Sandra@student. Guc.edu.eg Abstract: To survive today’s dynamic and challenging business world, companies need to pro‐act to change through innovation. One important catalyst of innovation is an organizational culture that would encourage and reward creativity and change. This research examines eight dimensions of innovation culture in Egyptian local and multinational organizations. These encompass a well defined and clear innovation strategy, a flat and flexible organization structure, the availability of resources to support innovation, and the institutionalization of favorable and supportive behaviors to promote innovation. They also include trust and open communication, supportive management and leadership, team work and collaboration, and continuous development of organizational members. The research was conducted through a survey on the students of a reputable MBA program who have at least two years of experience working in different local and multinational companies. Findings reveal that local firms lack all of the above determinants of innovation culture. On the other hand, although the innovation culture is more developed in multinational companies operating in Egypt, especially in terms of having a clear strategy and continuously developing their employees, they are still lagging behind in most of the dimensions mentioned above. While the research shades light on the cultural deficiencies that Egyptian organizations must rectify in order to encourage innovation, it lays the ground for further research on the area of variations in innovation culture within different organizational and cultural contexts. Keywords: innovation, culture, Egypt, MNCs

1. Introduction The business world has been undergoing sever changes throughout the past few decades. The pressures exerted by globalization, the fast base of technological change, the increasingly demanding customers and the growing competitive pressures have all necessitated radical changes in the rules of the business game through innovation. As such, innovation has become the key, not only to growth, but also to the survival of firms. This is true, not only on the organizational level, but also on the country level as countries now are categorized in terms of competitiveness as factor driven economies, efficiency driven economies, and on the highest scale, innovation driven economies. Egypt is one of the transitional economies that is characterized by a weak innovation performance and insufficient capacity to innovate as one of the problematic factors for doing business. It was ranked 109 among 144 countries in the innovation pillar in 2012/2013 global competitiveness report. With the country being relatively developed in the availability of scientists and engineers (ranked 61) and the capacity for innovation (ranked 80), while underdeveloped in the companies R&D expenditures (ranked 116), the question of whether Egyptian organizations provide the right climate for innovation would emerge. The answer to this question is particularly important in light of the fact that innovation has been identified as one of four main pillars driving long term competitiveness in the Egyptian sustainable competitiveness strategy developed in 2012. This means that the country has to achieve a leap frog in terms of innovation to be able to count on it in future growth; a challenge that can never be achieved without a supportive innovation climate both on the national and on the organizational level. An innovative organizational culture is a prerequisite of a successful organizational innovation. Innovations find their way in organizations where culture accepts and encourages change through new ideas or solutions. In other words, organizational performance is dependent on having a culture that accepts change and responds to it in an innovative way. This entails that the different organizational cultural dimensions be structured in a way to affect employees’ behavior towards innovation. These include the innovation strategy, the organizational structure, resources to support innovation, behaviors and mechanisms promoting innovation, trust and open communication, management and leadership, team work and collaboration, and quality development of organizational members.

Hadia Abdel Aziz and Sandra Marcos This research examines and analyzes the different determinants of innovative organizational culture in Egyptian local and multinational organizations. Although this area of research has been previously tackled in western contexts, little research has been conducted in 3rd world countries including Egypt. In particular, the research aims at identifying the deficient areas in organizational culture and climate that would contribute to the problematic lack of organizational innovation despite the availability of human skills. It also aims at highlighting the difference between local and multinational organizations in terms of how they promote and support organizational innovation. The results of this research would provide Egyptian organizations with an overall assessment of how their organizational culture contribute to promoting/ hindering innovation, as well as, a diagnosis of the most pressing cultural problems that hinder successful innovation. It also contributes to the academic literature concerned with the cultural differences between local and multinational organizations in terms of innovation, an area that was rarely tackled before. Finally, the paper recommends a preliminary roadmap of improvements needed along different cultural dimensions in order for Egyptian organizations to enhance their innovation performance. It also recommends further areas of research in order to deepen the understanding of organizational innovation culture and performance in the Egyptian context.

2. Literature review Many researchers tackled the issue of organizational innovation success and failure factors. Each highlighted either a single or a group of factors as vital for innovation. These can be grouped into product related, market related, project related and organizational related factors. Product related factors are concerned with the final products or services that result from the innovation process. These include factors such as product uniqueness, perceived value, quality, etc. Market related factors are concerned with market and competitive characteristics such as market structure, product market synergy, and timing of entry. Project related factors are concerned with the proper execution of the development project starting from idea generation to commercialization. Finally, organizational related factors are concerned with the organizational capabilities required to successfully launch new innovations. Creating and managing successful innovative organizations is not a straightforward task. It requires developing unique organizational capabilities that would promote creativity and innovation such as strategy and vision, creativity and idea management, organizational intelligence, harnessing the competence base, organizational structures and systems, management of technology, and culture and climate (Lawson and Samson, 2001). Culture is the pattern of values, traits, or behaviors shared by the people within a social unit. (Herbig and Dunphy, 1998). Within the context of organizations, organizational culture defines the principles, standards and behaviors that are generally accepted between organizational members. It is the shared social knowledge within the organization with respect to rules, norms and values that shape the behavior of its members (Colquitt et al., 2009). Creating a culture that would direct organizational members towards desirable behaviors is a prerequisite to achieving organizational goals (Martins and Terblanche, 2003). As such, the first step to innovation is building up a culture which encourages creativity, accepts change, and thrives to find out new methods of solving problems. Innovative cultures are characterized by challenge, freedom, idea support, trust, playfulness, debates, conflicts, risk taking and idea time (Sharman and Johnson, 1997). Dobni (2008) added that they always adopt concepts like flexibility, group work, spotting opportunities, acceptance of risk, openness and fast and accurate decision making. However, developing an innovation stimulating culture is a very difficult task. It requires thorough analysis of the existing culture, deep understanding of the innovation cultural dimensions, and then a careful change management plan to bridge the gap between the current and the desired culture. This should be conducted within the framework that is taking into consideration the organizational capabilities, and the surrounding environment of competitors and customers (Dombrowski and Kim 2007, 191). Many researchers discussed the issue of determinants of innovation culture. Some attempted to explore the relationship between one or more cultural dimensions on the organizational innovation performance (Johannessen, 1994; Brand 1998; Sarros, Cooper , and Santora 2011) while others tried to adopt a more holistic approach by drawing models for the different cultural dimensions that together have a direct impact on innovation (Martin and Terblanche, 2003; Ahmed, 1998; Herbig, and Dunphy, 1998; Dombrowski et al; & Dobni, 2008) . The most discussed dimensions are strategy, structure, management and leadership, resources,

Hadia Abdel Aziz and Sandra Marcos quality development of organizational members, teamwork and collaboration, trust and open communication, and behaviors towards innovation. The business's strategies and mission statement is the first aspect that shapes the culture inside the organization. To have a strong innovation culture, the organization must set clear understood innovative mission, vision, and strategies. An innovation strategy promotes the generation, development, and implementation of new products, businesses, and processes that provide long term opportunities for growth. It should be set to leverage the firm’s current competitive position and provide direction for its future development. As such, it should be developed after a thorough assessment of the organizational innovation capabilities and its external environmental context, as well as, the organizational goals and strategic intent (Scilling, 2008). Understanding and acceptance of the strategy among organizational members is essential to ensure its effective implementation (Irani, Sharp and Kagioglou, 1997). To this end, organizational members should associate their own success with the right implementation of the organization strategy (Dombrowski and Kim, 2007) The structure of the organization plays an important role in shaping its culture as it has the capacity to emphasize certain values that can either promote or hinder organizational innovation. In order for innovation and creativity to find their way in organizations, flat structure, and autonomy are recommended; whereas, hierarchy, formalization and standardization would hinder innovation (Martin and Terblanche 2003: Dombrowski and Kim 2007). Dombrowski and Kim (2007) added that flexibility, in terms of allowing employees’ job rotation; help generate innovations as it allows employees to widen their knowledge base. Herbig and Dunphy (1998) confirm that innovations do flourish more in a culture that adopts a flat hierarchical structure, where the communication goes smoothly between all organizational members, and each member has the power of making decisions and the responsibility of a certain task. On the other hand, Innovations do not find their way in bureaucratic environments. Daugherty et al (2011) proved that while centralized decision making even in a simple structures would slow down innovation, decentralization has a positive impact with idea generation and innovation practices. For an organization to have an innovative culture, it should make sure that resources are made available to help employees explore new ideas and implement them. These include time, data, tools, technology, people and many others (Martins and Terblanche 2003). Employees who perceive that all resources, including their time, are committed to achieving short term results are discouraged to innovate. On the other hand, providing a pool of resources to cover the exploration of long term possibilities is positively associated with innovation. This is particularly true for the most precious resource, time, that is needs by employees to observe, imagine, experiment and come up with new ideas (Moreno et al., 2008). The availability of idea management systems encourage employees’ creativity and facilitate the innovation process (Hyland and Beckett 2005, 336). Investing in R&D and allocating budgets for innovation support systems and mechanisms are considered among the important determinants of the innovation climate (Dombrowski and Kim, 2007). The values and norms that encourage innovation are translated into specific mechanisms and behavioral forms that either encourage or discourage innovation. The way mistakes are treated and whether they are allowed and perceived as a learning opportunity, the way new ideas are received and whether they are welcomed as long as they fall within the organizational boundaries; and the way diversity and conflict are handled all affect the innovation culture. Innovative organizations also constantly reach out for internal and external knowledge and encourage risk taking, experimentation and continuous learning (Herbig and Dunphy, 1998 & Martins and Terblanche 2003). Performance goals and basis for rewards and punishment are also important determinants of the organizational innovation culture. Innovative organizations ask employees to set innovation related performance goals in their Management by Objectives (MBO) programs. They expect faults and failures in the first stages of innovation and understand that tolerance for mistakes and even celebrating them is essential in promoting creativity and innovation. On the other hand, rewarding and compensating creative behaviors encourages and motivates people to be more innovative (Martins and Terblanche, 2003). Rewarding for creativity can take many forms including "Dual Ladder" systems that give members with innovative ideas the right to develop them while eliminating all bureaucratic stages and routines that can hinder their progress (Tidd, Bessant and Pavitt, 2005).

Hadia Abdel Aziz and Sandra Marcos Open and transparent communication within an atmosphere of trust and democracy is an important determinant of innovative cultures. Norms that promote open door communication, exposure of problems, and discussing disagreements should prevail. At the same time, emotional safety should be provided through a climate of trust (Martins and Terblanche, 2003). This would create an environment where people feel free to express their own views and ideas within a system that they perceive as trustworthy (Ismail, 2005) Leaders and managers are considered one of the important pillars in shaping the innovative organizational culture (Salama, 2011). Specifically the CEOs of innovative companies play a significant role in creating an organizational environment that promote or slow down the innovation inside the organization (Johnson, 2009). Top Management introduces the values that shape the “Glue Dimension” of the organization. If these values promote innovation and changes, it will encourage more innovation and less imitation. On the other hand, if they are more concerned with respect for formal processes and procedures, this would promote more imitation than innovation. (Valencia et al, 2011). Leaders who adopt a democratic approach make people more comfortable to give their opinions and interact with each other to find new solutions (King and Anderson 2002). They should encourage variability and divergent thinking rather than the “drive for results” leadership style that seeks efficient execution. Innovation leaders should encourage people to look at problems from different perspectives, take unfamiliar positions, identify and test their assumptions, and take risks. (Soken & Barnes, 2008). In organizations that have strong innovative cultures, managers stress on creating the suitable atmosphere for members to innovate and back their innovators. Moreover, managers should accept the change being introduced by the innovation and also spread the concept of change among their workers (Dombrowski and Kim 2007, 199‐200). Teamwork and cooperation is also considered a very important aspect for organizational innovation to flourish. This doesn’t apply only to cross departmental work groups inside the organization, but also to alliances and collaboration with other organizations. Hyland and Beckett (2005) highlighted the value that team work adds to innovation by explaining that it allows members to complement each other’s skills, take into account different perspectives, share information, and thus generate higher quality ideas and reach proper implementation of new products, services or processes. Martin and Terblanche (2003) added that work teams enable organizational members to trust and respect one another, solve differences of opinions and communicate more effectively; thus, facilitate sharing the organizational values. Enhancing the quality of members inside the organization makes a significant effect on shaping its culture. Organization members are the ones who build the culture and maintain it, and that's why it is important to choose the suitable members that are always keen to introduce new ideas, and encourage other members when they find new solutions (Steele and Murray, 2004). A continuous learning environment where the skills and knowledge of organizational members are constantly developed is also considered an important determinant of innovative cultures (Irani, Sharp and Kagioglou, 1997). It is crucial to understand that all the above mentioned determinants cannot be developed in isolation of one another. They are all parts of one system, and, hence, they interact, affect, and are affected by each another (Martin and Terblanche 2003). Jackson and Hinchliffe (1999) suggested a road map for organizations to craft the innovation culture. First managers should start with the strategic direction they aim for and settle on a set of attitudes that are needed to achieve the strategy. Second, and very crucial, is to get the commitment of top management. It is also important to adjust the organizational structure to match the new strategy, eliminating or adding up some components. Then finally, make sure that organizational members have the necessary qualifications to implement the new vision. However, it is also important to note that cultural change takes time and effort and that resistance is expected. Cultural change would be more difficult in organizations where the culture is conservative, the hierarchy is vertical, the resources are scarce, and the communication is inefficient (Tidd, Bessant & Pavitt 2005).

3. Methodology In order to examine the determinants of innovative culture in different types of Egyptian organization, a study was conducted on a sample of 200 Egyptian employees in different local and multinational companies. These were reached through a reputable part time MBA program that accepts only students with at least two years of work experience. The study survey was derived from previous literature and was tested for validity by a

Hadia Abdel Aziz and Sandra Marcos panel of 3 academics in the field of innovation and Human Resource Management. A pilot study on 15 respondents was conducted and reliability was tested though a test re‐ test procedure that proved to have more than 70% correlations on all items. The survey consisted of 28 statements grouped (3‐4 statements in each group) to measure the eight determinants of innovation culture previously identified in literature, namely; innovation strategy, the organizational structure, resources to support innovation, behaviors and mechanisms promoting innovation, trust and open communication, management and leadership, teams work and collaboration, and quality development of organizational members. The survey statements were structured on a five‐level likert scale that ranged from “1 ‐Strongly Agree, 2‐ Agree, 3‐ Neutral, 4‐ Disagree, and 5‐ Strongly Disagree” Questionnaires were distributed to different classes of two admission rounds of the MBA Program. A total of 146 complete questionnaires were received back for analysis (73% response rate). While 79 respondents (54%) were employed by multinational companies, 67 respondents (46%) were employed by local companies. Data were analyzed using the SPSS to test the following two hypotheses: H1: All types of Egyptian Organizations lack the following determinants of innovative organizational cultures: clear innovation strategy, a flat and flexible organization structure, the availability of resources to support innovation, the institutionalization of favorable and supportive behaviors promoting innovation, trust and open communication, supportive management and leadership, teams work and collaboration, and continuous development of organizational members H2: Multinational companies exhibit a higher level of development on the previously mentioned determinants than local firms. Data was analyzed using SPSS V. 13. Frequency distribution and descriptive statistics were performed to describe employees’ response to different questionnaire items in terms of frequencies, mean and variability. The one sample t‐ test was used to examine the first hypothesis that all types of local firms lack the determinants of innovation culture, and Analysis of Variance (ANOVA) was used to test the difference between local and multinational companies on the above mentioned determinants.

4. Results Results of the one‐ sample t test confirm the first hypothesis that Egyptian organizations lack the cultural determinants of innovation. This is well proven for all determinants with a 95% confidence level as indicated by the figures in table (1). Table 1: One sample t‐test analysis – Innovation culture determinants for all types of organizations Dimension Innovation Strategy Organizational Structure Resources Supporting Innovation Behaviors promoting innovation Trust and open communication Management and Leadership Teamwork and collaboration Development Of organizational members

Mean 2.29 2.56 2.76 2.59 2.57 2.60 2.53 2.23

St. Deviation 0.89 1.00 0.97 0.88 0.87 0.89 0.93 0.95

T‐ test 3.897 6.079 9.470 8.139 7.947 8.188 6.984 2.932

P‐Value 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.004

Further analysis on multinational and local firms revealed that out of the eight examined determinants of innovation culture, two are evident in multinational firms. These include a well declared innovation strategy and the constant development of employees as indicated by the figures in table (2). Results of the Analysis of Variance (ANOVA) indicate that there is a significant difference between multinational and local firms in all the determinants of innovation culture except for teamwork and collaboration where the difference between local and multinational companies is not significant at a 95% confidence level. Although the difference between the two types of organizations on the Management and leadership dimension is still significant, however, it can be considered at a lower level with a p‐ value of 0.046 as indicated by the figures in table (3).

Hadia Abdel Aziz and Sandra Marcos Table 2: One sample t‐test analysis – Innovation culture determinants for multinational vs. local organizations Dimension Innovation Strategy Organizational Structure Resources Supporting Innovation Behaviors promoting innovation Trust and open communication Management and Leadership Teamwork and collaboration Development Of organizational members

Multinational Firms Mean T‐ test P‐Value 2.06 0.615 0.539 2.31 2.900 0.004 2.50 4.678 0.000 2.40 4.182 0.000 2.23 2.405 0.018 2.47 4.857 0.000 2.42 4.102 0.000 1.96 0.037 0.712

Mean 2.58 2.86 3.08 2.83 2.98 2.77 2.68 2.55

Local Firms T‐ test 5.050 6.578 8.752 7.305 8.912 6.705 5.798 4.789

P‐Value 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Table 3: ANOVA – difference between multinational and local organizations on innovation culture determinants Dimension

F‐ statistic

P‐Value

Innovation Strategy Organizational Structure

Multinational 2.06 2.31

Mean Local 2.58 2.86

9.803 10.967

0.001 0.001

Resources Supporting Innovation Behaviors promoting innovation Trust and open communication

2.50 2.40 2.23

3.08 2.83 2.98

12.196 6.703 20.393

0.000 0.004 0.000

Management and Leadership Teamwork and collaboration Development of organizational Members

2.47 2.42 1.96

2.77 2.68 2.55

3.263 2.451 12.620

0.046 0.096 0.000

5. Discussion The study revealed that, overall, Egyptian organizations are weak on all determinates of innovation culture. They lack a well defined and clear innovation strategy as they still don’t realize the importance of innovation as a source of sustainable competitive advantage. Most organizations have vertical structures with many managerial levels and with rigid rules and regulations that don’t allow for flexibility. Resources are usually planned for efficiency with no extra resources provided to support innovation including information, time, financial support, or systems. Supportive organizational behaviors towards innovations are also missing in Egyptian organizations as new ideas are rarely welcomed, mistakes are not tolerated and innovation is not rewarded. Egyptian organizations also don’t enjoy an environment of trust and open communication where organizational members can freely share experiences and exchange ideas. Business related communication is only expected to go through the formal vertical communication channels. Managers of Egyptian organizations are mostly conservative with low acceptance of risk taking or change. Over and above, team work and collaboration, whether internal or external is not encouraged or supported. Finally, employee development within an environment of constant learning is not a characteristic of Egyptian organizations. Further analysis revealed that while all the above is impartially true for local firms, multinational companies stand at a much better position in all dimensions. They still have vertical structures and rigid rules, but decision making is more decentralized. They provide more resources for innovation especially information, but not time or financial resources. They welcome new ideas, but do not provide incentives or tolerate mistakes, and they enjoy more open communication and a better climate of trust. However, multinationals are particularly developed in the dimensions of strategy and employee development. This is justified by the fact that most multinationals have a well declared innovation strategy and mission that reflect awareness of the importance of innovation in sustaining their competitive advantage. This strategy is communicated worldwide irrespective of the level of involvement of each subsidiary in the innovation outcome. They also have an international HR system that emphasizes employee development through consistent provision of training and development activities. The fact that these particular two dimensions are related to the companies’ international system is worth noting.

Hadia Abdel Aziz and Sandra Marcos On the other hand, analysis also revealed that there is no significant different between local and multinational organizations in the dimensions of team work and collaboration and management and leadership support. Both types of firms don’t encourage teamwork, group interaction, and collaboration and alliances in sharing knowledge and experience. In addition, managers of multinational firms are not much different than managers of local firms in being conservative, risk averse, and reluctant to change or to give space to their employees to try new ideas. This could be explained by the fact that the Egyptian culture is characterized by a high level of power distance and a very high level of uncertainty avoidance. Moreover, it is characterized by high degree of formalization where laws, regulations and control are preferred as a strategy to reduce uncertainty (www.geert‐hofstede.com). Due to this combination, leaders concentrate power and authority in their hands and people are expected to respect and obey those in leadership positions.

6. Recommendations Results revealed that in order for Egyptian organizations to be able to count on innovation as a driver for future growth, they need exert lot of efforts to change their cultures into more innovative ones. Following the roadmap developed by Jackson and Hinchliffe (1999); first, Egyptian organizations must change their strategic direction based on thorough and deep understanding of the value of innovation for the organizations and the organizational capabilities required for successful innovation. Innovation values and attitudes such as risk taking, trust and collaboration must be established, encouraged, and communicated as core values of the organizations. Top management commitment and willingness to change is crucial to the success of the whole effort and, therefore, their buy in must be ensured. The organizational structure must be flattened with less hierarchical communication and more open doors, and rules and regulations should be made minimal and flexible. Resources should be made available to enable employees to communicate their ideas and implement them. These should be supported with organizational behaviors that would reward successes while dealing with mistakes and failures as a learning experience. Finally, team work and collaboration should be encouraged in an environment of trust and constant learning. Change agents and idea champions would play a very important role in supporting the above efforts of cultural transformation. While change agents are people inside or outside the organization who encourage change and handle resistance, idea champions are organizational members who become fascinated by a bright idea, and therefore, act beyond their normal organizational role to promote its development (King and Anderson, 2002). Different championing strategies are recommended to be used in different contexts. In the context of high power distance cultures, as in the case of Egypt, hierarchical championing is most suitable. Using this championing strategy, idea champions don’t challenge existing hierarchy; on the contrary, they try to channel innovations through the formal hierarchy by getting the buy in of top management (Shane, 1994). Results also highlight a very important area worthy of further investigation, that is, the performance and role of multinational subsidiaries in promoting innovation in Egypt. As the results indicate, although subsidiaries of multi‐national companies in Egypt have declared innovation strategies and are constantly developing their employees, they still have rigid rules and regulations, don’t provide resources to support innovation, don’t reward innovative behaviors, and don’t encourage risk taking. This would imply that multinationals, despite their innovation awareness and orientation, don’t promote innovation at their Egyptian subsidiaries. Hypothetically, subsidiaries of MNCs have a strong role in assimilating knowledge from different internal and external sources, and integrating and utilizing this knowledge to produce successful innovations (Phene and Almeida, 2008). Most importantly, MNCs subsidiaries play an important role in knowledge transfer and technology spill over to local firms (Abereijo, Ilori, and Onomola, 2012). Whether MNCS in Egypt actually play these roles and whether Egyptian FDI policies are tailored to ensure that they play them is a question worth of further research.

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Rethinking Employee Contribution: A Framework for Promoting Employee‐Driven Innovation Tuomo Alasoini Tekes, Helsinki, Finland tuomo.alasoini@tekes.fi Abstract: Finland is usually considered as one of the leading countries in innovation activity and policy. A new national innovation strategy, under the framework of “broad‐based innovation policy”, was approved in 2008 by the government. The strategy is based on the idea that the focus of innovation policy should be shifted increasingly to the promotion of demand and user‐driven innovation, and the promotion of better balance between technological and non‐technological innovations. Recent international evaluators, however, argue that the content of the new approach is still far from clear. This paper examines what broad‐based innovation policy could be in practice by using the Tekes programme “Liideri – Business, Productivity and Joy at Work” (2012–18) for the development of business through renewals in management, employee contribution and forms of working as an example. The paper focuses on the programme’s conceptual framework for promoting employee‐driven innovation (EDI). EDI is considered as a boundary‐spanning object, which helps exceed some of the limitations inherent in two more traditional policy discourses, industrial relations‐based workplace development and technology‐oriented innovation policy, giving a new vigour to innovation policy thinking. The paper contains an analysis on employees’ role in different approaches to productivity development and innovation, attempting to clarify the specific content of EDI. Thereafter, the paper tracks down the relationships of EDI with traditional workplace development and innovation policy and how employees’ contribution is viewed in them. This is followed by a short presentation of the Liideri programme. In the following section, the programme’s conceptual framework for the promotion of EDI is examined in greater detail. The paper deals separately with factors enabling EDI, EDI as a process and impacts of EDI. The paper suggests that the promotion of EDI needs to be closely interwoven with the development of management and raises also some critical viewpoints concerning EDI‐promoting policy approach. Keywords: employee‐driven innovation, employee participation, innovation policy, workplace development

1. Introduction Finland generally places near the top of international comparisons of innovation activities and systems (European Commission 2012; OECD 2012). Back in the early 1990s, Finland was the first country in the world to adopt a framework for science and technology policy that was based on systematic adoption of the concept of a national innovation system (Miettinen 2002). However, criticism of the framework’s one‐sided orientation towards technological innovations and engineering and natural sciences began to increase in the 2000s. In 2007, the Government assigned a high‐level group to draw up a proposal for a new national innovation strategy for Finland. The group submitted a proposal for a new kind of “broad‐based innovation policy” (Aho et al. 2008). The central idea of the proposal involved further expanding the target of innovation policy to give more significance to non‐technological innovations and increasing synergies of technological and non‐ technological innovations. The proposal also placed greater emphasis on the role of customers, users and employees in innovation. The Government approved the central recommendations of the strategy proposal in 2008. However, some international experts have suggested that Finland has not progressed very far in applying its new innovation thinking. Sabel and Saxenian (2008) argue that in key industries Finnish companies have focused too heavily on development paths that were successful in the past and on incremental process innovations. An international evaluation of the Finnish innovation system considers the content of the new broad‐based innovation policy to still be fuzzy, vague and potentially even “too broad” (Veugelers et al. 2009). Based on a recent Nordic comparison, Finland especially trails Denmark with regard to framework conditions of new innovation thinking (FORA 2009). Employees’ participation in development and innovation has in Finland more commonly occurred within the rather narrow framework of lean thinking than, for example, in Sweden or Denmark (Valeyre et al. 2009).

2. Aim and content This paper examines broad‐based innovation policy in practice, focusing on the “Liideri – Business, Productivity and Joy at Work” programme (2012–18) of the Finnish innovation funding agency Tekes to promote employee‐ driven innovation (EDI). This is used as an example of integrating workplace development into the new concept of innovation policy. We consider this case especially interesting, not only because Finland is usually

Tuomo Alasoini ranked as one of the leading‐edge countries in innovation policy, but also because Finland has gained a reputation as one of the leading countries in workplace development in the 2000s as well (Eeckelaert et al. 2012). The paper starts by clarifying the concept of EDI. Thereafter, we track down the relationships of EDI with two policy discourses – the traditions of industrial relations‐based workplace development policy and technology‐ oriented innovation policy. This is followed by a presentation of the Liideri programme and its framework for promoting EDI. In conclusion, the paper discusses challenges related to EDI‐promoting policies.

3. The employee in new innovation models Many influential management authors stress the need for a radical reform of management principles that have their roots in the history of the industrial period. For example, Hamel (2007) suggests that up to 80% of people’s value creation potential for the organisation is currently linked to their initiative, creativity and passion. In recent years, innovation research has focused on finding new models that would allow companies to accelerate innovation and make better use of diverse types of knowledge. Discussion on the new models has also highlighted a more active and diverse role in innovation for the ordinary employees. The role of ordinary employees contained in the new innovation models differs fundamentally from traditional Tayloristic view. The new models include similarities, but also differences, in comparison with the lean thinking and its innovation and development concepts. The central difference between lean and Tayloristic thinking can be considered the elimination of the strict line between planning and doing so that employees and their teams are given responsibility for continuous development of activities. Lean thinking can be characterised as “democratic Taylorism”, in which use of development methods and tools is taught and responsibility for development delegated from management and support functions to operative teams. One of the the guiding principles of lean thinking is standardisation of working methods and procedures. Standardisation serves as a foundation for their collective application in teams, their continuous improvement and their dissemination as “best practices” throughout the organisation. However, the planning ideology of lean thinking does not differ from Taylorism in its view of the content of operative tasks. According to lean thinking, breaking tasks down into small entities is often justified for reasons of standardisation and the opportunities for collective learning and continuous improvement that it offers (Adler and Cole 1993; Womack and Jones 1996). Lean thinking primarily approaches the employees’ role from the perspective of production management principles and techniques. High‐involvement innovation (HII) approaches their role from the perspective of learning theories. Its central theoretical framework is a resource‐based view of the organisation. The basic idea of HII is that an organisation can develop its abilities in a systematic manner and develop into a learning organisation. Bessant (2003) differentiates between eight of such key abilities. In particular, the approach emphasises the importance of the personnel’s involvement at all levels of the organisation. The personnel’s role is not limited to incremental innovations; rather, as the organisation’s ability of continuous improvement develops, the ability of the personnel to contribute also to radical innovations is expected to increase. Employee‐driven innovation is a broader umbrella concept that is not as closely linked to a specific theoretical view as HII. Rather than being a management or organisation‐driven concept to the same extent as lean thinking or HII, EDI makes employees’ internal desire for creativity, learning and development a clearer starting point. At a general level, EDI refers to active and systematic participation of employees in ideation, innovating and renewing of products and services and ways of producing them, with a view to creating new solutions that add value to customers. Within this generic definition, Høyrup (2012) has more specifically identified EDI processes on three different levels. In its least institutionalised form, EDI refers to self‐organised (continuous) remaking of jobs and activities. Employees plan and implement solutions that help them solve work‐related challenges and problems in a creative manner that is productive for the entire organisation. The second level is (fully) employee‐driven innovation that produces solutions that arise from employees’ self‐initiated ideation and are both recognised and acknowledged by the management. The most institutionalised level is employee‐ involving innovation. This refers to solutions based on commissions by management, customers or various stakeholders in which the employees have actively participated.

Tuomo Alasoini Practice‐based innovation (PBI) is also a broad umbrella concept. Its roots lie in discussion on the differences between different methods of knowledge creation in innovation research. Harmaakorpi and Melkas (2011) use the term PBI for innovations that arise by means of learning by doing, using and interacting (DUI mode) for which the starting point is practical problems (Mode 2), as opposed to science or technology development (STI mode). The writers further divide PBIs according to whether they are typically based on interaction and co‐ operation between organisations (DUI/Mode 2a) or interaction and co‐operation within an organisation (DUI/Mode 2b). In the latter type in particular, employees play a central role. The key requirement for ensuring that employees have a significant role in innovation is the elimination of organisational “silos” that prevent interaction and co‐operation. In the DUI/Mode 2b format, PBI focuses on organisational (or other social) and service innovations. The approaches diverge from each other not only in terms of theoretical rationale and their central innovativeness factors but also in their management rhetoric (Table 1). Lean thinking is more clearly based on a rational management rhetoric that emphasises the importance of production management, explicit knowledge and standardised operational processes. With regard to management rhetoric, PBI differs most clearly from lean thinking in that it stresses a perspective that emphasises the importance of normative management thinking, work community factors and tacit knowledge. Table 1: Employees’ role in development and innovation: comparison of four approaches

Lean thinking

High‐involvement innovation

Employee‐driven innovation

Innovation type that is the object

Mainly incremental

Incremental and radical

Central approach to innovations Underlying management rhetoric Key property promoting innovation in the organisation Conceptual degree of explicitness

Production management

Mainly incremental Increasingly radical as innovation capability develops Learning theories

Rational

Mainly rational

Rational‐normative

Standardised operational processes

Organisational innovation capability comprising eight key abilities Explicit framework

Enabling management

Interaction and co‐ operation within the organisation

Broad umbrella

A group of principles and generally applied techniques

Learning theories

Practice‐based innovation (DUI/Mode 2b) Mainly incremental

Innovation research Organisational culture Normative

4. Employee participation in different policy discourses Employee participation has long been a central theme in research on industrial relations (IR) (Crouch and Heller 1983; Garibaldo and Telljohann 2010). Employee participation can be divided into representative participation by employee representatives, works councils or other similar organs and direct participation by ordinary employees. In workplace development that originates from the IR framework, both forms of participation have been examined from the viewpoint of the employees’ right to participate in decision‐making and to be heard or at least informed in addition to the viewpoint of the benefits gained by the companies. Underlying the “benefit aspect” has been a constructivist view, i.e. the role of employee participation is not to ensure frictionless adoption of a ready‐made set of “high‐performance work practices”, but to help companies implement collaboratively constructed changes for the improvement of productivity and the quality of working life (Alasoini 2011). In traditional, science and technology‐oriented innovation policy, employee participation has typically not been made an issue in any way. If participation has been discussed at all, it may have been seen as a method of overcoming resistance by employees and making them commit to the adoption of new solutions, developed by someone else. In new broad‐based innovation policy discourse, a growing interest in agile, open and distributed innovation models has increased interest also in the role of ordinary employees. Employees’ active role in innovation is regarded as an increasingly important competitive factor to companies as market changes

Tuomo Alasoini will take place faster and they will become more difficult to predict, as producing innovation will be increasingly spread out from big corporations to smaller business with no specialised R&D personnel due to networking and outsourcing, and as the general level of skills and competencies in the workforce will rise (Alasoini 2012). The rationale of employee participation in the form of EDI differs from both the rationale of traditional workplace development policy and technology‐oriented innovation policy (Table 2). The new rationale “exceeds” the traditional IR‐based viewpoint by giving significant importance to broad employee participation in development and making it a key success factor in businesses where fast renewal and innovation are central competitive factors. The new rationale “exceeds” the viewpoint of traditional technology‐oriented viewpoint, as well, by giving significant importance to broad employee participation, not as a method of persuasion, but as a factor for generating collective learning and reinforcing a sense of inclusiveness among employees in connection with rapid changes in the workplace (see section 6.3.). Table 2: The rationale of employee participation in different policy discourses Forms of participation Typical objects of participation Rationale of participation

IR‐based workplace development policy Direct and representative participation Work tasks, work organisation and working conditions Employees have the right to participate through delegation, consultation, hearing or having access to relevant information. Collaboration between management and employees improves the quality and novelty value of new solutions.

Science and technology‐ oriented innovation policy Direct and representative participation New products and processes

Participation helps ‐ overcome employee resistance to the adoption of new solutions. ‐ adapt solutions, developed jointly by management and experts, to better suit local conditions by giving employees an opportunity to implement small adjustments.

Broad‐based innovation policy Employee‐driven innovation New products, services, processes, business models, work organisation, etc. Participation ‐ is a key success factor in complex environments where networking, fast renewal and innovation are central competitive factors. ‐ generates collective learning and reinforces a sense of inclusiveness among employees in connection with rapid changes.

5. The Liideri programme in a nutshell In 2012, Tekes launched a new six‐year programme, entitled “Liideri – Business, Productivity and Joy at Work”. Liideri is a programme for the development of business, in which companies renew their operations through developing management and forms of working and actively utilising the skills and competencies of their personnel. The purpose of Liideri is to be a “next‐generation” workplace development programme that represents an approach in keeping with a broad‐based innovation policy (Alasoini 2012). At the project level, this means, an interconnecting link between traditional objectives and targets in the development of working life, such as work productivity and quality of working life, and a link between them and corresponding objectives and targets in traditional innovation policy, such as renewals of products, services and business models. The programme has three focus areas. The first of them is management 2.0. This concept refers to management principles, processes and practices, which help an organisation to promote the initiative, creativity and innovation potential of personnel, with a view to achieving competitive edge based on them. The second focus area concerns employee‐driven innovation, using the framework presented by Høyrup (2012) as a starting point. The third focus area concerns new ways of working. This concept refers to work, which transcends the boundaries of time‐honoured temporal, spatial and organisational patterns and forms of work, or which in some other recognised way embody principles of management 2.0. Liideri supports research, development and dissemination of information to support Finnish workplaces in these three areas.

6. Conceptual framework for promoting employee‐driven innovation As demonstrated above, EDI is not a management or organisation‐driven concept to the same extent as lean thinking or HII. However, this does not mean that it doesn’t require strong management support (Høyrup 2012; Kesting and Ulhøi 2010). It could even be assumed that successful EDI requires change that extends all

Tuomo Alasoini the way to the principles of management, as called for by Hamel (2007). This view is also the starting point for the Liideri programme’s conceptual framework for promoting EDI (Figure 1). Each section of the following figure is examined below.

Management principles

Management processes Organisation of work Infrastructure of work

Employee-driven innovation

Ideati on

Innovat ing

Value creati on

Operational performance Well-being at work

Values and culture that support employees’ participation in innovation

Figure 1: Liideri programme’s conceptual framework for promoting employee‐driven innovation

6.1 Factors enabling employee‐driven innovation Management principles refer to fundamental assumptions or beliefs that guide management concerning the basic nature of people, what motivates people and what makes them perform well (Birkinshaw 2010). The fundamental questions include the extent to which people can be trusted, the amount of power and responsibility they can be given, and the extent to which people can be motivated by means of purely financial vs. other kinds of incentives. A business environment in which companies increasingly compete with the competitive advantages arising from innovations requires different principles for managing people than those needed in mass production. Hamel (2012) has proposed that management in the future should be based on the same values as its central technology architecture – the interactive internet. Such values are community, transparency, freedom, meritocracy, openness and collaboration. Management processes refer to an entity of interconnected practices that apply to management, helping the organisation reach its objectives (Birkinshaw 2010). Organisations have generic management processes that are independent of the form of ownership, industry or business model. Different organisations may, however, also have specific management processes that are tied to the business model. One of them is innovation management. One may assume that in organisations that seek lasting, long‐term competitive advantage by promoting EDI, the significance of a number of supporting management processes to innovation management is emphasised. These include, in particular, knowledge management, diversity management, human resource management and value management (Alasoini 2012). The new principles of management should also be reflected in the principles and practices applied to forms of work organisation and working and should be compatible with them. Such principles and practices differ in many ways from organisational thinking based on fragmentation of work tasks, characteristic of industrial mass production. Principles that enhance people’s initiative, creativity and commitment with regard to forms of work organisation and working include decentralisation, self‐steering, process‐orientation, customer‐ orientation, emergence, team base, networking and agility. New emerging forms that are based on these general principles can be very different. Common to all of them, in particular, is the fact that management

Tuomo Alasoini becomes a more shared activity and that work is done in a more individual ways and is more decentralised in terms of being done in different locations, at different times and with changing groups of people in different networks. Another important precondition for the dissemination of new forms of working is the continuous development of ICT, which creates new opportunities for reducing costs and increasing connectivity and speed of operations. The social infrastructure of work refers to various standards, systems or established practices that help people successfully handle their work tasks or solve problems encountered at work. Typical examples of the highly institutionalised social infrastructure of work include systems related to quality, information, enterprise resource planning, rewarding, working times, occupational health and safety, labour‐management negotiations, etc. Furthermore, supervisory work, facility solutions or various established co‐operation relationships can also be considered to be corresponding social infrastructure of work. New ways of managing people and organising work also require changes in these structures. The difficulty in changing the social infrastructure of work, underestimation of its importance during changes or mutually conflicting steering impacts of its various sub‐systems can represent major barriers to organisations’ possibilities for renewal. Organisations can achieve values and a culture that support the personnel’s participation in innovation by means of the above changes. The foundation for such values and culture could be considered as a kind of a moral contract or a fundamental, jointly accepted code of conduct between management and employees. It contains a shared view of what kind of conduct is correct, sensible and desirable in the organisation and what kind of remuneration employees are entitled to in return for their work contributions and the deployment of their skills and competencies. Remuneration does not refer only to financial compensation but also to intangible rewards such as trust, respect, loyalty, safe employment relationships or employability.

6.2 Employee‐driven innovation as a process The process of EDI is divided into three phases: ideation, innovating and value creation to customers. For succesful EDI activities to occur, it is extremely important that ideation and innovating and learning, which is derived from the value creation process, are seen as a communal process in the organisation or community in question. The communal nature (i.e. the opportunity to make use of different types of knowledge and create deep commitment) and the dynamism (i.e. the opportunity to act rapidly) of the new innovation thinking are what make it stand out from traditional direct participation and suggestion schemes. Collaborative development can take place in or be supported by various forms of organising, supplementing each other. Self‐ managing operational teams, for instance, may be at their best in producing small, incremental innovations and development ideas with fairly limited impacts. Networks of several organisations and various interactive virtual forums provide forms of organising with the opportunity to combine different types of knowledge and create the prerequisites for a new way of thinking that could lead to radical innovations as well. The communal nature of EDI also applies to learning. The arrows in Figure 1 that point backwards from the ideation, innovating and value creation phase illustrate how innovation production and organisational learning are, at best, interwoven with each other into a two‐part process of knowledge creation that simultaneously produces innovations and organisational learning. Traditionally, these have been considered as two separate processes: expert‐oriented innovation generation and knowledge acquisition based on training or learning on the job. Innovations, however, typically emerge through interactive processes. The generation of knowledge manifests itself as a process which, on the one hand, creates product, service and process innovations, but at the same time also generates learning among the participants in the innovation process, thereby improving the company’s innovation capabilities for the future. Innovations and organisational learning are, at best, the conscious, mutually supportive results of the same process.

6.3 Impacts of employee‐driven innovation Figure 1 separates the impacts of EDI into operational performance and well‐being at work. Direct and indirect impacts can be examined separately for both of these items (Table 3). With regard to operational performance, direct impacts arise as the accelerated pace of renewal for products, services and their production resulting from EDI increases the organisation’s ability to produce value for its customers. Better value creation ability can be seen, for example, in the developing properties of products, reduction in operational disturbances, shorter lead times or increased material and energy efficiency.

Tuomo Alasoini Table 3: Various impacts of employee‐driven innovation Operational performance Well‐being at work

Direct effects Improvements and renewals in products and services and in ways of producing them Increased “employee‐friendly” solutions in products, services and in ways of producing them

Indirect effects Broad‐based organisational learning Increased experience of inclusiveness in change situations among employees

Indirect impacts on operational performance are related to the organisational learning achieved by means of EDI. Organisational learning is broad‐based when ideation and innovating are carried out as genuine communal processes that also include the opportunity for joint critical reflection and evaluation of the process. The potential strength of EDI for other forms of innovation activities lies in the opportunity that it provides for producing more broadly‐based organisational learning within the organisation. This kind of learning means that, during the process of ideation and innovating, the organisation can simultaneously develop its own way of ideation and innovating and thus achieve long‐term competitive advantage for its operations. The direct impacts of EDI on perceived well‐being at work are associated with the fact that employees’ active and systematic participation means that issues of importance to them are better taken into consideration in the renewals. However, the indirect impacts on well‐being that result from the personnel’s experience of inclusiveness may be even more important. In particular, the opportunities to exert influence and utilise one’s skills and competencies, together with a feeling of the importance of one’s contribution and appreciation for it in conjunction with changes, contribute to the experience of inclusiveness. The significance of inclusiveness can be considered through the concept of a sense of coherence. This concept has recently been used to examine the problems of well‐being at work during changes in working life as well (Docherty et al. 2008). Rapid changes jeopardise the prerequisites of people to see work for their part as a comprehensible, manageable and meaningful entity. In a situation where challenges arising from change exceed people’s resources, negative stress will arise and consequently cause negative effects on health and well‐being. Inclusiveness can be regarded as boosting the sense of coherence in all three dimensions (Alasoini 2012).

7. Summary and conclusions This paper examined EDI as a boundary‐spanning object between traditional workplace development policy and innovation policy. A special focus was the Liideri programme’s framework for promoting EDI. This was used as an example of the new broad‐based innovation policy in practice. In relation to traditional IR‐based workplace development, EDI includes a new rationale regarding employees’ participation and a new “process‐ like” view of the quality of working life. From the viewpoint of traditional technology‐oriented innovation policy, EDI means expanding the group of relevant innovation actors and detachment from the concept of a narrow, institution‐centred innovation system. EDI is not as management or organisation‐driven concept as some of its counterparts. However, this does not mean that it has no need for strong management support. On the contrary, the credibility and long‐term nature of the support require management principles that recognise and acknowledge the role of ordinary employees as active and legitimate subjects in conjunction with change. Extending the reform to the principles of management is often necessary, because knowledge that derives from ordinary employees has in many organisations been traditionally undervalued in comparison with knowledge obtained from external sources. There is no reason to limit the scope of EDI to incremental improvements. Also radical innovations are often employee‐driven; they derive from doing something unique, valuable and difficult to imitate or plan in detail through standard management procedures. Without sufficient planning and managerial and organisational know‐how, attempts to promote EDI can lead to new problems in well‐being at work as well. For example, work load will increase if innovating is mainly experienced as an extra duty; employees will become frustrated if the time used for innovating and the work contribution do not lead to visible results; feelings of inequality will become more common among employees if they feel that the resources, results or effects of innovating are not distributed equally; or tensions within the work community will increase and co‐operation will deteriorate if innovating is not seen as a communal

Tuomo Alasoini process. Such matters have not historically been on the agenda of innovation policy or innovation management. Broad‐based innovation policy does not refer only to a linear expansion of the traditional innovation policy area to some new areas. For example, integrating EDI into the new concept of innovation policy will also create radically questions. Responding to them will require novel understanding and competence at the policy level and open‐minded rethinking of management processes at the company level.

References Adler, P.S. and Cole, R.E. (1993) “Designed for Learning: A Tale of Two Auto Plants”, Sloan Management Review, Spring, pp. 85–94. Aho, E. et al. (2008) Proposal for Finland’s National Innovation Strategy, Ministry of Employment and the Economy, Helsinki. Alasoini, T. (2011) “Workplace Development as Part of Broad‐Based Innovation Policy: Exploiting and Exploring Three Types of Knowledge”, [online], Nordic Journal of Working Life Studies, Vol 1, No. 1, pp. 23–43, http://ej.lib.cbs.dk/index.php/nordicwl/article/view/3311/3550. Alasoini, T. (2012) “A New Model for Workplace Development in Finland: Rethinking Employee Participation and the Quality of Working Life in the Context of Broad‐Based Innovation Policy”, International Journal of Action Research, Vol 8, No. 3, pp. 245–265. Bessant, J. (2003) High‐Involvement Innovation: Building and Sustaining Competitive Advantage through Continuous Change, John Wiley, Chichester. Birkinshaw, J. (2010) Reinventing Management: Smarter Choices for Getting Work Done, Jossey‐Bass, San Francisco. Crouch, C. and Heller, F.A. (Eds.) (1983) International Yearbook of Organizational Democracy: Volume I, John Wiley, Chichester. Docherty, P., Kira, M. and Shani, A.B.R. (Eds.) (2008) Creating Sustainable Work Systems: Developing Social Sustainability, Routledge, London. Eeckelaert, L., Dhondt, S., Oeij, P., Pot, F., Nicolescu, G., Trifu, A. and Webster, J. (2012) Review of Workplace Innovation and Its Relation with Occupational Safety and Health, Publications Office of the EU, Luxembourg. European Commission (2012) Innovation Union Scoreboard 2011, EU, Brussels. FORA (2009) Nordic Innovation Monitor 2009, Nordic Council of Ministers, Copenhagen. Garibaldo, F. and Telljohann, V. (Eds.) (2010) The Ambivalent Character of Participation: New Tendencies in Worker Participation in Europe, Peter Lang, Frankfurt a/M. Hamel, G. (2007) The Future of Management, Harvard University School Press, Boston. Hamel, G. (2012) What Matters Now: How to Win in a World of Relentless Change, Ferocious Competition, and Unstoppable Innovation, Jossey‐Bass, San Francisco. Harmaakorpi, V. and Melkas, H. (2011) ”Epilogue: Two Modes of Practice‐Based Innovation”, in Melkas, H. and Harmaakorpi, V. (Eds.) Practice‐Based Innovation: Insights, Applications and Policy Implications (pp. 437–452), Springer: Heidelberg. Høyrup, S. (2012) “Employee‐Driven Innovation: A New Phenomenon, Concept and Mode of Innovation”, in Høyrup, S., Bonnafous‐Boucher, M., Hasse, C., Lotz, M. and Møller, K. (Eds.) Employee‐Driven Innovation: A New Approach (pp. 3–33), Palgrave Macmillan, Houndmills. Kesting, P. and Ulhøi, J.P. (2010) “Employee‐Driven Innovation: Extending the License to Foster Innovation”, Management Decision, Vol 48, No.1, pp. 65–84. Miettinen, R. (2002) National Innovation Systems: Scientific Concept or Political Rhetoric, Edita, Helsinki. OECD (2012) Science, Technology and Industry Outlook 2012, OECD, Paris. Sabel, C. and Saxenian, A. (2008) A Fugitive Success: Finland’s Economic Future, Sitra, Helsinki. Valeyre, A., Lorenz, E., Cartron, D., Csizmadia, P., Gollac, M., Illéssy, M. and Makó, C. (2009) Working Conditions in the European Union: Work Organisation, Eurofound, Dublin. Veugelers, R. (2009) Evaluation of the Finnish National Innovation System, Ministry of Employment and the Economy, Helsinki. Womack, J.P., Jones, D.T. (1996) Lean Thinking: Banish Waste and Create Wealth in Your Corporation, Simon&Schuster, New York.

Environmental Innovation and Financial Performance: The Moderating Effect of Motives and Firm Size Petra Andries1 and Ute Stephan2 Centre for R&D Monitoring, K U Leuven, Belguim 2 Institute of Work Psychology, University of Sheffield Management School, UK

petra.andries@kuleuven.be Abstract: Although evidence shows that SMEs display very different environmental behavior than large firms, there is limited understanding of how firm size affects the relationship between environmental innovation and firms’ economic performance. In line with the resource based view, we hypothesize that the effect of environmental innovation on firm performance will decrease with firm size. Using survey data and annual account data on 1712 Flemish firms, we demonstrate how the moderating effect of firm size depends on whether these innovations are developed as a response to customer demand, to government regulation or subsidies, or due to voluntary codes of conduct in the industry. In particular, environmental innovations motivated by government regulation and subsidies have a positive effect on large firms’ economic performance, but a negative effect on that of small firms. Environmental innovations introduced because of voluntary industry codes of conduct or because of customer demand, have the same effect in both small and large firms. This paper is the first to demonstrate important boundary conditions related to firms’ size and motives under which environmental innovation results in higher firm performance. Its results have important implications for firms’ environmental strategies and for environmental policy development. Keywords: environmental innovation, financial performance, firm size

1. Introduction Over the past two decades, we have witnessed an increased debate and interest in environmental sustainability and regulation among academics, policy makers and industry. Traditionally, environmental economists have argued that environmental regulation threatens firm competitiveness and profitability by increasing capital and labor cost, diverting management attention, and crowding out more productive investments (Christiainsen and Tietenberg, 1985; Palmer, Oates and Portney, 1995). In the middle of the nineties, Michael Porter and his co‐author Claas van der Linde provoked great controversy by going against this general belief, arguing that well‐designed environmental regulations can pressure companies to become more efficient and can initiate innovation, thereby improving firm competitiveness and profitability (Porter, 1991; Porter and van der Linde, 1995). The discussion between defenders and critics of this so‐called “Porter Hypothesis” prompted a vast number of empirical studies finding a positive effect of environmental responsibility on firms’ economic performance (see Orlitzky, Schmidt and Rynes, 2003 for a meta‐analysis). However, these studies predominantly look at large firms. This is remarkable, since SMEs are known to display a very different environmental engagement than large firms. Evidence (for an overview, see Lepoutre and Heene, 2006) shows that, although most owners and managers of SMEs believe that the environment is an important issue, SMEs are much less likely than large firms to engage in environmental actions (Merrit, 1998) and the environmental activities they engage in are limited to small‐scale, ad‐hoc problem solving, such as emission reduction as opposed to pollution prevention (Hillary, 1997, 2000). Furthermore, while large firms often engage in voluntary environmental activities, SMEs are more responsive to regulatory n dother stakeholder pressures (Darnell et al., 2010). Given these differences in environmental behavior and responsiveness to environmental regulation between SMEs and large firms, this paper studies whether the effects of environmental actions on firms’ financial performance depend on firm size

2. Literature background 2.1 Environmental innovation Already in 1987, the World Commission on Environment and Development warned against the negative impact of economic growth on the natural environment. Governments and pressure groups around the world have been promoting the concept of ‘sustainable development’, which implies balancing economic development and improvement in environmental performance. An important way of improving environmental performance is through environmental innovation. Eiadat et al. (2008) define environmental innovation as a class of

Petra Andries and Ute Stephan manufacturing practices that include source reduction, pollution prevention, and the adoption of an environmental management system (Eiadat et al., 2008, pp. 133). Although the concept of sustainable development is by now well‐known, companies differ significantly in terms of their environmental innovation strategies. While some proactively modify current or develop new products, processes and management system, others merely do so when forced by legal and regulatory requirements (Steger, 1993; Van Wassenhove and Corbett, 1991). In particular, SMEs are much less likely than large firms to engage in voluntary environmental actions (Merrit, 1998) and point to regulation as the most important reason for adopting environmental improvement programs (Charlesworth, 1998; Petts et al., 1999). Recent work shows that they are more responsive to regulatory, value‐chain and internal stakeholder pressures (Darnell et al., 2010). If we assume that companies are rational in their adoption of environmental practices, this difference in strategy suggests that not all firms benefit equally from environmental innovation and that firm size is a moderating factor in this respect.

2.2 Firm size and the effects of environmental innovation Traditionally, economists have argued that there is an inherent trade‐off between environmental sustainability and firms’ economic performance. Expenditures on environmental innovation were expected to increase capital and labour costs, divert management attention and crowd out other, more productive investments (Palmer, Oates and Portney, 1995; Christiaeinsen and Tientenberge, 1985). More recently however, scholars in the field of industrial ecology claim that environmental activities can produce a win‐win situation for both the firm and the environment (Nelson, 1994; Panayatou and Zinnes, 1994; Esty and Porter, 1998; Reinhardt, 1999; Hart, 1995). Through the development of environmental innovations, firms can reduce waste disposal and raw materials cost, increase product value and firm competitiveness due to improved reputation and customer demand for environmental‐friendly products or services, reduce public and community pressure, and even help shape future regulations (Khanna, 2001; Yang et al., 2011; Konar and Cohen, 2001). Engagement in environmental innovation is hence expected to positively influence firm performance: H1: Environmental innovation has a positive effect on firms’ economic performance. However, according to the resource‐based view of the firm (Nelson and Winter, 1982; Wernerfelt, 1984; Barney, 1991), a firm’s resources and capabilities are crucial determinants of its innovative performance. Although SMEs with a highly proactive approach to environmental innovation exhibit a significantly positive financial performance (Aragón‐Correa et al., 2008), many small firms may not have the necessary resource configurations and organizational practices to deal with the multi‐dimensional nature and broad scope of environmental innovation (Noci and Verganti, 1999, Russo and Fouts, 1997; Darnall et al., 2007). As Khanna (2001, p. 310) explains, “Larger firms may experience lower marginal costs of abatement due to scale economies and have more personnel to meet the administrative and technical requirements”. They may also reap more benefits from environmental innovations because they can experience an increase in demand from a larger number of customers, and because – due to their higher visibility – their environmental activities have a greater influence on future environmental regulations (Khanna, 2001). Therefore, we hypothesize that: H2: The impact of environmental innovation on firms’ economic performance is moderated by firm size. Smaller firms reap fewer benefits from environmental innovation compared to large firms.

3. Data and methods 3.1 Sample In 2009, we surveyed a stratified random sample of 4901 Flemish companies regarding the environmental innovations they had developed in the period 2006‐2008. The companies – including private and publicly listed firms ‐ were selected from a broad range of manufacturing and service industries and from different size classes. After sending two reminders by regular mail and after intense telephone follow‐up, the response rate was 45 percent (2202 firms). A non‐response survey was conducted and showed no significant differences between respondents and non‐respondents with respect to the core variables. We merged our survey data to the BELFIRST database, which provides detailed information on Belgian firms’ financial performance. Each year, the majority of Belgian firms (including the Flemish firms) are legally bound to file their annual accounts at the Central Balance Sheet Office in order to provide third parties with reliable information on their financial health, employment and development (Sels et al., 2006). Subsequently, these data are added to the BELFIRST

Petra Andries and Ute Stephan database, an electronic database containing financial information on Belgian companies and businesses. After merging our sample of 2202 firms and after removing missing values on the variables that we constructed, we obtained our final sample of 1712 firms.

3.2 Measures and descriptive statistics 3.2.1 Environmental innovations An important shortcoming of many existing studies is their focus on either voluntary or regulation‐induced environmental innovations. Many of them investigate the effect of environmental regulation without controlling for the fact that a firm’s environmental innovation may be the results of a change in customer demand and not of the environmental regulation following these changes in demand (Blanco, Rey‐Maquieira and Lozano, 2009; Brännlund and Lundgren, 2009). By studying regulatory‐driven environmental innovation without controlling for voluntary activities, or vice versa, omitted variable bias may arise. We avoid this problem by asking firms about their voluntary as well as their regulation‐induced environmental innovations. In particular, we asked the firms whether they had introduced in the period 2006‐2008 any product, process, organizational, or marketing innovation that had resulted in environmental benefits (either for the firm itself or for the users of the innovation). If yes, we asked them whether or not these innovations were introduced as a response to (1) current environmental regulation or taxes, (2) expected future environmental regulation or taxes, (3) the availability of subsidies or other public financial incentives for environmental innovation, (4) an existing or expected future customer demand for environmental innovations, (5) voluntary codes of conduct or agreements to stimulate environmental responsibility in their industry. Companies did not need to choose between these five options; they were given the possibility to choose multiple motives. Given the high correlation between the answers to the first two items, we grouped them into one dummy variable Regulation, indicating whether or not the firm had introduced in the period 2006‐2008 any eco‐ innovation because of current or future regulations. Similarly, the dummy variable Subsidy indicates whether or not the firm had introduced in the period 2006‐2008 any eco‐innovation because of the availability of public financial incentives. The dummy variable Demand indicates whether or not the firm had introduced in the period 2006‐2008 any eco‐innovation in response to customer demand, while Codes indicates whether or not the firm had introduced in the period 2006‐2008 any eco‐innovation to comply with voluntary codes of conduct in its industry. 3.2.2 Firm size Not only do we hypothesize a moderating effect of firm size on the relationship between environmental innovation and firms’ economic performance, we also expect a direct effect of size on firm performance. According to the resource‐based view, smaller firms suffer from liabilities of smallness since the environment favors structural inertia (Singh and Lumsden, 1990), scale effects (Barron et al, 1994), and the availability of 'slack resources' in larger organizations (Berry and Taggart, 1998; Hite and Hesterly, 2001; Steensma et al., 2000; Mc Cartan‐Quinn and Carson, 2003). In our analysis, we use the number of employees in 2005 as an indicator for firm size. The average firm in our sample had 115 employees in 2005. We took the natural logarithm of 1 + the number of employees in 2005, and label it Ln_Size. Our second hypothesis proposes an interaction effect. To avoid multicollinearity we follow Frazier, Tix, and Barron (2004) and z‐standardized Ln_Size before calculating its cross‐products with Regulation, Subsidy, Demand, and Codes i.e. Regulation*Ln_Size, Subsidy*Ln_Size, Demand*Ln_Size and Codes*Ln_Size respectively. Regulation, Subsidy, Demand, and Codes were dummy‐coded variables and hence they did not need to be standardized (Frazier et al., 2004). 3.2.3 Economic performance In order to assess the economic performance implications of environmental innovation, we use the net added value for 2008 (expressed in thousand euro). This variable is obtained from the firms’ annual accounts. The average net added value in 2008 for the firms in our sample was 11499 thousand euro. Due to skewedness, we calculated the natural logarithm of 32871 + the net added value for 2008, thereby also taking into account the occurrence of zero and negative values for net added value 2008. We label this variable Ln_NAV08 and include it as the dependent variable in our regressions.

Petra Andries and Ute Stephan 3.2.4 Control variables To isolate the impact of environmental innovations on economic performance, it is important to control for other factors that could also have influenced performance (Khanna, 2001). We introduce several variables to control for possible confounding effects: firm age, export behavior, R&D intensity, past financial performance as well as sector characteristics. Complementary to the liability of smallness, the liability of newness is often identified as a threat to firm performance (Shepherd et al., 2000; for an overview see Eisenhardt and Schoonhoven, 1990). In order to control for this ‘asset accumulation gap’ (Hay et al., 1993), we include the age of the firm in our regressions. In order to account for skewedness, we took the natural logarithm of the age of the firm and labeled it Ln_Age. When studying the relationship between environmental innovation and firm performance, one needs to exclude the possibility that environmental innovation is merely reflecting the firm’s technological capabilities (McWilliams and Siegel, 2000; King and Lenox, 2001). In order to avoid this problem, we incorporate the firm’s R&D intensity as a factor that influences firm’s financial performance. Each firm was asked how much it spent on internal R&D in 2006. We divided these expenditures by the turnover in 2006 (from the annual accounts). Due to skewedness, we calculated the natural logarithm of the R&D intensity and labeled this variable Ln_RDint. We also introduce the net added value of 2005 as an indicator of past financial performance in our model. This will control for any residual unobserved heterogeneity across firms leading to systematic differences in financial performance. We observe that, on average, firms managed to improve their net added value from 10896 thousand euro in 2005 to 11499 thousand euro in 2008. Again, due to skewedness, we calculated the natural logarithm of 8193 + the net added value for 2005, thereby also taking into account the occurrence of zero and negative values for net added value 2005. We label this variable Ln_NAV05. 1 Finally, we control for sector effects. In the survey, companies were asked to provide their main NACE code . NACE, which is short for “Nomenclature générale des Activités économiques dans les Communautés Européennes”, refers to the industrial classification used by Eurostat and is the subject of legislation at the European Union level, which imposes the use of the classification uniformly within all the Member States. Based on the sector’s average R&D intensity (R&D expenditures/value added) Eurostat classifies the NACE codes into high‐tech, medium‐high‐tech, medium‐low‐tech, and low‐tech sectors. We construct a dummy variable Hitech, This variable receives a value of 0 if the company’s main NACE code corresponds to a medium‐ low‐tech or low‐tech sector. It has a value of 1 if the company’s main NACE code corresponds to a high‐tech or medium‐high‐tech sector. Based on the firms’ main NACE code, we also constructed a dummy variable ServIndu, which takes the value 0 for manufacturing firms, and 1 for service firms. Manufacturing and service firms represent 59% and 41% of our sample, respectively. Table 1 provides an overview of the descriptive statistics for the different variables in our models. Table 1: Descriptive statistics (1712 observations)

Me an

Ln_NA V08 Regul ation Subsid y Dema nd Codes

10. 584 0.2 14 0.0 84 0.1 14 0.2

Std. Dev.

Correla tions Ln_NA V08 0.427 1

Regul ation

Subs idy

Dem and

Cod es

Ln_S ize

Ln_ Age

Ln_R Dint

Ln_NA V05

Hite ch

Servi ndu

0.411 0.1815

0.277 0.1112

0.346 4

0.318 0.0725

0.344 1

0.27 60

0.400 0.1434

0.504 4

0.30 33

0.42 60

The companies were actually sampled based on their NACE code and number of employees, but were given the opportunity to correct their main NACE code on the questionnaire form.

Petra Andries and Ute Stephan

Me an

Ln_Siz e Ln_Ag e Ln_RD int

00 0.0 09 3.2 20 0.0 03

Ln_NA V05

Std. Dev.

Correla tions Ln_NA V08

Regul ation

Subs idy

Dem and

Cod es

Ln_S ize

Ln_ Age

Ln_R Dint

Ln_NA V05

Hite ch

Servi ndu

0.902 0.5959

0.267 8

0.17 29

0.14 35

0.20 08

0.727 0.1055

0.057 9

0.06 24

0.02 94

0.04 42

0.21 69

0.033

‐ 0.0143

0.021 3

0.03 18

0.251 0

0.16 36

0.78 78

‐ 0.08 44 0.15 56

0.645 0.6424

‐ 0.00 46 0.22 98

0.00 72

9.4 56

‐ 0.01 01 0.19 40

Hitech

0.2 97

0.457 0.0896

0.018 3

0.06 31

0.02 66

0.493

‐ 0.098 2

‐ 0.03 42

‐ 0.07 90

‐ 0.16 75 ‐ 0.16 36

0.4 14

‐ 0.00 95 ‐ 0.09 44

0.055 3

Servin du

‐ 0.01 62 ‐ 0.02 24

‐ 0.09 84 0.13 70

‐ 0.101 3

‐ 0.00 47

‐ 0.0798

0.03 85

4. Findings When looking at our basic regression model without interaction effects, we find a significant positive effect of Ln_Size on NAV08 (Table 2). Of the four indicators for environmental innovations, only Demand has a significant and negative effect on NAV08. Hence we cannot confirm our Hypothesis 1. As for the control variables, we find a significant impact of the variables Ln_NAV05, and Hitech. The results become more interesting when interaction effects are included (Table 2). Although the main effects of Subsidy remains insignificant, we find that Subsidy * Ln_Size has a significant positive effect on NAV08. Also Regulation * Size has a significant positive effect on NAV08, while the main effect of Regulation remains insignificant. The main effects of Size, Ln_NAV05, and Hitech remain significant. Table 2: Regression results (1712 observations) Regulation Subsidy

Ln_NAV08 0.020 ‐0.018

Ln_NAV08 0.004 ‐0.054*

Demand Codes Ln_Size Regulation * Ln_Size

‐0.061** 0.001 0.114***

‐0.045 ‐0.004 0.100*** 0.062***

Subsidy * Ln_Size Demand * Ln_Size Codes * Ln_Size

0.073** ‐0.038 0.023

Ln_Age Ln_RDint Ln_NAV05

‐0.004 0.368 0.301***

‐0.003 0.294 0.273***

Hitech Servindu R2

0.061*** ‐0.011 0.4410

0.055*** ‐0.008 0.4493

* p < 0.10; ** p < 0.05; *** p < 0.01 More insights can be gained when plotting the interaction effects of Regulation and Subsidy with Ln_Size. We do so by plotting the standardized scores of Regulation and Subsidy (at ± 1 standard deviation around their mean) against Ln_Size. As Figure 1 shows, the development of environmental innovations as a response to current and future regulation has a positive effect on NAV08 for large firms, and a negative effect for small

Petra Andries and Ute Stephan firms. The same goes for the development of environmental innovations motivated by the availability of subsidies (see Figure 2).

Figure 1: Economic effects of environmental innovations as a response to current and future regulation

Figure 2: Economic effects of environmental innovations motivated by the availability of subsidies

5. Discussion We find that the effects of environmental innovation on firms’ economic performance are indeed moderated by firm size, and that this moderating effect is more complex than presumed. In fact, whether size moderates the impact of environmental innovations depends on drivers behind engaging in these particular innovations. Environmental innovations introduced because of voluntary industry codes of conduct, have a similar effect on the economic performance of small and large firms. Moreover, this effect is close to zero and statistically insignificant. Environmental innovations introduced because of customer demand, have a negative effect on the economic performance and this effect is similar for small and large firms. On the other hand, environmental innovations introduced as a response to regulation or to the availability of subsidies have a negative effect on small firms’ financial performance, and a positive effect on large firms’ financial performance. In sum our research reveals important boundary conditions of the environmental innovation – firm performance relationship. This study has some important implications for firms’ environmental strategies. Large firms should reconsider the way they are currently monitoring and reacting to customer demand for environmental innovations. The

Petra Andries and Ute Stephan results of our study suggest that the costs for developing these innovations are – at least in the short term – not outweighed by increased turnover. Large firms appear to be much better in setting and implementing industry codes of conduct and in complying with current and future regulation – and possibly also influencing this regulation for their own benefit. Small firms, on the other hand, should think twice before developing environmental innovations simply because subsidies are available to do so. A thorough calculation is needed to verify whether these subsidies actually outweigh the costs involved in developing the innovation. Obviously, our findings also have important policy implications. They entail that environmental policies should be tailored to specific subgroups of companies. Policy makers cannot assume that one type of policies fits firms of all sizes. Whereas environmental regulation has a positive impact on the performance of large firms, it is detrimental for small firms. Policy makers should therefore consider adapting the stringency of regulations to firm size. In addition, if policy makers choose to stimulate environmental innovation through subsidies, they should consider granting relatively larger subsidies to small firms than to their larger counterparts. And finally, our findings provide partial support for the recent tendency of governments to foster industry initiatives developing voluntary codes of conduct. Especially for small firms, these actions provide an interesting alternative to regulation or subsidy schemes.

6. Limitations Notwithstanding its empirical and conceptual contribution, the study has several limitations. First, it uses rather general measurements of voluntary and regulation‐driven environmental innovations. While previous studies suggest that the effect of environmental innovations may depend (a) on the design of environmental regulations; in particular on whether or not they are preventative and prescribe a specific technology (Porter, 1991), (b) on the monitoring regimes of voluntary environmental programs (Darnall and Sides, 2008), (c) on the specific type of environmental innovations (e.g. product design practices versus production processes practices versus logistics processes practices; see González‐Benito and González‐Benito, 2005), and (d) on how advanced the firm is in terms of environmental responsibility (Hart and Ahuja, 1996; Nehrt, 1996). We are not able to make these detailed distinctions. Second, Hart and Ahuja (1996) question whether the positive economic effects of environmental innovations persist once they are adopted throughout the industry. Contrary to Guenster et al. (2006) who observe a strong time variation in the valuation of eco‐efficient firms, this study is unable to evaluate changes in the relation between environmental innovation and economic results over time. And finally, this study involves environmental innovation activities of Flemish firms. As the economic consequences of environmental actions are known to depend on the country in which the firm is located (Wagner et al., 2002; Darnall et al., 2007), replication of our findings in other regions and countries is necessary to test the generalizability of our findings. We hope our work inspires future research that overcomes these limitations.

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Organizational Innovation as Leverage for Open Innovation Practices: A Business Model Perspective Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco Public University of Navarra, Spain paula.anzola@unavarra.es bayona@unavarra.es tgmarco@unavarra.es Abstract: Open Innovation is currently one of the hottest topics in innovation management. However, there is still research to be done regarding the process through which companies incorporate Open Innovation practices and take advantage of them. Moreover, innovation is nowadays much more than just technology and R&D; it must include organizational innovation. A business model perspective may provide valuable insight into a very important question: how do firms turn their innovation efforts into value and how do they capture part of that value? This paper addresses this topic through an in‐depth case study. The firm studied is a brake systems designer and manufacturer that underwent a profound process of strategic change in order to adapt its evolving environment. In this process, not only market related decisions were taken, but also (and very importantly) deep organizational innovation took place. All this in a context of openness in which the company had already been moving, but which begun to be systematized thanks to the implementation of the new structure. With regard to the business model concept, this paper adopts the definition of Osterwalder and Pigneur (2009), the developers of the widely used “Business model canvas” tool for describing and discussing business models. Based on this framework, the paper analyses the process of change undergone by the firm and illustrates how and to what extent the organizational innovation contributes to the creation and capture of value, focusing especially on the way in which the Open Innovation practices are leveraged by an appropriate business model design. Keywords: open innovation, organizational innovation, business models

1. Introduction Open Innovation is one of the most fertile research fields within the broader one of innovation management. However, there is still a lack of knowledge regarding how firms implement and take advantage of it (Huizingh, 2011). Furthermore, it has been known for some time that innovation involves much more than technology and R&D (Chesbrough, 2007); however the literature available on organizational literature is relatively scant. This paper addresses this topic through an in‐depth case study. The firm studied is a brake systems designer and manufacturer that underwent a profound process of strategic change. In this process deep organizational innovation took place. All of this occurred in a context of openness to innovation practices in which the company had already been moving, but which was strengthened on the basis of this process. A detailed analysis is carried out of the changes that occurred in the firm due to the implementation of certain organizational innovation, paying special attention to the transformation in the collaborative practices for innovating. A business model perspective is used to explore the following question: how can firms transform their innovation activities into creating and capturing value? In short, with this analysis, and while being aware of the limitations of the methodology, the main objective pursued here is to provide understanding as to how organizational innovation may constitute a key factor for generation of value and also a trigger to optimize Open Innovation practices. As will be seen, the firm’s organizational innovation had a decisive effect on the establishment of a model of Open Innovation and so on the optimization of the generating and capturing of value through the development of these practices. The paper is structured as follows: first, we conduct a literature review and establish a theoretical framework, then we explain the analytical methodology used before turning to the details of the case study. Finally, we summarize the main conclusions to be drawn from the analysis.

2. Theoretical framework The third edition of the OCDE’s Oslo Manual (2005) defines organizational innovation as “… the introduction of a new organizational method in the practices, the organization of the workplace or the external relations of the firm”. For organizational change to be described as innovation it must involve “the introduction of an

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco organizational method (…) that has not been previously used by the firm and which has been implemented as a result of strategic decisions by its leadership”. This article pays special attention to the concept of organizational innovation in the belief that giving it an appropriate degree of recognition constitutes a significant advance in the analysis of innovation processes, something which is necessary to support technological innovation in a context of growing competition stoked by globalization (Ayerbe, 2006). With regard to Open Innovation, research in this area constitutes one of the most significant contributions to the literature on innovation management, in particular since Henry Chesbrough established the concept in 2003. According to Chesbrough, Open Innovation consists of “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 et al., 2006). This concept is based on the idea that in the innovation process, the search for, development and marketing of innovations is carried out with the participation of external actors (Enkel et al., 2009). Recently various researchers have made contributions to revising earlier work on Open Innovation (e.g. Dahlander and Gann, 2010; Huizingh, 2011; Lichtenthaler, 2011). Huizingh, among other issues, has alluded to the necessity to make more progress in research into the “how to” of Open Innovation. Our case study here seeks precisely to offer a compressed view of the complex process of innovation carried out by the firm (both with regard to Open Innovation and organizational innovation). In this regard it is worth highlighting that according to the Oslo Manual (OCDE, 2005) the introduction of an Open Innovation practice may be considered to be an organizational innovation when it involves a new form of organization. More specifically this means the introduction of a new organizational method in the firm’s external relations (the Manual makes explicit mention of examples of new forms of collaboration with other firms, with research organisms and with clients). With the objective of making the description and analysis of these innovation processes more systematic it was decided to use a business model perspective. In general this refers to the description of the different components or blocks which, when articulated, reflect the way in which a firm elaborates a proposition which generates value for its clients and itself captures some of that value (Demil and Lecocq, 2010). In this article we use the business model perspective in order to highlight how the organizational innovation process served to leverage the Open Innovation practices and how both kinds of innovation create value for the firm. In this way we use the business model concept as a tool to illustrate the changes that occurred in the firm and the way in which value was generated and captured on the basis of these changes.

3. Methodology A single case study methodology was used due to the necessity for an in depth analysis of the organizational change and Open Innovation practices of the firm. Though it is important not to lose sight of the limitations of this method, especially with regard to the possibility of making generalizations from its results, it still remains a very useful tool for understanding the “How” and “Why” of complex phenomena in their natural contexts (Yin, 2003). It is also useful as a basis for suggesting good practices (Huizingh, 2011). As has already been pointed out, the objectives of our study coincide exactly with the advantages of this methodology. The choice of Frenos Iruña, SAL as the object of study was made on the following basis: (1) it is an established firm, founded in 1956, (2) it is involved in Open Innovation activities and (3) it has undergone a significant organizational innovation process. With regard to the gathering of information, the principle of triangulation was respected (Jick, 1979) through the use of multiple sources, which strengthened the credibility of the information gathered (Yin, 2003). Thus various in depth interviews were carried out with the managing director of the firm and those in charge of several of its departments. Similar interviews were carried out with a representative external participant with the object of mitigating possible distortions and subjective interpretations. The interviews were complemented with information from the firm’s accounts, strategic 1 plans, reports and presentations, as well as industry reports and newspaper stories . 1 The data collection is framed by the development of the BMOI project (Business Models for Open Innovation), part of EURIS, which is supported by the INTERREG IV C program and financed by the European Union’s Regional Development Fund (ERDF).

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco With the objective of systemizing the information gathered and carrying out the desired analysis we used the business model concept as a methodological tool. In the first place we established the components of the business model. Once defined, the construct serves to describe, for each of these components, the change carried out by the firm. Various authors have proposed definitions for this concept. Chesbrough and Roosenbloom (2002), Amit and Zott (2001) and Morris et al., (2005), among others. Osterwalder and Pigneur (2009) developed a very large and detailed tool known as the business model canvas to discuss and develop business models. They identify nine characteristic components of the business model which cover five main areas:

Customers: Describes for whom the firm creates value and the type of relationships a company establishes with specific customer segments.

Value proposition: Describes the bundle of products and services that create value for specific customer segments.

Key resources and activities: Describes the most important assets required and the most important things a company must do to make its business model work.

Income and cost flow: Relates to the financial viability of the business model.

Partnerships: Describes the network of external partners that make the business model work.

In the description of each block we seek to go deeper in the understanding of how the organizational innovation contributes to the generation and capture of value, paying special attention Open Innovation practices, specifically identifying them in the case of alliances.

4. Case study: Frenos Iruña, Sal 4.1 The firm Frenos Iruña, SAL (henceforth, FISAL), located in Pamplona, Spain, was founded more than 50 years ago and was acquired by its employees in 1980. It currently designs, develops and manufactures components for brake systems for cars and industrial vehicles as well as for other markets, such as off highway vehicles and the wind power sector. In 2010, its turnover was around EUR 8 million and it had 77 employees.

4.2 The organizational innovation process in FISAL By the end of the 1990s FISAL had consolidated a significant redirection of its business from the automotive sector towards off highway vehicles. From that point on it began to take a series of strategic decisions to adapt itself to its environment, improve its technical efficiency and competiveness, diversify its business and develop a presence in a wider geographic range of markets. As a support for these decisions, the firm in 2001 also embarked on a process of organizational innovation starting with the introduction of Value Generating Units (henceforth VGUs) and continuing with the introduction of Business Lines in the 2009 strategic plan.

The VGUs Due to the existence of many distinct parts to be manufactured, requiring different fabrication processes, in 2001 FISAL implemented an organizational process based on VGU or “mini‐factories”. This organizational change involved a break with the departmental structure of the firm and the design of a flatter organization. It was motivated by the desire to ensure improvements to the manufacturing process through better production management. The traditional departments (administration, commercial, human resources etc.) became supports for the VGUs, around which the whole organization began to revolve. Each VGU is in charge of all of the processes relating to the family of products for which it is responsible and is made up of a manager, a technical team (made up of a person in charge of quality, a product design engineer and a person in charge of supplies, planning and billing) and a manufacturing team. The VGUs allowed the firm to improve its design and manufacturing processes, improve its technical efficiency and improve coordination of the various production activities.

The Business Lines After the introduction of the VGUs the most significant milestone in organizational innovation took place in 2009, when the firm’s Strategic Plan introduced the Business Lines into the organizational model. These structure the organization according to the different segments of clients with which the firm deals: automotive, off highway, wind power, aftermarket and foundry. Its objective is to

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco ensure the development of all the markets where FISAL is present, consolidate the firm’s traditional business and strengthen its new ventures. Through this new structure, the commercial side of the business is emphasized, with importance being given to the capturing and keeping of clients and efforts made to ensure that resources are assigned in a manner appropriate for the achieving of each Line’s objectives. FISAL’s client base has undergone considerable growth and diversification and it was decided to adapt the company’s organizational structure to this new reality. As well as articulating the Business lines with the VGUs (various VGUs may be involved in each line) the aim was to optimize the technology and advances acquired with the development of each new product and so guarantee the continual transfer of knowledge so that improvements made with one product could feed into those to come. In terms of the requirements set out in the Oslo Manual (OCDE, 2005), the VGUs and later the Business Lines are both organizational innovations in the workplace. The Manual establishes that this type of innovation occurs when new methods of allocation of responsibilities and decision‐making power between employees and the division of labor are implemented, as well as new structural concepts, for example, the integration of different activities by the company. As well as the aforementioned, in 2008 FISAL acquired Fundiciones Greyco, a firm that produces castings, a very important input for the firm’s range of products. This vertical integration can be understood as an innovation in the organization of the firm’s external relations, as it comes under the Manual’s “new methods of integrating providers” (Oslo Manual, 2005). It is important to note that that the organizational innovation carried out by the firm implied an open process, as it was implemented thanks to the collaboration with a consulting company. As stated by the General Manager of FISAL: "When implementing the VGUs (…) we worked hand‐to‐hand with consultants who were familiar with this type of model."

4.3 The changes in FISAL from a business model perspective Turning now to the previously explained business model construct we will describe and analyze the changes undergone by FISAL due to the implementation of the organizational innovations. The analysis will highlight the contribution to the creation and capture of value and the optimization of the Open Innovation practices due to these innovations in the organizational design. Clients Prior to the organizational restructuring FISAL mainly worked with the following two client segments:

In the automotive sector, the focus was on a specific niche, manufactures of vehicles with short production run (the usual number being around 20,000 vehicles a year).

In the off highway sector the clients were mainly manufacturers of tractors, excavators and vehicles generally related to public works and agriculture.

The firm put most of its efforts into the second sector, which represented 60% to 70% of its business. The successive strategic changes that have been described above resulted in a segmentation of FISAL’s clients and the implementation of the Business Lines is a clear reflection of this reality.

AUTOMOTIVE: On the basis of the segmentation strategy this niche was strengthened through the opening of new markets with the design and development of new products. Among these new products worthy of particular note is the fabrication of brake components for a prototype electric car for one client. Also worthy of mention is the entry into new geographic markets, with the help of collaborators, and even competitors.

OFF HIGHWAY: As in the case of the automotive sector, in this case there has also been an entry into new geographic markets and the development of new products.

WIND POWER: Braking systems are produced for manufacturers of wind power generators.

AFTERMARKET: The production and sale of replacement brakes is a long standing activity in the firm and represents a small proportion of its sales volume.

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco

FOUNDRY: Fundiciones Greyco was acquired by FISAL. Although it provides services for external clients its main function lies within FISAL itself, participating in the manufacture of braking systems.

From this perspective the organizational innovation embodied in the Business Lines contributed to the creation of value in the following ways:

Through the optimization of the use of resources and the organization of activities with the aim of capturing new clients and maintaining the loyalty and satisfying the expectations of existing ones.

The consolidation of the traditional business at the same time as developing new markets.

Value proposition FISAL’s value proposition lies in its specialization in short run production, the quality of its own design and in the involving of the client in the whole process, from the start of the project, through the design of the prototype and its testing and on to the production phase for a successful product. Without any doubt, this is one of the characteristics that define the essence of the firm. Manufactures of vehicles with short production runs have greater difficulties than those that produce with longer runs in obtaining high quality components. The bulk of brake manufactures are not competitive with production runs of less than 100,000 a year. FISAL, by contrast, has both its staff and production management orientated towards short production runs and can be competitive at levels as low as 5,000 units (though in general it works at around the 20,000 units a year level). Thus, producing well designed, quality niche products forms the basis of FISAL’s competitive advantage. On the basis of the systematization of the segmentation of clients, the firm manages a specific product range for each Business Line, defined as an organizational innovation, as well as a distinct approach to and treatment of those clients in each case. We now turn to setting out the differential characteristics of the value proposition of the automotive, off highway and wind power business lines.

AUTOMOTIVE: The focus here is on short production runs. FISAL offers quality design to clients who cannot permit themselves the luxury of designs produced for long production runs.

OFF HIGHWAY: The focus here is on design. Clients in this segment have difficulty finding suppliers who can provide them with products with the parameters of the automotive sector with regard to design and manufacturing quality.

WIND POWER: Though design is also very important here, price competiveness is of even greater importance. The products concerned are very heavy and involve a lot of raw material costs. It is also the case at the moment that the manufacturers of wind power generators are experiencing strong pressure on their profit margins.

In conclusion, it is safe to state that the organizational innovations carried out by FISAL have allowed it to clearly identify the characteristics of its value offer for each client segment and so allow the firm to concentrate on the most important issues for each Business Line in order to allow it to further construct and develop its competitive advantage. Resources and key activities The importance of internal design of products manufactured by the firm, as well as its capacity to carry out the whole process of development of new products, from the reception of the initial request till the delivery of the new product, specifically designed for the client’s needs and including the testing of prototypes and production processes, has already been indicated. Thus the firm’s knowledge base and dedicated facilities are very important resources. The design, development and testing of prototypes are key activities for the firm. According to this, the R&D activities tending to generate innovations are also a great factor of success. Indeed, FISAL has consolidated a long tradition of internal innovation, which has allowed the firm to support and develop its Open Innovation practices. In fact, it is through internal R&D activities that firms enable their capabilities of scanning and integrating external knowledge (Arora and Gambardella, 1990; Laursen and Salter,

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco 2006). Also, it important to highlight that the concept of Open Innovation involves an engagement with external sources of knowledge, not a total reliance on them (Chesbrough, 2003, Berchicci, 2013). The development of VGUs and Business Lines strengthens the development of internal technological innovation though the establishment of synergies and the continual transfer of knowledge among the various families of products. It has already been explained how the rupture of the firm’s departmental structure permitted the improvements of the process of design and fabrication through improved coordination of activities, leading to the optimization of technical advances. As a result of the interaction between the VGUs and various Business Lines, these advances flow naturally and quickly so that the improvements obtained in one product are incorporated into the rest of FISAL’s product range. Income And Cost Flow The firm’s income comes from the sales of its various products. Noteworthy among its costs are those associated with the design and fabrication of its products (these are proportionally greater than for larger automotive firms whose strategy is based on the acquisition of all the material already manufactured and its subsequent assembly). With regard to the results of the organizational innovations, the acquisition of Greyco is of particular importance. The vertical integration of the manufacturing process gives FISAL a completive advantage in the production of braking systems for wind power generators (a sector for which the importance of limiting costs has already been indicated) as it involved the incorporation into the firm of an essential input for the fabrication of its products. Alliances: Identification Of Open Innovation Practices We will focus solely on the alliances and partnerships carried out in order to develop innovations. Thus, the business model perspective allows us to clearly identify the practices introduced by FISAL which amounted to Open Innovation. Prior to the changes described here, the main collaborations were carried out with other brake manufacturing firms and through them FISAL incorporated new technology into its activities. Furthermore, FISAL had for some time been constructing relations with its clients based on trust and cooperation. Thus joint participation in the design of products was already habitual for FISAL. After the changes described, collaborative relations in the development of products with clients persisted and intensified. Furthermore, collaborations with external actors were systematized in accordance with the Business Lines, in order to carry out innovations in the design and technological development of material and products.

AUTOMOTIVE: Worthy of particular note here is the cooperation between FISAL and a client to develop the caliper for the braking system of the client’s prototype electric car. FISAL also has important relationships with material suppliers and technological centers.

OFF HIGHWAY: The firm’s collaboration with Universities is of particular importance for innovation in the design and manufacture of its products for this Line.

WIND POWER: In 2012, FISAL began a collaboration project with another firm in the same sector for the development of an improved braking system for wind power generators. Collaborations with clients and suppliers are also very important in this area. Finally, it is worth highlighting the collaborations with two technology centers (one involved in metallurgy research and the other specialized in the development of technology for the automotive industry), that could provide the necessary knowledge to extended its value proposition by adding new brake systems targeted at the wind power industry. For developing these new products, Frenos Iruña worked intensively both of these technology centers, gaining access to outside technical knowledge regarding the manufacturing of the new prototypes and also to outside testing facilities, in order to verify the adequacy of these new products, much larger than the ones traditionally produced, as the firm did not have the capacity to do the testing by itself. As was stated by the manager: “In order to enter the wind power business, and regarding the development of the product, we have worked with a research centre well known for its experience with foundry materials. Also, another research centre has provided the facilities to do the dynamometric tests to the new prototypes.”

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco Thus, the integration of knowledge gained through Open Innovation activities helps to generate additional value, and to capture part of that value. It has already been explained that these innovation methods also constitute a type of organizational innovation, in as much as they involve changes in how the firm deals without outside actors. There is no doubt that in the process of change studied here FISAL took the decision to redefine the way in which it related to certain external agents and so develop and strengthen collaborative relations with them. Once these practices become habitual it is logical that they lose their character of being organizational innovations and become part of a model of Open Innovation in the development of materials, models and markets. Organizational innovation related to the Business Lines involved a systemization of these collaboration practices, as we have seen. That is to say, FISAL’s processes of organizational innovation have had a decisive effect on the establishment of a model of Open Innovation and so on the optimization of the generating and capturing of value through the development of these process. Figure 1 provides snapshots of the business model of the company right before and after the innovation processes described above.

Figure 1: Diagram of the business model prior to and after the process of organizational innovation

Paula Anzola Román, Cristina Bayona‐Sáez and Teresa García‐Marco

5. Conclusion The culture of innovation impregnates FISAL’s strategy, both with regard to the development of knowledge and technology and with regard to management and organizational models and the appropriate way to approach the challenges arising therefrom. The case study carried out here on the basis of a business model perspective has allowed us to see both how processes of innovation occur in the firm and also how these processes contribute to the creation and capture of value. The introduction of new organizational methods in the form of the VGUs and Business Lines has had effects in various areas of the firm. It has optimized the utilization of resources and the coordination of activities and ensured the continuous transmission of technological advances and knowledge, it has allowed for the identification of competitive advantages in each of the areas affected and has led to a redirection of efforts towards the development of a growing body of clients. Furthermore, the organizational innovation represented by the vertical integration of Fundiciones Greyco has also produced important competitive advantages, especially in the area of wind power. Finally, the analysis carried out here shows how Open Innovation has been constructed through the introduction of innovations in the organization. It also clearly demonstrates the degree of openness in the firm and the importance of the incorporation of resources and knowledge from outside for its growth and development. The deep revision of the various aspects of the organization helped to produce an appropriate fit between all the elements of the new business model that was being implemented, Therefore, FISAL’s processes of organizational innovation have had a decisive effect on the establishment of a model of Open Innovation and so the optimization of the generating and capturing of value through the development of these process.

References Amit, R., Zott, C., 2001. Value creation in e‐business. Strategic Management Journal 22, p. 493‐520. Arora, A., Gambardella, A.,1990. Complementarity and external linkages: The strategies of the large firms in biotechnology. Journal of Industrial Economics 38 (4), 361‐379. Ayerbe, C., 2006. Innovations technologique et organisationnelle au sein de PME innovantes : complémentarité des processus, analyse comparative des mécanismes de diffusion. Revue internationale PME, 19(1), p. 9‐34. Berchicci, L., 2013. Towards an open R&D system: internal R&D investment, external knowledge acquisition and innovative performance. Research Policy, 42, 117‐127. Chesbrough, H., 2003. Open innovation: the new imperative for creating and profiting from technology. Harvard Business School Press, Boston, MA. Chesbrough, H., 2007. Business model innovation: it's not just about technology anymore, Strategy & Leadership 35, Iss 6, p. 12‐17. Chesbrough, H., Crowther, A.K., 2006. Beyond high tech: early adopters of open innovation in other industries. R&D management 36, p. 229‐236. Chesbrough, H.; Rosenbloom, R., 2002. The role of the business model in capturing value from innovation: evidence from Xerox Corporation's technology spin‐off companies. Industrial & Corporate Change, 11, n. 3, p. 529‐555. Demil B., y Lecocq, X., 2010. Business Model Evolution: In Search of Dynamic Consistency. Long Range Planning 43, p. 227‐ 246 Enkel, E., Gassmann, O., Chesbrough, H., 2009. Open R&D and open innovation: exploring the phenomenon. R&D management 39, p. 311‐316. Huizingh, E., 2011. Open innovation: State of the art and future perspectives. Technovation 31, p. 2‐9 Jick, T.D., 1979. Mixing qualitative and quantitative methods: triangulation in action. Administrative Science Quarterly 24, p. 602‐611. Laursen, K., Salter, A., 2006. Open for innovation: the role of openness in explaining innovation performance among U.K. manufacturing firms. Strategic Management Journal, 27,. 131‐150. Morris, M., Schindehutte, M., Allen, J., 2005. The entrepreneur's business model: toward a unified perspective. Journal of Business Research 58, p. 726‐735. Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, Third Edition. OECD/European Communities, 2005. Osterwalder, A., Pigneur, Y., 2010. Business model generation. Wiley, Hoboken, NJ. Yin, R.K., 2003. Case study research: design and methods. SAGE Publications, Thousand Oaks, CA.

Spin‐Up: A Comprehensive Program Aimed to Accelerate University Spin‐Off Growth Manuel Au‐Yong Oliveira1,2, João José Pinto Ferreira1, Qing Ye3 and Marina van Geenhuizen3 1 INESC TEC (coordinated by INESC Porto), Faculty of Engineering, University of Porto, Portugal 2 Department of Economics, Management and Industrial Engineering, University of Aveiro, Campus Universitário de Santiago, Portugal 3 TU Delft Faculty of Technology, Policy and Management, The Netherlands moliveira@fe.up.pt jjpf@fe.up.pt yeqi519@gmail.com M.S.vanGeenhuizen@tudelft.nl Abstract: The Spin‐Up project has the objective of determining what sort of entrepreneurship training and coaching program will contribute to the development of key entrepreneurial skills, both technical and behavioural, essential to enable and leverage university spin‐off growth. University spin‐off firms (USOs) tend to grow at a slower pace than corporate spin‐offs or other young high‐technology firms, which underlines the need for the project. The Spin‐Up project is funded by the European Commission within the scope of the Erasmus Program (Enterprise and University cooperation) / Lifelong Learning Program. The project commenced in 2011, and the consortium is made up by five entities from three countries and one associated partner country. 99 face‐to‐face interviews and surveys of CEOs and members of USO management teams revealed that a number of entrepreneurial skills were missing and hampering growth, namely skills (top 10) to: gain financial capital; internationalize; increase sales; be financially literate; manage marketing; manage human resources; manage operations; understand economic principles of business; grow based on strategic management; and understand an approach keen on intellectual ownership protection. These findings guided the development of the training program, to be delivered to USO CEOs and other USO senior managers. Full pilot training sessions have already been delivered in the Netherlands, in Finland, and in Portugal. The training was delivered based on: 1) initial exploratory questions; 2) subsequent providing of background theory; and 3) finalizing with further practical questions on the subject matter. In this way, engagement of the spin‐off firms was increased throughout and the training had a very practical approach, centered on problem‐solving and real life examples, challenging participants to think about their day‐to‐day issues hampering growth. The areas in need of specific training were defined as being innovation, marketing and sales; overall strategy; finance; internationalization strategy; and leadership and human resource management. Networking opportunities occurred between peers during the training sessions and also with various key specialists, like a business angel (in Portugal) and venture capitalist (in the Netherlands). In terms of what the consortium partners have produced, tangible materials include training manuals and case studies, to support the training effort. Keywords: spin‐up, university spin‐offs, growth obstacles, training, Portugal, Finland, the Netherlands, Poland

1. Introduction Increasingly, researchers and practitioners focus attention on the transfer of knowledge from university to the business world, be‐it through licenses, small university projects, research collaboration, or the establishment of spin‐off firms (Geuna and Muscio, 2009; van Geenhuizen, 2013; van Looy et al, 2011). It is particularly the effectiveness of the processes that raises questions and call for solutions and improvement. The Spin‐Up program, focusing on university spin‐offs’ growth, is a project funded by the European Commission within the scope of the Erasmus Program (Enterprise and University cooperation) / Lifelong Learning Program. The project commenced in 2011, and the consortium is made up by five entities from three countries:

INESC TEC (Portugal);

Advancis Business Services (Portugal);

Leaders2Be (the Netherlands);

The Technical University of Delft (the Netherlands); and

The Lappeenranta University of Technology (Finland).

Manuel Au‐Yong Oliveira et al. The University of Porto and the Technology Transfer Centre at the University of Lodz were also partners associated to the project, having contributed to the research effort. “Several researchers claim that university spin‐off firms do not grow or that they tend to grow at a slower pace than corporate spin‐offs and other high‐technology start‐ups. This situation resides, mainly, in the fact that university spin‐offs’ growth is highly influenced by the founders of these firms, who frequently lack key entrepreneurial skills” (van Geenhuizen and Ye, 2012a, p.2). So, the authors are part of a consortium put together to research university spin‐offs (USOs) – i.e. start‐ups that bring knowledge from universities to market (Pirnay et al., 2003). The objective of the consortium – within the SPIN‐UP – Entrepreneurship Training and Coaching for University Spin‐Offs Program (Oliveira et al., 2012) – was to first of all determine what skills tend to be lacking in these enterprises; and then subsequently to put together a program of specialized training and coaching in order to increase the growth rate of these companies. USOs are seen to grow slowly in comparison to other types of start‐up – for example, within the sample of 99 USO firms researched by the Spin‐Up consortium, the “average employment growth per firm is 1.6 fte [full time equivalents] per year” (van Geenhuizen and Ye, 2012a, p.9), despite the potential to behave otherwise given that USO are normally set up by knowledge‐intensive individuals such as university professors and / or university graduates (Sousa et al., 2013). This growth rate compares poorly to certain cases where the entrepreneurs have notably not finished their university degrees – the cases, for example, of Apple and Microsoft. This article describes the research and training activity of the Spin‐Up project to date, as well as discussing the next steps to be taken following the project end in September 2013.

2. SPIN‐UP research question As published in Oliveira et al. (2012), the Spin‐Up research question was: “What sort of entrepreneurship training and coaching program will contribute to the development of key entrepreneurial skills, both technical and behavioural, essential to enable and leverage university spin‐off growth?” The research question was approached using three steps:

An empirical research on missing skills among management teams of USOs.

Translating the results in a new training and coaching program based on ‘smart’, interactive learning, supported by various manuals.

Testing this program and based on the outcomes, eventually adapt the program.

The first two steps will be discussed in detail below.

3. The research data and methodology The research effort involved face‐to‐face interviews and web‐based and e‐mail‐based questionnaires. The research in Oliveira et al. (2012) involved a total of 64 face‐to‐face interviews and e‐mail / web questionnaires, performed in four countries: Finland, Poland, Portugal, and the Netherlands. The research effort has currently finished with a total of 99 interviews and questionnaires having been performed. The breakdown per country was as follows: 24 interviews/questionnaires in Finland, 18 in Poland, 28 in Portugal and 29 in The Netherlands. We composed a selected sample as follows (van Geenhuizen and Ye, 2012a): “To avoid a large differentiation in firm age, firm age limits were set at 2 years (lower limit) and 10 years (higher limit). 10 years was however used flexibly, particularly in those sectors where development and bringing to market goes relatively slowly, like in the medical life sciences and material (nano) science (15 years used as the maximum in these cases). Spin‐off firms were also selected such that they represented small as well as larger firms, and growing firms and firms that were stable and some even shrinking; this was to enable the assessment of a ‘causal’ relation between absence/presence of particular skills (experience) and different growth patterns. In terms of growth, the selection was aimed at 30% growing well, while 70% had to be a mix of stable, slow‐growing and declining spin‐off firms” (van Geenhuizen and Ye, 2012a; Oliveira et al., 2012).

Manuel Au‐Yong Oliveira et al. “We designed a full questionnaire for use in face‐to‐face interviews and a condensed questionnaire for use in web‐based or e‐mail surveys. The purpose of the full questionnaire (interview) was to measure (a) current entrepreneurial skills of the management team, using a five point scale (covering a range from absence to strong presence of particular skills) and dynamics herein (courses/training); entrepreneurial skills and experience at the start in the founding team, (b) firm demography and growth, and (c) strategy and business environment. In addition, (d) leadership and team integration were assessed. Accordingly, the interview questions are divided into four sections. The main goal was to design a skills map per firm (entrepreneurial skills) for the present situation, including a special map on leadership skills” (van Geenhuizen and Ye, 2012a; Oliveira et al., 2012). Annex I provides a description of the full questionnaire. Figures 1 and 2 present the skills maps (entrepreneurial skills and leadership skills), showing the aggregate results for each of the four countries.

4. Main findings From the Executive Summary of the Spin‐Up Research Report (van Geenhuizen and Ye, 2012a, pp. 2‐3):

“The university spin‐off firms in the sample (99 cases) have an age of 6 [years] on average. They generally experience a slow job growth rate (1.6 fte per year on average) and most of them are active in ICT [Information and Communication Technologies] and software technology (26% and 16%) and in the life sciences (14%).

The top five most often missing skills are concerned with (1) gaining financial capital, (2) internationalization, (3) human resources management, (4) intellectual ownership protection, and (5) financial literacy and management. These are named ‘common missing skills’.

This result is only slightly different from the missing skills perceived by the entrepreneurs as hampering growth of the firm, where sales skills has jumped to the third place and marketing management has entered: (1) gaining financial capital, (2) internationalization, (3) sales, (4) financial literacy and management, and (5) marketing management.” The importance of this type of results is confirmed by other studies with a focus on, for example, internationalization through knowledge relationships. Being actively involved in international knowledge relations, turns out to enhance growth of the firms (Taheri and Van Geenhuizen, 2011).

In addition, according to van Geenhuizen and Ye (2012a):

“Between the countries, there are some clear differences in missing entrepreneurial skills. For example, the Netherlands and Finland tend to be short of sales skills and Portugal of internationalization skills, while all countries ‐ except the Netherlands – are facing missing skills on gaining financial capital in the first place (table 1).

Table 1: Missing entrepreneurial skills hampering growth per country (rank order) (van Geenhuizen and Ye, 2012a, p.16)

Manuel Au‐Yong Oliveira et al.

With regard to available entrepreneurial skills, most often mentioned are (1) technology management, (2) product/process innovation, (3) market dynamics and competition, (4) digital skills, and (5) entrepreneurial processes.” Differences between countries are small, with some remarkable scores though, like a high rank for strategic management skills in Portugal.

“The pattern of available leadership skills is as follows. Most often available are: (1) focus on the good of the whole, (2) enable people to solve problems, (3) using a long‐term vision, (4) encourage people to use their talents, and (5) encourage people to come up with new ideas. There are almost no leadership skills absent. In addition, differences in available leadership skills between countries are small.”

Given the fact that spin‐off firms in general are rather heterogeneous (e.g. Mustar et al., 2006), the empirical research also aimed at exploring relationships between missing skills and firm characteristics (van Geenhuizen and Ye, 2012a):

“Missing entrepreneurial skills tend to be related to different categories of spin‐offs. A statistically significant relationship was found for technology level and firm size (with 10 fte [full time equivalents] as a borderline): low‐ and medium‐technology spin‐off firms as well as smaller firms have a larger chance to face common missing skills.” The result on technology level compares with a previous study (Van Geenhuizen and Soetanto, 2009), in which an important influence of technology level was found: High‐ technology spin‐offs are facing more obstacles to growth compared to medium/low‐technology spin‐offs, but they are also able to solve them more quickly. Thus, at a somewhat later age they face less obstacles to growth.

To underpin the need for training and coaching, the relationship between common missing skills and the performance of spin‐off firms was explored (van Geenhuizen and Ye, 2012a): “Spin‐offs experiencing common missing skills tend to face a larger chance for small growth compared to other firms, and the same applies to turnover size and profitability. These differences are statistically significant, the relationships are however not statistically significant.

As a conclusion: (1) there are clearly missing entrepreneurial skills; (2) technology level and firm size tend to cause differences in missing entrepreneurial skills; (3) missing entrepreneurial skills go along with a smaller growth of the firms.

The previous observations underpin the need for a training and coaching program and point to a need to differentiate such a program between low/medium technology and high technology spin‐off firms, and between small and larger spin‐off firms.

As an implication: given the pattern of missing skills (hampering growth), the focus in the training and coaching program is to be on: (1) Financing for growth (financial literacy and management, and gaining financial capital); (2) Internationalization for growth (doing business abroad); and (3) Sales and marketing management. Eventually, building skills on human resources management is added. Moreover, spin‐offs in Portugal tend to be behind in innovation level of their activities. This provides an argument for also focusing the training/coaching program on skills in innovation and innovation strategy.”

5. A discussion of the research findings per country using spider diagrams As a matter of visualization for each country, eight skills maps were constructed on the basis of entrepreneurial skills and leadership skills. Instead of using all skills, a limited number of dimensions were identified to perform as axes of the spider diagrams (Figures 1 and 2). The figures indicate different trends for the four countries in the Spin‐Up sample, which may mean that in the future the aim will be to develop tailored training sessions addressing each country’s specific reality. In the case of the Netherlands we can see that operations management, intellectual property and human resources are areas where entrepreneurial skills suffer from shortages. Financial management skills also scores quite low. Operations management in particular – defined as being related to channel management, procurement and daily operations in the Spin‐Up questionnaire – actually has far‐reaching outcomes and “underpins most of human activity and shapes the society in which we live” (Jones and Robinson, 2012, p.5), thus warranting attention in future. Finland showed a more balanced entrepreneurial skill set, though gaining financial capital and, again, human resources are lacking. Polish companies in the sample showed a more modest entrepreneurial skill set – gaining financial capital, financial management, intellectual ownership and human resources all scoring

Manuel Au‐Yong Oliveira et al. somewhat low. Finally, Figure 1 shows that in Portugal USOs are having difficulty in gaining financial capital. This may be due to the well‐documented internal economic crisis that Portugal is going through, meaning that there will be a shortage of capital to invest in entrepreneurial projects, investors being more conservative in view of increased market risks – bad debt being one of them, in view of the vast amount of companies which have been going bankrupt and due to the high unemployment rate – at 17.7%, in 2013, according to the Portuguese National Institute of Statistics (INE, 2013). Intellectual ownership is also an entrepreneurial skill lacking among Portuguese USOs, particularly, ICT and software companies do have difficulty in securing their intellectual property.

Figure 1a‐d: Entrepreneurial skills map of spin‐off firms in four countries (reproduced from van Geenhuizen and Ye, 2012a) Figure 2 is a depiction of the state of the leadership skills among the USOs of the sample, across the four countries. Leadership, “traditionally conceptualized as an individual‐level skill” (Day, 2001, p.583) can be seen to be a source of competitive advantage (Day, 2001). Leadership skills are strong in The Netherlands, though more opportunities may be provided and more information given by leaders of USOs here. In Finland the leadership skills depicted are even more equally distributed than in the Netherlands. In Poland leadership is once more strong, excelling in particular in the encouragement of human resources. Portugal is also very even in its leadership skill set, with the giving of information as a point of positive note.

6. The training program and the pilot Face‐to‐face interviews and surveys of CEOs and members of USO management teams revealed that a number of entrepreneurial skills were missing and hampering growth, namely skills (top 10) to (van Geenhuizen and Ye, 2012a, p.15):

Gain financial capital;

Internationalize business;

Increase sales;

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Be financially literate;

Manage marketing;

Manage human resources;

Manage operations;

Understand economic principles;

Grow following a consistent overall strategy; and

Use an intellectual ownership approach.

Figure 2a‐d: Leadership skills map of spin‐off firms in four countries (reproduced from van Geenhuizen and Ye, 2012a) These findings guided the development of the training program, to be delivered to USO CEOs and other USO senior managers. The pilot training was designed based on: 1) Initial exploratory questions; 2) Subsequent providing of background theory; and 3) Finalizing with further practical questions on the subject matter. Using this approach, the engagement of the participants was heightened throughout and the training had a very practical approach, centered on problem‐solving and real life examples, challenging participants to think about their day‐to‐day issues concerning growth. During the pilot training networking opportunities between peers arose. In Portugal in particular interaction with a Business Angel was promoted, for whom presentations were prepared by participants. This was welcomed as in Portugal gaining financial capital was a problem of the USO in the sample. In addition, in The Netherlands interaction with a venture capitalist was arranged, in that the participants could pose specific questions on the attractiveness of their firm for venture capital and the conditions involved in receiving this specific type of investment. The pilot training has already been delivered in full, in all of the countries involved (the Netherlands, Finland and Portugal). The training in all cases focused

Manuel Au‐Yong Oliveira et al. upon the following vital areas, for which specific training manuals and case studies were developed, by the consortium partners. Each area was approached in the manuals through skills and understandings concerning a) key concepts, b) future needs and developing the strategy, and c) deciding on the options. The areas are:

Innovation, marketing and sales tools for growth – Including key concepts about innovation, entrepreneurial marketing (including planning for marketing and ‘crossing the chasm’ concepts), pricing strategies, and sales and promotion (training manual developed by INESC TEC, namely by Oliveira and Ferreira, 2013);

Strategy for growth – Covering the market‐based view, resource‐based view, dynamic resource‐based view, relational view, as well as strategic approaches in action and obstacles to strategic growth (training manual developed by the Lappeenranta University of Technology – LUT – in Finland, in 2013);

Financial Planning for Growth – Including sections on financial information fundamentals (balance sheet, income sheet, financial reports analysis); the identification of future financial needs; and deciding on the best financing options (training manual developed by Advancis, namely by Meireles and Reis, 2012).

Internationalization for Growth – About the drivers and aims of internationalization; internationalization models; country choice and entry modes; barriers to internationlization; as well as discussing export strategies, and strategies for outsourcing and knowledge collaboration abroad (training manual developed by van Geenhuizen and Ye, 2012b, of Delft University of Technology).

Human Resource Management (HRM) and Leadership – Covering HRM as a high performance work system (compensation and performance related pay; appraisal and performance management; training and development; employee participation) as well as the basics about leadership (training manual developed by Leaders2Be and by Advancis).

The knowledge created, namely in the form of case studies and training manuals, was shared by the consortium partners. Partners in Finland, Portugal and the Netherlands were each responsible for holding the full pilot training in their country, based on the material produced. A major objective was to discuss problems that arose as well as lessons learned towards the end of the project, with the possibility to add changes and improvements to the training manuals and case studies about USOs.

7. A discussion of the importance of internationalization – A look at USO cases As the research was performed in Europe, involving European countries, and given the much publicized European crisis – for example, the cover of The Economist on May 25th‐31st, 2013 read: “The Sleepwalkers [showing a number of European political leaders in tow] – A euro disaster waiting to happen” – internationalizing was thus seen to be particularly important to USOs. However, this skill turned out not to be sufficiently developed among the sampled spin‐off firms. Indeed, “among almost 100 spin‐off‐firms in four countries, Finland, the Netherlands, Poland and Portugal, the two skills that are most often missing are skills in gaining financial capital and skills in internationalization. These two skills are also top missing skills that hamper growth of the firm, according to the CEOs of the spin‐ off firms involved” (van Geenhuizen and Ye, 2012b, p.2). However, what does internationalizing of a firm involve? “The term Internationalization… needs to be understood in a broad sense. It not only refers to producing for markets abroad (export or on‐site production), but also to subcontracting abroad, import activity, and knowledge collaboration with firms and research institutes abroad.” (van Geenhuizen and Ye, 2012b, p.3). In the Spin‐Up sample: “Among almost 100 spin‐off‐firms in four countries, Finland, the Netherlands, Poland and Portugal… slightly more than half of the spin‐offs have no exports and almost one‐third have no knowledge collaboration abroad” (van Geenhuizen and Ye, 2012b, p.2). As internationalization is often connected with growth, USOs CEOs need to become experts at international marketing, which can be described as follows: “The performance of business activities designed to plan, price, promote, and direct the flow of a company’s goods and services to consumers or users in more than one nation for a profit.” (Cateora and Graham, 2005, p.9). According to one Portuguese USO CEO: “our internal

Manuel Au‐Yong Oliveira et al. [Portuguese] market is very small. Germany has a market of 100 million Germans, all with money! In Portugal we only have 10 million people and they are poor, the economy is very small. Portugal has a critical mass problem. That limits projects a lot. In the USA you have 300 million rich people…” (CEO of a Portuguese software USO, interviewed by one of the authors on 17‐02‐2012). The importance of internationalizing a Portuguese company’s products and services is made evident by the comments above. Portugal is facing a small domestic market and, as a consequence, a company may only gain market significance if it seeks to grow its presence abroad. This is exemplified by the software company “SoftLeaders” (a fictitious name to protect the company’s privacy) mentioned above, 95% of its sales come from abroad. Furthermore, “SoftLeaders” has subsidiaries outside Portugal, in China and in the USA. However, few USOs start with the ambition of becoming a global player. Indeed, various important barriers to internationalization do exist (van Geenhuizen and Ye, 2012b):

“short of ideas (awareness) of attractive opportunities and countries

connecting with networks and persons (channels)

‘navigating’ unfamiliar business environments

dealing with procedural barriers, including product standards

understanding the competitive environment

understanding potential opportunities and risks

building the confidence, management time and other resources to pursue opportunities in business abroad” .

Another Portuguese software manufacturer in the sample is also having great difficulty in increasing sales. Founded in 2007 by students who had just finished their undergraduate degree and operating in the medical diagnosis field – producing diagnosis support systems – this company is currently looking to internationalize its operations to Brazil. In Portugal sales are a problem due to the crisis. Portuguese hospitals, which are a part of the national health system, have no capital to invest in their product, which can cost between 50,000€ and 100,000€ to purchase and install (including product training). The small size of the Portuguese market – with 900 doctors registered in the medical specialty targeted by this company – as compared to the size of the Brazilian market – which has 17,500 doctors in the same specialty – in addition to the internal crisis in Portugal means that internationalization is not a choice but an urgent need in some cases. Furthermore, as the software increases the productivity of medical personnel, it actually makes way for decreasing medical staff headcount. This plays against the sales of the product in a conflict‐avoiding society such as Portugal (Hofstede, 2001) that does not have a habit of making doctors redundant. To prevent or overcome barriers, internationalization – in this case, exporting – needs to be embedded in a conscious overall strategy and it should not be started before the spinoff is sufficiently prepared. This situation of ‘readiness’ includes the following (van Geenhuizen and Ye, 2012b):

A product/service that is in demand in markets abroad both in the current situation and near future and can be easily adapted to local requirements (standards, taste, etc.), as well as a consciously selected mode of entry (agent, own office, etc.), these as parts of an Export Plan that needs to be in place.

In the case of a stepwise development: a solid position in the domestic market which gives confidence abroad and provides cash flow and working capital to develop the market abroad.

Significant management time and strong managerial commitment in the USO.

Sufficient financial resources, to cover costs of product modification, travel, international marketing, but also human resources in place to run the export (additional staff).

Export knowledge and skills, for example, how foreign markets operate (e.g. standards), foreign currency management, export documentation, export credits insurance, country and industry sector profiles.

Access to trade networks in the host country, like marketing organizations, distribution channels and logistic networks.

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8. Marketing and sales training for USOs Sales and marketing was generally a problem area in all of the companies in the sample (it actually ranked nº3 amongst the entrepreneurial skills missing and hampering growth). In other words, all of the CEOs we interviewed each had the same priority: to increase annual sales of their products and services. A major area which was a novelty to many training participants was the material set out by Geoffrey Moore in Crossing the chasm – Marketing and selling technology products to mainstream customers (1999), made available to the consortium by one of the partners. Significantly, “all businesses, even those which are not high tech, can benefit from the ‘crossing the chasm’ concepts… as all businesses should aspire to introducing, at some stage in their life cycle, a discontinuous innovation into the marketplace. Technology products include software products, which hold a promise of generating millions for their creators and entrepreneurs. Many never fulfill this promise however. Why is that?” (Oliveira and Ferreira, 2013, p.22). The answer is that many companies fail to get over the chasm and into mainstream markets, as Figure 3 portrays, in a revised technology adoption process.

Figure 3: A revised technology adoption perspective (adapted from Moore, 1999) (reproduced from Oliveira and Ferreira, 2013, p.23) “One mistake is that a niche strategy is not followed, as Moore (1999) advocates, especially during the chasm period where a carefully selected target segment should be literally ‘invaded’, a segment part of the mainstream marketplace.” (Oliveira and Ferreira, 2013, p.22). The desire to ‘sell to all’, irrespective of what the customers represent, in an all‐out sales effort, more often than not based on little useful information, means that valuable resources will be wasted. Start‐ups need to rely on marketing messages by word‐of‐mouth, with consumers referencing each other. A number of informed users of the product need to reinforce it to enable entrance into the mainstream market – the early majority, in Figure 3, represents 1/3 of the total market and moving on to the late majority represents a further 1/3 of the total market – discussing these concepts was new to many training participants. Note that some USOs are highly specialized such that there is no mass market for them, but only a handful of global customers. Significantly, the training about marketing resulted in a discussion about why certain companies had so far failed to ‘cross the chasm’. On the other hand, how had certain competitors managed to get across?

9. Conclusion and future steps The Spin‐Up consortium has: a) determined a certain research approach; b) developed research tools – full and short versions of a questionnaire, to be delivered face‐to‐face as well as over the Internet (Annex I); c) performed research, involving 99 USO companies; d) analyzed the research data; e) decided upon the

Manuel Au‐Yong Oliveira et al. structure of a training program aimed at USOs in order to increase the growth of this type of firm; f) developed training materials, shared between the partners – case studies and training manuals; and, g) delivered full pilot training sessions in three countries, in order to test the training model. The Spin‐Up consortium has witnessed considerable interest in the university spin‐off (USO) information and knowledge that it has generated and communicated. Academics/lecturers and students alike, who have the ambition or realize that some day, in a not so certain future, they too may become entrepreneurs utilizing and bringing to market knowledge capital acquired in universities, tend to be intrigued as to the reasons behind the lack of USO growth. Future steps of the project include studying the best way to utilize and leverage the training materials generated by the consortium – the case studies and training manuals – as well as to assess the possibility of creating a medium for more wide‐spread dissemination of the project findings and results.

Acknowledgements The authors would like to thank Gonçalo Meireles, the consortium leader and CEO of Advancis, for having read this article to validate its contents.

Annex 1 – a description of the full Spin‐Up questionnaire The content of the full questionnaire involved (van Geenhuizen and Ye, 2012a):

“Entrepreneurial skills. Presence of important entrepreneurial skills in the management team (2011): 17 skills, e.g. concerning technology, management, finance, market and marketing, the establishing or maintaining of networks, strategy and planning etc. (all measured on a five‐point scale).

Founding team’s skills background (at start): Size of founding team; education of team members (discipline and level); pre‐start experience (experience of starting a firm, work experience).

Background of current management team skills (2011) (if different from the founding team): size of the team; education of team members (discipline and level); pre‐start experience (starting a firm, various work experiences).

Firm demography and growth: Year of establishment (start of project activities; legal registration); status in 2011 (fully independent / part of a holding etc.). Employment size (full time equivalents ‐ fte) at start including founding team members as well as employment size in 2011 (fte); size of turnover in 2011 (size classes); indication of profitability in 2011; level of internationalization of activities. Important missing resources other than skills and experience and years of occurrence. Education/training taken and effectiveness of these courses.

Strategy and business environment. What the firm actually sells: e.g. patented knowledge, systems, end‐ products, advice, etc.; type and scope of technology; type of customer market (e.g. energy, health care, transport, city planning, construction, etc.); newness of the product / process in the sector; type of intellectual ownership (IO) protection (patents, trademarks, etc.).

Assessment of leadership skills and team integration: Leadership behavior assessed through the agreement with various statements related to the interaction with the people being worked with.

Evaluation bias (self or team): Two questions with self‐assessment bias are Question 1 (entrepreneurial skills) and Question 4 (leadership behavior). Testing and discussion of the questionnaire brought to light a positive bias. Therefore a question was added on recent changes (strong increase), which may reveal a less positive pattern in the recent past” (Oliveira et al., 2012).

References Cateora, P.R., and Graham, J.L. (2005) International marketing. 12th ed. McGraw‐Hill, New York. Day, D.V. (2001) “Leadership development: A review in context”, Leadership Quarterly, Vol. 11, No. 4, pp 581‐613. GEM (2011) Global Entrepreneurship Monitor, Executive Report. London: London Business School, and Babson Park (MA): Babson College. Geuna, A., and Muscio, A. (2009) “The Governance of University Knowledge Transfer: A Critical Review of the Literature”, Minerva, Vol. 47, No. 1, pp 93‐114. Hofstede, G. (2001) Culture’s consequences: comparing values, behaviours, institutions, and organizations across nations. nd 2 ed. Sage Publications, Inc., Thousand Oaks, California.

Manuel Au‐Yong Oliveira et al. INE (2013) Instituto Nacional de Estatística – Statistics Portugal http://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_indicadores&indOcorrCod=0005599&selTab=tab0, accessed on 05‐07‐2013. Jones, P., Robinson, P. (2012) Operations management. Oxford University Press, Oxford, UK. Lappeenranta University of Technology (2013). Strategy for growth trainer manual. January. Leaders2Be and Advancis (2012) HRM and leadership trainer manual. May. Meireles, G. and Reis, C. (2012) Financial planning for growth trainer manual. August. Moore, G.A. (1999) Crossing the chasm – Marketing and selling technology products to mainstream customers. 2nd ed. Capstone Publishing Limited (a Wiley Company), Chichester, West Sussex. Mustar, P., Renault, M., Colombo, M.G., Piva, E., Fontes, M., Lockett, A., Wright, M., Clarysse, B., Moray, N. (2006) “Conceptualizing the heterogeneity of research‐based spin‐offs: A multi‐dimensional taxonomy”, Research Policy, Vol. 35, No. 2, pp 289‐308. Oliveira, M.A., and Ferreira, J.J.P. (2013) Innovation, marketing and sales tools for growth trainer manual. February. Oliveira, M.A., Ferreira, J.J.P., Xavier, A., de Sousa, J.C.C.P., Meireles, G., Sousa, M., Tomperi, S., Torkkeli, M., Salmi, P., Tolsma, A., Ye, Q., Tzmrielak, D., and van Geenhuizen, M. (2012) “Spin‐Up – Creating an entrepreneurship coaching and training program for university spin‐offs”. Academic paper presented at the 7th ECIE 2012 – Santarém, 20-21 Sept. Proceedings: Vol. 2, pp 530-538, Viva, C., and Lucas, F. (Eds.). Pirnay, F., Surlemont, B. and Nlemvo, F. (2003) “Towards a typology of university spin‐offs”, Small Business Economics, Vol. 21, pp 355‐369. Sousa, M., Barroca, A., Flohil, F., and Neto, C. (2013) “HRM, High Performance Work Systems and Leadership for the Growth of University Spin‐offs”. Investigação e Intervenção em Recursos Humanos IV – Os Novos Contextos da Gestão de Recursos Humanos. Escola Superior de Ciências Empresariais do Instituto Politécnico de Setúbal, 28‐29 January. Taheri, M., and van Geenhuizen, M. (2011) “How human capital and social networks may influence patterns of learning of academic spin‐of firms”, Papers in Regional Science, Vol. 90, No. 2, pp 287‐311. The Economist (2013) “The Sleepwalkers – A euro disaster waiting to happen”. May 25‐31. Van Geenhuizen, M. (2013) “From Ivory Tower to Living Lab. Accelerating the Use of University Knowledge”, Environment & Planning C Government and Policy (in print). Van Geenhuizen, M., and Soetanto, D.P. (2009) “Academic spin‐offs at different ages: a case study in search of key obstacles to growth”, Technovation, Vol. 28, No. 10, pp 671‐681. Van Geenhuizen, M. and Ye, Q. (2012a) Spin‐Up Research Report. Final version ‐ July. Van Geenhuizen, M. and Ye, Q. (2012b) Internationalization for growth trainer manual. August. Van Looy, B., Landoni, P., Callaert, J., Pottelsberghe, B. van, Sapsalis, E. and Debackere, K. (2011) “Entrepreneurial effectiveness of European universities: an empirical assessment of antecedents and trade‐offs”, Research Policy, Vol. 40, pp 553‐564.

Entrepreneurship Versus Self‐Employment in the Context of Social Changes in Romania: Individual and Contextual Factors Alina Badulescu and Roxana Hatos University of Oradea, Faculty of Economic Sciences, Romania abadulescu@uoradea.ro roxanahatos@gmail.com Abstract: Social change in Romania the last 20 years have brought great changes in labour market structure. These changes are explained both by former communist country characteristics and by the dynamics of the economy. There are systematic differences in social compositions of the country and there are different contexts in which economic activity is developed in various types of countries. Theories of entrepreneurship distinguish between push and pull type of mechanisms explaining self‐employment and business start‐up. As widely recognized, economic spill‐over effects of entrepreneurships are more significant in the case of enterprises that invest serious human, physical and financial capital than in the case of those adopting self‐employment as unique solution to grim prospects for employment. That is why we consider as a relevant research topic the description of Romanian population of self‐employed individuals starting from specific hypotheses derived from theory. The final aim is to assess the weight of the two types of entrepreneurs, by using recent survey data. The objective of the paper will be fulfilled by using bivariate and multivariate statistical techniques to analysing most recent EVS (European Values Study) data collected in Romania, which contains items identifying self‐ employed individuals. Subsequently, we will test hypotheses connecting the status of self‐employment with level of education, level of parents’ education, type of residence, occupation of parents and gender. Our expectations are that, contrary to the ideal‐type of daring‐educated‐upper‐class entrepreneur, most of our self‐employed individuals are of push‐ type, being less educated and having a more deprived socio‐economic background (with parents with lower status occupations, with lower cultural capital) than active employed citizens. The results of the statistical analyses will be interpreted against the theories in the area and will be related with the economic and socio‐demographic context of Romania. In the concluding chapter, the consequences of the findings for Romanian social and economic policies will be examined, and the necessity for the emergence of a solid economy and a large and a powerful middle class, will be discussed. Keywords: entrepreneurship, self‐employment, social change

1. Introduction When the state cannot provide a strong economy and secure jobs and private investors from abroad are missing, entrepreneurship is seen as a primary source of economic redemption. This grim has been, peculiarly, the situation of Romania: a post‐communist society bearing the lack of material, human and social resources that entails one of the most brutal communist dictatorships. Moreover, making the situation more difficult, as previous researches have already shown (Hatos, Ștefănescu and Hatos 2012; Hatos and Hatos 2011, Badulescu and Simut 2012), post‐communist countries have a negative balance‐sheet of entrepreneurship which is usually explained by the lack of economic and cultural resources, which are both necessary to support entrepreneurship. Popular visions of entrepreneurs tend to glorify this economic category with reference to the talents, skills, determination and courage on the one hand, but also thinking of supposed economic and symbolic returns of being self‐employed. Researches on the covariates of entrepreneurship display, however, a more nuanced view of entrepreneurship: many business owners start their enterprises due to a lack of alternatives on the labour market on which employed jobs usually appear most of the time economically more lucrative and safer. In our paper we investigate several causes and outcomes of self‐employment in post‐communist Romania using the 2008 EVS (European Value Survey) data. Our hypotheses are that push factors for entering self‐ employment predominate and that subjective benefits – job satisfaction produced by greater autonomy for business owners – compensate for the lack of economic and social outcomes of self‐employment. In the following pages we are building several hypotheses concerning the predictors of entrepreneurship relying mainly on the push factors. Then we build several hypotheses concerning the expected outcomes of entrepreneurship attempting to justify entry and persistence into entrepreneurship despite the apparent lack of impressive material returns. We are testing the hypotheses using the Romanian data of the 2008 wave of European Value Survey and show that while the predictions of push factors theory and the absence of

Alina Badulescu and Roxana Hatos significant economic returns are supported by these data, the effects in terms of job satisfaction are large enough to justify entering and persistence in self‐employment.

2. Predictors of entrepreneurship In this article we are regarding entrepreneurship following the definitions of Knight (1933) and Drucker (1970) as any kind of self‐employment in which a person is risking his or her own resources, firstly the material ones, in order to run an economic enterprise in the legal market. Most of the literature regarding the individual predictors of entrepreneurship underlines the impact of gender and age. It is noticed that men show a higher likelihood of being entrepreneurs than women (Georgellis and Wall 2005; Walker and Webster 2007). This issue can be explained by the fact that the mechanisms of cultural models’ reproduction and social roles’ transmission favour men. Deficiencies of women’s entrepreneurship have been recorded in recent researches in Western Romania too (Dodescu, Badulescu et al. 2011) Age has also been found to have a positive effect on business ownership (Walker and Webster 2007). This is not because youth tend to get into self‐employment less than older generation does, but because at a younger age the changes in occupational status occur more frequently (Evans and Leighton 1989). Moreover, older people have had already acquired a prosperous economic situation, thus not being motivated to start a business out of the desire to gain a large income. Therefore, we expect that Romanian entrepreneurs to be likewise more likely men and of younger age. Almost twenty years ago Amit and Eitan (1995) have consecrated in the economic literature the distinction among push and pull motives of entrepreneurship. They have highlighted the fact that many of the business owners are in the area of entrepreneurship because they had not find opportunities in the field of paid labour. A possible negative effect of education is predicted by the theory of push factors, attributing to those less educated a more fragile position on the labour market (Moore and Mueller 2002). However, in some instances advanced education is found to be also predictive of entrepreneurship – as highly educated people tend to start service businesses with increased added value. One can expect thus a non‐linear relationship of education and the probability of business ownership. Another possible push factor is the place of residence: the larger the settlement in which one resides the greater the economic opportunities and likewise the chances of finding appropriate paid job. Vice versa, in smaller localities the labour opportunities are scarcer and the more forceful the push towards self‐ employment (Hatos, Ștefănescu and Hatos 2012). We are expecting thus, a higher incidence of self‐ employment in the rural area and in the small towns than in the larger cities of Romania.

3. Outcomes of self‐employment Since we expect that the average level of education of self‐employed individuals is lower than that of employees, it is natural to anticipate that the occupational status of these persons to be on the average lower than that of those on paid jobs. It has been consistently found that the pecuniary gains of employment do not justify entering into self‐employment. According to most robust estimations the median incomes of self‐ employed are lower than that of employees controlling for education and age (Hamilton 2000; Moskowitz and Vissing‐Jorgensen 2002; Van Praag and Versloot 2007). In his famous article on the benefits of self‐ employment Hamilton (2000) finds that people entering self‐employment would be better off getting a paid job and that lower income is not explained by the fact that the lower skilled workforce is pushed into self‐ employment. Thus, we expect that self‐employed Romanians have been earning, on average, less than employee adults. Given these puzzling findings concerning the outcomes of self‐employment economic researchers had to look for other incentives that explain the resilience and risks undertaken by entrepreneurs. Two of them stand out as important: happiness and job satisfaction. General subjective well‐being, often equated with happiness, is found in Romania as well as in Europe to be highest among self‐employed individuals and lowest among self‐employed ones, with the employees somewhere in between (Bălțătescu 2009). However, as well‐being is correlated with other important variables

Alina Badulescu and Roxana Hatos related to employment status, like income it is possible that our analyses about the positive impact of self‐ employment on well‐being to be not so evident in our Romanian data. Regardless of other outcomes of employment status like income, self‐employment has been consistently across time and space in the developed world proven to provide better job satisfaction than employment (Andersson 2008; Benz and Frey 2008). This has been explained via the psychological outcomes of autonomy and heteronomy which adults are taking on high regard when evaluating their jobs (Benz and Frey 2008). We expect, in agreement with the previous literature, to find higher job satisfaction among Romanian self‐ employed than among employees.

4. Data and variables In order to answer the research questions and to test our hypotheses we have used the Romanian dataset of latest published wave of European Value Survey from 2008 (1489 nonweighted cases, representative sample of adult Romanian citizens). As most of the operationalization and measurements, the EVS does not distinguish between entrepreneurship and self‐employment, the latter being a more operational measure of entrepreneurship. Therefore, employment status stands as indicator of entrepreneurship and distinguishes between several important categories: employees, self‐employed, retired, housewives, students and unemployed among which one has to choose as main employment (or occupational status). Because entrepreneurship is defined not only as a factual status but as a general behavioural orientation (say habitus), current employment status might not be enough to indicate this orientation – as many former, ageing entrepreneurs might have retired, therefore the last employment status before retirement should also be considered. The independent variables entailed by the literature review are: 1) type of residence, measured by the number of inhabitants of the settlements where the person resides, instead of the administrative distinction among rural or urban settlements, and 2) highest level of education reached by the subject recorded in 7 categories corresponding to the ISCO classification of educational levels. The consequences of employment status followed in our research are: income, measured via the average income per household, social status, measured using two standard measures – SIOPS and ISEI (described in some details below), and subjective well‐being measured using a simple scale of life satisfaction (4 points, where 4 stands for very happy) and 10‐points scale of job satisfaction where 10 stands for extremely satisfied with the job. Social Status was measured in the EVS in several ways among which two the most frequently used in the empirical research stand out: the SIOPS and the ISEI. SIOPS stands for Standard International Occupational Prestige Scale and was basically developed by Ganzeboom and Treiman (1996) which assign prestige measures to hundreds of occupations classified according to ISCO 88 of ILO. The International Socio‐economic Index (ISEI) was developed by Ganzeboom and measures the standing of occupations according to their average education and income levels (Ganzeboom, De Graaf and Treiman 1992), more precisely through the average capacity of each occupation to transform education into wealth.

5. Results 5.1 Employees and self‐employees in Romania According to the 2008 EVS data collected in Romania, the proportion of self‐employed adults was less than 4% while that of the employees was around 42%, and of the retired or pensioned persons was 34%. The incidence of self‐employment is significantly lower than the European average of 9% recorded through the European Social Survey of the same year (Hatos, Ștefănescu and Hatos 2012). In the Romanian EVS the percentage of housewives or of students was higher than that of self‐employed people. Considering the present and the last occupational status when active (of the retired and pensioned) of the subjects we have built a new variable that identifies among present and past employees and self‐employed people. It turns out that around 6% of the Romanian adults are or had been self‐employed as their main occupation while the proportion of employees is an overwhelming 76%.

Alina Badulescu and Roxana Hatos

5.2 Predictors of self‐employment 5.2.1 Gender and age More men are or had been employed than women, the same being true for self‐employment. The contingency table of gender and employment status highlights the simple fact that men are more active on in the economic field than women nothing significant being inferred concerning the gender differentials in entrepreneurship. Our data shows that past and present male employees are 79% comparing with 7% past and present male self‐ employed and past and present female employees are 74% comparing with 4% past and present female self‐ employed. The hypothesis that entrepreneurs are older than employees is not supported by the Romanian EVS data either. The average age of present employees had been similar to that of the present self‐employed individuals in the Romanian data of EVS. Type of residence Self‐employed persons are more likely to be found in small localities (67% in places smaller than 10,000 inhabitants) while present employees are more easily found in larger places (44% in towns over 50,000 inhabitants and 48% in places smaller than 10,000 inhabitants). This implies that a large share of the Romanian self‐employed individuals is active in farm‐related occupations and probably even in farming. Table 1: Size of place of residence by type of employment (row percent) na

under 2,000 0

2,000‐ 5,000 42

5,000‐ 10,000 18

10‐ 20,000 9

20‐ 50,000 3

50‐ 100,000 3

100‐ 500,000 21

500,000 and more 3

employee present

employee past

self‐employed present

self‐employed past

no occupation

Total

Source: own calculations based on Romanian data of EVS 5.2.2 Highest level of education On average, employed people are better educated than self‐employed. The percentage of those who have fulfilled at least the first stage of the tertiary education among the present self‐employed is 5 points lower than that of the present employees, while the percentage of those that graduated only from basic levels of education is much higher for self‐employees (45% as compared to 14% for graduating the lower secondary education at best). The same difference is true in the case of the retired employees and self‐employees, where we found correspondingly discounted levels of education but the same difference. Table 2: Highest level of education by type of employment

Pre‐ primary education or none education

Lower secondary or second stage of basic education 11 20 14

(Upper) secondary education

Post‐ secondary non‐ tertiary education

First stage of tertiary education

Second stage of tertiary education

1 7 6

Primary education or first stage of basic education 2 18 8

employee present employee past self‐employed present self‐employed past no occupation Total

58 41 52

10 7 10

17 7 12

0 0 0

10 12 5.4

32 16 10.8

23 26 17

26 39 48.5

10 3 7.7

0 4 10.5

0 0 0.1

Source: own calculations based on Romanian data of EVS

Alina Badulescu and Roxana Hatos

5.3 Outcomes of self‐employment Given the more precarious education of the present and past self‐employed, it comes as no surprise the fact that the household average monthly income of the self‐employees is much lower than that of those who work for employers. Table 3: Average income per household (spring 2008, in lei)

Lei

n.a.

810

employee present

1,875

employee past

1,036

self‐employed present 1,589 920 self‐employed past no occupation

952

Source: own calculations based on Romanian data of EVS The average of income per household (see Table 3) in our data is 2,911 lei for employees and 1,509 lei for self‐ employed. Therefore, is no surprise that self‐employed persons hold occupations with status measures lower than that of those who are employed. While there had been an increase in occupation status among the present retirees and present employees and self‐employees, a 3‐point difference in average SIOPS and ISEI is recorded in both cases in favour of employees. Table 4: Employment status and social status (averages)

SIOPS ISEI

employee present

employee past

self‐employed present

self‐employed past

no occupation

Total

Source: own calculations based on Romanian data of EVS

5.4 Subjective well‐being Job satisfaction is on average higher with one‐scale point for self‐employed individuals than for employed ones, being actually the highest among the employment categories in the case of self‐employed. Thus, one of the main outcomes of self‐employments appears to be a high job satisfaction which appears to be conserved even after the self‐employed person retires. Table 5: Averages of job satisfaction per employment status groups (How satisfied are you with your job? (1‐ 10)) employee present

7.36

employee past

6.79

self‐employed present 8.37 self‐employed past

8.50

no occupation

6.29

Total

7.32

Source: own calculations based on Romanian data of EVS

Alina Badulescu and Roxana Hatos To the question How satisfied are you with the job? the results show that self‐employment past and present averages is 14.15, comparing to past and present employee average of 16.87. General happiness appears not being influenced significantly by employment status but rather by age: both retired employees and self‐employed individuals appear to be happier than their younger, active, fellow citizens. Moreover, being active seems to decrease happiness as not occupied individuals declare themselves being on average happier than currently employed or self‐employed individuals. Table 6: Averages of happiness per employment status groups (Taking all things together, how happy are you? (1‐4)) employee present

2.07

employee past

2.35

self‐employed present 1.94 self‐employed past

2.47

no occupation

2.22

Total

2.20

Source: own calculations based on Romanian data of EVS To the question Taking all thing together, how happy are you?, the results show that self‐employment past and present averages is 4.41 comparing to past and present employee average of 4.42.

6. Conclusions Incidence of present and past entrepreneurship in Romania is rather low: around 6% of adults are or had been self‐employed the moment of the data collection (spring 2008). This does not come as surprise given the post‐ communist legacy that depresses the propensity for self‐employment everywhere in the former communist countries (Hatos, Ștefănescu and Hatos 2012). Most of our expectations regarding the predictors and outcomes of self‐employment in Romania were met by the EVS 2008 data. It has been proven by our data that the push model of entrepreneurship is supported in the Romanian case, as elsewhere in Romania, self‐employed individuals being usually less educated than those on paid jobs, and residing more often in villages and small towns. The material and symbolic outcomes of entrepreneurship come in a logical manner: families of self‐employed Romanians earn on average less than those of employees and have lower average social status (measured using indexes of occupational status), than those working for salaries. One can ask, consequently, which are the rationales for embarking on a risky entrepreneurial career if the economic and social returns of such a decision are so low compared to the alternative of working for an employer. There are at least two different answers to this puzzle: firstly, for many of those in this situation self‐employment might be the only feasible alternative, given their poor education and some access to liquidity – this is an explanation corresponding to the push model of entrepreneurship; secondly, there are some important non‐economic returns for self‐employment which can offset the risks undertaken, the lack of large earning and the hard work. Large job satisfaction of Romanian business owners supports the theory that autonomy is one of the reasons for which people choose self‐employment and persist in this direction. Our self‐employees are found mainly in small localities (67% in places smaller than 10,000 inhabitants) and on average, employed people are better educated than self‐employed. Related to these conclusions one measure at national level could be of support these economic activities by providing technical support and assistance. Our model of self‐employment in Romania has its limits due to the fact that the analysed data are from 2008. Consequently the effects of the economic crisis could not be assessed in the light of our model. A further research on more recent data would reinforce the conclusions of the study.

References Amit, Raphael, and Eitan Muller. (1995) “‘Push’ and ‘pull’ entrepreneurship“, Journal of Small Business & Entrepreneurship 12(4), pp 64‐80.

Alina Badulescu and Roxana Hatos Andersson, Pernilla (2008) "Happiness and health: Well‐being among the self‐employed", Journal of Socio‐Economics 37(1), pp 213‐236. Badulescu, Daniel, and Ramona Simut. (2012) ”The Bank Lending to SMEs in Romania during Crisis Times. An Empirical Approach on the Relation Trust ‐ Length – Loyalty”, Conference Proceedings of the 7th International Conference on Currency, Banking and International Finance. How Does the Central and Eastern Europe Cope up with the Global Financial Crisis?, University of Economics In Bratislava, September 27‐28. Bălțătescu, Sergiu (2009) Fericirea în contextul social al tranziției postcomuniste în România. Oradea, Editura Universității din Oradea. Benz, Matthias, and Bruno S Frey (2008) "Being Independent is a Great Thing: Subjective Evaluations of Self‐Employment and Hierarchy". Economica 75(298), pp 362‐383. Dodescu, Anca, Alina Bădulescu, Adriana Giurgiu, and Ioana Pop‐Cohuț. (2011) "Women Entrepreneurship in the Western Romania. Research Results and Policy Recommendations" Theoretical and Applied Economics 1(1), pp 25. Drucker, Peter (1970) "Entrepreneurship in business enterprise", Journal of Business Policy 1(1), pp 3‐12. Evans, D. S. and L. S. Leighton. (1989) "Some empirical aspects of entrepreneurship", The American Economic Review 79(3), pp 519‐535. Ganzeboom, Harry BG, Paul M De Graaf and Donald J Treiman. (1992) "A standard international socio‐economic index of occupational status", Social Science Research 21(1), pp 1‐56. Ganzeboom, Harry BG and Donald J Treiman. (1996) "Internationally comparable measures of occupational status for the 1988 International Standard Classification of Occupations", Social Science Research 25(3), pp 201‐239. Georgellis, Y. and H. J. Wall (2005) "Gender differences in self‐employment", International Review of Applied Economics 19(3), pp 321‐342. Hamilton, Barton H. (2000) "Does entrepreneurship pay? An empirical analysis of the returns to self‐employment", Journal of Political Economy 108(3), pp 604‐631. Hatos, Adrian, Florica Ștefănescu and Roxana Hatos (2012) "Individual and contextual factors of entrepreneurship in Europe: cross‐country comparison", Actual Problems in Economics 9(135), pp 553‐563. Hatos, Roxana and Adrian Hatos (2011) "Individual And Contextual Determinants Of Entrepreneurship: An International Comparative Analysis", Annals of Faculty of Economics of University of Oradea 1(2), pp 107‐110. Knight, Frank Hyneman (1933) Risk, uncertainty and profit: with an additional introductory essay hitherto unpublished: London School of Economics and Political Science. Moore, C. S. and R. E. Mueller (2002) "The transition from paid to self‐employment in Canada: the importance of push factors", Applied Economics 34(6), pp 791‐801. Moskowitz, Tobias J and Annette Vissing‐Jorgensen (2002) The returns to entrepreneurial investment: A private equity premium puzzle? National Bureau of Economic Research. Van Praag, C Mirjam and Peter H Versloot (2007) "What is the value of entrepreneurship? A review of recent research", Small Business Economics 29(4), pp 351‐382. Walker, E. A. and B. J. Webster (2007) "Gender, age and self‐employment: some things change, some stay the same", Women in Management Review 22(2), pp 122‐135.

Environmental Obstacles and Support Factors of Social Entrepreneurship Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza University of Oradea, Oradea, Romania abadulescu@uoradea.ro sebastian.siposgug@gmail.com aborza@uoradea.ro Abstract. Social entrepreneurship is a growing field on research, focused on generating businesses and activities related to social value creation and social mission. Even if it is a relatively new concept, its contribution in meeting effective needs un‐ covered by public sector argues the increasing interest in approaching social entrepreneurship. As usual in emerging new research fields, studies have focused until recently on defining the concept and emphasizing differences distinguishing social entrepreneurship from classical entrepreneurship. Relatively few studies have addressed the issue of entrepreneurial process or factors influencing social entrepreneurship start–ups and their success. In this context, our paper aims to provide information and build knowledge to better understanding of the role played by environmental factors in this regard, as well as their perception among young people who intent to be or are involved in Romanian social enterprises. We used the methodological model proposed by the Global Entrepreneurship Monitor reports to identify individuals involved in social entrepreneurship and we distinguished between hybrid social enterprises and entirely social non‐ governmental organizations. We further assessed the innovative dimension of these enterprises in order to identify change agents as opposed to classical NFP organizations. The social entrepreneurs identified with this method rated the impact of multiple environmental obstacles and support factors on achieving their social mission. The perception of these factors by the general population and students with social entrepreneurial intent was also assessed. A multinomial regression model was constructed attempting to calculate the odds ratio of a person being either a social entrepreneur or intending to be one, compared to the general population based only on the differences in environment hostility and munificence perception. A second hypothesis was that the perception of these environmental factors would be different in the case of those who intent to start‐up a social enterprise when compared to those who have already started. This was tested by using a t test, and afterwards the difference in perception, which we dubbed perception error, was introduced in our model. The main practical implication of this research is bringing to attention the need for changing young individuals’ perception on the threats and opportunities which they will face when starting and running a social enterprise. The perception errors inevitably affect their entrepreneurial intent and might prevent valuable individuals from entering the field. Therefore social entrepreneurship trainings should also focus on fostering a realistic view of the environmental factors that might impact entrepreneurial success. Keywords: social entrepreneurship, environmental obstacles, environmental munificence, entrepreneurial intent, perception error

1. Introduction With the progress of civilization history recorded and due to new challenges that have arisen in the context of global economic crisis of recent years, debates on entrepreneurship and its role in contemporary life of communities acquires new meanings. Displacement of the focus known by the definition of the entrepreneur in the literature reflects a certain tendency to see entrepreneurship as a vector of control of social relations rather than a purely economic approach. It is considered that social entrepreneurship as a particular form of social and economic activity emerged only in the second half of the twentieth century. Certainly, primary forms of social entrepreneurship existed in the past, generally associated with charitable activities. As Ghenea (2011, p. 61) stated, "perhaps the most remarkable example of social entrepreneurship in the classical period (nineteenth century in Victorian Britain) is Florence Nightingale, who developed the first school for nurses." It is generally accepted that this kind of business activity is not focused on immediate financial profit. Social entrepreneurship aims at being an effective approach, even if it does not follow the personal profit of the entrepreneur but the fulfillment of social objectives with broader community impact; maximizing money invested for the good of the community or for solving social problems remains a priority.

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza

2. Conceptual framework 2.1 Specificity of social entrepreneurship Social entrepreneurship shares different objectives than a common enterprise, whose activities pursued by any means financial performance. It is "the entrepreneurial activity that starts from the identification of a social problem (e.g. on education, health, and on other social issues important to the community) and is based on solving the social problems through entrepreneurship specific methods (by structuring organization and finding solutions for action, funding and development of this organization)" (Ghenea 2011, p. 61). We can admit in these conditions that any form of social entrepreneurship is in subsidiary a form of political entrepreneurship. Social entrepreneurship is more strongly conditioned by a pre‐existing framework of government policy and, in general, a particular ideological construct that exists into a society at a certain time. "When entrepreneurship desires new (forms of) sociality, the Citizen's interest Takes priority and new Possibilities of life is the result. A shift from enterprising entrepreneurial Individuals to the Relationships between Citizens and fellow citizens " (Chell et al. 2010 in Hjorth 2013, p.6). If we take Schumpeter's perspective on the entrepreneur (essentially as innovative and ingenious individual and not as manager of economic activities), then we have to admit that social entrepreneurship appears to be quite limited. It is clear the fact that aiming at identifying and solving social problems, the social entrepreneur may seek only unconventional ways of solving widely known problems. The social entrepreneur’s creativity has a fairly narrow range of expression, and radical solutions are only exceptions. If, as Schumpeter states, the entrepreneur is a person who "brings a dream to reality", social entrepreneurship is an extremely problematic demarche: the difficulties faced by social entrepreneur are much larger than the resistance encountered any entrepreneurial endeavor. The social entrepreneur is not "a destroyer of the natural order" (in the words of Schumpeter's entrepreneur classic), perhaps contrary, he or she is a balancing agent who seeks to discover relationships that society at some point considers as abnormal. Deviation from the social norm is of course a judgment in the context. The social entrepreneur must see clearly the current of society in which he lives, but on the other hand he must be tough and strong enough to oppose this trend if it finds that the social effects of a given concept produce negative effects on the life. Decisions must be taken by a social entrepreneur who is not related only to a classical analysis of cost‐benefit. The social entrepreneur profile requires, precisely because of this, dimensions that classic entrepreneur profiles do not require. Like any businessman, the social entrepreneur must be a speculator of opportunities. In his case, however, the major difference is related to the ethical framework under which stands every real opportunity. The classic entrepreneur will speculate market’s weaknesses or regulatory vices with the sole purpose of profit. The social entrepreneur’s decision always has a vigorous moral dimension while the public welfare, good of the community, represents a general purpose of any activity of this type. It is assumed that the success of the social entrepreneur is strongly conditioned by a good resilience to failure whereas to function effectively, social entrepreneurship has to overcome a long series of public prejudice and mentality resistance. Albert Shapiro (1975) accounted between important features of entrepreneur and its ability to accept failures. The fact that in many cases some non‐profit organizations operate efficiently and provide services of social value does not automatically mean that their managers or administrators are social entrepreneurs. According to Peter and Waterman (1982) entrepreneurship is something beyond the solution of management discourse's diagnostic of what the Competitive Organization Needs in a globalized economy. Most times people who set up and manage small businesses or charitable organizations are not real entrepreneurs: they carry out template, even if the initiative belongs to them, they merely carry out the same organization or business that already exists either in their area or somewhere outside the country where it operates. Examples of this are sufficient and they are not representative of social entrepreneurship activities in the area: we can regard these initiatives as extensions of entrepreneurial activity; however, social entrepreneur is characterized by the ability to stimulate and answer the new public requirements. Also the use of new management strategies is specific to social entrepreneurship. In the case of social entrepreneurship, the managerial dimension of personality is well‐defined: if "entrepreneurs rely too often on intuition and subjective beliefs" (Tanțău 2011, p.7), the social entrepreneur is

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza forced to act on certain beliefs or concepts that have a common rational background. And we haven’t included here simple instrumental rationality, but a form of rationality which refers to moral and human principles and beliefs. We assume that social entrepreneurs make decisions and judge opportunities based on preliminary ideas of what constitutes freedom, public welfare, human rights and social progress. The interpretation of these differences is not unitary within the specialized research. The classic entrepreneur’s desire to escape the constraints is interpreted by some authors as an additional form of responsibility. "Gabriele Euchner (2000) believes that entrepreneurs have stronger values than managers namely: Commitment means both responsibility and engagement..." (Tanțău 2011, p 7). What appears less clear here is how the concept of responsibility it is understood. The thinking of entrepreneurs and managers has common grounds, but there are a set of major differences. In the case of social entrepreneurs „desire for social change is then not over‐coded by an interest in economic profit. While economic profit certainly is not excluded, it is balanced by seeking new sociality as result” (Hjorth 2013, p 35). The entrepreneur is the partisan of flexibility that often exceeds the set of social values that animate the type of modern civilization that defends Christianity and is publicly circulating in the Western world, in general. Social entrepreneurship losses substance when it is disconnected from the values of modern civilization and our culture. Social entrepreneurship is targeting ethical business building positive social impact and achieving this objective is only possible under constant connection to the world's values and modern European civilization.

2.2 Social entrepreneurship in Romania Given the widening debate on the social economy theme, it is natural the increased interest in social entrepreneurship in all EU countries. In Romania, these debates are limited due to the lack of an adequate legal framework (the number of organizations engaged in social entrepreneurship is relatively small) especially in the context of economic crisis. As Micsunica and Iorga (2012, p.7) stated, "in Romania there aren’t so far clear and consistent regulations in the social economy, specific types of social economy organizations, operating principles, limitations or existing facilities....". There are also opinions sharing the idea that in Romania there are still formulas that can be explained by "the silence of law". As Vîrjan (2011) stated, the social economy in Romania is regulated, but not enough fostered and encouraged. ”The existing legislative framework is governing some aspects of social economy entities, and those who want to practice social economy have to use legal artifices or seek other legal regulations as appropriate for that activity" (Vîrjan 2011, p.134). The need for conceptual clarification is felt in the space of legal regulations of social entrepreneurship. As noted in the second round table organized at the initiative of the organization Act responsibly ‐ CSR Social Network, held in January 2013 and focused on social entrepreneurship in Romania ‐ opportunities and challenges "in the absence of a clear definition and measurement of social impact tools (audit performed by a third party) entities operating in the social economy sector, introducing incentives and non‐financial measures of support may generate discrimination affecting competition in the free market or lead to abuses. In this regard, it was stressed the need to improve the definition of the social economy, as it appears in social welfare law ‐ in Law 292/2011” (CSR Media, 2013). In the area of public policy in Romania it is difficult to develop reliable measures as long as cannot be made estimations regarding the consistently of social effects. Either way, today social entrepreneurship appears as a support solution from inside EU community policies of sustainable development and generally creating a sustainable social environment. "A small but growing number of Europeans from central and eastern part, social reformers, were grouped as viable social enterprises and received support from international sources for their development. Although it has been considered as an alternative service for unemployment and human services, the concept of social enterprise in Central and Eastern Europe is starting already to reflect the realities recorded in the region "(Nicolaescu, 2011:80). It is of course quite clear that in Romania, a country facing major economic problems, social entrepreneurship culture expansion was not a government priority. However in the general society amid increasingly intense action awareness, one can see an increased interest of entrepreneurs for sustainable development (Badulescu and Petria, 2013). "Rose‐Ackerman (1996) argues that performance and survival rate of non‐profit organizations and for profit depends not only on the institutional structure, but also the characteristics of

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza business and entrepreneur motivation. It is obvious that nonprofit contractors must obtain a relatively high private result for having founded a nonprofit organization" (Nicolaescu, 2011:88). The literature, consequently paints the picture of a hostile environment in Romania. Few studies, however, analyze the perception of present and future social entrepreneurs of this environment. Our research proposes to bring new evidence that this perception could influence the decision to start a social enterprise. Furthermore we argue that in this case the perception is more important than the objective factors. Young entrepreneurs might lose motivation if the perception of environment is distorted towards adversity. These hypotheses are tested in the following section using empirical methods.

3. Research methodology In the following sections we will describe the instruments and data analysis methodology.

3.1 Investigated variables We will briefly present the instruments we used to gather data. 3.1.1 Social entrepreneurship Social entrepreneurship was measured by using the methodology proposed by Lepoutre et al. (2013) for the GEM studies. We used the criteria they proposed to identify social entrepreneurs: first we evaluated the explicit social characteristics, then we selected only those enterprises that were self‐sustaining, and then we evaluated innovation to differentiate between traditional NGOs and NFP social enterprises. 3.1.2 Environmental hostility and munificence In order to evaluate the perception of environmental hostility and munificence, we compiled two scales specific for social entrepreneurship, starting from the existing instruments that study them in relation to general entrepreneurship (Baum and Wally 2003; Ruvio and Shoham 2011; Lin and Shih 2008; Scheepers et al. 2008). Primary analysis of scale characteristics yielded an internal consistency of 0.67 (omega total) for the environmental munificence scale, and 0.79 (omega total) for the environmental hostility scale. These omega values are considered to be adequate, albeit a bit small. 3.1.3 Influence and strength of external factors We also gathered information regarding the participants’ perception of the impact of various external factors (i.e. Competitors, Government, Law, Labour market, Economy, Ecology, Demographics, External Politics and European Union) on the enterprises ability to achieve their goals This measure differs from that of environmental hostility and munificence in that we are interested in the direction of these effects (positive or negative), but also on their perceived strength. This reflects the amount of control entrepreneurs feel they have over their enterprise, compared to external influences. Initial scale analysis yielded an internal consistency of 0.9 (omega total). This value is generally considered to be high, therefore suggesting strong internal consistency. 3.1.4 Social entrepreneurship intent Social entrepreneurial intent was evaluated using a multiple response intent scale. The scale possible answers were “No intent now, or in the future”, “I intent to do so in the next two years, but I don’t have a specific plan”, “I intent to do so in the next two years, and I have already started preparing for it” and “I am currently volunteering in a social enterprise”. We did not force a single answer, however no participant choose more than one option. We then divided the participants based on their answers in for groups. We labelled them “no intent”, “general intent”, “specific intent” and “volunteering”, respectively.

3.2 Data gathering Data was gathered in February – March 2013, using an online form that was distributed to both enterprises and students acting in social enterprises in Romania. We invited 517 enterprises to participate in the study, and after applying the selection criteria of Self‐sustainability, we identified 28 social enterprises, according to the broad definition (social goal), and 23 social enterprises, according to the narrow definition (social goal and

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza social innovation). We choose to use the 28 enterprises selected according to the self‐sustainability criterion, as it allows for more statistical power in our analysis. We also invited 210 students to participate, and after initial validation 208 were used in the study. 2 were removed due to a high number of missing values. Their distribution according to the entrepreneurial intent scale is shown in Figure 1. All participants volunteered for the study, and their answers were anonymous and confidential.

Figure 1: Participant selection flow‐chart

3.3 Data analysis Data analysis was conducted using PASW Statistics 18.0. Missing value analysis was conducted, and after removing 2 students with more than 6 missing values, the rest of the cases showed no pattern of missing data. There were a total of 8 missing values in the dataset (0.04% of total data), and in the interest of preserving the rest of the data they were included in the analysis where possible.

4. Results 4.1 Descriptive data analysis As shown in Table 1 and Figure 2, all the factors are perceived to have a positive impact on the performance of social enterprises, with the exception of the Economy in general as perceived by social entrepreneurs. There are some differences, most notably between entrepreneurs and the general intent category. We shall investigate these differences in detail in section 4.3. Table 1: Perception of environmental factors influence on social enterprise performance Factor Entrepreneurs No intent General intent Competition with NGOs 38.00 34.7619 46.80851 Competition with FPOs 6.00 19.36937 30.61224 Government 16.00 8.849558 7.446809 Law 12.96 13.47826 13.54167 Labour Market 20.37 29.09091 35.41667 Economy ‐14.29 20.72072 19.38776 Ecology 16.67 20.58824 21.73913 Demographics 33.33 39.44954 29.34783 External policy 22.00 20.29703 27.90698 European Union 40.38 50.92593 39.13043

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza Figure 2 also allows us to see a general pattern. Entrepreneurs seem to constantly evaluate the environmental factors as less positive then the other categories. This offers initial support for our main hypothesis, that a perception bias exists, and that this bias, or error, might influence even the decision to become a social entrepreneur.

Figure 2: Graphical comparison of the perception of environmental factors’ influence on social enterprise performance among groups

4.2 A predictive model of social entrepreneurial intent The first hypothesis we tested was that a model could be constructed so as we can predict social entrepreneurial intent based on the perception of environmental factors. For this purpose, since we are conducting a prospective study, we decided to use a multinomial logistic regression model, as it has low requirements regarding data structure and distributions. The levels used in the dependent variable were specific intent, intent, volunteering activity and no intent. The reference category used was no intent. Table 2 shows the model fitting information. As it can be observed the model’s likelihood ratio test has an associated p value lower then 0.05, thus suggesting that at least one of the variables inserted into the model could be a significant predictor. Table 2: Model fitting information Model AIC ‐2 Log Likelihood Chi‐Square df Sig. Intercept Only 447.649 441.649 Final 441.839 417.839 23.811 9 .005

Table 3 shows that all three variables introduced into the model have parameters significantly different from 0, and therefore eliminating them from the model would not improve it. This can also be observed by comparing AIC values of the reduced models, as they are all higher than the full model value. Table 4 shows the parameter estimates of the proposed model. As one can see from this table, the odds ratio of the specific intent group does not seem to be influenced significantly by any of the investigated variables. However in the case of the general intent group the odds ratio are significantly influenced by perceived environmental hostility, munificence and the perceived strength of external influence. More specifically perceiving the environment as being more hostile decreases the odds of an individual to be in the

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza entrepreneurial intent group by 1.618 times. Perceiving the environment as being more munificent increases those odds by 1.611 times, while perceiving the external influences as being stronger further increases those odds by 1.161 times. Table 3: Model likelihood ratio tests Effect

Model Fitting Criteria ‐2 Log Likelihood of Reduced Model 424.099

Likelihood Ratio Tests Chi‐ Square df Sig. 6.260 3 .100

Intercept

AIC of Reduced Model 442.099

Environmental hostility

447.606

429.606

11.767

.008

Environmental munificence Strength of external factors

445.628

427.628

9.790

.020

444.965

426.965

9.126

.028

In the case of the Volunteering group, the only significant influence seems to be exerted by the Perception of Environmental Hostility. Namely, perceiving the environment as being more hostile decreases the odds of someone being in this group by 1.964 times. Table 4: Parameter estimates of the proposed model

Specific intent

General Intent

Volunteering

Std. Error

Wald

Sig.

Exp(B)

Intercept

‐2.381

1.679

2.012

.156

Environmental hostility

.157

.342

.210

.647

1.170

Environmental munificence

‐.264

.328

.647

.421

.768

Strength of external factors

.068

.086

.621

.431

1.070

Intercept

‐2.339

1.091

4.599

.032

Environmental hostility

‐.481

.200

5.795

.016

.618

Environmental munificence Strength of external factors

.477 .150

.186 .052

6.547 8.175

1 1

.011 .004

1.611 1.161

Intercept

‐1.248

1.287

.940

.332

Environmental hostility

‐.676

.257

6.943

.008

.509

Environmental munificence

.396

.232

2.922

.087

1.486

Strength of external factors

.087

.065

1.777

.182

1.091

The pseudo R squared value for our model was 0.123 using the Nagelkerke method, therefore the proportion of the total variability that is accounted by the model is 12.3%.

4.3 Measuring the perception bias A second hypothesis of our study was that the perception of environmental factors differs significantly between those with social entrepreneurial intent and those who are active social entrepreneurs. We started by testing for general assumptions of normality and equality of variances. For normality we used the Kolmogorov‐Smirnoff test, which yielded in all cases p values higher than 0.05, therefore we have failed to reject the hypothesis that the distributions are different from the normal distribution. For testing the equality of variances we used the Levene test, which also yielded in all cases p values higher than 0.05, therefore we cannot reject the hypothesis that the distributions have equal variances. Having met the requirements for using the independent samples t test, we proceeded by comparing the social entrepreneurs group with the social entrepreneurial intent group. The results are presented in Table 5 for the specific intent group and Table 6 for the general intent group.

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza Table 5: Levene and t tests for the comparison of social entrepreneurs group and the specific intent group Levene

T test

Scale F Sig. 0.260 0.613

t 0.621

df Sig. (2‐tailed) 38.000 0.539

Environmental munificence 1.910 0.175

0.987

38.000

0.330

Strength of external factors 0.778 0.383 ‐1.222 38.000

0.229

Environmental hostility

In the case of the students with specific social entrepreneurial intent all the t tests have associated p values higher then 0.05, therefore we cannot claim that the differences between the two groups are statistically significant. Table 6: Levene and t test for the comparison of social entrepreneurs group and the general intent group Levene Scale

Sig. (2‐tailed)

1.287 .260

1.992

.050

Environmental munificence 1.464 .230

‐.007

.994

.961 ‐2.714 75

.008

Environmental hostility Strength of external factors

Sig.

T test

.002

In the case of the general social entrepreneurial intent group the results are shown in Table 6. For the Environmental munificence the t test has an associated p value higher then 0.05, therefore we cannot claim that the differences between the two groups are statistically significant. In the case of Environmental hostility and the perceived Strength of external factors there exists a statistically significant difference between the two groups (p = 0.05, and p = 0.008 respectively). We can conclude that the general entrepreneurial intent group has a lower perception of Environmental hostility then the social entrepreneurs group (m1 = 4.34 and m2 = 4.95, respectively), and a higher perception of the Strength of external factors (m1 = 9.39 and m2 = 7.36, respectively).

4.4 Correcting for perception bias For the interest of our study we assume that the social entrepreneurs already operating on the market have an accurate perception of environmental factors, and therefore any significant difference from them would be due to the perception error of those unfamiliar with the field. In order to assess the influence the perception bias might play on social entrepreneurial intent we decided to compare the predictive model constructed earlier with a second model, which would include a corrected perception bias. For our purpose the correction used was the average difference between groups. This serves to move the average, while not artificially changing the variance due to random error. The corrected values were introduced into a second predictive model. As shown in Table 7, this model no longer offers superior predictive capabilities when compared with simply using the average. This is also evidenced by a decrease in AIC of the model when variables are removed from the model. Table 7: Model Fitting Information of the Perception Bias Corrected Model Model AIC ‐2 Log Likelihood Chi‐Square df Sig. Intercept Only 449.036 443.036 Final 453.102 429.102 13.933 9 .125

Removing the perception error from the investigated variables no longer allows for a valid multinomial logistic model, therefore no other statistical analyses could be performed.

Alina Badulescu, Sebastian Sipos‐Gug and Adriana Borza

5. Conclusions Our study successfully built a predictive model of social entrepreneurial intent of students, based on their perception of Environmental hostility, munificence and the strength of external factors. While the model cannot distinguish between those with strong intent (who have already started their business plan) and those with no intent, thus suggesting that their perceptions might be similar, it is successful in identifying those with general intent (want to start a social enterprise in the next two years, but haven’t started working on specific business plan) and those who do volunteer work for social enterprises. Perceiving the environment as more munificent, less hostile and with stronger external factors significantly increase the odds of a student being in the general intent group, as opposed to the no intent group. Perceiving the environment as less hostile, alone, seems to increase the odds of someone being in the volunteering group as compared to the no intention group. The main limit of the model used is that it doesn’t allow for causal inferences, and it serves mainly for exploratory purposes. However we decided to conduct further analyses in order to better understand this relationship. We found that there exists a significant difference in perception between the general intent group and working social entrepreneurs, and we decided to see how correcting for this perception error might affect our predictive model. However after performing the corrections, no model could be constructed that predicts data better than the group averages. While this is not causal evidence for the influence of perception error on social entrepreneurial intent, it is indirect evidence that such a causal relationship might exist, as correcting for perception error reduced the models capability to accurately predict categories. Based on our results we recommend that this relationship be investigated further, as it might provide an explanation for the low success rate of new social enterprises. A more positive perception of the environmental factors that influence the workings of a social enterprise might attract more students to the field, however if this perception if not accurate it might lead to early abandonment of businesses. Further studies will need to clarify this relationship, and perhaps lead to a causal model.

References Badulescu, D. and Petria, N. (2013), “Social Responsibility of Romanian Companies: Contribution to a “Good Society” or Expected Business Strategy?”, 9th International Conference on "European Integration ‐ New Challenges" – EINCO, 24‐ 25 May 2013, University of Oradea, Faculty of Economic Sciences Baum, J.R. and Wally, S. (2003) "Strategic decision speed and firm performance", Strategic Management Journal, 24(11), pp1107–1129. Dretcanu M. D. and Iorga E. (2012) Institute for Social Economy: the third sector. Recommendations for the proper functioning of social enterprises in Romania, București [online] www.ipp.ro/protfiles.php?IDfile=168. Ghenea, Marius (2011) Entrepreneurship. The road from idea to business opportunities and business ideas, Bucharest, Legal Universe Publishing. Hjorth, Daniel (2013) ”Public entrepreneurship: desiring social change, creating sociality”, Entrepreneurship and Regional Development, Vol. 25, No. 1–2, January 2013, pp 34–51. Lepoutre, J. et al. (2013) "Designing a global standardized methodology for measuring social entrepreneurship activity: The Global Entrepreneurship Monitor social entrepreneurship study". Small Business Economics, 40, pp 693–714. Lin, H.‐C. and Shih, C.‐T. (2008) "How Executive SHRM System Links to Firm Performance: The Perspectives of Upper Echelon and Competitive Dynamics". Journal of Management, 34(5), pp 853–881. McMullen, J. S. (2011) Delineating the domain of development entrepreneurship: A market‐based Approach to facilitating inclusive economic growth. Entrepreneurship Theory and Practice, 35 (1), pp 185‐193. Nicolăescu, Victor (2011) "Social enterprise in the contemporary socioeconomic context", Social Economic Journal, No. 1. Ruvio, A. and Shoham, A. (2011) "A multilevel study of nascent social ventures". International Small Business Journal, 29(5), pp 562–579. Peters, T. and Waterman, R. (1982) "In Search of Excellence". Newark: Harper and Row Publishers. Scheepers, M., Hough, J. and Bloom, J. (2008) The development of an instrument to assess the enacted environment for corporate entrepreneurship in South Africa. Management Dynamics, 17(4), pp 2–18. Tanțău A. Dumitru (2011) Entrepreneurship. Innovative thinking and pragmatic, Ed. C. H. Beck, Bucuresti. Vîrjan, Daniela (2011) "Social economy and the labor market in the current context", Journal of Social Economics, No. 1, p 134 [online] http://profitpentruoameni.ro/wp‐content/uploads/2012/03/Revista‐de‐Economie‐Sociala‐Nr.‐ 1_2011.pdf *** http://www.csrmedia.ro/masa‐rotunda‐antreprenoriatul‐social‐in‐romania‐oportunitati‐si‐provocari/ accesed 20.03.2013

Narrative Analysis of a Highly Creative Entrepreneur Pursuant to Scientific Evaluation Criteria Zuhal Baltas and Handan Odaman Baltas Knowledgehouse, Istanbul, Turkey zbaltas@istanbul.edu.tr handanodaman@gmail.com Abstract: Using scientific evaluation criteria, the current study investigates Steve Jobs’ personality profile, whose innovations in the field of technology are accepted as milestones in our daily and digital lives. Jobs is a world‐famous figure who still acts as a role model for entrepreneurial success. Based on the attitudinal, emotional and behavioral aspects of his narratives, we intend making an exhaustive illustration of his personality characteristics which brought him success in business. Entrepreneurs are actively involved in business creation and development. Thus, they have become the focus of personality research in the field of psychology. Predefined dimensions, such as the Big Five, have been used to explain their personality profiles (Ciavarella et al, 2004; Zhao and Seibert, 2006; Antoncic, 2009). Proactivity, need for achievement, tolerance for ambiguity, affiliation need, locus of control, self‐efficacy are some other factors referred in the literature, for describing entrepreneurial characteristics. In order to assess entrepreneurial potential, to make an effective selection of corporate entrepreneurs who will lead innovations and to predict the future success of entrepreneurial activities, we have attempted to consistently integrate earlier academic findings. Consequently, a tool has been developed based on the shorter version of Measure of Entrepreneurial Tendencies and Abilities, and Entrepreneurial Outcomes questionnaire (Ahmetoglu and Chamorro‐Premuzic, 2010; Ahmetoglu, Leutner and Chamorro‐Premuzic, 2011). It conceptualizes entrepreneurial profile by a six‐ dimensional personality structure. These are entrepreneurial awareness, opportunism and risk‐taking propensity, entrepreneurial creativity, need for progress, entrepreneurial outcomes and entrepreneurial leaders. Case‐based methodology and narrative analysis technique are used in the current study. The data comes from three sources: Steve Jobs’ biography written by Walter Isaacson (2011), the book of his quotations called “I, Steve: Steve Jobs In His Own Words”, edited by George Beahm (2011) and his Stanford commencement speech publically available on You Tube (Jobs, 2005). Keywords: Steve Jobs, case study, narrative analysis, entrepreneurial personality, entrepreneurial success, creativity

1. Introduction Innovation and corporate sustainability are intricately linked to each other. It is also argued that innovation stands for sustainability and compliance with norms leads the way for actualizing innovative opportunities (Nidumolu, Prahalad and Rangaswami, 2009). The driving force for organizational success is innovation. This paper presents the case study of a highly creative entrepreneur who did not only have an innovative mindset for initiating enterprises, but also implemented sustainable innovation for the six business sectors he led. Steve Jobs gave unique directions to personal computers, digital animation, music industry, mobile phones, tablet computing and digital publishing. We will focus on his personality profile and analyze his narratives with reference to six personality dimensions, which are found to be critical in the literature for explaining entrepreneurial characteristics.

1.1 The link between entrepreneurship and personality Psychological dynamics of entrepreneurship are prominently studied by various bodies of research. Apart from variables such as gender, cognitive thinking styles and emotional processes (Sexton and Bowman‐Upton, 1990; Baron, 2004; Cardon et al, 2005), personality has been the focus of attention for understanding entrepreneurs’ stable characteristics. Emphasizing the importance of personality assessment in entrepreneurship, Lachman (1980) argued that entrepreneurial personality affected entrepreneurial behavior and its measurement would enable differentiating entrepreneurs from non‐entrepreneurs. It is well known in academic research that a good measurement relies on a good operational definition. The subject of our study, Steve Jobs, is regarded as a milestone in successful entrepreneurship. That might evoke the thought that entrepreneurship is a well‐established concept, which describes a clear pathway for success. However, it is a term for which a unique definition has been hard to propose. Gedeon (2010) reviewed historical definitions of entrepreneurship under four theoretical frameworks. These were classified as dynamic theory, risk theory, traits school and behavioral school.

Zuhal Baltas and Handan Odaman Our understanding of the concept has direct references to the dynamic theory (Drucker, 1985) along with the risk theory (Bygrave and Hofer, 1991) and behavioral school (Gartner, 1989). These earlier conceptualizations respectively emphasize innovation, recognition and actualization of opportunities and entrepreneurship’s occurrence within a process. In our terms, entrepreneur is defined as an innovative person who creates value by bringing new and different ideas that will benefit individual or corporate level business results together with convenient opportunities. As a central aspect of this definition, innovation involves idea implementation, and it should be supported by creativity which refers to the generation of different and practical ideas (Amabile, 1996). As proposed by Gartner, entrepreneurship is a process. Therefore, entrepreneur is responsible from managing this process. We treat personality, which is emphasized by the traits school, as rather fixed characteristics influencing the effective management of this process. Traits covariate across individuals and the Five Factor Model has presented a theoretical construct that explains this covariation in a guiding manner (McCrae and John, 1992). Openness to experience, conscientiousness, extraversion, agreeableness and neuroticism are globally accepted Big Five traits which are used to assess personality constructs comprehensively (McCrae and John, 1992). They were widely applied for investigating entrepreneurship in relation to various factors, such as long term venture survival, entrepreneurial status and technological innovation (Ciavarella et al, 2004; Zhao and Seibert, 2006; Antoncic, 2009). These and some relevant studies reached differing results when the measured variable changed due to the research focus. However, the general tendency implied that entrepreneurial personality was positively related to openness, extraversion and neuroticism, while the relationship was negative for conscientiousness and agreeableness. It should be reminded entrepreneurial activities can take different forms such as corporate entrepreneurship which involves creating value as an employee for one’s corporate (Burgelman, 1983). The factor of conscientiousness then becomes more of a positive trait, since one recognizes the gap for innovative projects when he or she is highly conscious of already existing processes and systems in the corporate. Research explored a respectable amount of factors other than the Big Five. McClelland (1965) showed men occupied with entrepreneurship had higher scores for need for achievement compared to those having other occupations. Schere (1982) found that tolerance of ambiguity was higher for entrepreneurs than middle and top level executives. Jennings and Zeitghaml (1983) emphasized the importance of internal locus of control. However, Chen, Greene and Crick (1998) asserted that high internal locus of control did not necessarily indicate the perceived capability to do a task. They proposed entrepreneurial self‐efficacy as a distinct construct to assess entrepreneurial potential and avoidance. Roberts (1989) asserted technical entrepreneurs had a low need for affiliation and Crant (2001) suggested proactivity as a useful personality characteristic to understand entrepreneurial intentions. Incorporating the highlighted characteristics into one multi‐dimensional structure aroused as an instant need in the literature. Based on the shorter version of Measure of Entrepreneurial Tendencies and Abilities, and Entrepreneurial Outcomes questionnaire (Ahmetoglu and Chamorro‐Premuzic, 2010; Ahmetoglu, Leutner and Chamorro‐Premuzic, 2011), we have proposed six dimensions for measuring entrepreneurial personality. These are entrepreneurial awareness, opportunism and risk‐taking propensity, entrepreneurial creativity, need for progress, entrepreneurial outcomes and entrepreneurial leaders. Organizations are in a demand for determining the entrepreneurial potential and recruiting innovative candidates who will improve their business. Regardless of the nature of initiatives, entrepreneurial personality is also known to contribute to the success of entrepreneurship process (Schmitt‐Rodermund, 2004). From this perspective, these six dimensions meet organizational demands and they are extremely informative for analyzing the personality profile of a world‐famous entrepreneur who broke new grounds and changed our life styles by means of his innovations. The six dimensions collectively describe entrepreneurial personality with regard to a person’s past experiences, along with required tendencies and abilities for successful innovations. It is worth to note that our conceptualization of entrepreneurial outcomes focuses on the past, since earlier initiatives are considered to affect one’s present self‐efficacy and future entrepreneurial tendency.

Zuhal Baltas and Handan Odaman

2. Methodology of the current study The current study uses case‐based methodology. Although various definitions have been proposed for case studies, a simple and less paradoxical one would be the Webster’s definition, which conceptualizes the term as the detailed analysis of the relationship between an individual unit and its specific context (Flyvbjerg, 2011). In case studies, different trends can be followed for data collection, such as quantitative, qualitative or a combination of both (Flyvbjerg, 2011). The decision relies on finding the most relevant answer to one’s research question. In personality research, a worthy argument is that every individual is unique and this uniqueness is supported by one’s traits. Traits are consistent forms of behavior. Specifically, an individual’s behavior is guided by his interests, attitudes and life styles (Allport, 1937). In the present study, Steve Jobs’ life stories that describe his business trends are the focus of analysis. Therefore, the data is restricted by the selected case’s verbal accounts which illustrate his interests, attitudes and behaviors. Such data units are called narratives and a narrative analysis is conducted for the current research purposes. Narrative analysis aims to answer critical questions about the subject’s account. Specified on the questions of “how” and “what”, it investigates the motives behind that account, its context, components, the purpose it serves and psychological processes affecting it (Emerson and Frosch, 2004). As Riessman (1993) asserts, narrative analysis enables to study how an event is actively constructed through one’s personal experience and the meaning attached to it (pp70). Dealing only with verbal material, data to be analyzed can directly be received from the subject, from the events occurring in their natural settings like a talk show or from already existing resources (Smith, 2000). For the current case study, the data comes from three sources: The first one is Jobs’ biography “Steve Jobs”, written by Walter Isaacson (2011). The second one is the book of his quotations called “I, Steve: Steve Jobs In His Own Words”, edited by George Beahm (2011). This book contains Jobs’ statements recorded by the mass media. The third source is You Tube, which provides the online video record of his Stanford commencement speech (Jobs, 2005). Narrowing down the content search by six‐dimensional criteria (as proposed for entrepreneurial personality), we selected the most relevant and explanatory life accounts, in an attempt to come up with the best real life illustrations of studied personality dimensions.

3. Analysis of Steve Jobs’ personality profile using six dimensional criteria In our analysis, we will first explain what each personality dimension is, then state the notable events and expressions in Steve Jobs’ narrative accounts illustrating the specific criterion.

3.1 Entrepreneurial awareness It describes one’s ability to recognize entrepreneurial opportunities, which will drive the creation of economic or social value. If an individual is entrepreneurially aware, then he/she actively searches for new opportunities and identifies profitable ones that others need more time to see or even cannot see. Jobs’ entrepreneurial awareness first raise to the occasion with Blue Box, which also started his partnership with Wozniak (Isaacson, 2011). The digital Blue Box was a technical device which was used to make free long‐ distance phone calls. Jobs thought it should not remain a hobby, and they could make money out of it. He completed required components for its production and decided on its price. Blue Box costed 40 dollars, but its selling price was 150 which meant to provide good profit (pp 29). It was again Jobs’ idea to turn Wozniak’s circuit boards into a commercial product which gave birth to Apple I. This time, Jobs planned the production of 50 circuit boards to be sold at a price of 40 dollars each. It was expected to earn some profit of 700 dollars, but more importantly, this meant founding their own company (pp 62). Jobs’ active search for new business opportunities was also his way of holding on to life when he experienced the significant failure of his life. He got fired from Apple (Isaacson, 2011, pp 207), and he described the dramatic change, in his Stanford commencement speech (Jobs, 2005), as follows: “I have been rejected, but I was still in love. So, I decided to start over...The heaviness of being successful was replaced by the lightness of being a beginner again” (6:53). His entrepreneurial awareness enabled him to see a new gap of the sector. During a conversation with Nobel Prize winner biochemist Paul Berg, Berg mentioned him how it took so long

Zuhal Baltas and Handan Odaman to get results in laboratory experiments. Jobs advised him to do computer simulations, yet Berg argued such qualified computers were too expensive for universities. It was an important step in NeXT’s foundation. Jobs decided to produce a powerful personal computer for academicians to support them in their research (Isaacson, 2011, pp 212). His investment in Pixar was another significant indicator of his entrepreneurial awareness when the year was 1986. He figured out the future would be supporting Lucasfilm Computer Department’s work, invested in 10 million dollars and owned 70% of the company (Isaacson, 2011, pp 239). Toy Story, Monsters, Finding Nemo and the Incredibles were its some popular productions that won Academy awards. On May 25, 1998, Jobs shared his perspective on identifying the gap in the market for Bloomberg Businessweek (Beahm, 2011, pp 102). His statements were also mentioned in the epilogue of his biography (Isaacson, 2011, pp 567). Jobs emphasized the following “…A lot of times, people don't know what they want until you show it to them” (pp 567). His definition is clearly the essence of what entrepreneurial awareness refers to. Two years later in another interview for CNNMoney, Jobs directly expressed his active search for opportunities (Beahm, 2011). He stated that he was always keeping his eyes open for the next big opportunity. He said he did not know what that next thing might be, but he had a few ideas (pp 15).

3.2 Opportunism and risk‐taking propensity It covers two interrelated aspects: Utilizing the recognized opportunity and the urge to pursue it although it is risky. We assert that internal locus of control, which is the belief that one can control the events in his life, is likely to affect both aspects. The two characteristics can be defined by the decision to exploit an opportunity and the act of exploiting it. Internal locus of control implies that a person feels the events in his life are caused by his own actions. Therefore, it is considered to shape one’s expectations about the future. Earlier research showed that individuals with an internal locus of control would spend more effort for achieving a task, if they previously experienced a failure in that task (Weiss and Sherman, 1973). Jobs believed Apple was the only company that could take the full responsibility of user experience (Beahm, 2011, pp 74). He maintained the same attitude when he shared his thoughts about Apple’s decision to drop Flash on its products. He said, “…If the market tells us we’re making bad choices, we’ll make changes” (pp 42). Utilizing an opportunity means using network efficiently. After Jobs and Wozniak founded Apple and made a presentation at Homebrew Computer Club, one person, Paul Terrell was interested in their work. Terrell owned a computer store called Byte Shop and told them to keep in touch as he left the club. Jobs pursued this opportunity. The next day he was at the store saying, “I’m keeping in touch”. That was how he made Apple’s first sale (Isaacson, 2011, pp 66). Although he did not feel comfortable in doing so, Jobs preferred taking big risks. In his Stanford speech (Jobs, 2005), he shared his story of leaving Reed. Though it was scary (2:34), he took the risk to find his own way. He slept on the floor and used the deposits of coke bottles to buy food, but he had the privilege of taking the class he liked. Literally, Jobs preferred to “stay hungry, stay foolish” which turned out to be the most memorable message in his speech (14:14). Risk‐taking was a business strategy for him. When he did not use a backup for the floppy disk drive, and preferred a high capacity, but slow optic disc with NeXT, he explained its reason as follows: “We saw some new technology and we made a decision to risk our company” (Isaacson, 2011, pp 234). Later on November, 9, 1998, in his interview for CNNMoney/Fortune, Jobs explained that risking failure was essential for being a good artist and he saw Apple the same way. He stated that he would decide to take risks and failure would not be an issue, if he tried his best (Beahm, 2011, pp 91).

3.3 Entrepreneurial creativity It shows one’s level of thinking differently and his or her contribution to innovative culture. It is the ability to develop novel and practical ideas, and it is the central aspect for cultivating innovation. If an individual is entrepreneurially creative, he or she will be more likely to implement innovation.

Zuhal Baltas and Handan Odaman “I know I need to change something,” said Jobs in his Stanford speech (Jobs, 2005, 9:23). He looked in the mirror, and his answer was “No” when he asked himself whether he wanted to do the same thing if it were the last day of his life (9:20). This is what we call Jobs’ “personal innovative culture creation” and this was how Jobs explained Apple’s branding. As embedded in Apple’s “Think Different” motto, Jobs valued thinking outside the box. On August 18, 1997, he explained this with the following sentences for Time readers: “…What is Apple, after all? Apple is about people who think “outside the box,” people who want to use computers to help them change the world, to help them create things that make a difference, and not just to get a job done” (Beahm, 2011, pp 23). To be entrepreneurially creative, finding new and different ideas is not enough. They should be useful as well. When Jobs took control after returning to Apple, he strictly reminded that new products had not brought success, since they had not served the purpose. In one of the strategy meetings, he drew a four‐squared chart that had consumer and professional on one side, and desktop and portable on the other side. He said Apple needed to focus on developing four products that would fit greatly inside each square (Isaacson, 2011, pp 337). Jobs’ entrepreneurial creativity is highly evident in the projects he introduced, such as Apple I, II, Mac, NeXT, Pixar, iMac, iPod, iTunes, iPhone or iPad. In D8 Conference held between June, 1‐3, 2010, he shared how he shifted his focus to design iPhone while he was developing iPad (Beahm, 2011, pp 58). This shift is an incontestable reflection of Jobs’ entrepreneurial creativity, since he was inspired by his recent innovative project to produce the next innovative product of the future. Jobs shared his unique perspective on creativity and innovation in the epilogue of his biography. He said, “You always have to keep pushing to innovate…That’s what I’ve always tried to do‐keep moving. Otherwise, as Dylan says, if you’re not busy being born, you’re busy dying” (Isaacson, 2011, pp 570).

3.4 Need for progress It refers to a person’s eagerness to create positive change which will benefit not only oneself, but also others. It describes the motivation for sustainable improvement. Therefore, an individual with a need for progress makes plans for the future. Jobs liked to describe his products as the products of the future. This was especially emphasized in the launch of iMac (Isaacson, 2011, pp 354‐355). His focus on sustainable improvement was much related to the enriched user experience he promised in his products. In his interview for CNNMoney/Fortune which was published on February 21, 2005, he mentioned that the starting point had always been better user experience: “At Apple we come at everything asking, “How easy is this going to be for the user? How great it is going to be for the user?” After that, it’s like at Pixar. Everyone in Hollywood says the key to good animated movies is story, story, story. But when it really gets down to it, when the story isn’t working, they will not stop production and spend more money and get the story right. That’s what I see about the software business. Everybody says, “Oh, the user is the most important thing,” but nobody else really does it” (Beahm, 2011, pp 105). Jobs’ personal interest in better user experience can be inferred from his following account: “I love it when you can bring really great design and simple capability to something that doesn’t cost much…It was the original vision for Apple. That’s what we tried to do with the first Mac. That’s what we did with the iPod” (Isaacson, 2011, pp 7). Therefore, the positive change was providing better user experience which integrated good design with functionality and physical accessibility. Indeed, it was this vision which caused the big debate between him and John Sculley, who was the earlier CEO of Apple. While Sculley wanted to increase the price of Macintosh by 500 dollars, Jobs resisted it strongly (Isaacson, 2011, pp 157). For Jobs, creating magnificent things and contributing to humanity were much more valuable than making money (pp 41). He explicitly indicated that entrepreneurship was not “cashing in and moving on”, and the hardest work was “making a real contribution” and adding to the legacy of those who went before” (pp 569).

Zuhal Baltas and Handan Odaman

3.5 Entrepreneurial outcomes It takes into account previous initiatives that generated successful outcomes. Specifically, it aims to understand the nature of activities to which an individual attributes his life achievements. This might be the period when he was employed, when he developed processes, products or projects that were not planned by the management, or when he was occupied with social or income‐generating projects. Regarding this dimension, we would focus on Jobs’ entrepreneurial activities before he founded Apple Computer with Wozniak. As it will be seen, his successful attempts both as an individual entrepreneur and as an employer were important experiences enabling him to develop subsequent significant projects. On the Wired magazine published in February, 1996, Jobs personally mentioned the importance of earlier experiences in life: “A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem. The broader one’s understanding of the human experience, the better design we will have” (Beahm, 2011, pp 24). Jobs made his first entrepreneurial success at Hewlett‐Packard Explorers Club. He planned to build a frequency counter and needed some components produced by HP. He called HP’s CEO Bill Hewlett from his home number and asked for the missing parts. At the end of their conversation, Jobs did not only get the components, but also he was hired by Bill Hewlett to HP’s factory that produced the counters (Isaacson, 2011, pp 17). Jobs worked at HP that summer following the first‐year‐end at high school. As an income‐generating entrepreneurial activity, he was also occupied with newspaper delivery. Moreover, in his second year at high school, Jobs spent his weekends and summer working at Haltek as a stock clerk. Having a flair for bargains, he visited electronic flea markets and bought stuff like used circuit boards made of valuable parts or chips. He then sold them to his manager at Haltek (Isaacson, 2011, pp 17‐18). Jobs was a social entrepreneur as well. In the electronics course he took at high school, he created laser light shows with his friends, for parties (Isaacson, 2011, pp 20). He founded a student club called the Buck Fry, which organized music and light shows for students. Of course, the members of the club were also fond of playing pranks (pp 26). Jobs persuaded Wozniak, and they sold almost 100 copies of the digital Blue Box Wozniak had designed (Isaacson, 2011, pp 29). 1974 was the year he left Reed, went back to Los Altos, and waited at the lobby of Atari telling its personnel manager that he would not leave unless he was given a job (pp 42). In 1975, his boss Nolan Bushnell challenged Jobs with the design of a one‐player version of the tennis play called Pong and told he would gain promotion if he could complete it with less than 50 chips. Jobs decided to work together with Wozniak, and they achieved to make the game work with 45 chips. More importantly, they completed the task in 4 days (pp 53). This was a reflection of Jobs’ entrepreneurial success as an employee, since he acted proactively and finished the product’s development with limited resources.

3.6 Entrepreneurial leaders It describes the ability to influence and manage one’s team to implement innovative ideas. If an individual is an entrepreneurial leader, he transfers the excitement of new ideas to his team, allows them to initiate new projects, selects efficient team members, tries every way to overcome obstacles and emphasizes excellence in business results. Jobs was most criticized for his leadership style. Many might prefer describing him as a perfectionist despot, but he knew it was fundamental to protect the harmony in the team environment: “I’ve learned over the years that when you have really good people you don’t have to baby them. By expecting them to do great things, you can get them to do great things. The original Mac team taught me that A‐plus players like to work together, and they don’t like it if you tolerate B work. Ask any member of that Mac team. They will tell you it was worth the pain”, he said. He was supported by his team who prepared themselves a t‐shirt with the message of “90 hours a week and loving it!” (Isaacson, 2011, pp 124). Jobs believed the importance of giving enough space and making his team believe they could achieve anything. This was the motivation behind the innovative and perfectionist designs. Indeed, Jobs thought of each product as a work of art and his team as artists. When the design of Macintosh was completed, he said, “Real artists sign their work” and each team member’s signature was engraved inside the computers (pp 134).

Zuhal Baltas and Handan Odaman Jobs’ method of creating synergy in his team was rewarding them with short vacations. On these vacations that he personally attended, he gave key messages that reflected his strategic thinking. Jobs shared his dream design for the future in one of these vacations as well (Isaacson, 2011, pp 142‐144). Two of the mottos he shared, “The journey is the reward” and “It’s better to be a pirate than to join the navy” were later used as the celebration message of his birthday. On a billboard hired near Apple headquarters, his team wrote: “Happy 28th Steve. The Journey is the Reward.‐The Pirates” (pp 144). He knew that the selection of effective team members and making them feel part of the company’s vision were also critical. He thought the selection was related to finding the person who could be trusted and preventing the company being welled up with B type players (Isaacson, 2011, pp 552). In one of his interviews, Jobs explained the recruitment steps in detail: “It’s not just recruiting. After recruiting, it’s building an environment that makes people feel they are surrounded by equally talented people and their work is bigger than they are. The feeling that the work will have tremendous influence and is part of a strong, clear vision— all those things. Recruiting usually requires more than you alone can do, so I’ve found that collaborative recruiting and having a culture that recruits the “A” players is the best way. Any interviewee will speak with at least a dozen people in several areas of this company, not just those in the area that he would work in. That way a lot of your “A” employees get broad exposure to the company, and—by having a company culture that supports them if they feel strongly enough—the current employees can veto a candidate” (Beahm, 2011, pp 22). As a leader, Jobs had to deal with significant product problems as well. One such instance was experienced with the antennagate scandal. iPhone 4 was not recommended by the Consumer Reports because its antenna did not work properly. Although Jobs was depressed by the problem’s reflection on the media, he took control and wanted to “get to the bottom” of it. He made long meetings with his colleagues and came up with a brave, simple apology: “We’re not perfect. Phones are not perfect. We all know that. But we want to make our users happy”. He successfully persuaded Apple users that the issue was exaggerated. Indeed, iPhone 4 had a low return rate which was even under normal return average (Isaacson, 2001, pp 522). Jobs was well‐known for his pursuance of excellence and his perfectionism might be interpreted as a reflection of his urge for controlling his environment. Among numerous instances showing his need for perfection, an outstanding one would be his insistence that a computer should look beautiful even from the inside. He loved explaining its reason via referencing his adoptive father. He said, “A great carpenter isn’t going to use lousy wood for the back of a cabinet, even though nobody is going to see it” (Isaacson, 2011, pp 133). Jobs’ perfectionism was pretty determining in his leadership style.

4. Conclusion Personal computers, digital animation, music industry, mobile phones, tablet computing and digital publishing would not have developed without Steve Jobs. He gave unique directions to these sectors and acted as a role model for successful entrepreneurship. The current study’s goal was evaluating his life accounts in the light of scientific criteria and focusing on his personality profile in relation to the following dimensions: Entrepreneurial awareness, opportunism and risk‐taking propensity, entrepreneurial creativity, need for progress, entrepreneurial outcomes and entrepreneurial leaders. Based on the attitudinal, emotional and behavioral aspects of his narratives, we intended making an exhaustive illustration of Jobs’ personality characteristics which brought him success in business. Such an analysis will provide a deeper understanding of his personality profile that underlies his potential to change the world for the better.

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A Comparative Study of the Entrepreneurial Potential of Economics Students of the University of Oradea, Romania and Adnan Menderes University, Turkey Olimpia Ban1, Esin Sayin2, Dorin Coita1 and Ali Eleren3 1 Department of Economics, Faculty of Economic Sciences, University of Oradea, Oradea, Romania 2 Business Administration Department, ADÜ School of Economics, Adnan Menderes University, Nazilli, Aydin 3 Business Administration Department, School of Economics, Afyon Kocatepe University, Afyon, Turkey oban@uoradea.ro dcoita@uoradea.ro sayinesin@gmail.com eleren@aku.edu.tr Abstract: There are different assumptions regarding the determining factors of entrepreneurship, both at the macroeconomic level as well as at the individual level. The level of the entrepreneurial activity considerably varies from country to country, the factors of influence acting differently. The generic variables considered to influence the entrepreneurial spirit are: sex, age, education, the perception of the complexity of the administrative system (information and information resources), availability of financial resources, professional experience, tolerance to risk and the preference to be self‐employed (the existence of a successful model in the family or outside it). The purpose of the current study is to identify the entrepreneurial potential of the Economics students and the role of the educational offer in stimulating this potential. Two universities from different areas, yet resembling in what the potential and perspectives are concerned, have been compared: University of Oradea, Faculty of Economic Sciences and Adnan Menderes University, ADÜ School of Economics, Turkey. On one side, we analysed the curricula of the programmes of study of the universities making the object of the research, on issues directly related to entrepreneurship (on entrepreneurs in general, on family companies, mergers, entrepreneurial technologies, social entrepreneurship, entrepreneurial marketing, innovation, business planning, the relation with investors, business plan contests, tutorship and financial support programmes). On the other side, we carried out a survey based on a questionnaire applied to a sample of 327 students in Economics, out of which 177 students of the University of Oradea, Faculty of Economic Sciences, Romania and 150 students of Adnan Menderes University, Turkey. The validity of the items of the questionnaire was checked with Alpha Cronbach both for the results obtained in the research in Romania and for the research in Turkey, per total. The primary analysis of data and also the correlation of the items (through SPSS) have allowed us to infer conclusions. The results obtained reflect interesting similarities between the entrepreneurial information contained in the educational offer of the two universities, with interesting differences between the aspirations and intentions of the students of the two universities. Keywords: students, economic studies, entrepreneurial potential, survey, Romania, Turkey

1. Preliminaries The entrepreneurship is a multidimensional phenomenon, the conceptual and theoretical approaches being built on a variety of disciplines, such as: economics, sociology and psychology. There are different assumptions regarding the determining factors of entrepreneurship, both at the macroeconomic level and individual level. It is appreciated that a moderate economic growth together with high unemployment rate stimulates the entrepreneurial potential as a source of economic growth and job creation. (Caree and Thurik 2006) Very often, the determinants of entrepreneurship are investigated in accordance with a bi‐dimensional choice model, ignoring the fact that that in order to become an entrepreneur is a process made up of several choices. Some authors understand this process and divide it into stages, the first stages being: conception, gestation and launch, considered the entrepreneurship dynamics. The following stages are: adolescence, maturity and decline, being identified as entrepreneurship levels. (Sternberg and Wennekers 2005) Grilo and Thurik (2008) distinguish among seven stages of entrepreneurship: the conceive a business, to make the first steps in starting up the business, to have a new business, to gain experience in the business, to give up to not being an entrepreneur and to definitively give up to being an entrepreneur.

Olimpia Ban et al. The level of entrepreneurial activity considerably varies from country to country, the factors of influence acting differently. The generic variables considered to influence the entrepreneurial spirit are: gender, age, level of education, the perception regarding the complexity of the administrative system (van Stel 2005), the availability of financial resources, professional experience, tolerance to risk and the preference to be self‐ employed (Grilo and Irigoyen 2006). Empirical studies showed that the household income does not influence or only slightly influences the potential to become an entrepreneur, while another factor is intensified ‐ the tolerance to risk. (Davidsson 2006) At the individual level and from the perspective of economic theory, there is the income source choice theory. This theory is useful in describing some factors influencing the decision regarding the occupation. The emphasis lies on the importance of future entrepreneurs’ attitude towards risk Kishlstrom and Laffont (1979) and Parker (1996, 1997) show that the degree of adversity towards risk and the risk differences between two occupational alternatives determine the occupation choice. A research carried out among students in 26 countries regarding their entrepreneurial intentions generated interesting results (Sieger, Fueglistaller and Zellweger 2011). The research started from the Theory of Planned Behaviour (Fishbein and Ajen, 1975). According to this theory, the intention to manifest certain behaviour is influenced by a number of factors, such as: attitude, subjective norms and the control of perceived behaviour. The study mentioned investigated the students’ entrepreneurial intentions, delimitating the intentions to set up a firm and the intentions to get involved in the parents’ firms. The study involved students of several faculties, the analysis of results being distinctly made considering the countries and the faculties (specializations). In the case of the Romanian students, it was noticed that: the entrepreneurial intentions are stronger at the students of Faculties of Economic Sciences compared to the students of other faculties (not applicable in many other countries), more than two thirds prefer to get a job after graduation and only less than 5% intend to set up their own business, after graduation. The situation is changed in five years after graduation, meaning the percentage of those wishing to set up a company after graduation increases to 21.6%. The highest rated reason was that of "income increase” and the lowest rated reason was of "continuing the family tradition". In spite of all these, Romania occupies the 6th position, as an expression of the relation between the entrepreneurial background and the intention to start up or continue the family business (with 29%). One of the main themes of the study was to investigate the role of universities in encouraging entrepreneurship. The students were questioned regarding the universities’ educational offer on entrepreneurship: courses/seminars, communicational platforms and other resources. The themes followed: on entrepreneurship, in general, on family businesses, mergers, entrepreneurial technologies special entrepreneurship, entrepreneurial marketing, innovation, business planning, the relation with the investors, business plan contests, mentoring programmes and financial support. Of all the resources mentioned, only the courses/seminars on "business plans” "general entrepreneurship” were rated over 50%, as being resources provided by universities. The students surveyed expressed the highest need for: workshops and the relations with the entrepreneurs, courses on innovation, contacts for problems concerning the entrepreneurship. Romania occupied the first position regarding the strongest desire to benefit from entrepreneurial education, for the entrepreneurial resources which were missing from the educational offer. The purpose of the research cited was to see how useful universities are, generally, regarding the students’ entrepreneurial intentions and capacities.

2. The purpose of the current study The purpose of the current study is to identify the entrepreneurial potential of the economic students and the role of the educational offer in stimulating this potential. Two universities from different areas, yet similar considering the potential and the perspectives, were compared: University of Oradea, Faculty of Economic Sciences, Romania and Adnan Menderes University, ADÜ School of Economics, Turkey. The objectives of the research:

to establish the favourable conditions to have entrepreneurial initiative: the educational offer, the model provided by the father, family, close friends or a public person, the direct reception of some information

Olimpia Ban et al. on entrepreneurship (as courses, books, journals, governmental policies, entrepreneurship support institutions);

the respondents’ own perception regarding the training they have in the field of accounting, finances and marketing;

to determine the nature of the connection between the social‐demographic characteristics of the respondent (gender, age, number of family members, the average monthly incomes and expenses, the existence of an entrepreneur in the family or among the close ones, the father’s present status and their perception on the knowledge regarding tax payments, accounting records and completion of statements as invoices or ledgers or their knowledge regarding finances and marketing) and the intentions to set up a business after graduation;

The stages of the research:

On one side, we analysed the curricula of the programmes of study of the universities making the object of the research, on issues directly related to entrepreneurship (on entrepreneurs in general, on family companies, mergers, entrepreneurial technologies, social entrepreneurship, entrepreneurial marketing, innovation, business planning, the relation with investors, business plan contests, tutorship and financial support programmes).

On the other side, we carried out a survey based on a questionnaire applied to a sample of 327 students in Economics, out of which 177 students of the University of Oradea, Faculty of Economic Sciences, Romania and 150 students of Adnan Menderes University, Turkey. The students have been involved in the research by the method of availability sampling in June‐July 2012. They are students in different programmes of studies and different years, meaning students in Business Administration, Management and Marketing, Finance and Accounting and Economics and International Relations. The research instrument consisted in a questionnaire, structured into two parts. In the first part there were 19 questions concerning the social‐ demographic characteristics of the respondents (sex, age, number of family members, household monthly median income, household monthly median expenses, dwelling place, year of study, programme of study), including the information related to entrepreneurship and the intention to start‐up a business in the near future (the existence of an entrepreneur in the family, the job in view when graduating, the graduation from a entrepreneurship courses, the literature consulted on entrepreneurship, their knowledge on the facilities provided to entrepreneurs, the countries promoting entrepreneurship). In the second part, there were 67 questions meant to identify the attitude towards work, risk, taking responsibility, the desire for autonomy, formalism, pro‐active attitude, the perception on their own capabilities.

3. Methodology There was a secondary research and a primary, direct research. The secondary research was a documentary study of the curricula of BA studies and MA studies, valid in the academic year 2012‐2013 at the faculties and universities where the study took place. The direct research was the survey method, the instrument used being the questionnaire. The sampling method was the non‐probability sampling, the so‐called spot sampling. The sample was made up of 327 Economics students. The students were involved in research through the availability sampling method in June‐July 2012. Out of the 177 Romanian students, 73.4% are females and are in different specializations and different years, respectively Business Administration 38.4%, Management and Marketing 23.7%, Finance and Accounting 33.3% and Economics and International Relations 4.5%. Out of the total of 177 students surveyed, 55.9% are first year students, 2.3% are second year students and 41.8% are third year students. Out of the 150 Turkish students, 62.8% are females and 37.2% are males. They are up to 18 years old, 0.53%, between 19 and 23 years of (84.31%), between 24 and 30 years old (14.1%) and between 31 and 35 years old (1.06%). They study different specializations and are in different years of study, respectively Business Administration 22.68%, Management and Marketing 42.96%, Finance and Accounting 14.43% and Economics and International Relations 19.93%. Out of the total of 150 students surveyed, 0.53% is first year students, 50.79% are second year students and 48.68% are third year students.

Olimpia Ban et al. The research instrument was made up of a questionnaire, structured into two parts. In the first part, there were 19 questions on the social‐demographic characteristics of respondents (gender, age, number of family members, the average monthly income, the average monthly expenditure /family, stable address, year of study, programme of study), including the information on entrepreneurship and the intention to set up a business in the near future (the existence of an entrepreneur in the family, the job had in view after graduation, the graduation of entrepreneurship courses, the literature on entrepreneurship consulted, the knowledge on facilities provided to entrepreneurs, the countries promoting the entrepreneurship). In the second part there were 67 questions meant to identify the attitude towards work, risk, taking responsibilities, the desire for autonomy, the pro‐active attitude, the perception on their own competencies. The validity of the questionnaire was checked with Cronbach's Alpha coefficient of reliability. Cronbach's Alpha was calculated for the entire questionnaire, separately for the data on Romania and separately for Turkey. The Correlation Matrix was calculated to see the degree of association between items. The Cronbach's Alpha value for the questionnaire applied in Romania is 0.8139 and the Cronbach's Alpha value for the questionnaire applied in Turkey is 0.8787. The degree of reliability is good therefore the questionnaires can be declared valid.

4. Data analysis The first stated objective of the research was to establish the existence of favourable conditions to entrepreneurial initiative: the educational offer of the university where they study, the model provided by the father, family, close friends or a public person, the direct reception of information on entrepreneurship (as courses, books, journals, governmental policies, entrepreneurship support institutions). The analysis of curricula of the programmes of study of the universities participating to the research, on entrepreneurship directly related themes (general entrepreneurship, family businesses, mergers, entrepreneurial technologies, social entrepreneurship, entrepreneurial marketing, innovation, business planning, the relation with the investors, business plan contests, mentoring programmes and financial support) show a very disappointing representation. Thus, we can find in the university curricula only the optional course of Entrepreneurship, for a single specialization and the topics "entrepreneurial marketing" and "financing sources” in the Marketing and Finance courses. The Faculty of Economic Sciences of the University of Oradea has six BA programmes. Of all the programmes and years of study, only one specialization, one programme, Marketing has in the curriculum Entrepreneurship, an optional discipline, in the third year, second semester. The theme of entrepreneurial marketing is studied only as part of a wider marketing theme and without the explicit name of entrepreneurial marketing. For Adnan Menderes University, ADÜ School of Economics, Turkey the situation is similar. Entrepreneurship is an optional discipline for only two programmes of study, different according to the curricula. The rest of the topics are partially studied in the curricula of other courses, without any direct reference to the entrepreneurial initiative. The extent to which the subjects interviewed have an entrepreneur in the family or among close friends has showed a significant percentage of almost half, both in Romania(48%) and Turkey(46.16%), situations when they have an entrepreneur in the family, although only 30‐40% have an entrepreneur model in the family or close ones (Figure 7). This situation can be explained by the fact that entrepreneurship, in both countries, is not similar to the material or financial success. The type of entrepreneurship which is the most spread in these countries is the subsistence entrepreneurship, developed as a result of losing jobs, as single alternative of income source. Regarding the job had in view after graduation, most of the respondents are looking for jobs in the private sector(Romania 70%), followed by the public sector (Turkey 68%). A small percentage for Turkey (6.1%) and a very small percentage for Romania (1.1%) are thinking of setting up their own business. The higher percentage

Olimpia Ban et al. for Turkey can be explained considering the pre‐accession investment impetus existing in Turkey, due to still favourable market for the new entrants. This result is to a certain extent in correspondence with the results of the above mentioned study (Sieger, Fueglistaller and Zellweger 2011), which shows the significant increase of the entrepreneurial initiative only in five years since graduation. It is worth pointing out the lack of coherence among answers to similar questions about future intention jobs, differently positioned in the questionnaire. This lack of coherence can be explained by the uncertainty regarding the decision, the intention to start up a business being even smaller than the one stated.

Figure 1: The position of Romanian students (left), and Turkish students(right), respectively, according to the statement I prefer working in a firm to gain experience, before setting up my own business (from left Total agreement to right Total disagreement) The decision to choose a job instead of starting up a business is fully justified by the need for experience on the labour market, an explanation supported by over 70% of the respondents in Romania and Turkey. (Figure 1) Regarding the training they might have in the field of entrepreneurship (courses, journals, books, information from specialised bodies) the situation is, again, somehow similar for both Turkey and Romania. The respondents state that they attended entrepreneurship courses in a percentage of 20‐30% that they read at least a book on entrepreneurship (over 50% of Romanian students and below 50% of Turkish students) (Figure 2 and Figure 3). Also, the Romanian respondents state that they read at least one journal on entrepreneurship (over 50%), while only a percentage of 21% of the Turkish students did this (Figure 4). This situation might be explained by the access that the University of Oradea acquired a few years ago to a rich data base and electronic resources, intensely used by both the academic staff and the students. The respondents’ own perception regarding their knowledge on tax payment, accounting records and filling in documents like invoices or ledgers for the students of Oradea, shows a percentage of over 30% as indifferent, over 30% as assertive in their own forces and only 7.3 % as very assertive. In turn, the Turkish students are less assertive, with a percentage of over 25% as indifferent and over 50% as distrustful and very distrustful. The assertiveness regarding their knowledge on finances and marketing is relatively similar to their knowledge on tax payment, accounting records and filling in documents like invoices or ledgers both for Romania and Turkey. The information in the public space are even scarcer than in the academic environment, the respondents (a percentage of 60‐80%) are not aware of the opportunities provided by the government in the field of entrepreneurship (Figure 5) and do not know any public insitution which supports entrepreneurship (a percentage of 60‐70%)(Figure 6). This lack of assertiveness might be explained by the weak experience in the field of practice, insufficiently enriched by a very short practice stage for Romania (90 hours for the BA students and 60 hours for the MA students) and up to 6 months for Turkey (over 40% of the respondents in both countries are third year students, therefore they have already completed their practice stage). We examined the extent to which there are certain correlations among characteristics, possible associations between the job had in view after graduation and: gender, age, number of family members, the family income,

Olimpia Ban et al. the average monthly expenses, the existence of an entrepreneur in the family or among close friends and the father’s current job.

Figure 2: The extent to which the students surveyed in Romania and Turkey attended entrepreneurship courses

Figure 3: The extent to which the students surveyed in Romania(left) and Turkey(right) read at least a book on entrepreneurship

21%

43.70 % 56.30 %

Yes

yes no

79%

Figure 4: The extent to which the students surveyed in Romania(left) and Turkey(right) read at least a journal on entrepreneurship The data have been analysed using SPSS statistical analytical software. The hypotheses have been tested by the multiple regression analysis of correlations. The standard deviation situation and data trust looks like this.

Olimpia Ban et al.

90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00%

78.30% 63.68% Yes

36.32%

21.70%

Romania

Turkey

Figure 5: The extent to which the students surveyed in Romania (left) and Turkey(right) are aware of the opportunities provided by the government to entrepreneurs

66.50%

64.30%

70.00% 60.00% 50.00%

35.70%

40.00%

33.50%

Yes No

30.00% 20.00% 10.00% 0.00% Romania

Turkey

Figure 6: The extent to which the students surveyed in Romania (left) and Turkey(right) are aware of at least one public institution supporting entrepreneurship

80% 70% 60% 50% 40% 30% 20% 10% 0%

68% 61% 39% 32%

Yes No

Romania

Turkey

Figure 7: The extent to which the students surveyed in Romania (left) and Turkey(right) have an entrepreneur as a model The results obtained for Romania show the existence of a correlation, yet weak, between:

Q7. What job do you have in view after graduation? and Q3.Number of family members

Olimpia Ban et al.

Q7 and Q6.Is there an entrepreneur in your family or among your close friends?

The lack of a correlation has resulted between:

Q7 and Q1.Gender

Q7 and Q2.Age

Q7 and Q4. What is the average family income?

Q7 and Q5. What are the average monthly expenses?

Q7 and Q15. What is your father’s professional status at the moment? The result:

Q7 and Q26. Their knowledge on tax payment, accounting records and filling in documents like invoices or ledgers?

Q7 and Q27. Their knowledge on finances and marketing?

Table 1: Pearson correlations between items Q6

Pearson Correlation

‐,140(*)

‐,158(**)

Sig. (2‐tailed)

0.045

0.002

Pearson Correlation

‐,140(*)

‐,158(**)

Sig. (2‐tailed)

0.045

0.002

Pearson Correlation

0.061

,113(*)

Sig. (2‐tailed)

0.382

0.029

Pearson Correlation

0.061

,113(*)

Sig. (2‐tailed)

0.382

0.029

Pearson Correlation

0.08

,113(*)

Sig. (2‐tailed)

0.256

0.028

Pearson Correlation

0.08

,113(*)

Sig. (2‐tailed)

0.256

0.028

Pearson Correlation

‐,142(*)

0.001

Sig. (2‐tailed)

0.042

0.982

Pearson Correlation

‐,142(*)

0.001

Sig. (2‐tailed)

0.042

0.982

Pearson Correlation

0.078

,219(**)

Sig. (2‐tailed)

0.27

Pearson Correlation

0.078

,219(**)

Sig. (2‐tailed)

0.27

Turkey

Romania

* Correlation is significant at the 0.05 level (2‐tailed).

Olimpia Ban et al. For Turkey, a correlation, yet week, has been identified between the following variables:

Q7 and Q1.Gender

Q7 and Q2.Age

Q7 and Q4. What is the average family income?

Q7 and Q6. Is there an entrepreneur in your family or among your close friends? ?

Q7 and Q26. Their knowledge on tax payment, accounting records and filling in documents like invoices or ledgers?

Q7 and Q27. Their knowledge on finances and marketing?

The lack of a correlation has resulted between:

Q7 and Q3.Number of family members

Q7 and Q5. What are the average monthly expenses?

Q7 and Q15. What is your father’s professional status at the moment?

5. Conclusions Drawing conclusion is tightly related to the objectives which represented the base of the research. The analysis of the educational offer of the two universities regarding the themes on entrepreneurship has demonstrated the existence of a very poor offer, present only as an optional course and some isolated subjects in the curricula of other courses. In spite of all these, almost a third (26.3% for Romania and 33% for Turkey) attended a course on entrepreneurship. Considering the existing educational offer, we can infer that just a part of the students attended this course within the university curricula and the rest within different modules organized through European projects. The openness and the interest for entrepreneurship are emphasised by the individual and voluntary study of speciality books and journals (the percentages varying around 50% both for Romania and for Turkey), the only exception being the study of some journals in Turkey (where the percentage is only 21%). In return, an overwhelming percentage of the surveyed students are not aware of the opportunities provided by the government to entrepreneurs and do not know any public institution which supports entrepreneurship, both in Romania and in Turkey.

We can conclude that there is not a favourable environment from the point of view of information for the entrepreneurial initiative, despite the obvious interest showed by the students surveyed. The situation in Romania is very similar to that in Turkey, considering this point of view.

Regarding the model provided by the father, close friends or public persons, only approximately a third of the students surveyed (both in Romani and in Turkey) have an entrepreneur as a model, although they have an entrepreneur in the family or among close friends in a percentage of approximately 50%.

The conclusion might be that there are not too many successful models, examples of good practices and success. The subsistence entrepreneurship might not be but encouraging for the young graduates, It is requested the promotion of some successful entrepreneurship models.

We have investigated another possible precondition meant to encourage the entrepreneurial initiative, the existence of a good training in the business field or a good perception of the level of this training. The fields had in view been finances‐accounting: tax payment, accounting records and filling in documents like invoices or ledgers and marketing. The situation for the students of Oradea shows an average of trust of 3.27 on a scale from 1 to 5, for the knowledge on tax payment and marketing. For the Turkish students, the level of trust is below the average, on only 2.57 on a scale from 1 to 5. The trust regarding their knowledge on marketing is relatively similar to the trust related to tax payment, accounting records and filling in documents like invoices or ledgers, both for Romania and for Turkey.

The results show an average and below average trust regarding the students’ knowledge in key fields for the maintenance of a business (finances, tax payment, accounting records and filling in documents like invoices or ledgers and marketing), an aspect which can be explained by the lack of validation of this knowledge through the practice stage or a work contract. Not trusting themselves is an obstacle in setting up a business, the degree of uncertainty being much too high.

Olimpia Ban et al. We intended to establish a connection between the social‐demographic characteristics of the respondent (gender, age, number of family members, the monthly average income and expenses, the existence of an entrepreneur in the family or among close friends, father’s current status and their perception of the knowledge they have regarding tax payment, accounting records and filling in documents like invoices or ledgers and their knowledge on finances and marketing) and the intentions to set up a firm after graduation. Using Pearson coefficient, we pursued and noticed for Romania just a weak connection among the following variables: the job had in view after graduation and the number of family members, and the existence of an entrepreneur in the family or among close friends. For Turkey, it has been noticed a connection, yet weak, among the following variables: the job had in view after graduation and age, and the family income, and the existence of an entrepreneur in the family or among close friends and others.

Concluding, we can say that the common variable which influences the decision regarding the future job (including the initiative to set up a business after graduation), both for Turkey and for Romania, is the existence of an entrepreneur in the family or among close friends. Separately, considering the two countries, we can notice variables like the number of family members, age, gender or income, knowledge on finances, accounting and marketing which have a slight influence on the future job for Turkey.

6. Limitations of research and future directions The main limitation of the research is related to the non‐probabilistic creation of the sample, mentioning that the research had in view a balanced presentation on programmes of study and years of study. Another drawback is related to the failure to investigate the work experience of the respondents and its correlation with their intentions to start up their own businesses. A future direction of study to pursue in the future is the investigation carried out among BA and MA graduates (five generations) in order to establish the percentage of those who set up a business, the main fillips and brakes they had to deal with.

References Caree, M.A. and Thurik, A.R. (2006), The handbook of Entrepreneurship and Economic Growth, Edward Elgar Publishing Limited: Cheltenham, UK; International Library of Entrepreneurship: Bookfield, US. Davidson, P. (2006), Nascent entrepreneurship: empirical studies and developments, foundations and Trends in Entrepreneurship Research, 2(1), 1‐76. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior. An introduction to theory and research. New York: Addison‐Wesley. Grilo, I. and Irigoyen, I.M. (2006), Entrepreneurship in the EU: to wish and not to be, Small Business Economics, 26(4), 305‐ 318. Kishstrom, R. and Laffont, J. (1979), A general equilibrium entrepreneurial theory of the firm based on risk aversion, Journal of Political Economy, 87(4), 719‐748. Parker, S.C.(1996), A time‐series model of self‐employment under uncertainty, Economica, 63(251), 459‐457. Sieger, Ph., Fueglistaller, U. and Zellweger, T. (2011) Entrepreneurial Intentions and Activities of Students across the World, International Report of GUESS Project 2011 St. Gallen: Swiss Research Institute of Small Business and Entrepreneurship at the University of St. Gallen Sternberg, R. and Wennwkers, S. (2005), Determinants and effects of new business creation using Global Entrepreneurship Monitor Data, Small Business Economics, 24(3), 193‐203. van Stel, A. (2005) COMPENDIA: harmonizing business ownership data across countries and over time, International Entrepreneurship and Management Journal, 1(1), 105‐123.

Key Factors Affecting Strategy‐Minded Decision Makers in Their Innovations Choices Fernando Barbosa and Fernando Romero Department of Production and Systems Engineering, University of Minho, Guimarães, Portugal fbarbosa@dps.uminho.pt fromero@dps.uminho.pt Abstract: The rapid and continuous pace of technological change is a major challenge for all managers, who are often faced with innovations’ adoption decisions affecting the future of their companies. This is a fundamental issue on strategy, if we see strategy as a set of actions to make critical choices between two or more alternatives, in order to achieve competitive advantages or to respond to competitors. Strategy‐minded leaders try to predict the value that they will create with their choices in the organization. However, formulating strategy is a difficult task, due to the high level of uncertainty hampering the anticipation of future trends. An even harder work is the implementation of strategy, due to its interdependent relationship with strategy formulation, which is materialized in the organizational structure dedicated to fulfil the organization goals. In this work we propose to look at the factors that strategy‐minded leaders perceive that influence the adoption of innovations and we explore their relationships within several academic fields, of study, namely strategic management, organization theory, organization behaviour and organization development, adopting an holistic perspective that will allow for a better understanding of strategic adoption decisions. This analysis is grounded on field work that involved the collection of primary data from different enterprises. The research was based on a quantitative approach and on an intentional non‐probabilistic sampling strategy. The sample includes thirty four Portuguese firms, from different sectors. The selection criteria was based on the innovative performance of the firm, and on the concomitant presumption that innovative activities are well structured inside the firm. The sample includes micro, small, medium and large firms. A proportion of the sample includes conglomerates, and in fact, the sample represents approximately one hundred and twenty two firms, and a significant proportion of Portuguese gross expenditure on business R&D. A quantitative structured questionnaire was the main instrument of data collection, but some interviews with selected firms were also realized, in order to substantiate or consolidate some of the data that was obtained through the questionnaire. In this paper we present the preliminary results of the analysis of that data. Investment scheduling and costs appraisal, quantitative and qualitative advantages of the technology and strategic implications of its adoption are the factors that most often influence the decision of innovation adoption and the less common factors include the degree of formalization of decision procedures and the level/extent of the hierarchical chain. Keywords: strategic management, strategy formulation and implementation, innovation, change management, decision making, organizational structure

1. Introduction In this paper we provide an holistic perspective of the process of decision making regarding technology adoption, considering both strategy formulation and strategy implementation that will allow for a better understanding of strategic adoption decisions backed by relevant empirical data. The main research questions are: What are the factors that most often stimulate firm´s to innovate? What are the most important sources of innovation? What are the key elements that affect choices concerning innovation? The research questions developed out of the perception that the process of innovation adoption was hampered by difficulties related to the process of innovation implementation. We begin this work with a critical review of the existing literature about the concepts related to strategy and innovation, focusing on the strategic management process and in the innovation adoption process. Then we identify the methodology adopted in this work and finally the results are analyzed under the light of the research questions.

2. Conceptual framework Companies are encouraged to make decisions to survive in a hypercompetitive world, with rapid technological change, and the strategic choices that they must do and integrate are related with goals, range of products and services, competitive strategy, appropriate level of coverage and variety, organizational structure, administrative systems and labour policies (Rumelt, Schendel & Teece,1991). The survival in the present competitive landscape is assured by large investments, and the consequences of failure are severe, so the successful implementing of strategy is a crucial element of the process.

Fernando Barbosa and Fernando Romero To Rumelt, Schendel & Teece (1994) strategic management (also called “policy” or “strategy”) is related to the course of an organization, including the issues that are at the heart of top management preoccupations and those who are associated with the reasons why a business succeeds or fails. Hitt, Ireland & Hoskinsson (2011) state that “the strategic management process is the full set of commitments, decisions, and actions required for a firm to achieve strategic competitiveness and earn above‐average returns”, or in other words, it is the successful formulation and implementation of a strategy that creates value. According to Chaffee (1985), there is no agreement on the literature about the definition of strategy, in spite of the agreement on its existence. Volberda & Elfring (2004) states that its definition and management techniques depends on the researcher’s identification with some particular school of thought. Strategic management is a discipline that is influenced by various fields of knowledge, namely economics, organization theory, organization behaviour and organization development, where research has been interpreted according to the dominant approach (Hrebiniak & Joyce, 2005). Those approaches have been classified differently by different authors. The most important classification is the ten schools of thought of Mintzberg (1990), which, according to Volberda & Elfring (2004) provides a better insight about the importance of each one to the area of strategy. Each of these schools has a limited approach, but the whole set provides a comprehensive view of their influence on strategic management. The schools are divided in three classes: (1) the first three schools are “...prescriptive in nature, which are more concerned with how strategies should be formulated than with how they necessarily do form”; (2)The following class includes the next six schools, which have a “… focus on specific aspects of the process of strategy formation and are concerned less with prescribing ideal strategic behaviour than with describing how strategies do, in fact, get made.”; (3) the last class includes just one school that integrates the other schools in a unique perspective( Mintzberg,1990). Hitt, Ireland and Hoskinsson (2011) argue that the strategic management process has three strategic dimensions: Strategic Inputs, Actions and Outcomes. After a company determines its key competencies, resources and capabilities, based on internal and external environment analysis, it defines its mission and vision statements (Strategic Inputs). Then, in order to achieve profitable results (Strategic Outcomes) it must establish a set of actions, integrating strategy formulation and implementation (Strategic Actions). Strategy formulation issues are related to competitive rivalry and competitive dynamics, business and corporate level analysis, the international dimension, and cooperative issues and mergers and acquisition strategies, while strategy implementation issues are related with corporate governance, organizational structure and controls, strategic leadership and strategic entrepreneurship. Firms usually use two models to choose and implement strategies: the I/O (Industrial organization) Model of above Average Returns Model and the Resources Based Model of above Average Returns. The establishment of the basis to strategy is, in the I/O Model, the external environment, while in the Resources Based Model, it is the internal organization (resources and capabilities). Resources are the inputs to production processes and they can be tangible (financial, physical and technological) or intangible (human intellect, innovation and reputation). Capabilities are a set of resources that need to be integrated to fulfil a specific task, and the core competencies are capabilities that serve as a source of competitive advantage for a firm over its rivals (Hitt, Ireland and Hoskinsson, 2011). However, formulating strategy is a difficult task, due to the high level of uncertainty hampering the anticipation of future trends. An even harder work is the implementation of strategy, due to its interdependent relationship with strategy formulation, which is materialized in the organizational structure dedicated to accomplish the organization goals. In the literature there is not a clear agreement concerning the dominant framework related to the strategy implementation process. By contrast, on the field of strategic formulation, we can encounter some dominant frameworks, like SWOT and industry structure analysis (Okumus, 2003).

Fernando Barbosa and Fernando Romero Barney & Arikan (2005) suggests that more work is needed in the strategy implementation field from the perspective of the resource‐based theory, as strategy implementation could be a source of sustained competitive advantage on itself, although dependent on other strategic resources controlled by companies that are used in a complementary way. There is a gap on research concerning the top management process of strategic decision making, and the comprehension of its effects on firm’s strategies and operations, which seems to be conducting to difficulties in the implementation of CEOs strategic decision making, and the opportunity to provide them appropriate guidelines ( Priem & Cyocyta, 2005) Chetty (2010) points that there is a 70 percent rate of failure on executives’ efforts to implement strategy, which has a huge cost for organizations. This happens, because they don´t have a reliable framework to guide their actions over strategy implementation (Alexander, 1991). Hrebiniak (2006) argued that managers know little of strategy implementation and they are not trained to implement strategy, only to plan. Another problem is related to the general conviction that strategy implementation plays a minor role on their function, being more adequate for lower levels of management, forgetting that their commitment is essential to a successful implementation. He also argues that the top five obstacles that managers face are: (1) Inability to manage change; (2) Poor or vague strategy; (3) Not having guidelines or a model to guide implementation efforts; (4) Poor or inadequate information sharing; (5) Unclear responsibility and accountability; (6) Working against the organizational power structure. Strategy and innovation are distinct concepts both in terms of definition and function, being innovation a source of competitive advantage (Dobni, 2010), although Rogers (2003) considers “innovation” and “technology” to be the same thing (Sahin, 2006). The continued growth of the importance of innovation is also related with is capacity to make changes in the competitive position of firms. Thus, innovation and strategy are complementary (Dobni, 2010), and feed on each other. Innovation begins with signs of changes in the organizational environment. The major challenges faced by institutions are related to the comprehension of the factors that are behind them and to develop appropriate response strategies (Tidd, Bessant & Pavit, 2008.). The selection and adoption of innovation is a fundamental process of strategy implementation. To Damanpour (1991) “the adoption of innovations is conceived to encompass the generation, development, and implementation of new ideas or behaviours” and is “...generally intended to contribute to the performance or effectiveness of the adopting organization”, while ”innovation is a means of changing an organization, whether as a response to changes in its internal or external environment or as a pre‐emptive action taken to influence an environment”. Since companies have limited resources, and propensity to risk is also limited, they tend not to develop alone all the technologies, and seek alternatives to internal development. To make the decision for one of the alternatives, it is necessary to evaluate them in the context of the company (Gerhard & Voigt, 2009). Hall & Kan (2002) called technology adoption the process of “choice to acquire and use a new invention or innovation”. Rogers (2003) cited by Sahin (2006) and Taalikka (2002), defines adoption as “a decision to make full use of an innovation as the best course of action available”. To Chatterjee & Eliashberg (1990) it “involves a deliberate choice decision on the part of the individual” and Taalikka (2002) argues that ”a successful adoption and implementation need strong commitment from the managers participating in the adoption process” due to the challenging decisions and resistance from the organizational actors (See & Clemen, 2005). Literature shows that firms go through a set of phases in innovation adoption, which ranges between four and ten (according to different authors), with specific challenges to managers,. There is a widespread consensus that the earliest stages, namely the initiation and early implementations stages, are the most critical to innovation adoption. The initiation stage implies a formal decision to adopt an innovation and the early implementation stage, implies the experimentation of the innovation (Zeldin, Camino & Mook,2005).

Fernando Barbosa and Fernando Romero Goktan (2005) citing Greve (2003) states that more than create a new innovation, innovation adoption is related to the decision for an individual or organization to establish the use of an existing innovation. Organizations with mechanistic features tend to be slower, or more resistant, to the adoption of innovations, and organic organizations tend to be earlier adopters or implementers. The functioning and structure of a firm is affected by the adoption of innovations, and the extent of that influence depends on the degree of novelty of the adopted innovations (Damanpour, 1991). The reasons why firms adopt innovations is connected to the expectation of the development of organizational productivity and performance. However, the decision to adopt does not guarantee its implementation, because there is an organizational challenge to create conditions to its implementation and to fit the innovation to the values of the organization (Klein & Sorra, 1996). Small companies use preferentially product innovations to achieve competitive advantages, while large firms use other tools, such as economies of scale, learning curve effects, diversification and investment in new projects (Salavou, Baltas and Lioukas, 2004) Firms that adopted an innovation, have interest in identifying the obstacles that may encounter during the implementation process. In the literature we find strong connections between organizational issues of the adoption of innovation, organizational structure, leadership, market structure, organizational determinants, expectations, and organizational climate and it is suggested that organizational structure is responsible for about 60 per cent on firm´s innovation adoption. Research on adoption of one innovation is scattered once there are fewer comparison studies or innovation experiences (Cooper,1998). To Nemoto (2010) the most relevant factors influencing the adoption decision are: (1) Organizational characteristics; (2) Influence of employees; (3) Management Model; (4) Profile Manager; (5) Market; (6)Technological Aspects; (7) Competitiveness; (8) Resources; (9) Compatibility with administrative guidelines. Sultan & Chan (2000) identify factors that influence the adoption of new technologies: (1) Characteristics of subjects; (2) Factors of the Group and company; (3) Perception about the characteristics of the individual technologies. Despite his importance, companies do not allocate enough time, resources and staff to fulfil the firm´s innovation goals, and there is a lack of systematic innovation processes, which seems to reflect firms’ short‐ term orientation focus, while innovation implies a long term approach. Research suggests that major barriers to innovation are related to internal aspects of the organizations, namely the lack of resources, lack of market intelligence, unsuitable corporate culture, poor incentives, and badly defined innovation strategy, unclear responsibilities or badly defined innovation strategy, employees through the absence of market and innovation knowledge (Dobni, 2010). Dobni (2010), also argued that is necessary to integrate innovation and strategy practices, in order to achieve a better performance.

3. Methodology The data on which this study relies consists of primary data collected from the Portuguese business sector. The research was based on a quantitative approach and on an intentional non‐probabilistic sampling strategy. The sample includes thirty three Portuguese firms, from different sectors. The selection criteria was based on the innovative performance of the firm, and on the concomitant presumption that innovative activities are well structured inside the firm. Thirty four answers were received (17% response rate) and the sample includes five microenterprises, six small companies, twelve medium companies and eleven large companies. A proportion of the sample includes conglomerates, and in fact, the sample represents approximately one hundred and twenty two firms. Although being a non‐probabilistic sample, its scope and creditworthiness is important, since, according to official Portuguese R&D statistics (GPEARI, 2011), it represents 27.07% of total Portuguese investment in business R&D. A quantitative structured questionnaire was developed based on key concepts extracted from the scientific literature, on exploratory interviews conducted with some companies, and on the business experience of the researchers, and it was the main instrument of data collection. Some interviews

Fernando Barbosa and Fernando Romero with selected firms were also realized, in order to substantiate or consolidate some of the data that was obtained through the questionnaire. The extent and depth of the questionnaire limited the number of responses, but it provided a rich set of data. This paper presents only some preliminary results that support our arguments. Work is in progress regarding a detailed statistical analysis, and the formulation of additional explanatory models.

4. Analysis and discussion The results presented in this section are related to the inquiry on the factors that drive firms to innovate, the importance of several sources of innovation and factors affecting the adoption of innovation. Those results will be interpreted having in mind strategy issues. The need to innovate is common to most companies, regardless of size and sector. Companies are driven toward innovation by many signs coming from the organizational environment, internal or external, and it could be a source of competitive advantage the type of sources that firms use in their innovation. Technology evaluation processes enable the formulation of an opinion on what are the best options for technological investment, but in spite of that, managers do not always decide to opt for the best investment. There are several factors that influence the investment decision and they are important to know. Thus, it is possible to design strategies and forms of action for the promotion of technology adoption activity. The decision to adopt or reject an innovation could be explained by the type of needs that more often stimulate organizations to innovate or it can be related to the existence or inexistence of obstacles caused by a particular source of innovation established by strategy. In this section the aggregated results are presented in a series of tables. All tables present only the five most valued and the five least valued factors. For each table and question there were many more factors whose importance was asked to the respondents. Table 1 presents the factors that more often stimulate firms to innovate. We found that the three most common are, in descending order of importance, improve the quality of products or services (4.03), increase net sales (3.88) and the satisfaction of a specific request from a client (3,56). Table 1: Factors that more often stimulate firms to innovate Five most valued factors

Mean (n=34)

Improve the quality of products or service

4,03

Increase net sales

3,88

Increase range of products

3,56

Satisfaction of a specific request from a client

3,53

Improving production processes

3,53

Five least valued factors

Entering in a new market domestic

3,09

Compliance with legislation

3,09

Reduce environmental damage

2,94

Reduce energy consumption

2,82

Satisfaction of a specific request by a supplier

2,53

1=Never; 2= Rarely; 3=Usually; 4= Very frequently; 5= Always

The factors that less often encourage companies to innovate are the satisfaction of a specific request by a supplier (2.53), to reduce energy consumption (2.82) and to reduce environmental damage (2,94).

Fernando Barbosa and Fernando Romero Table 2 presents the importance of innovation sources. We found that the three most important sources are clients (3.85), other departments (3.56) and the internal R&D department (3.47). The less important sources are applications for patents (2.41), technological surveillance (2.74) and acquisition of patents, licenses and know‐how (with the same mean 2.74). Table 2: Importance of innovation sources Five most valued factors

Mean (n=34)

Customers

3,85

Other departments of the company

3,56

Internal department of R&D

3,47

Universities

3,24

Competitors

3,15

Five least valued factors

Business consulting/Consultants

2,79

Technology transfer organizations

2,76

Acquisition of patents, licenses and know how

2,74

Technological surveillance

2,74

Patent application

2,41

1= Unimportant; 2= Of little importance; 3=Moderately important;4= Important;5=Very important

Table 3 presents the factors influencing the adoption of innovations. We found that the three most valued factors that are relevant in influencing the decision to adopt the innovation are the definition of terms and costs (4.06), qualitative/quantitative advantages of technology obtained by the company (4.03) and strategic implications (4.00). The least valued factors are age of the decision maker (2.15), the resistance of employees (2.85) and the level/extent of hierarchical structure (2.88). Table 3: Factors influencing the adoption of innovations Five most valued factors

Mean (n=34)

Definition of terms and costs

4.06

Quantitative or qualitative benefits of technology achieved by the company

4.03

Strategic Implications

4.00

Quantitative or qualitative benefits of technology achieved by customers

3.88

Management support

3.85

Five least valued factors

Laws that regulating the use of technology

3.03

Working time of the decision maker in the company

2.94

Extension of level or chain hierarchy

2.91

Employees resistance

2.88

Decision maker age

2.18

1=Never; 2= Rarely; 3=Usually; 4= Very frequently; 5= Always

Fernando Barbosa and Fernando Romero Referring to table 1, we can see that the main factor that drives companies towards innovation is to improve the quality of products or service. This result is somehow familiar with several studies that highlight the importance of this factor and demystifies the idea that innovation is mostly related to new product development (Sullivan and Dooley, 2010), stressing the importance that companies assign to achieve profits on a short term, an idea that is reinforced by the score attributed to other factors: increase net sales, the range of products and the improvement of production processes. Innovation is realized in a incremental way, in order to increase organizational productivity and performance, where cost reductions assume a principal role. This focus may hamper the innovation process, particularly when a more long term perspective is taken into account in order to compete at a global scale. Referring to table 2, we can see that the main sources of innovation are the customers. This result is in line with several studies that stress the importance of the interaction of companies with customers, who may be engaged in the idea generation, avoiding, in this way, the uncertainty associated to customer acceptance. This also could reveal the inability that Portuguese companies have to deal with risk and uncertainty. It seems to reflect the hypothesis that Portuguese managers have a high rate of uncertainty avoidance, searching more structured situations, associated at rules, safety and predictability, with a low level of novelty and difference acceptance. It is also worth mentioning the managers’ perception of the importance of technological surveillance as a source of innovation. Despite being considered a key procedure and a best practice in innovation management, managers apparently do not value it. This fact, associated with the importance assigned to customers as the main innovation source, could reveal some lack of commitment from top management and/or the lack of company’s competencies or skills concerning innovation strategy implementation efforts. Analyzing table 3, we can see that the main factors that influence the adoption of innovation are the definition of terms and costs, followed by quantitative or qualitative benefits of technology achieved by the company and strategic implications, which are in line with the strategic actions related to strategy formulation. It seems that Portuguese companies are driven by a short term perspective, using incremental product innovation to achieve competitive advantages. This may be caused by the lack of human and financial resources regarding the challenges related to the implementation of strategies. Strategy implementation activities have longer timeframes than strategy formulation, involving more people, which increases the complexity of the task. On the other hand, the longer the duration the greater the possibility that competitor´s actions change, and that the company adjusts to those changes. These results could also reveal the difficulties in implementing business‐level cooperative strategies, vertical (combination of competencies at different stages) or horizontal (combination of competencies at same stages) business‐level complementary alliances, namely through subcontractors or the lack of competencies in project management. Top managers do not seem to appreciate two important issues of the innovation process, which could be strong inhibitors to the adoption process: employees resistance and the extension of the level or chain hierarchy. Regarding the extension of the level or chain hierarchy structure and the employees’ resistance it seems that formalization and the so‐called technostructure dominates the picture. It suggests that firms have a high degree of rules and procedures for managing the behaviour of employees. This issue is a very important one regarding the firm innovation process, because the greater the number of hierarchical levels, the higher is the probability of the emergence of the phenomenon known as 'mentality elevator': the conformation to rules laid down, encouraged by the chain of command, which cherishes more respect for the rules than the results obtained. The analysis made above may seem odd because it runs counter to some interpretations of related empirical results. The connection to customerss is usually interpreted as a positive thing, while in our interpretation it is considered as something that reflects some negative traits. The tendency for incremental product innovation is also viewed as a consequence of specific flaws in the innovative capabilities of firms. The above perspectives is a result of systematic personnel observations of the Portuguese reality made by the authors, and the

Fernando Barbosa and Fernando Romero realization that the empirical results obtained by structured questionnaires may be interpreted in a different way, when considering the connection between strategy and innovation. We also believe that these interpretations may be eventually applied to realities other than the Portuguese one, particularly at the SME level.

5. Conclusion In this paper we provide a perspective of the process of decision making regarding technology adoption, considering both strategy formulation and strategy implementation. A key finding or interpretation of this research was the realization that companies seem to be mostly concerned with short term profits, rather than creating long‐term value. The lack of resources, namely financial and human resources, could explain the managers focus on short‐tem profits. The rate of innovation failures is high, with high costs to firms and it is related to implementation matters. To face those constraints, it seems that a Portuguese manager prefers product innovations as the pathway to achieve competitive advantages in an incremental way. This focus could lead managers to take harmful decisions to the future of business, namely in the establishment of mechanistic organizational structures where communication is done in a formal way through hierarchies with a high level of chain extension command, where power and authority are based in the seniority and the responsibilities are rigid.

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Business Strategies in Contexts of High Uncertainty: A Case Study on the Innovation and Internationalization Processes of a Technological Portuguese SME Fernando Barbosa and Fernando Romero Department of Production and Systems Engineering, University of Minho, Guimarães, Portugal fbarbosa@dps.uminho.pt fromero@dps.uminho.pt Abstract: Innovation and internationalization of small and medium enterprises are widely cited as decisive factors, for the sustainable growth of European economies, which are facing a deep crisis. The European Union launched in March 2010 a European strategy, called Europe 2020, to prepare the EU economy for the future, where growth is based in three dimensions: smart, sustainable and inclusive. In the Portuguese case, these factors become even more relevant, since the country is facing an unprecedented crisis that brought to the surface the vulnerabilities of its economic and financial system. This article is a case study of a small Portuguese technology based firm, where we will examine, in the light of the literature on strategic management, and the evaluation and selection of technologies, its innovation and internationalization processes, which are critical to its survival in a hypercompetitive global industry. The evaluation of new ideas and business concepts is a challenge for companies, especially in its early stages of development where there is not a tangible commercial product. This organization is launching a worldwide pioneering product, as a result of its research and development and innovation activities, and will have, if things go right, a huge successful impact on their competitiveness. The identification of the organizational characteristics that enabled the company to enhance its innovative stance, and to embrace the challenge to internationalize its activities, may help similar organizations improve their innovation and internationalization processes, which are critical to increase their competitiveness. Keywords: innovation, internationalization, strategy, SMEs, innovation management, RDI certification

1. Introduction Through this case study, we aim to increase the knowledge about the main motivations, barriers and facilitating factors concerning firms’ innovation and internationalization processes, with a focus on the relationships between innovation, internationalization, financial results and public policy influence. This case study highlights a set of practices in the design of structured processes of innovation and internationalization of small and medium enterprises. We begin this work with a short review of the existing literature about the concepts related to companies innovation and internationalization processes. Then we identify the methodology adopted in this work and finally, the Tekon Electronics case will be analyzed.

2. Conceptual framework The current competitive landscape of companies is marked by the global economy and rapid technological change. Firms face increasing and difficult challenges, regarding those factors (particularly the hyper competition and the development of disruptive technologies that destroy the value of existing technology and create new markets), and struggle to understand the factors behind them, to develop appropriate response strategies (Tidd, Bessant and Pavit 2008) and to manage effectively and efficiently the information in order to become an important source of competitive advantage. In this way, companies are urged to seek new ways of implementing and acquiring technology (Salas 2009). They have to make choices and the consequences of failure are serious (Rumelt, Schendel, and Teece, 1991). Technology evaluation is a fundamental aspect in the process of decision making, and this term is often used in the literature, in a way that leads to confusion and imprecision, to identify the whole process of evaluation, selection and adoption (Wang 2006). Nevertheless, researchers have already identified many methodologies and critical aspects of this process (Jolly, 2006). Insufficient knowledge of evaluation methodologies and techniques is often a constraint in the decision processes of SMEs. Small firms say that a major barrier to implementation of an innovative idea is the lack of an appropriate valuation technique and, very often, are guided by intuition and experience (Ordoobadi, 2006).

Fernando Barbosa and Fernando Romero Thus, it assumes significant importance the establishment of appropriate metrics for evaluating investments in new technologies and a systematic process of technology management (Drucker, 1993) according to the nature of the technology and its level of maturity. The evaluation of new ideas and business concepts, and the concurrent management of innovation processes is a challenge for companies, especially in its early stages of development where there is not a tangible commercial product and uncertainty is high (Damodaran, 2001). Most approaches suggest that most evaluation methods used are essentially quantitative and derive from traditional financial evaluation techniques, but they do not include non‐quantitative factors (intangibles, both in terms of benefits, or in terms of costs or risks) that may have great importance in terms of evaluation and adoption, and which seem to be more appropriate to less resourceful organizations such as SMEs ( Ordoobadi,2011). The case study addressed in this article shows the importance of such items. According to Hoch (2011), when the market of innovative firms at national scale shrinks or new business opportunities arise outside, these companies have a tendency to start their internationalization process, whose relationship with innovation has been little explored by researchers. Vásquez and Doloriert (2011) state that the main drivers for the internationalization process are the constraints related to the internal market (the competition level, market growth and the saturation level) and the opportunities related with the external environment: demand, attractiveness and knowledge of the potential markets. In addition to the ability to develop technologically advanced products that add value and ensure competitiveness and growth of business enterprises, it is of particular importance the factors behind the choice of target markets, which conditions the establishment of an effective internationalization strategy. The entry mode choice in a foreign market is a challenge and a critical decision, and will have a great impact in the company’s performance. Researchers have identified a large number of practices and models concerning the entry choices modes that a firm could adopt, but there is not an agreement on which is the best entry strategy in foreign markets (Nakos,2011). A widely known model on internationalization processes is the Uppsala process model developed by Johanson and Vahlne (1977). This model reveals two patterns of the internationalization process: 1) the establishment of a chain, which represents the gradual order that firms follow in their international operations: no regular export; independent representative; sales subsidiary and manufacturing; 2) Companies make their investments in the markets that they can better understand in order to reduce the uncertainty in new markets – the notion of psychic distance. This concept is related to factors that hamper information flows between firms and the market, such as differences in language, level of education, business habits, cultural environment, legal environment and political systems, The Uppsala model was updated by the authors (Johanson and Vahlne, 2009) to incorporate the effect of networks on the internationalization process, acknowledging that learning processes of companies, and their commitments, are as much linked to the network of relationships as to national institutional aspects. Tykesson and Alserud (2011) found evidences that the Uppsala Model is applicable to SMEs and argued that the network effects on the updated version of the Uppsala Model are more significant that the psychic distance factor, which plays a huge role in uncertainty, but that it can be overcome if company is part of a strong network. Wu and Zhao (2007), regarding the case study of Huawey Technologies, argued that hi‐tech firms do not always follow the Uppsala model, using as an entry mode in new overseas markets joint ventures or FDI or contractual arrangements. Driscol (1995) developed a framework based on three choices to enter in external markets which are export‐ based, contractual‐based (includes licensing, franchising, management contracts, turnkey contracts, non‐

Fernando Barbosa and Fernando Romero equity joint ventures, and technical know‐how or co‐production arrangement) and investment‐based through acquisitions (stock acquisition control, joint venture and start‐up investment). Some of these conclusions are applicable to the present case study, as shown below.

3. Research method We use the case study methodology as valid way of exploring existing theory and as a exploratory way to provide an integral vision and a general understanding of a phenomena (Yin, 2009). In this research, we analyze the innovation and internationalization processes and their relationships in a small Portuguese technology based firm and its foreign market entry mode decision. Following a literature review, two in‐depth interviews were conducted with managers in Tekon Electronics. It was possible to relate the empirical data with several ideas advanced by the literature. The methodology is not prone to generalizing the results, due to the specificity of the context, but it highlights a set of good examples concerning the key factors for the establishment of an innovation and internationalization effective strategy for small and medium businesses.

4. Company profile The Tekon Electronics parent company began its operations in 1982, having specialized in the commercialization of equipment and systems for industrial automation. The Company offers a full and very comprehensive range of products, as a sales representative of several national and international brands, so as to provide a number of solutions capable of responding to a broad range of needs and requirements. An engineering department was created in 2000, responsible for the design, development and integration of automation components and systems, tailored to customers requirements. At the same time, it started to produce temperature and level sensors, diversifying the business areas of the company. The company has 37 employees, and it is a young, highly skilled team (62% of the employees have qualification level VI or higher). The development of the company has always been sustained by a policy of recruiting skilled technicians and supported by a policy of continuous training, with the aim to be able to create innovative solutions and to generate responses to an evolving and increasingly demanding market.

5. Innovation process The process of internal product innovation on Tekon Electronics began when, about twenty years ago, the company decided to manufacture temperature and level sensors, reducing exposure to the commercialization of electric and electronic material. To achieve this goal, it became an importer of automation systems, acting as a sales representative of recognized global brands in Portuguese territory. This strategy led the company to a major change, since the commercialized products were high technology products, and it was essential to provide the company with highly qualified human resources specialized in engineering. The Engineering Department naturally arose in 2000, with the intention to develop automation systems and, at the same time, produce some sensors. This strategy had some drawbacks, including the fact that it was not able to produce sensors on a large scale, and framed in a global offering. The parent company made some attempts to become manufacturer of this type of equipment, and acquired equity on four companies, notably one university spin‐ off, but the intention was never implemented, and the company left in 2011. The same strategic direction continued to be pursued by the organization, i.e., to transform the parent company into a manufacturer of technology products in specific market niches that did not collide with the products commercialized by the firm. In 2010, it initiated their production, creating its own R&D department. Four new elements were hired exclusively to this department. The investment in this project was around € 1 million, in a countercyclical move relative to the economic and financial crisis in 2009, providing Tekon Electronics with a modern infrastructure. In 2011 the Tekon Electronics R&D team moved to the new and modern facilities. The parent company began to foster the creativity of employees, in order to generate ideas for the development of new products. In order to support this effort, the company created a very simple system, called ideiatec, based on Outlook email, and that consisted in a dedicated email where all employees could

Fernando Barbosa and Fernando Romero submit their ideas. These ideas would have to comply with pre‐established criteria, being awarded with incentives. The system worked well, but it generated more ideas for process innovation than for product innovation. Afterwards, the company applied to membership of the so‐called COTEC SME Innovation Network, in order to conduct a benchmarking with companies that were part of this network. Through this same organization (COTEC), the firm certified its activities according to the RDI (Research, Development and Innovation) Management Portuguese Norm. Initially, the implementation of this norm complicated the process of innovation in the organization. Because it is a very recent norm, consulting firms are struggling in their analysis and interpretation. It moves away from the traditional scope of certification in quality management systems, the main playground of consulting firms. Considering the four dimensions of innovation on which the norm builds (product, process, organizational and marketing), it becomes difficult to standardize certain processes and transform them into measurable results. However, certification was a good source of learning and it was useful to change some internal practices, and to structure the process. Of particular relevance to the organization was the systematization of learning processes (an activity not previously performed), the formalization and structuring of technology watch activities, the development of projects and the evaluation of research and development results. Performing evaluations in the Portuguese context is fraught with difficulties, because fear of failure is a strong cultural barrier that inhibits an attitude more prone to risk and to innovation. Another positive factor was the learning held at generating ideas. Hiring people as a source of new knowledge, with expertise in the development of new products, and exclusively dedicated to R&D activities, proved to be a major challenge, both for the organization and for the new four employees. The new R&D function required a paradigm shift in the relations between the functional departments within the firm, and the reassessment of its mission. It demanded a change of mentality of people and work routines, installed due to a culture of 28 years of work geared only to the commercialization and marketing of products produced elsewhere. It was a routine that intrinsically did not embodied the perspective of design, development and production. On the other hand, there was a lot of pressure and expectations placed on the new team of employees to develop "genius" ideas. However, despite the resistance to change, there has been a continuous learning and adaptation process and the building of bridges of cooperation between these two opposite views. The organization realized that the implementation of the RDI management norm is just the first step of an effort that must be supported continuously at all layers of the organization. On the other hand, these two apparently opposing and conflicting cultures (a commercial one, and a product development one), have proved to be a source of competitive advantage for the organization and a source of mutual learning. The high level of standards, know‐how and feedback imposed by the organization's commercial perspective is a source of continuous challenges and high expectations regarding the R&D team. If the new internally developed product goes through all the different stages of the evaluation process in the commercial perspective, it is a sign of its appeal and market differentiation. There are very few companies operating in the automation sector in Portugal, and they are usually composed of small development offices that have a more limited, and a much less comprehensive overview of the market. The organization has a sales team that enriches the innovation process with real market inputs, allowing the detection of trends, opportunities and threats, and reducing considerably the risk of conceiving a product inappropriate to market needs. The organization performs an active and focused technology watch that allows the detection of customers' needs or problems to solve, to survey competitive products and positioning, and the sensing of opportunities in niche markets and new customers. The meetings between technical and commercial staff are a source of information in this matter. Regarding the management of ideas, and as previously mentioned, the company began with a simple process for idea management. When it began to implement the RDI management standard, and in partnership with a consulting firm, it developed a specific software for that purpose, in which the organization acted as a beta tester, providing feedback about the capabilities and functionality of the software, and incorporating into the

Fernando Barbosa and Fernando Romero software the information needs of the company. It still uses it, and there was a gradual improvement in the quality of the ideas submitted over these four years. The process of evaluating ideas also evolved within the organization. Initially, decisions about the continuity of ideas were taken by management and the marketing department, in order to have a faster decision. However, other views were not incorporated. Now this process consists of two phases. In a first one, the ideas are evaluated by an innovation committee that was created for that purpose, and that meets all the department heads, forming a multidisciplinary team with a high degree of autonomy, which incorporates multiple perspectives, and that has increased the effectiveness of the process. This new structure contributed to decrease the resistance to implement innovative ideas, since each department contributes in a systematic way in the process. If necessary, other collaborators may occasionally participate in this committee. Only in a second step, and once the idea has been validated by the committee of innovation, does it go to the management of the company. The current criteria considered in the analysis of the potential of an innovative idea are related to five dimensions: technical feasibility, alignment of the idea with the firm's strategy; financial and economic viability, market analysis, competition and costs. The adoption of these criteria reveals a maturation of the process, focusing on key aspects, essential for a quick decision, so as not to neglect the time to market. The analysis was initially more complex, and several factors which were included did not add value to the process, and on to the contrary, it hindered and delayed it. Following the technology watch process, and the generation of ideas and their evaluation, innovative ideas with commercial potential are classified as innovation projects. The parent company uses equity to finance each R&D project, leading to extra care in their analysis and prioritization. The firm does not use any specific methodology for prioritizing projects, only the calculation of the Internal Rate of Return, the Payback Period and items that give rise to those indexes, which are estimated roughly. An intensive market study can be difficult to make and it may delay excessively the project. At this time, the company has several projects underway, having difficulty deciding which one moves first. It also has a portfolio of projects in stand‐by, either because they are not aligned with the strategy or because resources are allocated to other areas. Each R&D project is viewed as an investment project. The company invested €300,000.00 in 2013. The total amount allocated to R&D is not set in advance. The allocation is decided on a project basis. One of its strategic objectives is to have a broad portfolio of products, to be offered in international markets. In this sense, projects that take less time to execute, and that are in line with this strategy, end up being prioritized. Typically, the project schedule includes four phases. The most important phases are the conception and design phase (phase 1) followed by the proof of concept phase (phase 2), which is divided into several sub‐activities, due to the large amounts of resources and time that it consumes. The most significant deviations from planning occur in terms of schedule implementation and deadlines, followed by deviations in costs. The reason is due to the difficulty in managing subcontracted activities, particularly in the accomplishment of the lead time from suppliers. This is something that the firm wants to improve, and the solutions point to a greater involvement and partnership with suppliers, and the preference for the selection of suppliers who wish to participate proactively in product development. The company still has no patented product and may not follow this type of protection. It is betting on a technology and a product (wireless sensors) that took about two years to develop. The product is being adopted slowly, due to a certain conservative attitude of the industrial customers, but the firm believes that it may be the trend for the future. The organization adopts a posture of second mover, because it is not yet prepared to be a first mover.

6. Internationalization process The organization is now taking the first steps in its process of internationalization. Despite the decline in the internal market, this was not the main driver of the company's internationalization process. It wants to leverage the business, providing a range of innovative products, whether in the domestic or foreign market. The Portuguese market is too small to get a return on the investment made on the development of a new product, so that internationalization is a natural path to follow, once the innovation process is properly consolidated. The products destined to the international market must be prepared to compete on a global

Fernando Barbosa and Fernando Romero scale and the firm bets, as referred above, on a differentiation strategy. The product was developed having in mind, from the beginning, the international market. Small scale exportation was the elected entry strategy in foreign markets. It will be done primarily through the appointment of a network of distributors, which means that each country must have already a distribution network more or less defined. The goal is to find distributors who can implement the brand, and that connect with its values. Great care is taken in the selection of the distributor, to avoid damaging the incipient brand name. The appointment of a bad distributor could cause irreparable damage to the company's image and undermine the process of internationalization. The target countries were selected taking into account factors such as macroeconomic analysis of the country, the rate of GDP growth, competition analysis and market maturity. It was combined with the knowledge that the company has from specific external markets where it is more active, generally linked to the brands that the firm commercializes in Portugal, or where it has established some relationships, through international sales meetings. The firm also resorts to consultation of people living in those countries, and with which the firm has commercial relations, or through experience brought by employees that are more or less active in those countries. The culture of every country is an important factor that is taken into account in terms of defining the trading and commercial approach. It is possible to identify similar patterns in some countries. In Portugal, Spain, Italy and France customers are very sensitive to the discount, either as a percentage, or in monetary value, at the expense of the final product price. In the case of countries like Germany, Belgium and the Netherlands, this sensitivity is not as visible. In Germany, due to its industrial specialization, it is necessary to work with key potential customers in a different way that competitors do, and find a point of differentiation based on a combination of product and pricing strategy. In this market, the main difficulties in market entry are related to the awareness of the Tekon brand (incipient) and the not very good association between Portugal and industrial competence (Portugal industrial brand). The pricing strategy depends on the way the company will position itself in the market, which is different from market to market, and is conditioned by the entry strategy in each market. The following questions are set in order to pave the way for strategic decisions: what type of customer we want to attract (final/retailer/ wholesaler/distributor)? Should we develop a pricing strategy specific to each market? Should we develop a specific price strategy for each trading block? The discounts are visible and/or invisible? The final consumer price is attractive to the final consumer and/or distributor? The company studied its presence in Portuguese‐speaking countries. In these countries, the entry strategy was indirect exportation, due to several factors: these countries do not have properly formalized and transparent distribution channels, the share of manufacturing is less than 5% of GDP, and a direct presence would require a large initial investment whose risks the firm is not prepared to assume. In these countries there was the possibility of territorial extension of the representation of some brands (already represented in Portugal), and the language itself was a facilitator. The presence in some of these markets through indirect routes is made through national partners, who already have an established position in these markets, facilitating the introduction of the company's products. The presence in the United States required a different technology certification process, more expensive and time consuming than the European one, and it also required a new technical configuration of the product. These were factors that would entail high costs and a high level of uncertainty of product acceptance, which led the company to abandon the idea of entering this market. Under these considerations, the organization has set as priority targets the constituent countries of the European Union, since entry is facilitated due to lower risks in terms of various aspects, such as customs and monetary affairs, legal issues related to product safety and testing, and maturity of the markets. Although the rivalry between competitors in these more mature markets is fierce, they are appealing markets due to their size and international projection. The first market to be explored was the Spanish one and the company anticipated its entry, when the product was still in a prototype phase, to be able to be present at an important fair which is held every two years, and which marked the international presentation of the products offered. The company, at this early stage, opted to appoint an agent, with which it already had working relations, and

Fernando Barbosa and Fernando Romero who knows very well this market. So far, the results are good, and sales are starting. The next market to be worked out is the German one, where the company will be present at one fair which will be held next month.

7. Discussion The Tekon Electronics case provides an interesting insight into the relationship between innovation and internationalization processes in the Portuguese SME context. It also illustrates that the systematization and structuring of the innovation process inside small organizations is an extremely important factor that increases considerably the probability of success, as mentioned above in the literature review section. The systematic and continuous effort related to the improvement of the internal processes of the organization was coupled with a careful approach to the external market, and some approaches referred in the literature were indeed applied by the company. The key successful factors, in this case, seem to be related to the continuous commitment from top management in innovation, the change towards innovation practices, the hiring of human resources with high expertise, global product thinking, multidisciplinary teams, organization learning with innovation processes, formalization and structuring of technological watch, R&D project development, evaluation of R&D results, entry choice mode in known external markets by small steps and the knowledge from the cultural aspects of each country. The commitment and deployment of external, dedicated managers and the systematic approach to innovation management seems to confirm other studies reporting the positive impact of these determinants (D’Angelo, 2013) in the internationalization processes of SMEs. The key barriers are related to the fear of failure, Portugal brand name in the field of industrial technology, brand awareness of Tekon Electronics as well as a lack of cultural information about the country, and those findings are important to help similar organizations in developing strategies to mitigate them. Previous connections of the firm in terms of international markets account for the social factors that have facilitated, or at least not hampered, as reported in other instances the process of internationalization (Ellis and Pecotich, 2001). The fact that the firm is a representative of international brands, the knowledge of the market opportunities that such a position confers, and the existing social bridges that were built as a consequence, were extremely important factors affecting the decision to internationalize. The firm adopted a product differentiation strategy with an high innovative content, in a technology that has not yet reached significant penetration in the target market (industrial market), relying on a gradual move towards increased adoption. The innovative content of the product seems to be an important determinant of success in internationalization efforts (Rees and Edwards, 2010; Pett and Wolff, 2009), and in this case we suggest that indeed it played a fundamental role.

References Damodaran, A. (2001). The Dark Side of Valuation: Valuing Old Tech, New Tech, and New Economy Companies, Financial Times Prentice Hall, London. D’Angelo, A., Majochi, A., Zuchella, A. and Buck, T. (2013) “Geographical pathways for SME internationalization: insights from an Italian sample”, Vol. 30, No. 2, pp 80‐105. Driscoll, A. (1995) 'Foreign market entry metods: a mode choice framework', in Paliwoda, S.J. and Ryans, J.K. (eds) International Marketing Reader, Routledge, London and New York. Drucker,P. (1993). The practice of management. New York: Harper Collins, Reissued ed. 1993. Hoch, C.G. (2011). A relação entre a internacionalização e a inovação na empresa: Um estudo de caso, MSc Dissertation, Universidade Federal do Rio Grande do Sul. Retrieved from: http://www.lume.ufrgs.br/handle/10183/35176 Ellis, P., and Pecotich, A. (2001) “Social factors influencing export initiation in small and medium‐sized enterprises”, Journal of Marketing Research, Vol. 38, No. 1, pp 119‐130. Johanson, J. and Vahlne, J‐E. (1977) “The internationalization process of the firm ‐ a model of Knowledge development and increasing foreign market commitments”, Journal of International Business Studies, Vol. 8, No. 1, pp 23‐32. Johanson, J. and Vahlne, J.‐E. (2009) “The Uppsala internationalization process model revisited: from liability of foreignness to liability of outsidership”, Journal of International Business Studies, Vol. 40, pp 1411‐1431. Jolly, D. R. (2012) “Development of a two‐dimensional scale for evaluating technologies in high‐tech companies: An empirical examination”, Journal of Engineering and Technology Management, Vol. 29, No. 2, pp 307‐329. Nakos, N.E. (2011)” Market Entry Options”, In Keilor, B.D., Kannan, V.R. and Wilkinson, J.R. (eds.) International Business in the 21st Century, Praeger, Santa Barbara. Ordoobadi, S. (2006) “Development of a Tool for Managing Technological Innovations in Small Manufacturing Companies”, Proceedings of the 7th Asia Pacific Industrial Engineering and Management Systems Conference, Bangkok, Thailand.

Fernando Barbosa and Fernando Romero Ordoobadi, S. (2011) “Inclusion of Risk in Evaluation of Advanced Technologies”, The International Journal of Advanced Manufacturing Technology, Vol. 54, No. 1‐4, pp 413‐420. Pett, T.L., Wolff, J.A. (2009) “SME opportunity for growth or profit: What is the role of product and process improvement?” International Journal of Entrepreneurial Venturing, Vol. 1, No. 1, pp 5‐21. Rees, M. and Edwards, R. (2010) “Innovation roles in SME internationalization”, 17th International Conference on Management Science and Engineering, ICMSE 2010, Melbourne, 24‐26 November. Rumelt, R.P., Schendel, D. and Teece, D.J. (1991) “Strategic Management and Economics”, Strategic Management Journal, Vol. 12, pp 5‐29. Salas, J.A.P. (2009) “Best Practices for Industry‐University Research Collaboration”, Master Dissertation, Massachusetts Institute of Technology, Cambridge. Tykesson, D. and Alserud, M. (2011) The Uppsala Model’s Applicability on Internationalization processes of European SMEs, Today ‐ A Case Study of Three Small and Medium Sized Enterprises. (Master Thesis). Retrieved from: http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=2058238&fileOId=2436198 Tidd, J., Bessant, J. and Pavitt, K. (2008) Gestão da Inovação, Bookman, Porto Alegre. Vásquez, F. and Doloriert, C. (2011) “Case‐Study of Internationalization in Peruvian SMEs”, Journal of CENTRUM Cathedra .Vol.4, No. 1, pp 77‐99. Wang, Y.‐T. (2006) Information Technology Investment Decisions and Evaluation in Large Australian Companies, Ph.D. Dissertation, Nathan, Griffith University. http://www4.gu.edu.au:8080/adt‐root/public/adt‐ QGU20070716.175827/index.html Wu, D. and Zhao, F. (2007) “Entry Modes For International Markets: Case Study Of Huawei, a Chinese Technology Enterprise”, International Review of Business Research Papers, Vol.3, No.1, pp 183 – 196.

Co‐Ownership of Intellectual Property: Exploring the Value Appropriation and Value Creation Implications of Co‐Patenting With Different Partners Rene Belderbos1, Bruno Cassiman2, Dries Faems3, Bart Leten4 and Bart Van Looy5 1 KU Leuven, UNU‐MERIT & Maastricht University 2 IESE Business School, KU Leuven & CEPR 3 University of Groningen & KU Leuven 4 KU Leuven, Vlerick Business School & FWO Flanders 5 KU Leuven & IGS, University of Twente bart.leten@kuleuven.be Abstract: Combining interview data and empirical analyses, we explore the value appropriation and value creation implications of R&D collaboration involving co‐ownership of intellectual property (i.e. co‐patents). We make an explicit distinction between three different types of co‐patenting partners: intra‐industry partners, inter‐industry partners, and universities. Our findings indicate that the value appropriation challenges of IP sharing are particularly strong for intra‐ industry co‐patenting, where partners are more likely to face overlapping exploitation domains. Co‐patenting with universities, and to a lesser extent also with inter‐industry partners, is associated with higher market value, as appropriation challenges are unlikely to play a role and collaboration may signal novel technological opportunities. Whereas we find some evidence that co‐patenting corresponds to higher (patent) value, patents co‐owned with firms are significantly less likely to receive self‐citations, indicating constraints in terms of future exploitation and development of co‐owned technologies. Keywords: intellectual property, R&D collaboration, value appropriation, value creation

1. Introduction The open innovation paradigm conceives Research and Development (R&D) as an open system, emphasizing that firms can benefit from a wide variety of collaborative activities with external knowledge sources (Chesbrough 2003, 2006). Scholars (e.g. Belderbos, Carree & Lokshin, 2004b; Cassiman & Veugelers, 2006; Chesbrough, 2003; Faems, Van Looy & Debackere, 2005; Laursen & Salter, 2006) emphasize the need for inter‐ organizational R&D collaboration as it allows for the synergistic blending of external and internal ideas into new products, processes and systems. At the same time, these scholars acknowledge the appropriation challenges such open innovation model entails. The more firms collaborate with external partners, the more difficult it becomes to appropriate the outcomes of such collaborative efforts across the different partners (Di Minin & Faems, 2013; Henkel, 2006; Chesbrough & Rosenbloom, 2002). Laursen and Salter (2005) therefore refer to the ‘paradox of openness’, emphasizing that the creation of innovations often requires openness and commercialization of innovations requires appropriability. In this paper, we focus on co‐patenting as a potential window to investigate this openness paradox. In practice, co‐patenting implies the joint ownership of collaborative outcomes. Existing research on this particular phenomenon emphasizes the disadvantages of co‐patenting. Hagedoorn (2003), for instance, labels co‐patenting as a second‐best strategy that firms prefer to avoid. Belderbos et al. (2010) find a negative relationship between the share of co‐patents in firms’ patent portfolios and firms’ financial performance. At the same time, these studies provide evidence that co‐patenting is not a fading phenomenon. The number of co‐owned patents steadily increased in the US over time (Hagedoorn, 2003; Goossen, 2013) and the share of European Patent Office co‐patents within patent portfolios of R&D intensive firms remained stable between 1996 and 2003 (Belderbos et al., 2010). In sum, whereas studies stress the disadvantages of co‐patenting, one also observes that co‐ownership of intellectual property (IP) remains an empirically relevant strategy for companies developing technology jointly. The purpose of this paper is to explore the role and performance implications of co‐patenting in the setting of collaborative R&D activities. In particular, we focus on the potentially different implications of co‐patenting with different types of collaborative partners, where we distinguish intra‐industry, inter‐industry and university partners. We proceed in two steps. In a first step, we rely on interviews with 10 IP managers from large organizations that engage in R&D collaboration and co‐patenting on an international level to further

Rene Belderbos et al. explore the advantages and disadvantages of IP sharing in collaborative R&D activities. In general, these interviews confirm that co‐ownership of IP might indeed restrict firms’ ability to fully appropriate the market potential of knowledge that is generated in collaborative R&D. At the same time, they suggest that the value appropriation challenges of co‐patents heavily depend on the type of partner involved in the collaborative activities. Second, our interview findings indicate that ex‐ante negotiations of co‐patenting arrangements may also enhance value creation within collaborative R&D. In the second step of our study, we rely on panel data from 164 European, U.S., and Japanese firms to test some of the insights that emerged from our interviews. Our quantitative analyses show a significantly negative relationship between the share of co‐patents with intra‐industry partners and firm performance – measured as market value. Co‐patenting with universities, and to a lesser extent with inter‐industry partners, increases market value. At the patent level, we observe that co‐patents on average tend to receive more patent citations. More detailed analyses show a strong negative partial correlation between co‐patenting with firm partners and focal firms’ self citations to these patents, whereas a positive correlation is observed between co‐ patenting and other firms’ citations. Together these results provide a more detailed perspective on the value appropriation consequences of co‐ patenting as these differ across types of partners. On the one hand, co‐owned technologies may be associated with more value creation. On the other hand, individual firms may face liabilities in appropriating the returns to these technologies and in drawing on these technologies in their subsequent R&D and patenting efforts. These liabilities are most outspoken in intra‐industry partnerships where a high probability of overlapping exploitation domains for co‐owned technologies is present between the partners. Results are consistent with the notion that appropriation issues play a more limited role in inter‐industry partnerships ‐ where exploitation domains are likely to differ ‐ and in partnerships with universities, which less likely work on commercialization trajectories. Jointly, these findings provide a more nuanced perspective on the role of co‐patents in addressing the openness paradox in collaborative R&D activities. At the same time, we identify important avenues for future research on joint ownership of IP in open innovation settings, emphasizing the need to further explore both value appropriation and value creation implications of collaborative IP arrangements, and the importance of making an explicit distinction between co‐patent ownership rights and exploitation rights. In the next section, we rely on existing literature and our interviews to explore the role and performance implications of co‐patenting. Section 3 discusses our data and methods. Empirical results are presented in Section 4 followed by a discussion in Section 5.

2. Exploring the role and performance implications of co‐patenting A co‐patent is a patent where the ownership is shared by two or more assignees. As such, co‐patent arrangements are clearly different from other multi‐party patent arrangements such as cross‐licenses, pooled patents, and patent infringement arrangements. 1 In case of co‐patents, both applicants have the right to exploit the invention on their own behalf. At the same time, considerable differences can be observed between national patent offices in terms of transfer of ownership as well as license agreements. Both legal and management scholars (e.g. Hagedoorn, 2003; Paradiso & Pietrowski, 2009; Merges & Locke, 1990) have emphasized the complexities co‐patenting entail. At the same time, when inspecting the evolution of co‐patenting intensity over time, one observes a steady increase of co‐patenting which coincides largely with the overall growth rates of patent activity (Hagedoorn, 2003). As such, the proportion of co‐patents remains stable over time (Appio, Landoni & Van Looy, 2012; Belderbos et al., 2010). To address the constraints in their internal technology development capabilities, firms heavily rely on collaboration with external partners to jointly develop new technologies (Ahuja, 2000). Because of the above mentioned complexities, collaborative partners generally tend to prefer splitting the intellectual ownership on the outputs of collaborative R&D among the involved partners (Hagedoorn, 2003). However, scholars have identified particular circumstances in which partners are likely to come to joint IP ownership of collaborative R&D outputs. Hagedoorn (2003), for instance, argues that, in particular types of R&D collaboration (i.e. small 1

See Hagedoorn (2003) for a discussion of the legal differences between co‐patenting and other multi‐party patent arrangements.

Rene Belderbos et al. scale, informal partnerships), it might be very difficult to divide the intellectual property on R&D outputs between the partners. In such circumstances, partners are likely to rely on co‐patenting as a second‐best option. In addition, Teng (2007) argues that, when R&D outputs have potential to become a core competency for one partner and there is substantial risk that the other partner might abuse individual‐owned IP for strategic reasons, the former partner is likely to prefer joint IP ownership above splitting IP ownership among the two partners. Finally, Hagedoorn, Van Kranenburg, and Osborn (2003) provide evidence that, when firms have engaged in co‐patenting activities in the past, they are more likely to engage in co‐patenting in later collaborative activities. This latter finding suggests that, when firms have learned how to effectively arrange and manage co‐patents, they are more likely to rely on them in subsequent collaborative efforts. In sum, existing findings suggest that, despite the complexities and challenges of co‐patenting, co‐ownership of collaborative R&D outcomes occurs in particular circumstances. As a first step in this study, we conducted interviews with 9 IP experts operating in multinational firms and one IP expert of an internationally renowned knowledge institute to further explore the role and performance implications of co‐patenting. We asked interviewees to reflect on (i) the benefits and liabilities of co‐patenting for collaborative R&D activities, and (ii) the potential performance implications of co‐patenting. Subsequently, we systematically compared the content of the interviews with existing literature on co‐patenting. The interviews clearly showed that co‐ patenting implies important value appropriation risks. At the same time, however, interviewees also indicated that the ex‐ante negotiation of co‐patenting arrangements might affect value creation processes in collaborative R&D activities. Below, we discuss these two aspects of co‐patenting in detail.

2.1 Value appropriation implications of co‐patenting Whereas single owned patents create a temporary monopoly for the patent owner, co‐patenting resembles a duopoly (or tight oligopoly) in which the joint owners of the patent can compete against each other (Hagedoorn, 2003). In our interviews, it was acknowledged that, compared to fully owned patents, co‐ ownership of knowledge creates fewer opportunities for realizing monopoly rents. In addition, it was stressed that sharing ownership of knowledge ‘creates uncertainty on the control that each co‐owner has on the co‐ owned IP.’ Prior research on the performance implications of co‐patenting has largely ignored the type of partners involved in the co‐patenting activities. Interviewees, however, emphasized that the challenges of appropriating value from co‐patents heavily depends on the type of partner involved. First of all, they indicated that value appropriation concerns are likely to be low when ownership of knowledge is shared with universities. When the partner is a university, the risk that this partner might become a competitive threat for the focal firm is rather limited because universities often lack the incentives and abilities to commercially exploit the co‐owned knowledge. In addition, interviewees stressed that, when they engage in collaboration with universities, ‘it is a standard procedure to contractually negotiate that universities do not have the right to license such co‐owned knowledge to our competitors.’ Regarding co‐patenting with private firms, interviewees emphasized that the value appropriation consequences of co‐patenting depend on whether partners are active in similar domains. In particular, it was stressed that, when partners are active in different industries and markets there is a relatively high likelihood that they will use the co‐owned knowledge for different exploitation purposes. In contrast, when partners are active within the same industry, the risk that they will deploy the co‐owned knowledge for similar purposes is higher, implying a risk of intensified competition which could jeopardize value appropriation. Based on these insights, we expect that co‐patents with intra‐industry partners, where the risk of overlapping application domains is relatively high, create more challenges to appropriate value than co‐patents with inter‐ industry partners or with universities. As information on co‐patenting activities disseminates, analysts and investors are likely to take these consequences into account in their assessment of future profitability prospects. This implies that the negative association of co‐patenting with market valuation in prior research has identified, should primarily be a feature of co‐patents with intra‐industry partners.

2.2 Value creation implications of co‐patenting Our interviews also suggest that negotiating co‐patenting arrangements ex‐ante might influence the collaboration processes and hence value creation resulting from collaboration. First, following the open

Rene Belderbos et al. innovation paradigm, organizations that engage in collaborative R&D efforts have the opportunity to synergistically combine their complementary knowledge sources. This allows generating technological inventions that organizations could not realize on their own (Carson et al., 2003; Doz & Hamel, 1997; Vanhaverbeke, 2006). At the same time, it is stressed that, in order to effectively realize such synergies, intensive interaction between partners is necessary (Doz, 1996; Faems, Janssens & Van Looy, 2007). Existing studies on inter‐firm R&D collaboration, however, signal that the willingness of partnering firms to engage in intensive interaction is often limited by ex‐ante concerns to appropriate knowledge. Scholars suggest that firms’ ability to come to joint value creation in collaborative projects might be restricted because of ex‐ante concerns that the other partner might opportunistically appropriate jointly‐developed knowledge. In our interviews, IP experts referred to the importance of ex‐ante contractual IP allocation procedures to mitigate such knowledge appropriation concerns. In particular, they described that, at the start of the collaboration, partners tend to contractually define the existing knowledge domains of both partners based on their existing technological expertise and capabilities. In addition, they contractually agree that, when collaborative R&D efforts result in intellectual property in one of the unique knowledge domains, the owner of this domain will become the sole owner of the patent. At the same time, several interviewees stressed the likely presence of a ‘gray [knowledge] zone’ where it is difficult to determine ex‐ante who should be the owner of intellectual property. For these particular knowledge domains, interviewees pointed to the relevance of co‐ patenting arrangements, where partners contractually agree to share the ownership of knowledge that is jointly generated. Based on these observations, we expect that, when partners contractually define the option of co‐patenting for knowledge domains that are non‐partner specific, ex‐ante knowledge appropriation concerns are mitigated, resulting in a higher willingness to effectively engage in joint value creation activities. Recent findings of Carson and John (2013) provide first support for these observations. Analyzing 147 R&D outsourcing contracts, they find that ‘clients who share property rights with their contractors face reduced opportunism during project execution’ (Carson & John, 2013, p. 1065). Interviewees also referred to the relational function of ex‐ante co‐patenting arrangements in collaborative R&D activities. Our interviewees emphasized that co‐patents might contribute to increased levels of trust between collaborative partners, which might strengthen the intensity of cooperation between involved partners. In sum, we find strong indications that co‐patenting arrangements might reduce ex‐ante knowledge appropriation concerns and subsequently increase the level of trust between partners in the collaboration. In line with existing literature on collaborative R&D (Dyer & Singh, 1998; Cassiman & Veugelers, 2006; Faems et al., 2008), we expect that, in such circumstances, the willingness of partners to effectively combine their complementary knowledge will be higher, increasing effective joint value creation.

3. Data and methods To more formally corroborate these value creation and value appropriation challenges of co‐patenting we conduct two types of empirical analyses. At the patent level we explore whether an indicator of patent value (forward citation) differs systematically between the three types of co‐patents and single firm‐owned patents. In a second empirical model we examine the relationship between co‐patenting activities of firms and a forward‐looking measure of firms’ financial performance (i.e. Tobin’s q) as an indicator of value appropriation. We constructed a panel dataset (1995‐2003) consisting of the technological activities and financial performance of 164 R&D‐intensive European, US and Japanese firms. We rely on firms’ patents to examine co‐ patenting behaviour and to construct measures of technological performance based on patent value (i.e. citations). We collected firm patent data at the consolidated level, using data from the European Patent Office (EPO). Since we are interested in IP sharing and appropriation, we focus our analysis on patent applications that are subsequently granted. We classify patents by the year of application. We used information on the ownership of the patents to distinguish between solitary‐owned and co‐owned patents. A patent is considered as co‐owned when it is jointly owned with an economic actor that is not part of the consolidated focal firm. Patents that are jointly owned by firms and individual persons have been excluded. Patent applicant (assignee) names referring to individual persons, firms and universities are identified by sector allocation algorithms (source: Van Looy, Du Plessis & Magerman, 2006).

Rene Belderbos et al. We defined the corporate co‐owners of patents as intra‐industry partners or inter‐industry partners based on the main sector(s) in which the assignee firms operate. To determine the main sector(s) of firms, we identified the technology class(es) in which the firm has filed most of its patents. Technology classes are linked to 44 sectors via the concordance table developed by Schmoch et al. (2003). The same procedure is used to identify the main sectors of partnering firms (co‐assignees on co‐patents) of the focal firms, using assignee name harmonizing algorithms (Van Looy et al, 2006) and the consolidation exercise to identify patents belonging to the same firm in the patent database. If the focal firm and the partner are active in the same sector, the co‐ patent is defined as intra‐industry; in all other cases it is defined as inter‐industry. Our assumption is that the likelihood of interaction between intra‐industry partners is larger than in the case of inter‐industry partners. Patented technologies differ in their technical and economic value. Patent forward citations have been advanced as a measure for the value of patents. We apply a fixed 4‐year window to calculate the number of citations patents receive to establish a comparable citation window across patents. We include all citations (in patents filed in various patent offices) to the patent and its equivalents within the patent family (patent documents that share the priority date). Citations are calculated on the PATSTAT database, which contains citation information for patents from all the major patent offices in the world. We also make a distinction between self‐citations by the focal firms and non‐self‐citations. Self‐citations are citations in subsequent patent applications by the same focal firm and its consolidated subsidiaries. The distinction between self‐ citations and non‐self‐citations allows us to investigate whether the patent‐owning firm or other firms build upon a patented invention in later technological activities. Forward self‐citations have been found to be a better predictor of the economic value of patents than non‐self citations (Hall et al., 2005) as self‐citations indicate that the patents are a source of future development and exploitation by the firm itself.

3.1 Patent level analysis In the patent level analysis, we examine the characteristics of the firms’ patent grants, including their co‐ patent status, applied for between 1996 and 2003. Together the 164 firms account for 85.706 patent applications during the observed time period, which were subsequently granted. The empirical model at the patent level has the number of forward citations as dependent variable. We apply Poisson regression models with robust standard errors and firm fixed effects to analyse the partial correlations between forward citations and whether or not the patent is co‐owned (by different types of partners). We differentiate the dependent variable between self‐citations and non‐self‐citations received to explore differences in citation patterns and future exploitation of patented technologies in detail. The explanatory variables of interest in the model are dummy variables indicating whether the patent is a co‐ owned patent with an intra‐industry, inter‐industry or university partner. The analysis includes a full set of 3‐ digit IPC technology field dummies, year of application dummies, and parent firm dummies. Additional models control for the number of technology fields in which the patent is classified, the number of non‐patent citations, the number of backward patent citations and the number of inventors listed on the patent.

3.2 Firm level analysis The second empirical model examines the relationship between co‐patenting activities of firms and a forward‐ looking measure of firms’ financial performance, Tobin’s q. We use a specification of the market value function that is predominant in the literature: an additively separable linear specification. The key independent variables measure information available to financial analysts that affects their assessment of the future income streams and stock value of the firm. We follow prior literature on the market valuation effects of R&D and patents (e.g. Hall et al., 2005 by calculating stock variables for all R&D and patent related variables (examining patent data from 1978 and R&D data from 1985). In the case of patents, the time lag with which information reaches investors is of importance. We classify patent grants at the year of application (the year the collaborative R&D was conducted). However, EPO patent applications generally take a minimum of 1.5 years and usually 2‐3 years before they are published by the patent office and become fully visible to investors. On the other hand, the publication date is not always representative of the timing of patent disclosure, as firms may disclose their patent filings earlier to investors. Generally we can expect that patents filed in year t are most likely to affect market valuations in t+2 or t+3. We present the results of models with 2 year lagged patent variables, as adding additional lags reduces the number of observations for the firms in the dataset without improving the efficiency of our estimates.

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Rene Belderbos et al. While the two‐year lag due to the phenomenon of the delayed’ effects of patent applications on market value helps to alleviate concerns of reverse causality, our analysis cannot rule out endogeneity stemming from unobserved heterogeneity. We therefore interpret our results as partial correlations (associations) rather than causal relationships. Given the two year time lag and our panel data covering 1995‐2003, we analyse the relationship between co‐patenting and market value during 1997‐2003. The dataset contains 1059 observations on 164 firms. We estimate the market value model with ordinary least squares and cluster error terms at the firm level. The dependent variable in the financial performance analysis is (the natural logarithm of) Tobin’s q, i.e. the ratio of the market value of a firm and the replacement (book) value of the firm’s assets. Tobin’s q is a forward‐looking indicator that contains the stock market’s assessment of firms’ future financial results from current technological activities. Information on the market and book value of firms is collected from financial databases. The key explanatory variables of interest are variables reflecting the intensity of co‐patenting activities with different partners. We include three indicators of co‐patenting activities representing the degree to which the firm is engaged in co‐patenting with intra‐industry, inter‐industry and university partners. Each of these variables measures the share in firms’ total granted patent stock of patents of that particular co‐patenting activity, with a two year lag. Patent stocks were calculated as a perpetual inventory of past and present granted patents of the firm with a constant depreciation rate (δ) of 15 per cent. As control variables we include four indicators for the firm’s technological activities: R&D intensity (R&D/assets), patent propensity (patents/R&D, with a 2‐year lag; R&D in million Euros), patent citations (citations/patents, number of citations per patent), and the ratio of self‐citations to total patent citations (self‐citations/citations). R&D and citation variables are constructed as stocks using the same formula as for patent stocks and the same depreciation rate (δ) of 15 per cent. For the construction of R&D stocks, listings of annual R&D expenditures of firms back to 1985 are used. For calculation of initial R&D stock values, an annual R&D growth rate of 8 per cent is applied. Annual R&D expenditures and asset data have been deflated. Second, we control for technology diversification by including the (natural logarithm of the) number of 3‐digit technology classes in which the firm is active (technology diversification). Third, we include a set 17 NACE 2‐digit dummy variables to control for industry differences. Fourth, we include home country (US, Japan, and 11 European countries) and year (1996‐2003). Finally, we control for firm size by including the logarithm of total assets.

4. Empirical results 4.1 Patent‐level analyses Table 1 presents the empirical results of the poisson regression models of the number of citations a patent receives. Model 1 includes the dummy variables indicating whether the patent is a co‐patent or not and sets of 3‐digit technology field, firm, and year dummies. Model 2 adds other patent characteristics, with the exception of the number of inventors – the patent characteristic correlated with co‐patent status. Model 3 also adds the latter variable. Models 4 and 5 present the comparative results of the specification of model 3 for the alternative dependent variables self‐citations and non‐self‐citations. The empirical results show that, controlling for technology field, patenting firm, and year of application, co‐owned patents with partner firms (intra‐industry or inter‐industry) are significantly correlated with higher forward citation rates. The coefficients imply an 11‐13 % citation premium for co‐patents. The coefficient for university co‐patenting is relatively large, but not significantly different from zero. In model 2, the additional patent characteristics, with the exception of the number of technology classes of the patent, have positive coefficients and are statistically significant, while the co‐patenting coefficients remain largely unchanged. When the number of inventors is included in model 3, however, the coefficients on co‐patents are sharply reduced and become insignificant, while the coefficient on the number of inventors itself is positive and highly significant. While these findings are not in contrast with the notion that IP sharing may have positive value creation effects, in general it appears difficult to disentangle the effect of co‐patenting from the number of inventors’ effect, as co‐patents are associated with larger inventor teams. In models 4 and 5, the empirical results reveal some interesting contrasts. Whereas co‐patents do appear to receive more citations from other firms (12‐14 %), co‐patenting with other firms is associated with a significantly smaller number of self‐citations (in the range of 32‐48 %). At the same time, university co‐

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Rene Belderbos et al. patenting is not significantly associated with a greater or smaller incidence of self‐citations and non‐self‐ citations. The positive effect on non‐self‐citations may have a natural explanation: compared with focal firms’ single owned patents, co‐patents with other firms will increase the probability that these partner firms cite the patent in their future technology development efforts. More salient is the strongly negative effect on self‐ citations. This suggests that firms build less in their future R&D efforts on co‐owned inventions as compared to single owned inventions. This interpretation is in line with the notion of appropriation difficulties of shared technologies, which may restrict focal firms to exploit and build on co‐owned technologies. We examine the appropriation effects of co‐patenting in more detail in the firm performance analysis. Table 1: Robust poisson regression of forward citations received (patent‐level)

copatent - interindustry copatent - intraindustry copatent - universities

Model 1 all cites

Model 2 all cites

Model 3 all cites

Model 4 selfcites

Model 5 nonselfcites

0.114** [0.046] 0.130*** [0.043] 0,213 [0.163]

0.119*** [0.046] 0.129*** [0.043] 0,179 [0.164] 0.021*** [0.002] 0.038*** [0.005] 0,066 [0.107]

Included Included Included

0,025 [0.046] 0,021 [0.043] 0,084 [0.165] 0.019*** [0.002] 0.037*** [0.005] 0,055 [0.107] 0.058*** [0.003] Included Included Included

-0.488*** [0.052] -0.322*** [0.073] -0,151 [0.178] 0.019*** [0.002] 0.024*** [0.005] 0,093 [0.166] 0.088*** [0.003] Included Included Included

0.142*** [0.051] 0.118*** [0.045] 0,159 [0.183] 0.019*** [0.002] 0.042*** [0.005] 0,046 [0.118] 0.047*** [0.003] Included Included Included

backward patent citations non-patent citations number of technology fields number of inventors 3-digit IPC dummies firm dummies year dummies

Observations 85706 85706 85706 85706 85706 -464959 -467367 -183918 -404446 Loglikelihood -461334 Pseudo R2 0,129 0,133 0,14 0,115 0,151 * significant at 10%; ** significant at 5%; *** significant at 1%, robust standard errors in parentheses

4.2 Firm‐level analyses We now turn to the analysis of financial performance – market valuation. Table 2 shows the results of the analyses on market valuation. Model 1 excludes the focal co‐patenting variables and model 2 shows the results when these are added. Consistent with prior research, Model 1 shows that R&D intensity, the ratio of patents to R&D the citation ratio and the ratio of self‐citations have positive and significant coefficients. Firms that exhibit greater technology diversification, and which are larger, have lower values for Tobin’s q. In model 2, we observe a negative and significant coefficient for the stock of co‐patents with intra‐industry partners. The estimated coefficient implies that a standard deviation (0.032) change in the share of co‐patents with intra‐industry partners is associated with a reduction in Tobin’s q by about 10 percent. In contrast, co‐ patenting with inter‐industry partners has a positive and weakly significant effect on market valuation. The estimated coefficient suggests that a standard deviation increase in the inter‐industry co‐patenting share is associated with an increase in Tobin’s q of about 6 percent points. Co‐patenting with universities has a strongly significant coefficient, and suggests an association with Tobin’s q of a similar magnitude: a standard deviation change in university co‐patenting enhances q by roughly 6 percent points. When we estimate random effects models rather than OLS models with clustered standard errors, smaller but significant coefficients are estimated for university and intra‐industry co‐patenting, while the coefficient on inter‐industry co‐patenting becomes insignificant. The ranking of effects is fully in line with the view that IP sharing is unlikely to hamper appropriation if it concerns collaboration with universities, and more likely in intra‐industry partnerships than in inter‐industry partnerships.

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Rene Belderbos et al. Table 2: Co‐patenting and market valuation (Tobin’s Q) Mode l 1

3.552*** [1.076] 0.748*** [0.251] 0.021* [0.012] 0.924*** [0.312] 0.137*** [0.045] -0.310*** [0.084] included included included

Mode l 2 -3.185*** [0.855] 1.793* [0.991] 5.955** [2.673] 3.823*** [1.034] 0.725*** [0.253] 0.021* [0.012] 0.950*** [0.306] 0.139*** [0.044] -0.336*** [0.085] included included included

1,059 0,555

1,059 0,572

intraindustry copatenting t-2 interindustry copatenting t-2 university copatenting t-2 R&D/assets patents/RD t-2 citations/patents t-2 selfcitations/citations t-2 firm size techology diversification country dummies year dummies 16 sector dummies Observations (firms) R squared

5. Conclusion Relying on both qualitative and quantitative data, this paper explores the role and performance implications of co‐patents. Our findings provide a richer understanding of the challenges and opportunities that firms face when they have to make strategic decisions on IP ownership in open innovation activities such as collaborative R&D. First, we show that the challenge to appropriate value from sharing IP ownership depends on the type of partner involved. Second, we provide first indications that engaging in co‐patenting arrangements with collaborative partners might at the same time create value. Below, we discuss how our findings enrich our understanding of the value appropriation challenges and the value creation opportunities of co‐patenting.

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Organizational Innovations – Constituents and Determinants Within Underdeveloped and Immature Markets Muamer Bezdrob1 and Aziz Šunje2 1 PING d.o.o. Sarajevo, Sarajevo, Bosnia and Herzegovina 2 School of Economics and Business Sarajevo, Sarajevo, Bosnia and Herzegovina mbezdrob@ping.ba aziz.sunje@efsa.unsa.ba Abstract: Innovation is widely considered as a critical source of organizational competitive advantage and one of the most important determinants of organizational performance. Consequently, innovations and innovativeness have been thoroughly studied from many different aspects – phenomenological, managerial, operational, business and alike. A great majority of those studies are performed in and related to mature markets. Thus, the purpose of this research is to adapt the existing knowledge base and design and test a theoretical model of organizational innovation that is applicable to immature and underdeveloped markets such as the market of the Federation of Bosnia and Herzegovina (F B&H). This model must comprise both the determinants and constituents of innovations, i.e. the elements which predict and define organizational innovations on the operational level. In order to design a desirable model, the literature was reviewed systematically both from theoretical and empirical perspectives. During this research process, all necessary hypotheses for a theoretical model were formulated. Consequently, corresponding measurement and structural models of organizational innovation were specified. For the purposes of model testing a questionnaire was developed and sent to more than 300 firms in the F B&H that meet a strict business profile, yielding 156 valid responses. The confirmatory factor analysis and structural equation modelling are used for testing and validation of the hypothesized model. The proposed model is rather complex, but very intuitive. It integrates previous research results with results obtained through a rigorous theoretical approach to model design and development. A very important research finding is that all measures from the model were fully validated. In addition, research results indicate that the context in which the firm operates and, especially, the firm’s human resources capacity determine the firms that are apt for organizational innovation. Surprisingly, the obtained results suggest that the size and power of the firm do not have a significant impact on innovativeness. Simultaneously, research results have revealed two concepts – management innovations and technical innovations, which define organizational innovations. The designed model is fully applicable to market conditions in the F B&H, which provides yet another proof that the relevant theories related to organizational innovation are applicable to the conditions of immature markets. Keywords: innovations, innovation model, immature markets, innovation determinants

1. Introduction Innovation and innovativeness represent one of the most important concepts, not only in modern business and management, but probably in all contemporary human activities. Furthermore, in times of quick changes and great business uncertainty, innovativeness is likely to be a strategic priority of almost any business organization. Studies about the phenomenon of innovation are present in the economic literature since the 1920s. Joseph Schumpeter (1939) was the first great economic theorist who believed that innovations represent one of the main drivers of economic changes. Later on, this phenomenon was further researched and analysed, where the most notable and famous are the works of Alfred Chandler (1962) and Clayton Christensen (1997). Nevertheless, the profound and systematic research on this important aspect of the modern economy started some 30 years ago (Anderson et al. 2004). Many important issues related to the innovation are thoroughly elaborated in the existing literature, such as the main reasons (causes) why organizations undertake innovations (Herring and Galagan 2011) or the main outcomes (effects) of innovations (Stock and Zacharias 2011). However, the main focus of this study is a general picture of (organizational) innovation phenomenon on a firm level. Thus, the first research question of this study is: Q1: What are the main factors (principal constituents), which define organizational innovation, and what are the main factors (principal determinants), which have important and significant influence on organizational innovation?

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Muamer Bezdrob and Aziz Šunje Almost all notable research activities were performed in and related to the mature markets of the most developed countries of the world. Such a fact leads to the second research question: Q2: Is the existing theory related to organizational innovation adaptable and applicable to the conditions of immature market of the Federation of Bosnia and Herzegovina? These two research questions outline the scope of this study. Its main goal is a design of an overall theoretical model of organizational innovation, which should be founded on the existing literature and empirically verifiable. That model has to be applicable to any market conditions, particularly to those of the F B&H. Finally, it should be open for further modifications and applicable for future research.

2. Literature review There are many different definitions of innovation (e.g. Crossan and Apaydin 2010; Damanpour 1992), but in each of them one can find “novelty” and “change” as the two most common determining terms. Within the context of this study, the term “organizational innovation” implies the adoption or implementation of any system, practice, process, structure, product or service that is new to the adopting organization. It is important to be noted that this research refers to the innovations that are new to the adopting organization and not those that are new to the world. Such a broad definition of organizational innovation encompasses all kind of innovations, which could be broadly classified into four groups: operational innovation, product/service innovation, strategic innovation and management innovation (Hamel 2007). The existing literature related to the first and second groups is well integrated into the literature on technological innovation (Lam 2005). Likewise, the existing literature on strategic and management innovation, even though rather scarce in comparison with the literature on technological innovation, is quite comprehensive (Berghman 2012; Mol and Birkinshaw 2007) and could be treated as a single type of innovations related to the management model in general. In line with such a distinction, this study considers technological innovations and management innovations as the basic or main constituents (defining elements) of organizational innovation. At the same time, this study is focused on the factors that have the most significant influence on innovative activities of organizations or, otherwise stated, it is focused on the determinants of organizational innovation. There is a plenty of scientific research on this topic, whether on personal and group level (Rank et al. 2009; Taggar 2002) or organizational level (Damanpour 1991; Kimberly and Evanisko 1981). These latter studies are of particular interest, since they provide a theoretical foundation for this research.

2.1 Organizational Innovation – the model The importance and relevance of innovations to the economy as a whole, gave rise to an enormous number of articles related to the many different aspects of this concept (Calantone et al. 2010; Crossan and Apaydin 2010; Smith et al. 2008). Such a wealth of literature is well suited for this study, since it is, first and foremost, interested in a design of an overall model of organizational innovation, which has to comprise both the principal constituents of organizational innovation, on the one hand, and the main factors that predict organizational innovation, on the other hand. This model has to be strongly founded on the existing literature and, simultaneously, applicable to the many different market conditions, but particularly to the market conditions of the F B&H. Along with the abundance of literature on innovation, there is a myriad of definitions of innovation types (Garcia and Calantone 2002), which are classified in many different ways (Damanpour et al. 1989; Hamel 2007). For this study, the most important typology of innovation is the one which differentiates between administrative and technical innovations (Damanpour 1991). In accordance with this differentiation, the study considers organizational innovation as a construct defined by two sub‐constructs – management innovation and technical innovation. As previously stated, this research is focused on the innovation processes which happen on the organizational level. There are quite a lot of studies which analyse an impact of different contextual factors on organizational innovation (Balasubramanian and Lee 2008; Mazzarol et al. 2010). Accordingly, organizational context – a set

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Muamer Bezdrob and Aziz Šunje of organizational attributes (Mol and Birkinshaw 2009), represents an important determinant of organizational innovation, so the first research hypothesis is: H1: The organizational context has a direct and positive impact on organizational innovation. Beginning with what is called the "Schumpeterian hypothesis" (Samuelson and Nordhaus 1995), there are many studies that observe the link between firm’s size and power and its propensity towards innovation (Bertschek and Entorf 1996; Damanpour 1992; Mazzarol et al. 2010). Even though the findings of these studies are somewhat discordant, the second research hypothesis is established as follows: H2: The organizational strength has a direct and positive impact on organizational innovation. People who promote innovation constitute the most important element of the innovation processes (Birkinshaw et al. 2008). A positive link between organizational innovation processes and personal characteristics of managers and employees were found in many studies (e.g. Damanpour and Szabat 2006; Østergaard et al. 2011), as well as a positive correlation between the levels of education and innovation (Kimberly and Evanisco 1981, Mol and Birkinshaw 2009). Furthermore, well established HRM functions have a strong positive impact on innovation (Shipton et al. 2006). Thus, the following hypothesis could be proposed: H3: The organizational human resources capacity has a direct and positive impact on organizational innovation. These three hypotheses, together with the previously defined organizational innovation construct, determine the organizational innovation conceptual model (Figure 1).

Figure 1: Conceptual model of organizational innovation

3. Data and methodology To test the hypothesized model, a survey questionnaire was sent to 320 firms that were randomly chosen from within the whole population of the firms that comply with the following profile:

registered in the F B&H,

employing at least 20 people,

established in 2002 or earlier,

not belonging to financial, health care, social welfare, educational or public sector.

A total of 186 responses (58.1%) were received, out of which 156 were valid (48.75%). The responding firms have the average size of 175.5 (S.D. 334.3) employees and the average age of 17.5 (S.D. 4) years. The estimated population of the firms that comply with the described profile is about 1500, so the expected statistical error is around 8% (95% confidence level). The firms are proportionally distributed among different industries and different geographical parts of the F B&H.

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3.1 Measures All variables in the model were measured using the data from the conducted survey and from the official balance reports of the corresponding firms. The measurement spans five‐year period from the year 2006 to the year 2010. 3.1.1 Context (F1) This construct relates to situational factors under which firms conduct their business. Based on a measure from Mol and Birkinshaw (2009) a four‐indicator measure was used for this construct:

“Ownership Structure” (X1) – ranks (1 ‐ 8) firms based on the ownership type and foreign capital share.

“Age” (X2) – ranks (1 ‐ 6) firms based on their life span from the year of incorporation to the year 2012.

“Industry Dynamics” (X3) – ranks (1 ‐ 4) firms based on the dynamics of the industry sector to whom they belong.

“Export Scope” (X4) – ranks firms based on a ratio of exporting revenue to total revenue (1 ‐3).

3.1.2 Organizational strength (F2) This construct relates to the firm’s size and power. To measure this construct, three most common size parameters was used:

“Average Number of Employees” (X5) – ranks (1 ‐ 6) firms based on the average number of employees during the 2006‐2010 period.

“Average Equity” (X6) – ranks (1 ‐ 6) firms based on the average equity value during the 2006‐2010 period.

“Average Fixed Assets” (X7) – ranks (1 ‐ 6) firms based on the average amount of firm’s fixed assets during the 2006‐2010 period.

3.1.3 HR (human resources) capacity (F3) This construct relates to the strength of firm’s overall human resources and associated systems. Based on combined measures from Mol and Birkinshaw (2009) and Chang and Huang (2010) a four‐indicator measure for this construct was developed:

“Managerial Expertise” (X8) – ranks (1 ‐ 6) firms based on the managers’ experience in different functional areas and firm’s engagement in managerial education and skills improvement.

“Expert Foundation” (X9) – ranks (1 ‐ 5) firms based on the ratio of employees with a graduate level to the average number of employees during the 2006‐2010 period.

“Educational System” (X10) – ranks (1 ‐ 9) firms based on their training plans and educational budget.

“Employees Enablement” (X11) – ranks (1 ‐ 5) firms based on their HRM functions (employee’s socialization and orientation) and equipment availability to the employees.

3.1.4 Organizational innovation (F4) This second‐order construct relates to all types of innovation that organizations adopt or implement. 3.1.5 Management innovation (F5) This construct relates to the aggregate level of innovative activities from within the management domain. To measure this construct, measures from the previous research on management innovation were taken over and adapted (Bezdrob and Šunje 2012):

“Process” (Y1) – ranks (1 ‐ 5) firms based on the implementation of the following management practices: QMS, TQM, 6σ, SCM and Lean Manufacturing.

“Strategy & Performance” (Y2) – ranks (1 ‐ 3) firms based on the implementation of the following management practices: BSC, EVA, Strategy Planning and Benchmarking.

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“Customer & Information” (Y3) – ranks (1 ‐ 3) firms based on the implementation of the following management practices: Brand Management, CRM, Operations Research and ERP.

“People & Structures” (Y4) – ranks (1 ‐ 3) firms based on the implementation of the following management practices: HRM, 360‐degree Feedback, PMO and Matrix Organization.

3.1.6 Management innovation (F6) This construct relates to the aggregate level of innovative activities from the technical domain. A simple three‐ indicator measure, which refers to the level of innovative activities within the firms’ production systems and structures, was used:

“Product Innovativeness” (Y5) – ranks (1 ‐ 4) firms based on whether they introduced new or modified products or not.

“Process Innovativeness” (Y6) – ranks (1 ‐ 4) firms based on whether they introduced new or modified production processes or not.

“Structural Innovativeness” (Y7) – ranks (1 ‐ 4) firms based on whether they introduced new or change the existing organizational structure or not.

3.2 Results All model variables are measured on an ordinal scale. Table 1 contains the means and standard deviations of and covariance between all variables, where alternative parameterization is used for the underlying variables of model’s ordinal variables (Jöreskog 2004). To test the hypothesized model we employed structural equation modelling (SEM) because it enables a concurrent testing of several dependence relationships within a single theoretical model (Hair et al. 2009). Following the two‐step approach (Anderson & Gerbing 1988), LISREL 8.80 was used for both measurement and structural model testing. Table 1: Means, standard deviations and covariance between model variables

Variable

Mean

S.D.

X1 X2 X3

Ownership Structure Age Industry Dynamics

2.25 1.93 0.73

0.90 2.00 2.37

0.82 ‐0.73 0.74

3.98 ‐0.76

5.59

X4 X5

Export Scope Avg. Number of Employees Average Equity Average Fixed Assets

0.14 1.39

1.10 1.40

‐0.13 ‐0.12

0.18 0.53

‐1.18 ‐0.40

1.21 0.33

1.95

2.08 1.68

1.93 1.52

‐0.31 ‐0.21

0.71 0.80

‐0.27 ‐0.16

0.20 0.32

1.94 1.57

3.73 2.46

2.32

Managerial Expertise Expert Foundation Educational System

2.14 0.25 2.39

1.60 1.04 2.99

‐0.06 0.04 ‐0.19

0.30 ‐0.13 ‐1.04

‐0.26 0.28 ‐0.36

0.17 ‐0.05 0.01

0.56 ‐0.23 ‐0.90

0.55 0.02 ‐1.14

0.58 0.03 ‐1.01

2.54 0.49 1.87

X6 X7 X8 X9 X1 0 X1 1 Y1 Y2

Employees Enablement

4.17

1.87

‐0.11

‐0.14

0.60

‐0.50

‐0.44

‐0.74

‐0.46

0.83

Process Strategy & Performance

‐3.97 ‐0.97

3.60 1.11

1.53 0.44

‐0.11 ‐0.55

‐0.70 0.49

0.08 ‐0.08

0.32 ‐0.18

0.05 ‐0.16

0.02 0.00

0.67 0.37

Y3 Y4 Y5

Customer & Information People & Structures Product Innovativeness

‐1.05 ‐0.89 1.94

1.21 1.02 1.57

0.31 0.25 ‐0.07

‐0.61 ‐0.61 ‐0.17

0.75 0.21 0.03

0.04 0.01 0.04

‐0.04 ‐0.06 0.13

‐0.15 ‐0.15 0.00

‐0.08 ‐0.12 0.04

0.48 0.38 0.51

Y6 Y7

Process Innovativeness Structural Innovativeness

1.60 1.23

1.33 1.77

‐0.01 0.03

‐0.31 ‐0.23

0.08 ‐0.28

‐0.12 ‐0.08

‐0.06 0.03

‐0.26 0.30

‐0.25 0.31

0.43 0.97

X9 X1 0 X1

Variable Expert Foundation Educational System

X9 1.09 1.27

X10 8.92

X11

Employees Enablement

0.86

2.84

3.50

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Muamer Bezdrob and Aziz Šunje 1 Y1

Y2 Y3 Y4 Y5 Y6 Y7

Variable

Mean

S.D.

Process

0.09

2.84

0.19

Strategy & Performance Customer & Information People & Structures Product Innovativeness Process Innovativeness Structural Innovativeness

0.12 0.33 0.32 0.25 0.21 0.35

0.84 1.39 1.02 0.88 1.34 1.52

12.9 3 ‐0.24 2.32 0.16 1.96 0.00 1.98 0.21 0.22 0.46 0.42 0.50 1.84

1.24 0.84 0.86 0.50 0.46 0.63

1.46 0.82 0.66 0.61 0.44

1.04 0.34 0.45 0.50

2.47 1.54 1.03

1.78 1.22

3.12

3.2.1 Assumptions The dataset contains responses from 156 firms. There were no missing data and no univariate outliers. Considering the hypothesized model complexity, this sample size is just adequate for the model estimation (Hair et al. 2009). Since all data are ordinal, both univariate and multivariate normality were violated. All variables showed a moderate non‐normality (skew < 2, kurtosis < 7) except variable Y1 (skew > 2, kurtosis > 7). Thus, in accordance with the recommendation for dealing with non‐normal and ordinal data (Finney and DiStefano 2006), the Satorra‐Bentler scaling method for χ2 and standard errors is used for model estimation. 3.2.2 Measurement model Since a poor fit was found for the initial model, a post hoc model modification was done in order to develop a better fitting model. Based on modification indices and theoretical relevance, the following covariances between error terms were added to model specification: X1 ↔ X4, X2 ↔ X4, X5 ↔ X9, and Y5 ↔ Y7. The model fitting is examined through several absolute, incremental and parsimony goodness‐of‐fit indices (Table 2). All these fit indices suggest an acceptable fit for the measurement model. Table 2: Goodness‐of‐fit measures of measurement and structural model GoF Index χ (df); p‐value

GoF Guideline p > 0.05

Measurement Model 148.49 (124); p = 0.066

Structural Model 148.925 (123); p = 0.056

RMSEA 90% CI of RMSEA SRMR

RMSEA < 0.08 % SRMR < 0.08

0.036 0.0 ‐ 0.056 0.105

0.037 0.0 ‐ 0.057 0.101

CFI PNFI

CFI > 0.95 PNFI > 0.50

0.984 0.737

0.983 0.731

Construct validity is assessed through convergent validity, discriminant validity and face validity. All factor loading estimates are of expected direction and all are statistically significant as required for convergent validity. Table 3 displays standardized factor loadings for the measurement model. It could be seen from Table 3 that all factor loadings fall very near or above the cut‐off value of 0.5 (Hair et al. 2009). Furthermore, the estimates of the average variance extracted (AVE) all exceed cut‐off value of 0.25 (25%), and the construct reliability (CR) estimates are above cut‐off value of 0.6 (Hair et al. 2009). Combining these results with a fact that the overall model fits very well, it could be concluded that convergent validity for the model was provided. In addition, all AVE estimates for the model’s constructs are greater than the squared inter‐construct correlations, which indicate that there are no problems with discriminant validity. The proposed model has six constructs, where each construct describes a specific aspect of the reality and has a clear purpose within the model, which indicate face validity of the model.

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Muamer Bezdrob and Aziz Šunje Table 3: Standardized factor loadings, average variance extracted, reliability estimates Ownership Structure ‐ X1

0.81*

Age ‐ X2

‐0.50*

Industry Dynamics ‐ X3

0.47*

Export Scope ‐ X4

‐0.88*

0.81*

0.90*

0.93*

0.49*

0.53*

0.84*

0.60*

0.64*

0.86*

0.76*

0.88*

0.84*

0.90*

0.62*

47.5%

77.7%

60.8%

62.5%

47.5%

0.77

0.91

0.72

0.87

0.84

Avg. Number of Employees ‐ X5 Average Equity ‐ X6 Average Fixed Assets ‐ X7 Managerial Expertise ‐ X8 Expert Foundation ‐ X9 Educational System ‐ X10 Employees Enablement ‐ X11 Process ‐ Y1 Strategy & Performance ‐ Y2 Customer & Information ‐ Y3 People & Structures ‐ Y4 Product Innovativeness ‐ Y5 Process Innovativeness ‐ Y6 Structural Innovativeness ‐ Y7 Average Variance Extracted (AVE) Construct Reliability (CR)

* ‐ significant at 0.001 3.2.3 Structural model The testing of structural model (Figure 2) consists of the structural model specification and the assessment of structural model validity. The model specification, which implies proposing hypotheses and establishing structural relationships, was described above. Structural model fitting is examined through the same goodness‐of‐fit indices as for the measurement model (Table 2), where all fit indices suggest that the structural model provides a rather good overall fit, too. The final step in structural model validation is the examination of structural path estimates (Table 4). It could be seen that all but one structural path estimates are statistically significant and in the predicted direction. The path between factors F2 and F4 is in the expected direction, but its t‐value is below the critical level for a Type I error of 0.05, hence it is not supported. On the other hand, given that four of the five estimates are in compliance with the proposed hypotheses, these results provide a strong support for the proposed theoretical model. The chi‐square difference between the structural and the measurement model is Δχ2 = 0.435 with one degree of freedom (p = 0.51). Insignificant chi‐square difference indicates that the model fit could not be improved by estimating another structural path.

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Muamer Bezdrob and Aziz Šunje

Figure 2: Structural model of organizational innovation Table 4: Structural path estimates Structural relationship F1 Æ F4 F2 Æ F4 F3 Æ F4 F4 Æ F5 F4 Æ F6

Unstandardized Parameter Estimate 0.299 0.095 0.218 0.751 0.646

Standard Error

t‐value

0.139 0.141 0.089 0.206 0.175

2.154 0.672 2.466 3.647 3.695

Standardized Parameter Estimate 0.345 + 0.109 0.571 + 0.785 * 0.524 *

* ‐ significant at 0.001; + ‐ significant at 0.05

3.3 Discussion The results obtained by testing the measurement model indicate a rather good fit between the theoretical model and real world represented with the data sample. The observed absolute and incremental goodness‐of‐ fit indices (Table 2) confirm that the model imposed covariance matrix (Σ) is similar to the data sample covariance matrix (S). Such an outcome from the first step of SEM analysis points to the overall empirical model validity, meaning that the measurement validity of all proposed constructs was fully confirmed. The second step of SEM analysis was the testing of the proposed hypotheses through the specified structural model (Figure 2). Once again, a good fit between a theoretical model and real world was found (Table 2). However, the most important part of structural model testing is model’s structural path analysis (Table 4). Structural paths represent proposed hypotheses and, as it could be seen from Table 4, all but one of them are statistically significant and in expected directions. Practically, this means that all but one proposed hypotheses are confirmed. Therefore, the following can be asserted:

The organizational propensity to innovation is predicted with the context in which the firm operates and with firm’s human resources capacity. However, the organizational size (strength) is not a significant predictor of the organizational propensity to innovation.

Management innovations and technical innovations represent significant constituents (defining elements) of organizational innovation.

Finally, the research findings suggest that the context in which the firm operates, and firm’s human potential, determine the firms that are apt for organizational innovation. At the same time, the size of the firm has no

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Muamer Bezdrob and Aziz Šunje significant impact on organizational innovative activities. In other words, the successful validation of the designed model provides important insights about how and which factors affect the firms’ readiness to introduce innovative systems, products, structures, processes and practices.

4. Conclusion This study aims to explore the main constituents of organizational innovation, as well as to explore the main factors which significantly affect firms’ innovation activities under the conditions of underdeveloped markets. Relying strongly on the existing knowledge base, efforts were focused on the design of a theoretical model of organizational innovation that could be used under the market conditions of the F B&H. The analysis has shown that the designed theoretical model is valid and applicable, and that hypotheses H1 and H3 are supported, while hypothesis H2 is not. Accordingly, it was found that context and human resources capacity significantly determine firm’s aptitude for organizational innovation. Simultaneously, it was found that management innovation and technical innovation are two main concepts which define organizational innovation. The main implication of the research is that the designed theoretical model of organizational innovations is fully applicable to market conditions in the F B&H. Moreover, the research provides yet another proof that all relevant theories and practices are applicable to the conditions of immature markets. This research and its results contribute to the body of knowledge related to organizational innovation by designing an applicable model with corresponding constructs and individual indicator items, i.e. by designing measurement scales and types that could be used in future research.

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Muamer Bezdrob and Aziz Šunje Garcia, R. and Calantone, R. (2002) "A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review", Journal of Product Innovation Management, Vol. 19, No. 2, pp. 110‐132. Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2009) Multivariate Data Analysis, 7th Edition, Prentice Hall, Upper Saddle River. Hamel, G. (2007) The Future of Management, Harvard Business School Press, Boston. Herring, S. and Galagan, P. (2011) “Why Innovation? Why Now?”, T+D, Vol. 65, No. 9, pp. 26‐28. Jöreskog, K.G. (2004) "Structural Equation Modeling with Ordinal Variables Using LISREL", [online] Scientific Software International, www.ssicentral.com/lisrel/techdocs/ordinal.pdf. Kimberly, J.R. and Evanisko, M.J. (1981) "Organizational Innovation: The Influence of Individual, Organizational and Contextual Factors on Hospital Adoption of Technologies and Administrative Innovations", Academy of Management Journal, Vol. 24, No. 4, pp. 689‐713. Lam, A. (2005). “Organizational innovation”. In Fagerberg, J., Mowery, D.C. and Nelson, R.R. (Eds), The Oxford Handbook of Innovation, Oxford University Press, Oxford, pp. 115–47. Mazzarol, T., Reboud, S. and Volery, T. (2010) "The Influence of Size, Age and Growth on Innovation Management in Small Firms", International Journal of Technology Management, Vol. 52, No. 1/2, pp. 98–117. Mol, M.J. and Birkinshaw, J. (2007) Giant Steps in Management: Innovations That Change the Way You Work, Financial Times/Prentice Hall, Harlow. Mol, M.J. and Birkinshaw, J. (2009) "The Sources of Management Innovation: When Firms Introduce New Management Practices", Journal of Business Research, Vol. 62, Issue 12, pp. 1269‐1280. Østergaard, C.R., Timmermans, B. and Kristinsson, K. (2011) "Does a Different View Create Something New? The Effect of Employee Diversity on Innovation", Research Policy, Vol. 40, No. 3, pp. 500‐509. Rank, J., Nelson, N.E., Allen, T.D. and Xu, X. (2009) "Leadership predictors of innovation and task performance: Subordinates' self‐esteem and self‐presentation as moderators", Journal of Occupational & Organizational Psychology, Vol. 82, No. 3, pp. 465‐489. th Samuelson, P.A. and Nordhaus, W.D. (1995) Economics, 15 Edition, McGraw‐Hill, New York. Schumpeter, J.A. (1939) Business Cycles: A theoretical, historical and statistical analysis of the Capitalist process, McGraw‐ Hill, New York. Shipton, H., West, M.A., Dawson, J., Birdi, K. and Patterson, M. (2006) "HRM as a Predictor of Innovation", Human Resource Management Journal, Vol. 16, No. 1, pp. 3‐27. Smith, M., Busi, M., Sall, P. and van der Meer, R. (2008) "Factors Influencing an Organisation’s Ability to Manage Innovation: A Structured Literature Review and Conceptual Model", International Journal of Innovation Management, Vol. 12, No. 4, pp. 655–676. Stock, R.M. and Zacharias, N.A. (2011) "Patterns and Performance Outcomes of Innovation Orientation", Journal of the Academy of Marketing Science, Vol. 39, No. 6, pp. 870‐888. Taggar, S. (2002) "Individual Creativity and Group Ability to Utilize Individual Creative Resources: A Multilevel Model", Academy of Management Journal, Vol. 45, No. 2, pp. 315‐330.

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How Organizational Creativity Influence Firm’s Profitability: The Moderating Role of Corporate Entrepreneurship Katarzyna Bratnicka, Bartłomiej Gabryś and Mariusz Bratnicki University of Economics in Katowice, Poland kbratnicka@gmail.com bargab@ue.katowice.pl mabrat@ue.katowice.pl Abstract: This paper applies a corporate entrepreneurship research to explore boundary conditions for traditional assumption of the creativity literature, the notion that increase in novel and useful idea generation will increase the likelihood of firm profitability. Based on the assumption that organizational creativity is two‐dimensional construct (which are novelty and usefulness) We attempt to answer the following research question: What is the strategic role of creativity in entrepreneurial organizations when firm’s profitability is considered? Keywords: organizational creativity, corporate entrepreneurship, firm profitability

1. Introduction: Despite the central role of creativity as the basis of competitive advantage and a primary source of firm profitability, our understanding of organizational creativity representing a strategic asset remains limited. Unfortunately, little is known about the strategic role of creativity in entrepreneurial organizations within dynamic, hostile, and complex environment and performance of small – to medium ‐ sized enterprises. The interaction between organizational creativity, as a firm level variable and corporate entrepreneurship in which the firm operates has not been investigated, to the best of ours knowledge. Starting with organizational creativity as dynamic capability, we summarize our study into a preliminary substantive theory of the creativity in organization and discuss dominant in the literature relationships between organizational creativity, firm profitability and corporate entrepreneurship. Proposed conceptual model outlines the development of high performance via organizational creativity with moderating role played by corporate entrepreneurship. Additionally, the model provides the sound foundation for uncovering environmental conditions of creativity in entrepreneurial organizations.

2. Theoretical framework: creativity, corporate entrepreneurship and profitability Organizational theory on creativity has been extensively developed in recent years, but no current comprehensive model explains the organizational creativity in strategic context. The critical review of different theoretical lenses used to analyze creativity in organizations show two dominant paths (James and Drown 2012). On the one hand, there are research describing the nature of creativity – performance relationship, which are oriented on identifying mediating and moderating variables and aimed at building a broad theoretical background. On the other hand, there is a whole range of empirical studies testing fragmental theoretical models. Drawing primarily from the path breaking works we develop conceptual model making organizational creativity the basis of a dynamic theory of the high – performance organization and building research agenda. Figure 1 outlines the three main constructs: organizational creativity, corporate entrepreneurship and firm profitability. This framework suggests that firm profitability derives from certain level of entrepreneurial behavior, which in turns depends on the level of organizational creativity. In conclusion, Figure 1 portrays the organizational configurations, including various elements, which leads to fundamentally different conception of organizational creativity which are commonly found in literature on creativity theory and practice.

2.1 Creativity as multidimensional construct Several significant studies have shaped the construct of creativity. Recently, creativity is defined as “the production of high quality, original, and elegant solutions to problems” (Mumford et al. 2012: 4). Woodman, Sawyer and Griffin define organizational creativity “as the creation of valuable, useful new product, service, idea, procedure, or process by individuals working together in complex social systems” (1993: 293). Guided by Harrington’s (1990) framework, Liu, Bai and Zhang (2011) point out that definition of organizational creativity

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki includes four components: creative environmental establishment, creative output generation, member’s creative participation, organization’s creative integration. In this vein, Sminia (2011) describes creative dynamic capability as consisting of firm’s potential to initiate and create frame breaking change.

H1 Firm profitability

Organizational Creativity • Novelty • Usefulness Corporate Entrepreneurship • Corporate Venturing • Strategic entrepreneurship

Source: Own preparation Figure 1: The moderating role of corporate entrepreneurship on firm profitability Barreto (2010) suggests a conceptualization of dynamic capability as consisting of firm’s potential to systematically solve problems based on propensity to sense opportunities and threats, making timely and market‐oriented decisions, and changing its resource base. These insights from dynamic capabilities theory opens up a way towards a processual understanding of organizational creativity. That is dynamic capabilities, which explicitly rest on the ability to repeatedly creative solutions to business problems. In consequence, we suggest the following definition of organizational creativity: Organizational creativity is the firm’s ability to generate new and useful ideas to address rapidly changing opportunities and threats by making timely and market‐oriented decisions, and to frame breaking changes in` its resource base. Most operationalizations of creativity treat creativity as a unitary construct (Kozbelt, Beghetto, & Runco 2010).Creativity is often measured as a combination of novelty and usefulness melted into a single scale. Interestingly, it is increasingly recognized that creative solutions require both the generation of alternatives and the selection of which alternative to pursue. Sue‐Chan & Hempel (2010) developed a new operationalization of creativity based on treatment of novelty and usefulness as two separate dimensions. Similarly, Choi (2004) and Juillerat (2011) maintained that there are differences in both antecedents to, and consequences of, novelty and usefulness. Moreover, the different dimensions of creativity are likely to be differentially influenced by individual’s task and organizational elements. Hence, we consider the novelty and usefulness as two distinct dimensions of organizational creativity. In sum, if organization lacks the resources to implement the idea, its profitability would be unaffected by novelty. In somewhat different tone, organization may be highly skilled at implementing novel ideas, but if it has nothing to implement, its profitability would be unaffected.

2.2 Creativity and profitability The most important relationship in organizational creativity field is perhaps the one between creativity and profitability. Researchers have shown confidence in the compulsory and direct link between organizational creativity, profitability and growth. Creativity is crucial for organizational innovation and survival (Augsdorfer et al. 2012). At the level of organization, creativity is essential factor for high profitability (Wang and Cheng 2010), reconciling management paradoxes (Low and Purser 2011) and for developing new behaviours in surprising situations (Bechky and Ockhuysen 2011). Contrary, established bases of evidence from several researches also seem to counter the notion that creativity will seamlessly increase performance (Litchfiled 2008). Nevertheless, despite widespread beliefs in its benefits there have been relatively few empirical examination of its consequences in an organizational setting (Gong et al. 2009). Thus, according to earlier suggestions (Poon et al. 2006), and recent findings (Simsek and Heavey 2011), the foregoing arguments suggest the following: organizational creativity is associated with higher level of firm’s profitability.

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki

2.3 Organizational creativity and corporate entrepreneurship Creativity and entrepreneurship are independent constructs, but they also have complementary qualities (Henry and LeBruin 2011; Hitt and Ireland 2011). In fact, creativity is characteristic or capability of entrepreneurs and their activities (Cesinger et al. 2010; Ogilvy 2011), more specifically socio‐cognitive networks (Belussi and Staber 2011) and, perhaps most importantly, in the production of entrepreneurial opportunity (Alvarez et al. 2011; Hansen et al. 2011; Venkatraman et al. 2012). Along the similarity lines Perry‐ Smith and Coff (2011) stated the role of generating and selecting entrepreneurial ideas in the developments of new ventures and argue that entrepreneurial creativity is the capacity to identify novel and useful solutions to problems in the form of new products and services. Simply being creative is not sufficient. Rather it is the firm’s ability to take entrepreneurial action that may determine the extent to which creativity impacts firm performance.

2.4 Corporate entrepreneurship and profitability The notion that corporate entrepreneurship increase the level of organization profitability which lead to higher rate of growth has been added to the growing body of research on entrepreneurial orientation vein (Rauch et al. 2009; Zahra et al. 1999). This is true, but only to a limited extent, because it may also be that entrepreneurial orientation is only predisposition to different corporate entrepreneurship activities (Dess and Lumpkin, 2005; Miller 2011; Short et al. 2009). Entrepreneurial orientation is the key construct in the entrepreneurship literature (George 2011). The point is that the profitability almost certainly arises as function of the corporate venturing (bringing new business to corporation through internal corporate venturing, cooperative corporate venturing, and external corporate venturing) and strategic entrepreneurship (innovating in the pursuit of competitive advantage manifested in firm’s strategy, product offerings, served markets, internal organization, and business model) as various forms that corporate entrepreneurship can take (Morris et al. 2011).These arguments suggest that organization with higher level of corporate entrepreneurship are more likely to be effective achieving higher rate of profitability. It leads us to propose, that organizational creativity has a positive direct relationship with firm profitability through moderating role of the corporate entrepreneurship. This led us to: Hypothesis 1: The relation between organizational creativity and firm profitability is moderated by corporate entrepreneurship

2.5 The role of organizational environment Although most research within the organizational creativity field has not paid due attention to bounding assumptions, one ongoing debate regarding boundaries of this perspective bear mentioning – this related to environmental conditions. In this vein, Ford (1996) summarise evidence that institutional environment plays an important role in shaping creative activities. Manimala (2009) argue that both general and task environment are important to entrepreneurship, and they are, in fact, in interaction with entrepreneurial individuals. A careful review of entrepreneurship literature suggests that a dynamic context fosters the relationship between entrepreneurial orientation and performance (Frank and Kessler, 2010). Similarly, Baron and Tang (2011) observed encouraging moderating role of environmental dynamism in creativity‐firm innovation relationship. Uncertainty of environment promotes speed of strategic change, and in consequence strategic performance, where intense competition exerts more pressure on the firm, hence a variety of interactions (capability, entrepreneurial orientation and market conditions) are associated with small firm growth (Chaston and Sadler‐Smith 2012). Under intense market conditions firms with low entrepreneurial orientation and low capability show lowest growth rate, whereas firms with high entrepreneurial orientation and high capability show highest levels of growth. Additionally, the level of environmental complexity is likely to affects the proactive strategic efforts (Oliver & Holzinger 2008) The degree to which hostility is present in environment is positively associated with entrepreneurial behaviours (Ding, Malleret and Vekamuri 2009), and in interaction with technological sophistication positively influencing entrepreneurial processes and behaviours (Kreiser et al. 2011). Further, interaction of hostility and turbulence increases the positive effect of entrepreneurship strategy on performance (Wiklund and Shepherd 2005).

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3. The sample and measures To test ours hypothesis, a field study of small and medium firms using mailed questionnaires were conducted in 2011. To obtain details for 250 firms we used database from Regional Chamber of Commerce and Industry in Katowice. All firms were operating in Upper Silesia region, situated in the mid‐south of Poland. We decided to focus only on small and medium sized firms (up to 249 employees – with regard to EU definition). To collect a data we used postal survey, which gives us responses from 158 firms (representing a response rate at 63,2% level). Unless otherwise indicated, all questionnaire items used a Likert‐type response scale anchored at 1 “strongly disagree” and 7 “strongly agree”. The current study uses three variables to account for exigencies that may influence the research model and to control the interpretational confounds. These variables are firm age, firm size and industry. To measure organizational creativity we selected a new twelve‐item operationalization of individual creativity which measured novelty and usefulness as two separate dimensions (Sue‐Chan and Hempel, 2010). Next, it was adopted for organization‐level. In addition, we examined the two of the new studies that have sought to establish construct validity at an organizational level measure of organizational creativity, that is four‐item scale developed by Weinzimmer, Michel and Franczak (2011) and seventeen‐item operationalization by Liu, Bai and Zhang (2011) which categorized the organizational creativity in Chinese context, along four dimensions: creative environment establishment, creative output generation, members’ creative participation, organization’s creative integration. To measure corporate entrepreneurship, we asked managers to indicate the extent to which their firm used corporate venturing and/or strategic entrepreneurship. More specifically, corporate venturing was measured using a three‐item scale, which aggregates internal corporate venturing, cooperative corporate venturing and external corporate. Strategic entrepreneurship was measured using a five‐item scale, which aggregates strategic renewal, sustained regeneration, domain redefinition, organizational rejuvenation and business model reconstruction. We measure firm performance by asking respondents to compare the development of their own firm over the past 3 years relative to that of other important competitors, using ten‐item scale. It was based on the multi‐ item measure of firm performance on survey scales that have been developed and validated in prior research: Gupta and Govindarajan (1986): growth in sales, growth in market share, profit to sales ratio (ROS), return on total asses (ROA), cash flow from operations (OCF), operating profit (EBIT), return of investment (ROI); Wiklund and Shepherd (2003) :growth in the number of employees and customer satisfaction; Gupta and Govindarajan (1986): R&D activities, new product development; and Wiklund and Shepherd (2003) product/service innovation, process innovation, adoption of new technology. Comparing the conceptualizations offered by prior research suggests three widely recognized dimensions of firm performance and key indicators of each were formulated: growth, profitability, and innovativeness. To capture firm performance and ensure comparability with a maximum amount of existing creativity and entrepreneurship studies we decided to use two established dimensions: growth (average annual growth in number of employees in the last three years and the average annual growth in sales in last three years) and profitability (return on sales (ROS), and return on assets (ROA) in the last year) as suggested by (Shea, De Cieri and Sheehan, 2010). The last objective performance variable concerns the commercialization of innovation. It measures the proportion of total annual sales in the past financial year that was from new, or significantly improved, products or services. To conduct organization‐level analyses, above mentioned measures were aggregated to create a score for firm performance. For the purpose of this paper we use only profitability indicators leaving growth and commercialization of innovation to be calculated in our forthcoming another article.

4. Research results To obtain reliable and valuable results we were following rigorous statistical procedure with regards to both methodological and procedural issues. First we calculated correlation between variables: creativity (aggregated – [TO] and for its two dimensions novelty [TO_N] and usefulness [TO_U] separately), and meta‐ variables: corporate entrepreneurship [FPO] and firm profitability [EO] (return on sales (ROS), and return on assets (ROA) in the last year). Results are presented in Table 1. As Table 1 suggest there exist relatively high level of correlation between variables, specially between TO and FPO (0,79) which might means that this two phenomena are very close in understanding by our respondents or

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki they do not see this phenomena as separate one. Next step in our statistical procedure was looking for moderating role played by Corporate Entrepreneurship between Creativity and Firm Profitability. Three Models were calculated with regards to statistical procedure (see Table 2). Table 1: Correlation analysis for Creativity, Corporate Entrepreneurship and Firm Profitability TO_N

TO_U

FPO

TO_N 1,000

0,726

0,954

0,792

0,141

N=158 N=158 N=158 N=158 N=157

p= ‐‐‐ p=0,00 p=0,00 p=0,00 p=,078

TO_U 0,726

1,000

0,899

0,657

0,218

N=158 N=158 N=158 N=158 N=157

p=0,00

p= ‐‐‐ p=0,00 p=0,00 p=,006

0,954

0,899

1,000

0,792

0,185

N=158 N=158 N=158 N=158 N=157

p=0,00 p=0,00

p= ‐‐‐ p=0,00 p=,021

0,792

FPO

0,657

1,000

0,154

N=158 N=158 N=158 N=158 N=157

p=0,00 p=0,00 p=0,00

p= ‐‐‐ p=,054

0,141

0,154

0,218

0,185

1,000

N=157 N=157 N=157 N=157 N=157

p=,078 p=,006 p=,021 p=,054

p= ‐‐‐

Where: TO_N – Creativity Novelty TO_U – Creativity Usefulness TO – Creativity aggregated FPO – Corporate Entrepreneurship EO ‐ Firm Profitability Source: Own preparation Table 2: Moderation analysis for influence of FPO on TO_N & TO_U and EO relation Model 1 Model 2 Model 3 Control Variables b p b p b p Age ‐0,067 0,459 ‐0,055 0,537 ‐0,071 0,438 Size 0,219 0,015 0,215 0,016 0,214 0,018 Industry 0,017 0,837 0,018 0,821 0,019 0,812 Variables TO_N

‐0,064

0,577

0,406

0,350

TO_U

0,259

0,023

‐0,020

0,956

Moderator

FPO

0,204

0,667

Interaction

TO_N*FPO

‐1,112

0,237

TO_U*FPO

0,716

0,420

0,040

0,087

0,096

R2 adjusted

0,021

0,057

0,047

158

Source: Own preparation

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki As Table 2 suggest interaction between TO_N and FPO as well as between TO_U and FPO is not statistically important, so there is no moderation effect of Corporate Entrepreneurship between Creativity treated separately (Novelty and Usefulness) and Firm Profitability. Our next calculation considers Creativity as aggregated variable (see Table 3). Table 3: Moderation analysis for influence of FPO on TO and EO relation Model 1 Model 2 Model 3 Control Variables b p b p b p Age ‐0,067 0,459 ‐0,049 0,585 ‐0,052 0,566 Size 0,219 0,015 0,203 0,023 0,207 0,023 Industry 0,017 0,837 0,017 0,833 0,013 0,877 Variables TO

0,173

0,229

0,306

0,282

Moderator

FPO

0,183

0,698

Interaction

TO*FPO

‐0,307

0,649

0,040

0,070

0,071

R2 adjusted

0,021

0,045

0,034

158

Source: Own preparation As Table 3 suggest interaction between TO and FPO is not statistically important, so there is no moderation effect of Corporate Entrepreneurship between aggregated Creativity and Firm Profitability. Due to lack of moderation effect in the next step we were trying to find out which model (scheme) is more appropriate for relation between Creativity, Corporate Entrepreneurship and Firm Profitability. First scheme (A) represents situation when both, Creativity (two dimensional: Novelty and Usefulness separately) and Corporate Entrepreneurship, interact each other and as an effect of this interaction they influence Firm Profitability: FPOO Scheme A: EO TO Scheme B represents situation when we consider only influence of Creativity (two dimensional: Novelty and Usefulness separately) on Firm Profitability: Scheme B: TO EO The last scheme (C) presents a situation when we consider only influence of Corporate Entrepreneurship on Firm Profitability: Scheme C: FPO EO Statistical analysis of these three schemes is presented in Tables 4,5 and 6. Comparison of these three schemes, we took for that Adjusted R2 because of different number of explaining variables, suggest that the best model is represented by Scheme B – so direct influence of Creativity on Firm Profitability has the highest explanation potential. Second best is A and than C.

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki Table 4: Scheme B influence of TO_N & TO_U on EO

Value

0,219

0,048

Adjusted R2

0,036

F(1,156)

3,891

0,022

Estimated standard deviation

0,202 D(a) t(a)

Constant

0,567

0,069

TO_N

‐0,006

0,018 ‐0,319 0,750

TO_U

0,047

0,022

8,224 2,138

p 0,000 0,034

Source: Own preparation Table 5: Scheme C influence of FPO on EO

Value

0,154

0,024

Adjusted R2

0,017

F(1,156)

3,754

0,054

Estimated standard deviation

0,204 D(a) t(a)

Constant

0,657

0,051 12,819 0,000

FPO

0,025

0,013

1,938

0,054

Source: Own preparation Table 6: Scheme A influence of TO_N, TO_U and FPO on EO

Value

0,220

0,049

Adjusted R2

0,036

F(1,156)

3,933

0,022

Estimated standard deviation

0,202 D(a) t(a)

Constant

0,664

0,036 18,286 0,000

TO_N*FPO

‐0,008

0,005

‐1,414

0,159

TO_U*FPO

0,012

0,006

2,090

0,038

Source: Own preparation We followed exactly the same procedure for aggregated Creativity (Tables 7,8 and 9) receiving exactly the same results, where highest potential of changes in Firm Profitability is represented by Scheme B – direct influence of Creativity on Firm Profitability, Second best is A and than C.

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki Table 7: Scheme B influence of TO on EO

Value

0,185

0,034

Adjusted R2

0,028

F(1,156)

5,480

0,021

Estimated standard deviation

0,202 D(a) t(a)

CONSTANT

0,608

0,064 9,542 0,000

0,034

0,014 2,341 0,021

Source: Own preparation Table 8: Scheme C influence of FPO on EO

Value

0,154

0,024

Adjusted R2

0,017

F(1,156)

3,754

0,054

Estimated standard deviation

0,204 D(a) t(a)

Constant

0,657

0,051 12,819 0,000

FPO

0,025

0,013

1,938

0,054

Source: Own preparation Table 9: Scheme A influence of TO and FPO on EO

Value

0,168

0,028

Adjusted R2

0,022

F(1,156)

4,495

0,036

Estimated standard deviation

0,203 D(a) t(a)

Constant

0,689

0,034 20,292 0,000

TO*FPO

0,004

0,002

2,120

0,036

Source: Own preparation Obtained results allowed us to reject Hypothesis 1. that the relation between organizational creativity and firm profitability is moderated by corporate entrepreneurship. When explanation of Firm Profitability is considered one should take Creativity separately as analysis of Schemes A,B and C proved.

5. Discussion and conclusions For research purpose, this study addresses the various theoretical challenges that await those seeking to apply strategic management and corporate entrepreneurship theory to the nascent field of organizational creativity. Our efforts contribute to the literature in the following ways. First, and foremost, the present research examined assumption within the creativity literature by proposing boundary conditions in which organizational creativity might positively impact firm profitability. The research extends organizational creativity theory by

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Katarzyna Bratnicka, Bartłomiej J.Gabryś and Mariusz Bratnicki exploring the moderating role of corporate entrepreneurship which occur to be more probably a mediator or influencing firm profitability separately than as a moderator. Second, the insights developed here advance creativity literature by operationalizing organizational creativity as dynamic capability. Our general idea is to build a strategic management organization theory concept of creativity referring to whole organization, not forgetting about individuals as a source of creativity, which is the main focus of psychology, and where the traditional reference of creativity comes from. In these sense our perspective is more comprehensive than approaches used in prior studies mostly carried out from psychological and social viewpoint, while the lenses of strategic management and corporate entrepreneurship were largely ignored. For practitioners, this paper has a very clear message: organizational creativity matters as well as corporate entrepreneurship but probably this relation is more based on mediation than on moderation. A major implications of this discussion that is helpful to characterize organizational creativity in terms of dynamic relationship with corporate entrepreneurship and profitability. This family of concepts are related to significant issues required for success: defying the scope activities through the lenses of novelty and usefulness of ideas, using corporate entrepreneurship to strengthen the process of organizational creativity, activating the forces of firm profitability by creative and entrepreneurial means, joining organization profitability with evolutionary and revolutionary changes in environment, and finally overcoming inertia from the success earned so far. The concepts of organizational creativity and corporate entrepreneurship are quite broad and involve multiple dimensions. The current study crossing these two domains only selects a representative set of the categories for characterizing each of the domains. Nevertheless, the study is quite comprehensive in that, that it is one of only a handful to simultaneously include measures of the organizational creativity and corporate entrepreneurship related to firm profitability. Nonetheless, additional work is needed to understand how such configurations influence organizations strategic efforts.

Acknowledgements We gratefully acknowledge the research support from the National Science Centre (grant number 2011/01/B/HS4/01075)

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Innovation and Entrepreneurship Assessment Initiatives: A Critical View Cagri Bulut, Eda Evla Mutlu and Murat Nazli Yasar University, Izmir, Turkey cagri.bulut@yasar.edu.tr evla.mutlu@yasar.edu.tr nazli.murat@gmail.com Abstract: Entrepreneurship and Innovation related regional and national development has become a phenomenon for the last decades; however the outcomes of these endeavors have attracted many researchers, agencies and international organisations such as European Commission, Global Entrepreneurship Monitor etc. through their projects, programs, departments or initiatives. Therefore, this study examines the worldwide known six Innovation and Entrepreneurship Initiatives (here after IEIs) assessing of entrepreneurship and innovation. The main IEIs are (IUS) Innovation Union Scoreboard, GEM (Global Entrepreneurship Monitor), GII (Global Innovation Index), and ICI (Innovation Capacity Index), GEINDEX (Global Entrepreneurship Index) and WCY (World Competitiveness Yearbook). This research includes the observation of some commonly used IEIs in terms of sample size, the quality (research and development, technology, creative output, expenditure on research and development, level of research whether it is firm, country or employer entrepreneur level etc.) and the quantity of indices, measurement method, survey frequency and some other specifications. Indices are compared with each other to expose both the similarities and the differences; however there is still a big gap on the comparison of state and degree of entrepreneurship and innovation in nations. Although there are some obstacles in the measurement of IEIs, they present a broader point of view to the researchers and practitioners. As a result of the diversity in measurement methods, sampling sizes, indicators etc., there is not a single method for evaluating these indicators which makes it difficult to make a comparison. As a result, for the proper establishment of IEIs, standardization of the initiatives should be considered. This research sheds a light for further scientific debates in this field of study. Keywords: entrepreneurship, innovation, index indicators, measurement method

1. Introduction The identification of innovation indicators and the comparison of developing economies and the other countries is important for the countries to built their strategies (Wonglimpiyarat 2010). In this sense, to analyze the competitiveness of the firms, countries or international organisations, measurement methods of innovation and entrepreneurship are needed. There are various definitions of entrepreneurship and innovation in literature. Acs and Szerb (2009, pp.17) defined entrepreneurship as a dynamic interaction of entrepreneurial attitudes, entrepreneurial activity and entrepreneurial aspiration that vary across the stages of economic development and according to Oslo Manual, innovation is the implementation of a new or significantly improved product (good or service) or process, a new marketing method or a new organisational method in business practices, workplace organisation or external relations (OECD‐Eurostat 2005, pp. 46). Innovation and Entrepreneurship related regional and national development has become an important issue in the last decades. Some governmental and non governmental initiatives are interested in the measurement of these issues, as a fact, there are various indices operated by various initiatives. We observed the specifications of indices to expose the main differences in inputs and outputs. This research includes the observation of some commonly used IEIs in terms of sampling method, the quality and the quantity of indicators (research and development, formation of new technology, scientific and creative output, expenditure on research and development, level of research whether it is firm, country or employer entrepreneur level etc.), measurement method, survey frequency and some other specifications. The main IEIs are IUS (Innovation Union Scoreboard), GEM (Global Entrepreneurship Monitor), GII (Global Innovation Index), ICI (Innovation Capacity Index), GEINDEX (Global Entrepreneurship Index) and WCY (World Competitiveness Yearbook). In this manner, indices will be compared to each other to expose both the similarities and the differences, and advantages and disadvantages. There is a brief explanation of each initiative about the

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli measurement methods, indicators and sampling level of analysis. These data mainly extracted from the reports on websites, where availability came into prominence, are also evaluated. Results demonstrate the evaluation of IEIs in terms of their practices and scopes. Research results conclude with suggestions and a new research agenda for both researchers and practitioners in terms of questioning the diversity of measurement methods, indicators and the obstacles in comparison. The research will shed a light for further scientific debates in this field of study.

2. Literature review In this complex and changing world, innovation and entrepreneurship are occupying an essential role for economic development. Although since the late 1880s there have been reports of the use of the term “innovation” to mean something unusual, none of first precursors of innovation have been as influential as Joseph Alois Schumpeter. The research of entrepreneurship and innovation owes much to Schumpeter’s contributions. He identified innovation as the critical dimension of economic growth and the “entrepreneur” is the central innovator (Sledzik 2013). Along with this influence, for instance, the European Union's innovation program, and its main development plan, the Lisbon Strategy, are influenced by Schumpeter. From a Schumpeterian angle, indicators concerning the framework conditions of development will have an effect on the index regulatory quality (Hanush and Pyka 2007).

Due to these effects, the methods that are used in the measurement of innovation have been changed in the course of time. When this period of time is researched, the approach to the measurement of innovation can be divided into four phases (Stone et al. 2008): In the first phase, between 1950 and 60’s, the main focus was on inputs in innovation measurement. These inputs were research and development, capital and intensity of technology. In the second phase, between 1970 and 80’s, as a result of the science and technology activities, the focus was on main outputs such as patent, publications, products and transformation of quality. In 1990s, the focus was on the results of survey research. This phase contains the comparison of innovation capacities, indices and surveys. In 2000s, the last phase, process indicators come into prominence. These are information, intangible resources, network structure, demands, management techniques, return of risk and system dynamics.

In the measurement of innovation and entrepreneurship, Marcotte (2013) compares entrepreneurship indices and implies the lack of the conceptual clarification and a single measurement. Besides, some researchers focused on the tangible and intangible resources. For instance, Stone et al. (2008) categorized information and communication technologies, infrastructure, production material, equipment and facility as tangibles; patent, databases, progress of research and development, organizational processes, knowledge and skill of workforce as intangibles. However, some programmes focus on the “soft side” of the innovation process such as awareness, information and consulting programmes and demand the use of intensive case studies and user‐ surveys (Papaconstantinou and Polt 1997, pp.10).

The level of analysis in the measurement of innovation and entrepreneurship was analyzed and divided into three parts as firm, regional and national level. There are different measurement tools in the firm‐level process in different resources. At the core of the literature on regional innovation is the concept of ‘innovative milieu’. It was discussed by Camagni et al (1997) which is a complex network of informal social relationships within a limited geographical area which enhance the local innovative capacity through synergetic and collective learning processes. The research made in the national‐level innovation basically focuses on the interactive collection of institutions that support the innovative activities within a country (Neely and Hii 1998).

However, the evaluations ought to be more “user‐oriented”, that is to address the informational needs of the policy makers, firms and programme administrators on various levels. Therefore they should encompass an appropriate mix of methods to produce these different types of information (Papaconstantinou and Polt 1997).

As it was mentioned by Georghiou and Roessner (2000), the evaluation work has had less of an impact in the literature that it deserves because much of the most detailed and valuable work is not easily obtainable. This

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli situation actually encourages the researchers, agencies and international organizations to make a positive impact in the literature.

3. Methodology The innovation and entrepreneurship data in the initiatives have been reached from several websites of the organisations, organisational reports, manuals, regional sources and feedback from organisations. The initiatives are compared to each other in a detailed way, the similarities and the differences among each initiative are analyzed. Basically, the publishing organisations, sample size, researched countries, main indicators (R&D expenditure, human resource infrastructure etc.) or sub‐criterias, their measurement methods (surveys etc.), level of research (firm level or country level etc.) and what type of index they are (innovation or entrepreneurship index), are meticulously researched for the purpose of a unique comparison of the worldwide known IEIs. The collected data for the six indices present significant information for the researchers, international organisations and future scientific studies. Indices/Initiatives are below:

IUS / European Commission (EC)

GII / INSEAD‐WIPO

ICI / Lopaz‐Claros & Mata

WCY / International Institute for Management Development (IMD)

GEM / GEM

GEINDEX / Acs & Szerb

Besides, the trends of these indices are evaluated in order to support our comparison. Among the databases, Scopus is preferred to catch the attention of the scientific researchers to specific indices. Trend of every index is searched in all fields (source title, article title, keywords, affiliation etc.) via Scopus analytic result tool. Google Trends is also used to illuminate the google search trend of these indices.

4. Innovation and entrepreneurship initiatives Six initiatives are presented respectively in this research and the detailed evaluation and comparison of these initiatives are as follows:

4.1 Innovation union scoreboard Innovation Union Scoreboard (IUS) 2013 includes a specific ranking system, called European Innovation Monitoring System which is established by Community Research and Development Information Service with the collaboration of Eurostat. This system includes the innovation scoreboard of European Communities and some other countries. The countries are categorized among the category of (ranked from more innovative to less innovative); innovative leaders, innovation followers, moderate innovators and modest innovators. There are three main indicators such as enablers (human resources, open research system, finance and support), firm activities (investments, linkages, entrepreneurship, intellectual assets) and output (innovators, economic effects) and totally 25 indicators (EC 2013). IUS uses Statistical Office of European Communities’ (EUROSTAT) data (EC 2013), which is a department of European Commission. EUROSTAT’s task is to process and publish comparable statistical information within Europe and to define a common statistical language that embraces concepts, methods, structures and technical standards. Besides the countries in Europe, Eurostat considers the data of other countries such as USA, Japan, South Korea and Turkey. There is the principle of “apples have to be compared with apples – not with pears” (Eurostat 2012). Community Innovation Surveys are conducted every two years by Eurostat to collect data from product (goods and services) and process (organisational and marketing) innovation (Eurostat 2013a). The survey is based on Oslo Manual (Eurostat 2010). CIS includes six indicators which are: SMEs innovating in‐house, Innovative SMEs collaborating with others, Community designs per billion GDP, SMEs introducing product or process innovations, SMEs introducing marketing or organisational innovations, Sales of new‐to market and new‐to firm innovations as % of turnover (EC 2013).

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli OECD does research along with the 34 members. The researched components are; information resources, development of new products and processes, patent applications, licenses and staff education. OECD puts emphasis on the firm level analysis and has some key activities such as the relationship between innovation measurements and the macroeconomic performance, high quality and comparable data base, role of the public, multidisciplinary approaches in data collection, social goals and its effects (OECD 2010).

Unlike Eurostat, the OECD is not directly involved in carrying out any innovation surveys but it develops the overall measurement guidelines (Oslo Manual) which, countries then implement in specific surveys such as the CIS for Europe or other surveys in other countries. As a fact, published reports’ data come from Eurostat and the national sources which collect the primary data.

Europe 2020, defined as “the common indicator for next decade” by European Commission, has employment, innovation, education, social inclusion and climate/energy as main targets. The measurement is done through eight indicators and R&D is one of them. As a result of these evaluations, 2020 targets of Europe result in country specific recommendations for every European Commission member (Eurostat 2013b; Eurostat 2013).

According to science, technology and innovation reports of Eurostat (2011; 2012); analysis include 38 countries, where 27 of them is in European Community. R&D expenditure as of GDP, R&D intensity (expenditure as % of GDP), R&D personnel (headcount) as a percentage of persons employed, R&D expenditure in EUR million by sector of performance, enterprises with technological innovation (product, process, ongoing or abandoned), regardless of organisational or marketing innovation in Community Innovation Surveys, people were employed in Knowledge Intensive Activities (KIA), average annual growth rate of R&D full time personnel etc. is given, where 2011 and subsequent year data is not available.

There are other measurements carried out by EC, but not discussed in this research such as; Innobarometer which is held by Eurostat. It aims to explore the ways in which firms innovate, the effect of non‐R&D based innovation, outsourced or transferred innovation, innovation in public administration etc. (EC 2013a). In addition, Flash Eurobarometer surveys held by European Commission cover the development of entrepreneurship, how entrepreneurial mindsets are being fuelled and what encourages people to become entrepreneurs. To collect data, interviews are held with over 26.000 randomly selected respondents via fixed‐ line telephone (EC 2010).

4.2 Global innovation index The Global Innovation Index is published by INSEAD‐WIPO collaboration, which is formed in France in 2007. GII covers 141 economies which is 94.9 % of the world population. There are 84 indicators totally, which are separated into two groups as: input (Institutions, human capital and resource, infrastructure, market sophistication and business sophistication) and output (knowledge and technology outputs, creative outputs) sub‐indexes. These indicators are composed of: 62 quantitative data, 16 composite indicators and a survey (qualitative) data of 6 indicators (INSEAD‐WIPO 2012, pp.429).

As discussed by INSEAD‐WIPO (2012, pp.104), GII relies on some other institutions’ survey results such as Eurostat’s Community Innovation Survey, World Economic Forum’s Executive Opinion Survey, UNESCO Institute for Statistics’ Network of Science and Technology Indicators, National Science Foundation’s United States Business R&D and Innovation Survey (BRDIS).

According to the global innovation index ratings, the first five countries are Switzerland, Sweden and Singapore, Finland and United Kingdom respectively. Among the 141 country, some rankings of the countries according to their score are Mexico (79), Turkey (74), Greece (66), Brazil (58), Spain (29), Belgium (20), Germany (15) and Hong Kong (8) (INSEAD‐WIPO 2012).

In GII, there are several reports on innovation policy areas such as science and R&D, domestic market competition, high skill migration, information and communication technology, trade and foreign direct investment. The ranking of countries changes according to their situation and ranked in a scale of lower, lower‐mid, upper‐mid and upper level (Atkinson et al. 2012, pp.9).

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli For instance, in country ranks on science and R&D policy, lower‐mid tier countries are Turkey, Argentina, Belgium, Greece, Poland, Ireland and Romania among the scale of upper‐tier, upper‐mid tier, lower‐mid tier, lower tier. Some lower tier ones are Bulgaria, Mexico, Indonesia and Thailand. Some upper‐tier ones are Spain, France, Canada, Singapore and Denmark (Atkinson et al. 2012, pp.39).

4.3 Innovation capacity index ICI methodology is built by the inspiration of Porter (1990), who divides countries into three categories as factor‐driven, investment‐driven and innovation‐driven. Lopez underlines that countries should not be interpreted rigidly instead should be considered as steadily and gradually approaching from the factor‐driven to the innovation‐driven stage. For the first stage, ICI applies Porter’s level‐of‐development framework to high‐ income, upper‐middle and lower‐middle‐income and low‐income classification of World Bank. For the second stage, ICI also classifies the countries as political regime according to The Economist’s Democracy Index consisting of full democracies, flawed democracies, hybrid regimes and authoritarian regimes. As a result, countries are categorized as income levels and also as political regime, which creates 16 categories totally, though low income‐full democracy and low income‐flawed democracy categories are void (Lopaz ‐ Claros and Mata 2011). This differentiation can bring more realistic outcomes to the table in comparing the countries.

ICI measurement method is composed of 61 indicators in which five of them; institutional environment, human capital, training and social inclusion, regulatory and legal framework, R&D, adoption and use of information and communication technologies are the main indicators (Lopaz ‐ Claros and Mata 2011).

ICI is a measurement evaluated for 131 countries. In the ICI ranking report of 2010‐11, ICI clusters the countries according to their income level and political regime. Rankings are also evaluated according to institutional environment, good governance, R&D infrastructure, human capital, training and social inclusion, etc. Among the 131 country, some rankings are Brazil (81), Turkey (62), Romania (55), Poland (40), Italy (36), Belgium (23) and Japan (16). The top five is Sweden, Switzerland, Singapore, Finland and United States respectively (Lopaz ‐ Claros and Mata 2011).

As far as ICI does not conduct survey, data sources are; International Telecommunication Union, The World Bank’s World Development Indicators (WDI), The World Bank/International Finance Corporation’s Doing Business Report (DBR), The United Nations Development Programme’s Human Development Report (HDR) and The World Economic Outlook (WEO) of IMF (Lopaz ‐ Claros and Mata 2011).

4.4 World competitiveness yearbook The Business School called International Institute for Management Development (IMD), developed the World Competitiveness Yearbook (WCY) and divides a firm’s competitiveness into four categories, which are; economic performance (domestic economy, international trade, international investment, employment, prices), government efficiency (public finance, fiscal policy, institutional framework, business legislation, societal framework), job efficiency (productivity, labor market, finance, management practices, attitudes and values) and infrastructure (basic, technological and scientific infrastructure, health and environment, education). Under these main titles, there are 329 indicators and 17 year time series (IMD 2012). Therefore, a multidimensional structure in dealing with the firm’s competitiveness exists.

An Executive Opinion Survey is conducted by IMD in order to complement the statistics that they use from international, national and regional sources. Statistical indicators are acquired from international, national and regional organizations, private institutions and their network of 54 Partner Institutes worldwide. The sample size is proportional to GDP of each country, a total of 4210 sample for 2012 (IMD 2012).

According to World Competitiveness Scoreboard 2012 report, economies are ranked from the most to the least competitive. Some countries are placed as Brazil (46), Portugal (41), Italy (40), Spain (39), Turkey (38), India (35), France (29), Japan (27), Belgium (25), United Kingdom (18) and Denmark (13) among 59 economies in terms of competitiveness level. First five competitive economies are Hong Kong, USA, Switzerland, Singapore and Sweden respectively (IMD 2012).

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4.5 Global entrepreneurship monitor Since 1999, GEM has been evaluating the individual attitudes, their entrepreneurial wants and entrepreneurial activities on a yearly basis and also GEM investigates the role of entrepreneurship, entrepreneurial activities of the countries and their characteristics due to their socio‐economic standing (GEM 2011).

There are two different but complementary surveys under application: Adult Population Survey (APS) and National Expert Survey (NES). APS measures the entrepreneurial activity, attitudes and aspirations of individuals and NES measures factors that impact national entrepreneurial activity, socio‐economic milieu of country such as; government policies, entrepreneurial education & training, entry regulation etc. While doing this research, GEM generally considers the innovation and entrepreneurial activities of small firms rather than the firms which are innovative, in a big industry and have high technology (GEM 2011).

APS is applied to at least 2000 people and NES is applied to at least 36 experts for each country. The data collection is via responsible national teams and each team is led by a local university or an academic institution (GEM n.d.).

Global reports are published every year through website and the economies are considered to be in three categories; factor‐driven, efficiency‐driven and innovation‐driven according to Porter (1990) such as ICI. The data can be viewed in the form of a graph or table as a benefit of the website. Through these indices; GEM has a variety of layout options, charts and tables are available on the website.

4.6 Global entrepreneurship index Geindex is developed by Zoltan Acs and Làszlò Szerb, consists of 31 variables; 17 of them from GEM, 14 as sub‐ criteria, 3 as side‐criteria and a super index which is an average of side criterias. Both the individual and corporate side of entrepreneurship is evaluated. A total of 65 country is compared for the purpose of clarifying the entrepreneurial attitudes, activities and intentions in international, individual and firm level. According to Acs and Szerb (2009, pp.16), although there are several indices for every issue, they rarely indicate how to improve their current position as GEINDEX does and it uses outside sources for data such as GEM; which means no survey is conducted.

Countries are ranked separately according to the entrepreneurial activities sub‐index, the entrepreneurial aspiration sub‐index and global entrepreneurship index. In the entrepreneurial activities sub‐index, some rankings are China (55), Romania (48), Turkey (42), Hong Kong (30), United Kingdom (24), France (17) and Belgium (10). Top five is Denmark, New Zealand, Ireland, Puerto Rico and Sweden respectively. In the entrepreneurial attitudes sub‐index, some rankings are Brazil (46), Turkey (44), Singapore (40), Belgium (33), France (22) and United States (12). Top five is New Zealand, Australia, Sweden, Denmark and Finland respectively. In the global entrepreneurship, some rankings are Turkey (40), China (39), Spain (30), Japan (25), United Kingdom (21), Hong Kong (18) and Belgium (12) among 64 countries. Top five ranking is Denmark, Sweden and New Zealand, United States and Australia respectively (Acs and Szerb 2009, pp.44).

However there are some deficiencies in the aspiration sub‐indices. It involves only a few aspects of business strategy, the quality of human resources, potential training, investment and operational efficiency and business culture (Acs and Szerb 2009, pp.19). The potential entrepreneurial activity of the established businesses is missing. Entrepreneurial attitudes sub‐index’s weakness is that it incorporates only a few factors relevant for measuring entrepreneurial attitudes (Acs and Szerb 2009, pp.18).

5. Findings As the indexes are briefly explained, the comparison table is composed according to sample size, quality and quantity of indicators, reseacrh level, method and subject.

As seen in figure 1 and 2, the trends of innovation indices are compared via google trends tool. WCY used to be the trendiest index since the middle of 2011’s. Though, for the last 12 years, the trends of WCY decreased, while GII increases (Figure 1). Also GEM has a greater trend with respect to GEINDEX (Figure 2).

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Innovation inputs; human resource and research, infrastructure systems, development of markets and business world, outputs are; scientific and creative outputs

Firm

Institutional environment, Human capital ‐ training and social inclusion, regulatory and legal framework, R&D, adoption and use of information and communication technologies

Country

Measurement of totally 61 (5 main) indicators, no survey conducted

4 main competitiveness factors divided into 20 sub‐ factors, factors are: economic performance, government efficiency, business efficiency, infrastructure

Individual and country

329 indicator (4 main factor), 20 sub‐factors; each have the same weight, 17 years time series, executive opinion surveys (every year) conducted

Entrepreneurial attitudes, entrepreneurial activity, entrepreneurial aspirations

Small scale firm, individual

20 indicators, 2 different surveys per year

Focusing on entrepreneurial attitudes, activities and intention

31 variable, 14 sub‐criteria, 3 side criteria and super index, no survey conducted

INSEAD & WIPO Lopaz‐Claros and Mata

59 country, sample size is proportional to GDP of each country, totally 4210 sample for 2012

GEM

85 country,at least 2000 individuals, 36 experts (for each country)

GEINDEX

Acs and Szerb

WCY

131 country, sampling depends on outsource

IMD

EU‐27 countries and others, sampling depends on outsource

3 main factors: Enablers (human resources, open research system, finance and support), Firm Activities (investments, Iinkages and entrepreneurship, intellectual assets), Output (innovators, economic effects)

65 country, sampling depends on outsource

Subject

Research Level Firm

141 country (94.9 % of world population), sampling depends on outsource

84 indicators: two groups as: input (Institutions, human capital and resource, infrastructure, market sophistication and business sophistication) and output (knowledge and technology outputs, creative outputs) sub‐indices

Individual and firm

Organisation

25 indicators, data from Eurostat (application of community innovation survey), OECD etc.

Main Indicators

GII

Method

Sample

ICI

IUS

Index Name

Table 1: Comparison of indices (I: innovation, E: entrepreneurship)

Among the databases, Scopus is chosen to catch the attention of scientific researchers to specific indices and the trend of every index is analyzed in all fields (source title, article title, keywords, affiliation etc.) by using Scopus analytic result tool. As seen in figure 3, GEM is referred more than GEINDEX. In the innovation indices, WCY attracts more attention than the other indices. The leadership of GEM (in entrepreneurship indices) and WCY (in innovation indices) is parallel with google trends results. All this data (via scopus and google trends) is gathered on 04.06.2013.

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WCY

IUS

GII

ICI

Figure 1: Trends of innovation indices via google trends. Color representation: Blue for IUS, red for GII, yellow for ICI and green for WCY. 100 represent the greatest search of all terms

GEM

GEINDEX

Figure 2: The trends of entrepreneurship indices via google trends. GEM trend is greater than GEINDEX where 100 represent the greatest search of all GEM and GEINDEX terms. As a fact, GEINDEX trend line is on x axis when compared to GEM

Figure 3: Trend of indices via Scopus

6. Conclusion During this research, a total of six IEIs have been evaluated with the purpose of stressing the differences and similarities among each initiative. As a result of the diversity in measurement methods, sampling sizes, indicators etc., there is not a single method for evaluating these indicators which makes it difficult to make a comparison, as it is clarified in the comparison table.

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli The measurement differences are mainly based on various indicators and surveys. The content of the applied surveys should be in conformity with the innovation framework and the prioritized items in the measurements. As far as the indices conduct a variety of surveys, the results of the analysis are not efficient for a comparison.

Innovation is a continuous process. Firms constantly make changes to products and processes and collect new data from several resources and it is much more difficult to measure a dynamic process than a static activity (OECD‐Eurostat 2005, pp.15). Besides, focusing on different groups in various indices ends up with different outcomes. For instance, while OECD ‐ Eurostat focus on employer enterprises excluding the teams and self‐ employed people, GEM focuses on small firms, individuals instead of firms which have high technology and are innovative. As (GEM 2012, pp.92) discussed, most importantly, individuals take place as an owner‐manager in various jobs and this, at least now, can not be tracked by using GEM data. To make some international comparisons and to determine the level of national innovation and entrepreneurship, databases should be kept up‐to‐update. For example, during the collection and publication of data and in research and development performance, delays exist. For this reason, every organisation wishes to make a prediction of presenting their science and technology programs and evaluating their policies (OECD 2002, pp.212). Eventually, the delays mentioned above will influence the analysis and also the decisions of the managerial level. For instance, while the data of 2006‐2010 was available in 2011 Eurostat Science and Technology Report, 2011’s data was not available in 2012 report (Eurostat 2012) but in 2013’s report (Eurostat 2013b).

To consider the obtained data by surveys, it is difficult to make an international comparison due to the changing situations of the countries and globalization. OECD states this difficulty as; the international comparison of the answers of the national surveys that provides the research and development data, is difficult. The national norms differ from international definitions or classifications. The perception of these norms, along with the national point of view, will create differences (OECD 2002, pp.25).

Innovation is divided into four categories in Oslo Manual. These are product, process, marketing and organisational innovation. Although product and process innovations are known in business environment, marketing and organisational innovation are known in some firms for some countries. Their definitions could not be determined as in the process and product innovation (Oslo Manual 2005, pp:46). For this reason, the reflection of these differences in definitions to the surveys and the probability of different perceptions in various regions should be considered as well. As discussed by OECD; science, technology and innovation (STI) surveys need to be redesigned to understand innovation in a better way (OECD 2010).

So far, there has been no acceptance of a dominant variable or an index to measure entrepreneurship across countries. In fact, some researchers are skeptical about the feasibility of constructing such an index and describe it as a “search for heffalump (Carland et al. 2001) or a holy grail (Hindle 2006)”. These researchers refer to the difficulty of constructing a definition and/or an index of entrepreneurship (Acs and Szerb 2009, pp.12).

In addition, there are some problems in the measurement of research data and development activity which is an element of innovation. Depending on the existing order in organisations and the traditions in doing research and in education, the comparison of science and technology indicators of other countries is very difficult (OECD 2002, pp.195). Despite the obstacles and complexity in measurements and lack of standardization, google trends and Scopus show briefly which indices are preferred but the reasons of why some indices are more preferred than the others should also be evaluated.

As a result, to provide a proper establishment of a point of view for the measurement of innovation and entrepreneurship and the understanding of what the items are inside this view, standardization of the initiatives should be considered.

References Acs J. Z. And Szerb L. (2009) The Global Entrepreneurship Index (Geindex). Jena Economic Research Paper, 028. Atkinson D. Robert, Ezell J. Stephen, Stewart A. Luke (2012) “The Global Innovation Policy Index”, [Online], Http://Www2.Itif.Org/2012‐Global‐Innovation‐Policy‐Index.Pdf

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Cagri Bulut, Eda Evla Mutlu and Murat Nazli Carland, J. W., Carland J. C. And Ensley M. D. (2001) Hunting The Heffalump: The Theoretical Basis And Dimensionality of the Carland entrepreneurship index, Academy of Management Journal, Vol 7, No.2, pp 51‐84. EC (2010) “Entrepreneurship in the EU and beyond: A survey in the EU, EFTA countries, Croatia, Turkey, the US, Japan, South Korea and China: A analytical Report”, [online], http://ec.europa.eu/public_opinion/flash/fl_283_en.pdf EC (2013) Innovation Union Scoreboard, Belgium. EC (2013a) Industrial Innovation: Innobarometer sheds light on innovation across Europe, [online], http://ec.europa.eu/enterprise/policies/innovation/facts‐figures‐analysis/innobarometer/ EUROSTAT (2010) Community Innovation Survey, [online], http://epp.eurostat.ec.europa.eu/portal/page/portal/microdata/cis EUROSTAT (2011) “Science, Technology and Innovation in Europe”; Publications Office of European Union, Luxembourg. EUROSTAT (2012) “Science, Technology and Innovation in Europe”, Publications Office of European Union, Luxembourg. EUROSTAT (2013) Europe 2020, [online], http://ec.europa.eu/europe2020/index_en.htm EUROSTAT (2013a) Innovation Statistics, [online], http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Innovation_statistics EUROSTAT (2013b) “Science, Technology and Innovation in Europe”, Publications Office of European Union, Luxembourg. GEM (2011) “Global Entrepreneurship Monitor – Key Indicators”, [online], http://www.gemconsortium.org/key‐indicators GEM (2012) “GEM Manual: A Report On The Design Data and Quality Control of the Global Entrepreneurship Monitor.”, [online], http://www.gemconsortium.org/docs/download/2375 GEM (n.d.), Data collection, [online], http://www.gemconsortium.org/Data‐Collection GEORGHIOU L. and ROESSNER D. (2000) Evaluating Technology Programs:Tools and Methods. Research Policy 29.4, pp.657‐678. Hanush H. And Pyka A. (2007) Appropriability, Proximity, Routines And Innovation ‐ Applying A Comprehensive Neo‐ Schumpeterian Approach To Europe And Its Lisbon Agenda, Conference Paper, Denmark. Hindle, K. (2006) A Measurement Framework For International Entrepreneurship Policy Research: From Impossible Index to Malleable Matrix. International Journal of Entrepreneurship and Small Business, Vol 3, No.2, pp 139‐182. IMD (2012) “World Competetiveness Index”, [online], www.imd.org INSEAD‐WIPO (2012) Global Innovation Index: Stronger Innovation Linkages for Global Growth, Fontainebleau. Lopaz ‐ Claros, A. And Mata, Y. (2011) The Innovation For Development Report 2010 ‐ 2011 Papers, [Online], Http://Www.Innovationfordevelopmentreport.Org/Ici.Html Marcotte, C. (2013) Measuring Entrepreneurship At The Country Level: A Review And Research Agenda, Entrepreneurship & Regional Development: An International Journal, 25:3‐4, Pp 174‐194. Neely, A., Ve Hii, J., (1998). Innovation And Business Performance: A Literature Review. Cambridge: The Judge Institute Of Management Strategies. OECD (2002) “Frascati Manual 2002: Proposed Standard Practice for Surveys on Research and Experimental Development, The Measurement of Scientific and Technological Activities, OECD Publishing. OECD (2010) Towards A Measurement Agenda for Innovation, OECD Publishing. OECD‐Eurostat (2005) “Oslo Manual: Guidelines For Collecting And Interpreting Innovation Data”, 3rd Edition. Papaconstantinou G. And Polt W. ( 1997 ) Policy Evaluation In Innovation And Technology: An Overview. Porter, M.E. (1990) “The Competitive Advantage Of Nations”. New York: Free Press Sledzik K. (2013) “Schumpeter’s View On Innovation And Entrepreneurship” , [Online], Http://Papers.Ssrn.Com/Sol3/Papers.Cfm?Abstract_Id=2257783 Stone, A., Rose, S., Lal, B., And Shipp, S. (2008) Measuring Innovation And Intangibles: A Business Perspective. Washington: Institute For Defense Analyses ‐ Science And Technology Institute. Wonglimpiyarat, J. (2010) Innovation Index And The Innovative Capacity Of Nations. Futures 42 , Pp 247 ‐ 253.

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Innovation Through Offset Agreements: An Empirical Study in the Brazilian Defence Industry Alex Carlos and Regina Leite University of Minho, Braga, Portugal lobo935@hotmail.com rleite@eeg.uminho.pt Abstract: Brazil, one of the BRICS countries (Brazil, Russia, India, China, and South Africa), is becoming one of the most important players in the global economy. Recognized as the leading economic power in the South American region, the country seeks a permanent seat in the United Nations Security Council. Nonetheless, to secure a place in this strategic UN organ and become a prominent player, Brazil needs to strengthen its economy and war power through updated military equipment. The Brazilian Government has put innovation on the political agenda and has been using the practice of offset contracts or agreements as a means to promote innovation and overcome the main insufficiencies of the defence sector. The present paper aims to explore the role of offset contracts in the innovation process in the context of Brazilian Defence Industry. Specifically, it intends to evaluate if the offsets performed between 2009 and 2011, the same time period used in other national surveys, are related to: i) the number of product and process innovation introduced; ii) the degree of autonomy in terms of innovation development; and iii) the degree of novelty of innovations. Our empirical study comprises an electronic survey of the member companies of the Brazilian Defence and Security Industries Association, based on the Oslo Manual. The results show that participation in offset agreements is related to process innovation. We have not found statistical evidence that offset contracts leads to new or significantly new products. The study also indicates that participation in offsets is not associated with the degree of autonomy or the degree of novelty, both in product and process innovation. Nevertheless, the interviews conducted with the Armed Forces experts highlight the importance of participating and benefiting from offset agreements. Keywords: technological Innovation, product innovation, process innovation, Oslo Manual, offset agreement

1. Introduction Brazil, one of the founding members of BRICS (Brazil, Russia, India, China, and South Africa) and one of the major world economies and a leader in the South American region, is trying to assert itself as a universal power. Together with China and India, the country will become one of the most important players in the global economy. In 2050 those three countries will be responsible for 40% of global production. In 2020, according to calculations, the production of these three emerging countries will overcome the production of Canada, France, Germany, Italy, UK and US all together (United Nations Development Programme 2013). These data points to a significant growth of Brazilian economy in the next years. However, an economically strong country needs the ability to express itself and be heard, therefore, Brazil is seeking a permanent seat in the United Nations Security Council. To achieve these goals, the Brazilian Government, among various measures, decided to invest in innovation. The latest National Strategy of Defence launched in December 2008 (Ministry of Defence 2008) suggests several measures to promote technological development of all the branches of Brazilian armed forces through the Brazilian Defence Industry (BDI). The BDI refers to the industries and companies that, according to the Brazilian legislation, participate in research, development, production, distribution and maintenance of defence products (Ministry of Defence 2012). In this context, the improvement of BDI and the update of military equipment will focus, whenever possible, on dual‐use technology (Ministry of Defence 2008) as a way to develop other industries, increasing their productive capacity, and generating wealth for the country. Dual‐use technology products and processes can be used both in the civilian or military spheres (European Union Council 2009), thus enhancing the country’s potential for innovation. The Brazilian Government has adopted the practice of offset contracts or agreements as a means to promote innovation and obtain technologies otherwise inaccessible and without which it would take several years to achieve.

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Alex Carlos and Regina Leite The government’s idea is to shorten time, skipping steps into the technological baseline of developed nations, through offsets aiming technological transference and the so desired innovation ability. The present paper aims to explore the role of offset contracts in the innovation process in the context of BDI. Specifically, it intends to evaluate the offsets performed between 2009 and 2011 with the purpose of answering the following question: Which is the effect of offsets in innovations (of products and processes) in BDI’s companies? For such, we will present a brief literature review of the main topics, measuring instrument, data processing and analysis, and discussion of empirical results and main conclusions.

2. Brief literature review 2.1 Innovation concept and major barriers Innovation is traditionally perceived as an idea, process or product which is new to a certain individual entity (Rogers 2003). Recently, innovation has been portrayed as the combination of invention and market (Carvalho, Lopes and Reimão 2011). There are several types of innovation. One of the most used was developed by the Organisation for Economic Co‐operation and Development ‐ OECD (Organisation for Economic Co‐operation and Development 2005). This kind of innovation includes product innovation (introduction of a new product and/or improved in the market), process innovation (appliance of a new and/or improved method of production or logistics), marketing innovation and organisational innovation. When we refer to offsets, technology transference and the defence industry, is difficult to dissociate the subject of technological innovation. The OECD defines technological innovation as the introduction of a new product in the market, a new service or a significant technological change on a product or a process (Organisation for Economic Co‐operation and Development 2005). Only the product and process innovations are considered technological innovations (Afuah 1998) and these will be the main objects of the present paper along with offsets. The Oslo Manual (Organisation for Economic Co‐operation and Development 2005) defines the guidelines to apply in research and development (R&D) surveys to measure technological innovation. Its guidelines tried to avoid the use of the word “technological” in “technological innovation” just calling it product or process innovation. This assessment tool has the advantage of identifying some innovation obstacles commonly called innovation barriers. In Brazil, the last Innovation Research (PINTEC) carried out by the Brazilian Institute of Geography and Statistics (IBGE), based in Oslo Manual, pointed out the lack of funds, lack of qualified personnel, high costs of innovation and high economic risks as being the major barriers to innovation stated by Brazilian companies (Brazilian Institute of Geography and Statistics 2010). Although not new to the country, the Brazilian Government is now using offsets with the purpose to exceed barriers and achieve the desired innovation ability.

2.2 Offset agreements Offsets are, by definition, a growing practice in international weapons trade which forces the seller to offset the buyer through a reinvestment agreement in favour of the buyer proportional to the money earned by selling of military equipment (Brauer and Dunne 2004). Offsets can also be defined as industrial compensations for the purchase of defence items or services (Bureau of Industry and Security 2012). The same have been increasingly used since its inception and today are estimated to represent between 20% and 30% of international trade (Howse 2010). In order to better understand the offsets process, it’s important to identify some keywords as well as its main participants or players. An offset agreement is the responsibility due to a commercial sale contract of military goods or services. This offset is usually due to a government (buyer) by a company or other government

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Alex Carlos and Regina Leite (seller). In a commercial contract, the buyer and the seller become fulfiller or offeror and recipient or beneficiary on the offset, respectively. The offset can be fulfilled through a compensation clause in the commercial contract or an offset agreement. It usually depends on the complexity of the transactions. One single offset agreement or clause can refer to one or more offset transactions which will aim to complete the obligation/requirement. The vast majority of countries have laws, policies and regulations regarding offsets (Brauer and Dunne 2009), so obligation is stipulated based on the value of the commercial contract and each country’s legislation. In the Brazilian case, obligation to reimburse is 100% of the commercial contract value for contracts over 5 million US dollars (Ministry of Defence 2002). To influence a country’s commercial scale, to obtain popular support for defence expenses and to develop the local industry are some of the reasons for the country to take part on an offset (Confer 2008). Furthermore, the following reasons have also been reported in the literature: make corrections in the labour market, increase capital for investments, promote strategic industries, correct information asymmetries, reduce investments risks and provide alternative funding sources (Waller 2003). If we pay attention to the abovementioned reasons, we can establish a certain degree of correlation with innovation barriers, namely the lack of funds, the lack of skilled personnel, high innovation costs and excessive economic risks. Offsets are often classified as been direct, meaning that the compensations are directly associated to object acquisition or indirect, meaning that the return can be directed to non‐related activities of the acquisition contract (Pargac 2006). There are several ways to fulfil an offset such as co‐production, financial assistance, direct investment, under permission production, direct purchases, subcontracting, technology transference and personnel training (Bureau of Industry and Security 2012). In Brazil, all these terms are accepted as long as they are included into a transference context of a non‐ mastered technology, which has been a crucial requirement in Brazilian defence’s purchases (Mitra 2009). Based on dual‐use technology potential over 35% of offsets traded all over the world refer to technology transference (Suman 2010).

3. The Brazilian experience with offsets: An exploratory research After a brief review of the literature we recall the research question: What is the impact of offsets upon innovation at BDI’s companies? In order to obtain the answer in November 2012 we have conducted a survey inquiry to associated companies of Brazilian Defence and Security Industries Association (ABIMDE). This choice is due to the fact that Brazilian Ministry of Defence is currently interacting with the BDI through ABIMDE (Ministry of Defence 2012). The time frame for this analysis was from January 2009 until December 2011 due to the implementation of National Strategy of Defence (Ministry of Defence 2008) in December 2008 and the performing of an innovation research (PINTEC 2011) made in Brazil by IBGE (Brazilian Institute of Geography and Statistics 2012). In the beginning of 2009 started the offset agreements regarding the Submarine Development Program (PROSUB) with an execution timeline of 15 years and the Helicopters Acquisition Program (H‐X‐BR) with an execution timeline of 12 years. The amount involving both offsets agreements is roughly 8.500.000.000,00 US dollars. After the statistical data analysis six semi‐directive interviews were made with organization, negotiation and execution offsets specialists (two Brazilian Navy officers, two Brazilian Army officers and two Brazilian Air Force officers) with the purpose of complement some data and look more closely to a few answers given by the inquired companies (Barañano 2008).

3.1 Measuring instrument The present research is based on an online survey to the ABIMDE companies and it’s divided into nine parts: the Company’s characterization (part 1), the respondent’s characterization (part 2), product innovation (part

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Alex Carlos and Regina Leite 3), process innovation (part 4), innovation activities (part 5), cooperation (part 6), government support (part 7), barriers to innovation (part 8) and offsets agreements (part 9). The survey follows the PINTEC guidelines (Brazilian Institute of Geography and Statistics 2012) regarding parts 3 to 8. Parts 1, 2 and 9 were written to answer the specific interests of the present research. This paper is based on parts 1, 2, 3, 4 and 9 of the original questionnaire. Part 1 was constituted by multiple‐ choice questions related to the companies’ characterization, namely their position in Brazil, how many years they have, how many employees they employ, their main activity and their target markets. Part 2 was also constituted by multiple‐choice questions intended to characterize the respondent, such as age, number of years in the company, their position in the company and educational level. Parts 3 and 4 were also composed by multiple‐choice questions to know if the company innovated in products and the quantity of implemented innovations (1; 2; 3; 4; 5; or more than 5). They used check box questions to know the degree of novelty (new or significantly improved to the company but already existing on national markets; new or significantly improved to national markets but already existing on international markets; new or significantly improved to international markets) and the degree of autonomy to innovate (entirely by the company; by cooperation with other companies; by cooperation with an institute and/or educational entity; by other companies; by an institute and/or educational entity; or other) and also to know how, where and by whom the innovation was made. Part 9 was constituted by multiple‐choice questions and intended to verify companies’ participation on the offsets (yes or no).

3.2 Statistical procedures The collected data were subject to statistical analysis using the SPSS software – Statistical Package for the Social Sciences, version 20.0. The frequencies were calculated (absolute values and percentage values) to categorical or nominal variables and non‐parametric tests of Chi‐square ( ²) or Mann‐Whitney (z‐score) were used to analyse the relations between variables. As recommended by the literature (Field 2009), the Chi‐square’s test was used to test the association between to variables whenever these were categorical type. Mann‐Whitney’s test was used to test the differences when dependent variables were ordinal in nature or alternate without normal distribution and/or without variance’s homogeneity and if the independent variable was categorical by nature. By agreement, it was accepted that there were statistically significant differences whenever the level of significance was under .05 (p .05).

3.3 Data analysis and results 3.3.1 Description of the companies and the respondents From the 172 companies of ABIMDE, only 147 were considered eligible to participate in the survey. A total of 54 companies have completed the questionnaire, representing a response rate of 37%. Nine questionnaires that were returned were not used in the statistical analysis because the companies did not develop innovative projects or were not formally constituted between 2009 and 2011. So, 45 companies were considered to the present research. The survey uses the company as unit of analysis. Although most companies were located in São Paulo (69%), companies from Rio de Janeiro (13%), Minas Gerais (7%), Paraná (5%), Ceará (2%) Rio Grande do Sul (2%) and Santa Catarina (2%) (Figure 1) have also returned the questionnaire. A total of 69% of these companies had been established more than 10 years ago, 22% between 3 and 10 years and 9% are quite recent since they present less than 3 years of existence. Twenty‐five companies (56%) employ more than 49 employees, five companies (11%) had between 50 and 99 employees, ten companies (22%) had between 100 and 499 employees and five other companies (11%) exceed 499 employees. Twenty‐five companies (56%) were industries, nineteen (42%) provided trading services and one company (2%) was responsible for trading products.

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Alex Carlos and Regina Leite 85% of the companies provide goods and services to civilian and military sectors which illustrates the existence of dual‐use technology. Thirty‐nine companies (87%) have products innovation and twenty‐three (51%) have processes innovation. All the companies which innovated in processes have also innovated in products. The other way around is not true. This finding is based on the idea that the introduction of a range of new products in the markets is supported by productive processes (Damandopour and Gopalakrishinan 2001). Six companies did not develop any innovative projects between 2009 and 2011, although they had developed activities for such.

Figure 1: Brazilian map (division by Federal States) A total of 67% of the respondents were more than 41 years old, 40% worked for more than 10 years in the company, 87% were directors or managers and 58% had obtained some academic degree after completing the undergraduate course (specialization, master’s or/ and doctoral degree). 3.3.2 Main research questions and results To answer this research’s main question, three questions will be answered in the subsequent sections. Have companies that participated in offsets become more innovative? To test for differences in the amount of innovative products and processes, introduced into market between 2009 and 2011, among companies that participated in offset agreements and those that did not, we have performed the Mann‐Whitney test. The number of products and innovative processes developed were used as dependent variables and participation in compensation arrangements was considered as the independent variable. Table 1 presents the descriptive statistics and the Mann‐Whitney (z‐score) test for the number of new or significantly improved products (goods and/or services) introduced as a result of companies’ participation in offsets between 2009 and 2011. Table 1: Number of new products (goods and/or services) introduced due to participation in offsets between 2009 and 2011 Participation in offsets N (%) Average innovative products (S.D.) z p Yes 6 (15.4%) 3.67 (1.86) ‐.04 .97 No 33 (84.6%) 3.73 (1.94)

There were no significant differences in the number of innovative products developed by the companies that participated in offsets and those that did not participate in any of the reference periods (p> .05). Table 2 presents the descriptive statistics indicators and results of Mann‐Whitney (z‐score) test for the number of innovative products introduced between 2009 and 2011, as a result of companies’ participation in offsets.

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Alex Carlos and Regina Leite Table 2: Number of new processes introduced due to participation in offsets between 2009 and 2011 Participation in offsets N (%) Average innovative processes (S.D.) z p Yes 4 (17.4%) 5.25 (1.50) ‐2.02 .04 No 19 (82.6%) 2.95 (1.99)

We have found statistically significant differences in terms of the average number of innovative processes among companies that participated in offsets between 2009 and 2011 and those that did not (Table 2). When it comes to innovative processes, the results show that companies that participated in offsets between 2009 and 2011 present an average of 5.25 innovative processes while those that did not participate present, on average, 2.95 cases in the same period. During the interviews with the specialists of the Armed Forces, we have asked why offsets are associated with the amount of innovation processes and not related to the amount of products innovation. Our interviewees pointed out the concern in mastering innovative processes from which it is possible to evolve to products that are adjusted to Brazilian specific needs as well as defence’s innovations high costs. This urges companies to present solutions, mostly in the form of innovative products. Nevertheless the companies have to be updated with the productive processes. One of the interviewees says: “In order to achieve an innovative or quality product… you have to improve your process therefore innovating in this sense” (Specialist 1, Brazilian Air Force). Do companies with larger spreading of innovation (new or significantly improved to international market) participate in offsets? To evaluate if the degree of novelty is related to the participation in offsets we have conducted Chi‐square tests. Innovative products (Table 3) and process (Table 4) were considered as dependent variables and participation in offsets as independent variable. Fisher’s exact test was applied in both tests because expected frequencies are inferior to 5. Table 3: Degree of novelty of innovative products introduced in markets between 2009 and 2011 due to participation in offsets Participation in Innovative products offsets New or significantly improved New or significantly improved to New or significantly ² (d.f.) p to the company but already national markets but already improved to existing on national markets existing on international markets international markets Yes 0 (0%) 1 (16.7%) 5 (83.3%) 5.424(2).11ª No 8 (24.3%) 14 (42.4%) 11 (33.3%)

ª Fisher’s exact test Table 4: Degree of novelty of innovative processes introduced in markets between 2009 and 2011 due to participation in offsets Participation in Innovative processes offsets New or significantly improved New or significantly improved to New or significantly ² (d.f.) p to the company but already national markets but already improved to existing on national markets existing on international markets international markets Yes 0 (0%) 1 (25%) 3 (75%) 3.685(2) .23ª No 5 (26.3%) 9 (47.4%) 5 (26.3%)

ª Fisher’s exact test There is no statistically significant relation between the degree of novelty of product or process innovation and participation in offsets. However, the results suggest a tendency for companies that participate in offsets to have higher ability for spreading their innovations internationally than those that did not. According to one of the interviewees: “To have in your portfolio that you have received technology from other countries is the major factor for a company’s emergence in international markets” (Specialist 2, Brazilian Navy).

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Alex Carlos and Regina Leite This means that companies can enhance their international exposure by participating in offset agreements since they are encouraged to innovate in order to fulfil the demands of international markets. Are the most independent companies to innovate (only by the company) those that participate in offsets? To determine if the degree of autonomy in innovation is associated with participation in offsets, we have conducted Chi‐square tests, introducing independence to innovate in terms of products (Table 5) and processes (Table 6) as dependent variables, and the participation in offsets as the independent variable. We have applied Fisher’s exact test. Table 5: Degree of autonomy in terms of innovation development (products) between 2009 and 2011 due to participation in offsets Participation in offsets Yes No

Products development ² p Entirely by the By cooperation with other companies and/or by cooperation with (d.f.) company an institute and/or educational entity 4 (66.7%) 2 (33.3%) .079(1) 1.00ª 20 (60.6%) 13 (39.4%)

ª Fisher’s exact test Table 6: Degree of autonomy in terms of innovation development (processes) between 2009 and 2011 due to participation in offsets Participation in offsets Yes No

Processes development Entirely by the By cooperation with other companies and/ or by cooperation with ² (d.f.) p company an institute and/or educational entity 3 (75.0%) 1 (25.0%) 1.011(1).59ª 9 (47.4%) 10 (52.6%)

ª Fisher’s exact test We have not found statistically significant correlations between the degree of autonomy to innovate in products or processes and the participation in offsets. However, in terms of frequencies, companies that participated in offsets seem to be more independent to innovate (the observed tendency was higher to processes than products). According to our interviewees, companies that participated in this type of agreement searched solutions together with other entities, based in cooperative experience related to the offset. After achieving a certain technological level companies tend to innovate independently as shown in the following interview extract: “EMBRAER (Empresa Brasileira de Aeronáutica – Brazilian Aeronautics’ Company – one of the world’s largest aeronautics’ companies) is the living proof. “EMBRAER was unimportant before the offset” (Specialist 1, Brazilian Air Force). It is worth mentioning that this company had recently won its competitors to supply aircrafts for the United States Air Force (USAF).

4. Conclusion Before presenting the main findings of this research, it is important to remember that the surveyed companies were divided into two groups: those who participated in offset agreements and those who did not. We have compared the participants and non‐participants in terms of the support received from the Government, development of innovation activities (R&D and staff involved), cooperation for innovation, and barriers to innovation (not used for the purposes of the present study). These statistical tests allow us to analyse the existence of different characteristics between the two groups of companies that could have an impact on innovation. There was only one aspect that presented a statistically significant difference: the barrier to innovation related to the lack of funds. This finding suggests that companies that have not participated in the offsets have presented the scarcity of funding as an obstacle to innovation more than participants. This happens mainly as a consequence of financial investments made by the offset offeror to the recipient firms. Bu doing so, the beneficiaries get access to external funds from the fulfillers that can be used for innovation. Generally, the results of this exploratory research show that offsets have the ability to fulfil the goals for which they are being used by Brazilian Government regarding innovations. Data gathered from ABIMDE’s companies

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Alex Carlos and Regina Leite suggest that those who participated in offset agreements innovated more in processes than those that did not. These data are supported by the interviews to the extent that the search for innovative processes could lead to innovative products. Another interesting finding is the opening of international markets to companies that participated in offsets and their cooperative ability in search for innovative solutions. According to our exploratory study offsets show a proven effect in the amount of innovations from the companies that participate in offsets and a tendency to contribute to innovations’ quality (degree of novelty and degree of autonomy to innovate). The present study intends to serve as a starting point for future researches and does not aim to generalise its findings. One of this study’s constraints is the reduced size of the available population for this research. In subsequent studies, questionnaires could be handed out to respondents and, filled in the presence of the researcher in order to increase the number of answers. When talking about offsets (Filgueiras 2012) or defence industry (Castellacci and Fevolden 2012) it is not unusual to find small populations or samples available for researches. This can be easily explained by the confidential nature of military industry. Another significant fact is that offsets are long‐term contracts so its outcomes take time to generate. Literature on the subject is scarce due to its specific goals and interests (Filgueiras 2012). Previous studies have shown a relationship between technological innovation and offsets (Silva 2001; Cruz 2005; Filgueiras 2012). However, they were all carried out with companies that had already participated in offsets considering different populations and time frames in the data gathering process. The present study has an unprecedented character since, for the first time, companies that participate in offsets have been compared with those that have not, using the same population and time frame, with the purpose of detecting potential differences in their innovations’ results. This research could be replicated considering longer time frames and taking into account the new legislation implemented after 2011. Further analysis could include the company’s activity, namely industry, trading goods and/or services to enable more suitable offset solutions for each sector.

References Afuah, A. (1998) Innovation Management. University Press, Oxford. Barañano, A. M. (2008) Métodos e Técnicas de Investigação em Gestão. Sílabo, Lisbon. Brauer, J., and Dunne, J. P. (2004) Arms Trade and Economic Development, Routledge, London. Brauer, J., and Dunne, J.P. (2009) Arms Trade Offsets: What do We Know? [Working Paper nº 0910], University of the West of England, Bristol. Brazilian Institute of Geography and Statistics (2010) Pesquisa de Inovação Tecnológica, IBGE, Rio de Janeiro. Brazilian Institute of Geography and Statistics (2012) Pesquisa de Inovação, IBGE, Rio de Janeiro. Bureau of Industry and Security (2012) Offset in Defense Trade ‐ Sixteenth Study, Bureau of Industry and Security, Washington. Carvalho, J. E., Lopes, J. A., and Reimão, C. M. (2011) Inovação, Decisão e Ética, Sílabo, Lisbon. Castellacci, F., and Fevolden, A. (2012) Capable Companies or Changing Markets? Explaining the Export Performance of Firms in the Defence Industry, Norwegian Institute of International Affairs, Oslo. Confer, B. S. (2008) An Analysis of Second‐Tier Arms Producing Countries Offset Policies: Tecnology Transfer and Defense Industrial Base Establishment, Air Force Institute of Tecnology, Wright Patterson AFB. Cruz, R. L. (2005) Offset: O Exemplo do Setor Aeroespacial Brasileiro, Universidade da Força Aérea, Rio de Janeiro. Damandopour, F., and Gopalakrishinan, S. (2001) "The dynamics of the adoption of product and process innovations in organizations", Journal of Management Studies, Vol. 38, No. 1, pp 45‐65. European Union Council (2009) Council Regulation (EC) No 428/2009, [online], EUR‐Lex, eur‐ lex.europa.eu/JOHtml.do?uri=OJ:L:2009:134:SOM:En:HTML. Field, A. (2009) Discovering statistics using SPSS, SAGE, London. Filgueiras, E. Q. (2012) "A Conjuntura Político‐Econômica 2007‐2010 e a Transferência de Tecnologia nos Offsets da Aeronáutica", Revista da Universidade da Força Aérea, Vol. 25, No. 30, pp 6‐17. Howse, R. (2010) "Beyond the countertrade taboo: why the WTO should take another look at barter and countertrade", University of Toronto Law Journal, Vol. 60, No. 2, pp. 289‐314. Ministry of Defense (2002) Portaria Normativa nº 764/2002 – Diretrizes de Compensação Comercial, Industrial e Tecnológica. Ministry of Defence, Brasília. Ministry of Defence (2008) Nationl Strategy of Defence. Ministry of Defence, Brasília. Ministry of Defence (2012) Livro Branco de Defesa Nacional. Ministry of Defence, Brasília.

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Alex Carlos and Regina Leite Mitra, A. (2009) "A Survey of Successful Offset Experiences Worldwide". Journal of Defence Studies, Vol. 3, No. 1, pp. 43‐62. Organisation for Economic Co‐operation and Development (2005) Oslo Manual (3rd ed), OECD, Paris. Pargac, P. (2006) What Issues Does the Czech Republic Face Concerning Offsets in Context of Military Purchase, Naval Postgraduated School, Monterey. Rogers, E. (2003) Diffusion of Innovations (2nd ed.), Free Press, New York. Silva, J. P. (2001) Utilização de Contrapartidas Associadas a Grandes Compras na Dinamização da Inovação Tecnológica: Uma Metodologia de Estruturação de Casos, Universidade Técnica de Lisboa, Lisbon. Suman, M. (2010) Defence offsets: proving detrimental to the services. [online], Indian Defense Review, www.indiandefensereview.com/news/defense‐offsets‐proving‐detrimental‐to‐the‐services/. United Nations Development Programme (2013) Human Development Report 2013 ‐ The Rise of the South: Human Progress in a Diverse World, Communications Development Incorporated, Washington DC. Waller, R. L. (2003) "The Use of Offsets in Foreign Military Sales", Acquisition Review Quarterly, Summer 2003, pp. 223‐233.

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Individual and Mandatory Innovation in Automotive Industry: A Case Study Cristian Chiru, Versavia Ancusa, Razvan Bogdan and Bogdan Suta Politehnica University of Timisoara, Timisoara, Romania chiru.cristi@gmail.com vancusa@cs.upt.ro razvan.bogdan@cs.upt.ro bogdan.suta@cs.upt.ro Abstract: In automotive industry, product development life cycle follows the traditional three stages: the exploratory stage, the development part and finally, the mature phase. A large multi‐national corporation, like those in automotive industry, may use one or more locations for a certain phase. In our country, Continental subsidiaries are focused mainly on the development and production stages. A development phase characteristic is that the production level is highly responsive to any optimization upgrade. Therefore, any innovation at this stage is critical as it may provide increased productivity, leading to economic growth. Innovation in Continental, Timisoara, Romania is highly encouraged, not only by structured internal programs, but also by the corporation culture. Product development incorporates testing, a sine‐qua‐ non segment, taking into account its inherent nature that poses a threat to human safety. Testing is generally a tedious process, involving highly skilled engineers and many detail‐oriented tasks. This paper aims to present how innovation occurred in the testing phase for a certain car‐line display. Initially, the testing was done manually, by entering in an input file the variables to be tested. The file would be sent to the Electronic Control Unit (ECU) and the testing engineer would manually check if the correct image would be exhibited. A test scenario would last for more than 120 hours. A first attempt at improving this involved a camera which would capture the display and send the image to the computer, for checking. Although this version of automated testing was considered acceptable by management standards, a newly appointed testing engineer observed several unused facilities of the ECU while learning the technical manual. Using those facilities with flair, this individual devised a new automated technique that uses only the ECU and improved software on the testing environment. The time for a test scenario decreased from an average of 50 hours in the first automated version to 18 hours in the second one. This case study comes to show that to confer carte blanche for a specific task (even if there already is an accepted procedure for that task) plays an essential role in insuring employee‐driven innovation. Keywords: testing, innovation, automotive industry, development phase

1. Introduction This paper analyses the concept of employee‐driven innovation and its application in the local automotive industry. Employee‐driven innovation is based on what is termed as “the reconstruction of the work practice” or “remaking everyday work practice.” In the context of globalization, corporations seek to extend their productivity and clients. Moreover, they also have to face an internal challenge of motivating people to develop the contracted projects. In order to face such challenges, the management levels are in a continuous challenge to construct and apply different strategies that can work together to reach the goals. The paper is structured in three main sections. The first explores the concept of employee‐driven innovation through specialist literature review while the second considers when and where this novel type of innovation can be encouraged in order to maximize the effects. Before drawing conclusions, a successful case of EDI is presented, preceded by a technical interlude in testing, in order to clarify its practical complexity.

2. Literature review While employee‐driven innovation (EDI) is increasingly being considered a vital source of innovation processes within a company, the concept can be further described when observing enterprises where, at all levels, ordinary employees might be an essential source of innovation and improvement. This relatively young scientific view on EDI concerns regular staff members, who are employed in their own expertise area, but are not necessarily deemed as / required to be innovative in that field. However, they develop ideas at all stages in the enterprises, ideas that might represent remarkable sources of bottom‐up innovation processes (Hoyrup, et al., 2012). By harnessing the power of those ideas, the growth potential, both of the enterprise and the employee would be improved. It should be noted that while the employees’ aim is not necessarily innovative, they would like to be acknowledged for their inventive ideas. Therefore, EDI can be seen as a form of direct

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Cristian Chiru et al. participation that can lead to new concepts. Such ideas create value and innovation when implemented in the company. In (Kesting & Ulhøi, 2008), the authors point several important attributes of the innovation concept, in relation to which it should be mentioned that the content and products of innovation can be ideas, products and processes. Furthermore, this paper emphasizes that innovation is based on interaction among employees who are assigned to accomplish a certain task. Such interaction can lead to significantly improved development processes or related stages within a company. Sundbo (2003) argues that EDI is a bottom‐up process in the organization since it is basically a social process. In Sundbo’s words, “single individuals alone do not create innovation within modern firms”. In this respect, the EDI concept is related to that of management. On one sense, management should be prone to EDI implementation; on the other, precise technical implementation details might not be at hand for the management team. A typical top‐down EDI process involves inviting employees to participate in formally organized innovative meetings (Hoyrup, et al., 2012). However, in another paper, Kesting opinionated that decisions about major innovations are generally facing a “resisted increased participation” (Kesting & Ulhøi, 2010). EDI has developed in the last few years, becoming an important topic in many industries. The research question (Spiegelaere, et al., 2011) in this regard can be expressed as: “How do industrial relations attributes affect EDI?” The goal of EDI is to speed up internal innovation and also to enlarge the spectrum of markets a company is using to offer its products (Chesbrough & Crowther, 2006). Lately, different industries such as computers, semiconductors, biotechnology are switching to an open innovation approach. This is based on the idea that the company interacts with its internal and external setting from different points of analysis. The key point to this technique is based on the corporation’s aptitude to carry out both internally and externally technology management assignments along the innovation process (Chesbrough & Crowther, 2006). Different empirical studies such as the one presented in (Diaz‐Diaz, et al., 2006) show that the automotive industry is a typical successful example of adopting this strategy. Better performance emerges in the field of R&D when such a technique is adopted. (Ili, et al., 2010) states that the automotive industry is prone to reducing costs by adopting innovation programs and better face the globalization paradigm.

3. Implementing EDI in the local continental AG branch Since 2000 Continental AG has established a strong presence in Timisoara, where only in November 2012 they finished building a € 20 million site, while employing over 2000 people. The impact of Continental AG in the local community is extremely beneficial and their connections with “Politehnica” University of Timisoara lead to the creation of several laboratories and numerous research projects. Innovation is almost always one of the most important requirements of those outsourced projects, nonetheless that does not mean that innovation is not encouraged internally. As a result of that internal policy, every year an internal innovation program called Continental Idea Management (CIM) is launched. During this program, individuals are asked to be innovative during a certain time frame, collect ideas and then the management rewards the best ideas. Each department has allotted a special fund in the annual budget with the purpose of incentive for the employees that have offered viable ideas. Proportional with the implications of each submitted idea in terms of time improving, cost reduction, logistic etc., there are different amounts of prizes to be offered to the employers. All these employee incentives are part of the next‐month regular salary. Falling into the top‐down EDI implementation (Hoyrup, et al., 2012) CIM is a mandatory innovation program, therefore having the pitfall of resisting to the directive to innovate on command, as it was argued in (Kesting & Ulhøi, 2010). Moreover, the benefits of idea‐based rewards are questionable and argued to be not so beneficial by (Gurteen, 2007). In order to improve internal innovation, EDI would be a more appropriate solution. In contrast to CMI, EDI is based on individual innovation, thus dependent on a person’s creativity, spontaneity and inclination to create at a certain point. An advantage of EDI is that the employee does not feel pressured into creating something, furthermore he/she feels encouraged to try as there are no consequences if they fail. However, when dealing with such a substantial and large company branch, the EDI technique must be tested on a small scale first, and if the experimental results confirm its success, further implementation can be done. This leads us to research where to implement localized non‐pressured EDI for a first experiment in the local Continental branch. In order to do that the following questions needed to be answered:

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Is there a group of people which are critical points for EDI? If so, how can those be identified?

Is there a time‐frame in the product developments’ life in which EDI is best established?

We started to study the workflow and, as described below, we have managed to identify several critical points and a time‐frame for them.

3.1 Product development model The V‐cycle (Figure 1) is the model used in Continental AG Corporation to represent the system development of any project. The two sides reflect the main stages of the project, starting with the first stage concerned with the system requirements analysis and design at various levels of complexity. This shapes the exploratory stage in which highly skilled analysts working in multi‐disciplinary teams alongside clients’ requirements set the directives for the other employees. Innovation is already a priority at this stage. A large multi‐national corporation, such as those in the automotive industry, may use one or more locations for a certain phase. In our country, subsidiaries of Continental focus mainly on the development and production stages. This is reflected in the v‐cycle by the right side of the V in Figure 1. A characteristic of the development phase is that the future production level is highly influenced by any optimization upgrade. Therefore, innovation at this stage is critical as it may provide increased productivity, thus leading to economic growth.

Figure 1: V‐cycle model used in Continental corporation (Federal Highway Administration (FHWA), 2005) In the automotive industry, product development follows an interweaving bi‐fold path that allows the hardware and software development of the product to be as parallel as possible. A very common encountered timeline resembles the one presented in Figure 2. As previously stated, in a multi‐national company, like Continental, each of the sub‐stages might happen in a different country, too. In our local branch, some stages might require partial involvement while others are fully undertaken by this branch. It makes sense to first start EDI at the fully‐involved stages, as the others might depend on practices in other branches of Continental. Out of those stages the most complex one to analyse is the coding and unit testing stage as the other phases (CSC Integration test or the System Integration and Test) present only the testing activity. The pitfall of this model is that it does not explain the interaction among people and because EDI is a social process, these data need to be correlated with the development model. We should therefore append that model with measurements specific for social networks.

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Figure 2: Product development timeline Local Continental branch involvement marked as partial (light grey) or fully (dark grey)

3.2 Modelling the social dimension in a coding and unit testing project phase A typical Continental coding and unit testing project involves a number of 4‐6 teams that include developers and testers. Each developer interacts directly with all the testers. At the same time each tester cooperates strongly with the other testers from his/hers team and with all their counterparts from the other 3‐5 teams. The project manager of each team is coordinating the workload of the whole team but has no real involvement in the coding or testing of the product. In assessing the interconnectivity of the developer team several problems emerge:

The interconnectivity varies greatly during the duration of the project

Different teams have different degrees of interconnectivity

It might be difficult to differentiate between the social interconnectivity and the work‐related one (e.g.: one might prefer to work more closely with a friend for a minor task in the project, while a major task with a not so‐close friend might present a weaker interaction)

People might leave/arrive mid‐project changing the whole dynamics

We resorted to simulating the developers and testers interaction using a complex network. Complex networks are used to represent interactions and can be interpreted after the computation of certain parameters. Comparing complex networks representation to other ways of studying interaction has several properties such as: scalability, measurability and clarity of inference recommend them as the preferred simulation substrata. For the actual programming part a code was created that requires as inputs: the number of teams, the average number of developers and testers in a team and the degree of interaction between developers. The code also provided the user with a possibility to enter a variation degree for the number of developers and testers in a team. A randomization of the actual interaction was our answer to modelling the developers’ interaction. The results of our program were then rendered using Gephy, a dedicated freeware program (www.gehpy.org). In Figure 3, three simulation results are presented and rendered using node size proportional with the betweenness centrality. This type of centrality “measures the degree to which the node under study can

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Cristian Chiru et al. function as a point of control in the communication” (Leydesdorff, 2007). If the node is a point of control in communication it can be argued that its position is the most favourable to implement any type of innovation because it has enough decision power and information to make an impact.

Figure 3: Complex networks simulation results of testers and developers interactions in an automotive project At around 20% interaction in the development team we noticed the emergence of focus points. The focus points might represent any category of managerial structure, like project leaders or brand responsible, or a developer working on a critical fraction of the code. More than 20% lead us to too many focus points. Several simulation results are presented in Figure 4.

Figure 4: Too many focus points appear at higher interaction between developers When looking at the closeness centrality of the nodes, i.e.: “the efficiency of each vertex (individual) in spreading information to all other vertices” (Okamoto, et al., 2008) as expected, by increasing the interaction level in the development teams those nodes become more important than the testers. The results of those simulations are depicted in Figure 5. However, from a certain point of around 40% interaction in the development team, the whole network seems to favor the importance of the developers over the testers. A discussion is adequate at this point: closeness centrality is a measure of influence that treats the network as a whole, while the betweenness centrality is a measure of local influence of the vertex. The closeness centralty shows that many developers and the testers are most influencials in the whole network, while the betweenness centrality only identifes the testers and the project leaders. We consider the betweenness centrality the more valuable measurement in this case because developers belonging to different teams work in independent areas of the project. This partial autonomy is not thoroughly quantized by the complex network representation, thus rendering the closeness centrality measurement partialy flawed when interpreting. In order to validate the simulation results, we surveyed the Continental employees what is the degree of interaction in a development team. The employees were equally chosen from the developer and tester position, the survey was anonymous and consisted in a verbaly asked question, to which we wrote the response. The answers varied between 10% to 25 % with an average of 18.79%. This empirical measurement

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Figure 5: Various interaction strengths in the development teams correlated with information spreading efficiency (closeness centrality)

3.3 Location of critical innovation points Based on our model the critical points appear to be the testers. So this helps us formulate our first conclusion: in our local Continental AG branch, those testers need to be stimulated or at least to be unhindered in innovating. This helps us to establish where EDI implementation would bring the most profit, although it does not answer the question of when to start implementing EDI at that level. However, with EDI as the goal, one must take into consideration that testing follows the development phase. This answers our second question, that relates to timing: the best time for EDI is not at the beginning of the project, but after some data (in this case some code) may be provided to the focus points of the network. From the management point of view, this implies that the testers should be given free hand to tinker with the existing solutions. The existing solutions are usually redundant, or easily made so. This helps to maintain operational continuity, as the previous working solution should not be discarded until a third party (also a tester, but from a different team) together with the project manager approve the innovation. In order to illustrate a successful case of EDI following these guidelines, we must first explore the testing options with their facilities and pitfalls.

3.4 A technical overview of the testing options Software testing can be categorized as: manual, semi‐automatic and full‐automatic. Manual testing involves a tester (programmer) and several test cases, previously created, based on clients’ requirements. A simulator (Vector CANoe) is used to emulate an ECU (Electric Control Unit) – the hardware component, which is simultaneously developed. The programmer loads and runs each test case on the simulator and manually compares the obtained results with desired results. A test report stating the results is compiled by the programmer.

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Cristian Chiru et al. Semi‐automatic testing still involves the active participation of the programmer, although the test cases are now loaded in a batch manner, under the designation of a test scenario. Detailed signals are automatically generated and the whole batch is usually run on a cluster (a hardware mock‐up of the final product). Each step involving result visualization requires human confirmation to be entered on the testing computer. The tester must answer if the test case has passed or failed by actively looking at the display and checking if the desired result is present. Fully automated testing is much more convenient: after starting the testing program, the programmer only reviews the results following the end of the batch run. In the automotive industry, fully automated testing is usually done in one of two ways: (a) by using a camera to capture the display of the cluster or (b) by creating a tool – a frame grabber – that blocks the display image, accesses the buffer that holds that image and then transfers and converts the result as an image to be used later. The testing program then compares the image (obtained in either way) with the desired result and issues a pass or a fail. The whole process is basically independent of human presence (except by the initiation action). This makes fully automated testing extremely suitable to running over‐night, without supervision. However, each fully‐automatic testing method presents pitfalls. The version that involves a camera, in addition to needing an extra hardware component, needs extensive calibration of that component. For example, if the camera is out‐of‐sync with just 1 millisecond, all the test cases will fail, though they might otherwise pass. The colour of the pixels captured by the camera must also be calibrated, moreover, in the event that the properly calibrated camera breaks down, none might be the wiser until the whole batch is done thus resulting major delays. The calibration needs human involvement and a certain degree of technical training. Using a frame grabber, fully automatic testing becomes much easier, as the whole purpose of the tool is to block the image on the testing clusters’ display and then capture it (“grab”) using a backdoor into the display’s buffer in order to finally send it back to the testing computer and resume running the next test cases. There are still some time constraints, however less strict then in the camera fully‐automated testing. A new class of problems might occur if the grabber is not properly designed, in which case the captured image might not be the real image on the display. Both versions of automated testing need another tool that generates the reference images, used to compare the captured image to. In Table 1 are summarized the testing methods previously presented, together with the technical expertise and involvement details. Table 1: Testing methods comparison Type

Manual Semi‐automatic Fully‐automatic with camera Fully‐automatic with grabber

Extra hardware required N N Y

Extra software required N Y (1) Y (1)

Y (2)

Human involvement in testing

Programmer technical training

continuously sequentially calibrate camera, start the process start the process

high medium medium

Decision to pass/fail taken by human human computer

low

computer

3.5 EDI in action In order to illustrate the application of EDI we present the case of a young testing engineer. This engineer was employed in order to continue a semi‐automatic version of testing, which was developed by a previous engineer in order to upgrade from the manual version. The testing engineer would manually check if the correct image was exhibited for each step of the process. A test scenario lasted more than 120 hours. The management decided that the duration was too long and issued a “directive to create” an improved version. This improved version was a fully‐automatic with camera type of testing. The time needed to develop the reference photos for this version took around 100 hours. It should also be mentioned that before each batch test run, the camera needed to be fully calibrated, resulting in extra time required for each sequence. Although this version of automated testing was considered acceptable by management standards, this newly

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Cristian Chiru et al. appointed testing engineer, while learning the technical manual, observed several unused facilities of the ECU. Benefiting from the liberty to improve, this individual devised a new automated technique that uses only the ECU and improved software on the testing environment. The time for a test scenario decreased from an average of 50 hours in the first automated version to 18 hours in the second one. The time spent in order to develop the faster fully‐automatic version was 1 month (160 hours), because the reference images were already generated with the previous version of fully‐automated testing.

4. Discussion Referring to the previously presented case, Table 2 presents the summarized results for 1 run and extends them for a number of runs. Due to their nature, projects in the automotive industry have several releases and each release requires exhaustive testing as the industry’s safety standards are extremely strict. Table 2: Testing time for various testing options (all values are presented in working hours)* manual testing was not actually used in this project ‐ it’s presented here for academic comparison Type of testing

Manual* Semi‐automatic Fully‐automatic with camera Fully‐automatic with grabber

Actual testing time 200 120 50

Time to develop

Overhead for each run

1 run

5 runs

Time for 10 runs 15 runs

0 0 100

0 0 2

200 120 152

1000 600 360

2000 1200 620

3000 1800 880

4000 2400 1140

160

178

250

340

430

520

20 runs

Since fully‐automated versions do not need constant human supervision, they might be run after‐hours or overnight, thus greatly improving time. In Table 3, such an example is presented, where the after‐hours testing time was considered 0, as it represents 0 working hours. Still, if testing extends beyond the 16 hours, it encroaches working hours and testers cannot use the equipment to do other testing. Table 3: Testing time for various testing options with the after‐hours time reduced to 0 (all values are presented in working hours) * manual testing was not actually used in this project ‐ it’s presented here for academic comparison Type of testing

Manual* Semi‐automatic Fully‐automatic with camera Fully‐automatic with grabber

Actual testing time 200 120 50

Time to develop

Overhead for each run

1 run

5 runs

Time for 10 runs 15 runs

0 0 100

0 0 2

200 120 118

1000 600 190

2000 1200 280

3000 1800 370

4000 2400 460

160

162

170

180

190

200

20 runs

The results presented in Tables 2 and 3 show that either fully‐automatic version represent an obvious improvement compared with the semi‐automatic or manual options. When comparing just the fully‐automatic options, a note should be made on the number of runs. In 2012, this project had 16 releases requiring at least 1 run/release. In some cases, even more runs/releases are necessary. Even if some of the clients’ requirements change, the updates needed for the testing software entail less than 20 hours. In 2013, this project continues and is expected to have at least an equal number of releases. By allowing the testing engineer to spend 160 working hours on software that was not in the project managers’ plans, in 2012 those hours were fully recovered after the first 15 runs and in 2013 further gain is expected. The concept of EDI is a novel one as is the study of social interaction using complex networks. This paper presents a way of adding social interaction to an automotive industrial workflow with the aid of complex networks. Applying betweenness centrality to this model, it is relatively unproblematic to determine points that are most favourable positioned for EDI. These critical points can implement any type of innovation because they have enough decision power and information to make an impact.

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Cristian Chiru et al. Another question answered by this paper relates to the appropriate timing of EDI which proved to be not at the beginning of the project, but after some data (in this case some code) may be provided to the focus points of the network. In implementing EDI, the management should develop strategies to give free hand to the critical points first, while maintaining operational continuity. This process was successfully implemented at the local Continental AG branch and by the action of one critical point at least 4 months of workload have been gained. It might be argued that this is an achievement at the development stage, where innovation is not a commonplace occurrence. The process however can be translated at the exploratory phase where we expect it to complement existing innovation techniques. While this translation to the exploratory phase is possible, this idea was targeted for an automotive product development. It also works in any embedded systems industry in almost any country, as it does not depend on the reward system or any specific social dimensions, moreover the presented model can be applied to any company that follows the studied employee structure. Future work should be focused on how to extend EDI to the other non‐critical points, without disrupting the company’s workflow.

Acknowledgements The authors would like to thank Timisoara Continental AG Corporation for their support and enthusiastic involvement in this study.

References Chesbrough, H. & Crowther, A., 2006. Beyond high‐tech: Early adopters of open innovation in other industries. R&D Management, 36(3), pp. 229‐236. Diaz‐Diaz, N., Aguiar‐Diaz, I. & De Saa‐Perez, P., 2006. Technological knowledge assets in industrial firms. R&D Management, 36(2), pp. 189‐203. Federal Highway Administration (FHWA), 2005. Clarus Concept of Operations, Publication No. FHWA‐JPO‐05‐072: US Department of Transportation. Gurteen, D., 2007. Building a Knowledge Sharing Culture. [Online] Available at: http://www.gurteen.com/ [Accessed 03 2013]. Hoyrup, S. et al. eds., 2012. Employee‐Driven Innovation – A New Approach. 1st ed. s.l.:Palgrave Macmillan. Ili, S., Alberts, A. & Miller, S., 2010. Open Innovation in the automotive industry. R&D Management, 40(3), pp. 246‐255. Kesting, P. & Ulhøi, J. P., 2008. Employee Driven Innovation: The Discovery of the Hidden Treasure, s.l.: The Danish Agency for Science,Technology and Innovation. Kesting, P. & Ulhøi, J. P., 2010. Employee‐Driven Innovation: extending the license to foster innovation. Management Decision, 48(1), pp. 65‐84. Leydesdorff, L., 2007. Betweenness centrality as an indicator of the interdisciplinarity of scientific journals. Journal of the American Society for Information Science and Technology, July, 58(9), pp. 1303‐1319. 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). Spiegelaere, D., StanVan, G. & GuyVan Hootegem, G., 2011. Employee Driven Innovation & Industrial Relations, Leuven, Belgium: K.U. Leuven. Sundbo, J., 2003. Innovation and strategic reflexivity: an evolutionary approach applied to services. In: L. Shavinina, ed. The International Handbook on Innovation. Boston: Elsevier Science Ltd., pp. 87‐114.

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Costs as a Decision‐Making Criteria in the Planning of Innovation Processes Piotr Chwastyk Institute of Innovation Processes and Products, The Opole University of Technology, Opole, Poland p.chwastyk@po.opole.pl Abstract: Implementation of innovation is currently the most effective response to the needs of the global market. It is also a very important element for business development and competitive rivalry. Implementation of innovation requires a correctly executed innovation process. Success can be achieved through proper management. Difficulties arise in the planning stage and are associated with uncertainty in achieve objectives. Further phases of the process are dependent on the results of the previous phases. This feature makes that the process planning and implementation of innovation are very difficult. Due to the dynamic nature of the innovation process is the need to continuously decision‐making process. One of the important criteria that have an impact on decision‐making is the cost. The cost of the innovation process is often the decisive factor in deciding to start, continue or terminate the innovation process. For this reason, cost estimating is an important task in the management process. This problem was inspired to undertake a study on cost estimation of the innovation process. The aim of the research is to develop guidelines for cost estimation during the process planning innovation. This paper presents the results of research that was conducted in Polish enterprises. The research involved analysis of innovation processes have been implemented with success to identify best practices in management. This paper describes the three‐step approach to cost estimation of innovation processes. It ensures the possibility of getting more and more accurate results. For each of the steps proposed a set of techniques for cost estimation presenting their advantages and disadvantages. The proposed solution is designed to enable managers to better manage innovation processes based on reliable cost information, which will reduce risk in decision making. The aim of this solution is to achieve reproducibility and standardization in the process planning, which will allow for more effective implementation of innovation. Keywords: innovation process, decision‐making, cost estimation

1. Introduction Rapidly developing market poses difficult problems for businesses. Surviving on the competitive market requires a flexible approach to the ever‐changing conditions. Not only adapt to the demands of the market is important, but also to anticipate upcoming changes and proper preparation for them. Innovation is the best way to prepare for these new market conditions. They also allow for the development of the company and the effective fight against competitors. Important elements of the innovation are the ability to perceive the market opportunity, creating conditions for the development of innovative solutions and the ability to organization and management of innovation processes. But the most important element of innovation is the ability to make decisions under uncertainty. The uncertainty is associated with the implementation of activities that have a unique character (Rothwell 1992). They were not carried out in the past and thus can yield surprising results. Therefore, managing the process of innovation brings with it a high risk that may affect the need for high costs and even the failure of the realized process. Risk is an integral part of the decision making process. The risk reduction improves the quality of decisions that have an impact on the correct course of the innovation process. Develop methods to reduce the uncertainty of information in decision‐making is an important task in the management of innovation processes. This article takes the problem of cost estimating of the innovation process. Costs are the most frequently mentioned criterion determining many decisions. For this reason, skillfully executed cost estimation process can effectively contribute to increase the knowledge about the process of innovation and provide a greater level of assurance decisions. The key to thrive for enterprise in the twentyfirst century is based on product quality, competitive cost, fast delivery and flexibility. Although an innovative approach for enterprise development, the processes may still be time consuming and less cost effective. For enterprises the timely introduction of innovative solutions is important to gain a competitive advantage. Demanding customer also expects to receive innovative products to meet the demanding needs. The desire to quickly take advantage of the profits that will soon be implemented innovation can adversely affect the quality of the innovation process. This situation may result, for example, to neglect of assessing the profitability of the innovation process manifested in underestimated costs that reduce operating objectives or overestimated costs, which could lead to the

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Piotr Chwastyk resignation of implementation the innovation striking in the company's image and loss of market. This highlights the importance of selecting appropriate methods for cost estimation of innovation processes

2. Decision‐making in innovation processes The innovation decision making, in the traditional view, focuses on the economic assessment of the innovation. It means that the adoption of innovation depends upon its relative value of productivity and profitability (Rogers 1995). It is argued that the decision to adopt an innovation is depended on a rational thinking which takes into account the benefits to be occur as the result of the adoption of that innovation and the costs associated with its adoption (Maguire 2002). In this sense, it is proposed that a rational thinking is used by managers to evaluate costs and benefits of the adoption of innovations in terms of material values (George 1998). The decision to adopt an innovation depends on its estimated profit, namely its economic worthiness. Thus, from the economic perspective, the innovation decision making is reduced to intentional, conscious and rational processes which are driven essentially by objective factors. It posits that firms adopt an innovation when the gathered information permits to confirm that the potential gains outweigh the risks (McCardle 1985). Otherwise, they will gather more information before making a decision or they will choose not to adopt the innovation if the profit estimate is very low (Oliva 1991).

Source: based on (Frambach and Schillewaert 2002) Figure 1: Groups of criteria in decision making process Decision‐making processes of innovation refers not only to the economic dimension. Consideration must be given also the role the recipient of innovation (market acceptance) and the organizational level of enterprises (figure 1). Important here is the knowledge about the acceptability of proposed innovative solutions by customers. Acquiring this knowledge is facilitated by proper communication with potential customers and the right tactics in the market activities which can reduce the risks associated with market acceptance (Frambach and Schillewaert 2002). From the point of view of adopter a significant is the level of organization of the company. It takes into account the level of resources and technological capabilities. Innovation, which are closer to the used technology gives a greater chance of successful innovation, than to introduce new technology. In addition to the perception of their abilities to adopting of innovation, you must also consider the environment, which mainly concerns the assessment of the level of competitiveness in the market. Fierce competition between firms increases the chance of the decision to adopt innovation (Gatignon and Robertson 1989).

3. Research method and main findings The validity of the decision‐making problems in the process of innovation was a premise for the start of the research. The innovation processes planning and cost estimating of innovation processes were analyzed in this research. The following paper relates to aspects of cost estimating process innovation and this part of research will be described. In this area of research, the aim is to build a model that will allow for the indication of places where the cost estimated of the innovation process will provide important information for decision‐making. On the basis of the model will also proposed cost estimation techniques that allow to obtain reliable and accurate results adequately to the data available. Research scheme is shown in figure 2 The study was preceded by an analysis of the publications in the field of innovation in order to determine the model of the innovation process and the identification of management tools to support these processes. The next step was a preliminary study in one of the IT companies. This gave an empirical confirmation of the accuracy of the selected model, research hypotheses was defined, and also was specified the scope and method of research.

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Source: Author Figure 2: Research scheme of innovation processes in Polish enterprises As a research method adopted direct interview, which he co‐developed as a result of the preliminary studies. Such a research method was adopted because of the wide variety of innovation processes analyzed, different sizes of enterprises and the lack of detailed documentation of innovation processes. Often innovation processes were planned in an informal way. Direct interviews were carried out with persons who manage of innovation processes and are responsible for their implementation. During the interview collected information on innovations that have been implemented with success. Specific questions was related to determining the areas of innovation, idea generation, ideas evaluation methods and their selection, planning of innovation processes, ways of decision‐making and cost estimation methods. Main part of the research was devoted to the problems of planning processes of innovation and cost estimation of the innovation process. This part of the study enabled the development of pre‐planning models of innovation processes and estimating the costs of these processes. The last stage of the study, which is currently carried out, provides for verification of models. This part is implemented in the next group of companies and non‐profit organizations. The main part of the research was conducted in 30 Polish companies mentioned in the national rankings of innovative companies. More than 100 innovation processes relating to product innovation, process, organizational and market were analyzed. As a result of research, it was observed that companies implement mainly an incremental innovations that involve the introduction of minor changes in their products. This way of conducting innovation policy allows to

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Piotr Chwastyk realize the innovation with shorter time horizons and less capital‐intensive. Innovation processes are easier to plan and execute. Increased frequency of incremental innovations is well perceived by the public as a result of a higher frequency of introduction of new products into the market. This approach, observed in Polish firms, coincides with the global trend (Cooper et al 2003). Radical innovations are rare. Require a long lead time, complex and costly process, characterized by a high level of risk and uncertainty, which translates into difficulty in making decisions. The advantage of these innovations is possibility to gain a large competitive advantage and create huge value for company (Christensen, 2005). These innovations, however, require large capital and well‐organized processes within R&D. These are serious obstacles for polish companies. Regardless of the type of innovation, decision on starting the innovation process are often made on the basis of the level of costs to be incurred as a result of this process. The accuracy of the cost determination is reflected in the quality of decisions, therefore the costs should be estimated at the appropriate time to obtain reliable results with the required accuracy. Based on the research on innovation processes in Polish companies, it was observed that the cost estimates were carried out only in the early planning stages of the innovation process. Estimating costs at this stage, in the absence of complete information about the innovation process can be carried out only in an intuitive way. The results depend only on the knowledge and experience of the person entrusted with the task of estimating costs. The results are not very accurate and the differences in the assessment of the cost compared to the actual costs of the process of innovation often reach tens of percent. Because managers are aware of these inaccuracies, the estimated costs are often overstated. It is safer to overestimate costs than underestimate them, which may require to interrupt the process of innovation because of exceeding the budget. But on the other hand, the innovation process with overestimated cost can be rejected. For these reasons, estimating the cost of innovation processes should be carried out using methods that will reduce the size of errors. It was also observed that in most cases decisions were made intuitively. Such conduct was the result of lack or uncertainty of information. Even though intuition is considered a highly useful human faculty, it is still somewhat controversial to use intuition as the basis for decision making, because it is seen as opposing analytical forms of thinking (Sundgren and Styhre 2004).

4. Cost estimating in the innovation processes It is vital that estimate the costs of the innovation process in the early stages of planning. This is due to the need to secure adequate funding for the implementation of this process. Knowledge of the costs can also specify the cost‐effectiveness of the process in relation to the expected benefits of innovation. The nature of innovation processes, especially the sequential nature of the phases, complicates this task. Therefore, on the basis of the Stage‐Gate model which accurately reflects the relationship of individual stages, was proposed a gradual process of cost estimating. Each of the successive phases of the process allows to obtain further information relevant to the estimation of costs. Therefore, each next step of cost estimation takes into account the increase of knowledge about the process. This leads to more accurate results. Model for cost estimating of the innovation process should therefore indicate places of cost estimation which are important for making decisions. It should also allow the use of appropriate techniques for cost estimating matched to the accuracy of the information. In the innovation processes the places where plans are developed are also suitable places to perform cost estimation (Jurczyk‐Bunkowska 2012). Hence, we can distinguish cost estimation for each phase of the innovation process. Within each phase is carried out further details the plans, which allows to distinguish three stages of cost estimation due to accuracy (figure 3):

budgeting ‐ including cost estimation when specified area of innovation, defined goal of innovation, type of innovation and time horizon,

cost estimation of innovation process phases ‐ are indicative estimated cost of each phase of the innovation process developed on the basis of partial objectives that describe the expected results of each phase,

cost estimation of innovation process tasks ‐ provides the most accurate estimate of costs based on detailed plans for the implementation of the different phases that describe the tasks to carry out and the allocated resources.

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5. Cost estimation techniques 5.1 Budgeting The size of the budget is an important criterion in the decision to initiate the process of innovation. It also allows you to secure the financial resources to ensure the safe conduct of the process. Innovation processes often require large financial outlays. Frozen funds for the duration of the innovation process can lead to reduce the possibility of the activities in other business areas. Therefore, a good solution is to define separate budgets for each phase of the innovation process. There is no blocking of large financial resources. If funds are missing, we gain the time needed to collect them before we start the phase of the innovation process. Funds are launched when you start the next phase of the process. It allows rational financial management. Due to a dynamic nature of innovation processes planned budget should be flexible. Do not forget that. Therefore, dividing it into different phases of the process, we provide the possibilities of flexible shifting of funds between budgets of each of the phases, if necessary.

Source: Author Figure 3: Idea of cost estimation in innovation process planning Budgeting of innovation processes is an expenditure estimation based on the overall design of the innovation process: identified the area of innovation, objective of innovation, time horizon and type of innovation. These general guidelines do not allow for determine precisely the necessary expenditures for future innovation process. The most accurate cost estimation techniques in the area of budgeting belongs to bottom‐up method (Nordern 2010). They require the development of detailed plans of the process. For process innovation is not possible because the results of the successive phases of the process have an influence on the course of the next phase. Therefore, in this case we can use only the methods of top‐down and zero‐level budgeting. For the techniques belonging to the first group includes methods analogous. Their application requires a reference material ‐ a database of innovation processes carried out in the past. In the analogous methods, the cost is determined on the basis of similarity assessment to the object, the cost of which is known. Examples of analogous methods are: regression analysis (Lewis 2000), neural networks with back‐propagation (Chen and Chen 2002) , hierarchical methods (Hair et al. 2010). Zero level budgeting is used when there is no comparative material. This situation occurs when the company realize the innovation process first time. In this case, it is possible to estimate the budget on the basis of knowledge, experience and intuition. In zero‐level budgeting method are used expert systems. The inaccuracy of the results is mainly due to subjective judgments of experts.

5.2 Estimating the cost of the phases of innovation process Planning phases of innovation processes is based on defined sub‐objectives. There are three main phases: front end, development and commercialization. The first phase is to generate innovation ideas, their development, analysis and evaluation. This should lead to select those solutions which yield the greatest guarantee for success. Next phase of the innovation process is the development of the approved innovation ideas and the necessary research and tests to prove the possibility of their implementation. Implementation of innovation takes place in phase called commercialization. Defined objectives of each phase also determine the effects that it intends to get after their completion. These effects are important information for cost

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Piotr Chwastyk estimation process. Front end is an analysis and evaluation of the proposed solutions. Number of ideas to evaluate is a parameter that will determine the amount of costs. Development phase is to analyze the details of an innovative solution that determine the level of novelty. Cost estimation can be performed based on the number and type of novelty used in innovative solution. The aim of commercialization phase is to reach specific groups of customers. In this case, the determinant of the cost will be size of diffusion of innovations such as market area. In the planning of phases in the innovation process we have reason to use parametric methods (Cavalieri et al 2004). In these cases, costs will be a functions of the parameters describing the desired effects of each of the phases.

5.3 Cost estimation of tasks within the phases of the innovation process The next level of detail in the plan of the innovation process occurs in the definition of the tasks to be performed. This is the operational planning. Applies to determine the tasks, assign them the resources and the determination of their duration. This is defined also the order of the tasks and their priorities to achieve the desired result. These data permit an estimation of the costs with a high degree of accuracy. In this case, the analytical methods are used. The cost of single task is estimated and suitable summing the costs of all tasks let calculate the total cost of the phase. To determine the costs at the operational level can use methods tailored to the type of innovation. Examples of this methods are ABC (Activity Based Costing) (Cooper and Kaplan 1988) and FBC (Features Based Costing) (Brimson 1998).

5.4 Comparison of selected methods for cost estimation The most important decisions are made at the beginning of the innovation process. For this reason, the cost estimation using qualitative methods are favored. This is because they allow to predict the cost of the entire process without the need for detailed information on the process. Although the accuracy of these methods may be questionable, qualitative methods provide a good platform for the entire decision‐making process that accompanies all phases of the innovation process. However, managers often stop with the cost estimation by qualitative methods. Trusting their intuitions or expert evaluation, accept the results. They do not try to verify the cost of processes, even if the emergence of new information provides opportunities for this. Accept the differences between estimated costs and actual costs, as long as the level of costs will not significantly exceed the budget. For this reason, most often occurs, in the case of innovative projects, the cost overestimation that will freeze financial resources. This results in the freezing of large financial resources that could be used for other purposes. For this reason it is necessary to estimate the cost of innovation processes using different methods, applying the principle of selection of increasingly accurate methods when the process plan is supplemented by subsequent information. To cost estimation a lot of methods can be used. Some of them were listed in this publication. These methods, among which you can choose the ones that allow to obtain reliable results on the basis of available data. Each of these methods has a number of advantages, but each has its limitations (table 1). Those responsible for cost estimating of the innovation process should be knowledgeable about existing methods and choose this one for which the reliability of the results did not raise objections. The solution for cost estimating of innovation processes, as shown in figure 3, consists of three stages. The places for cost estimating was chosen so that allowed to obtain more detailed information on the expected cost. Therefore allows the use various methods starting with qualitative methods and ending with accurate quantitative methods. The possibility of applying different techniques for estimating the cost of innovation in the planning process is shown in figure 4.

6. Summary The proposed idea of cost estimation is the answer to the problems of decision‐making in the planning and implementation of innovation processes. The main advantages of this approach in costs estimating are:

Obtaining information about future costs in important places of innovation process for decision‐making. The level of costs is, in most of the cases, a decisive factor for initiation and continuation of the process. Knowing what costs will be incurred as a result of planned activities is a valuable information for management of innovation process.

Verification of the results. Repeatedly estimating the cost with using different estimation techniques is the ability to verify the previous results.

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The accuracy of the results. The gradual process of estimating costs is assumed that with the increase of knowledge about the process it is possible to accurately estimate the costs. With the development of more detailed plans may be used more accurate cost estimation techniques, from the intuitive methods at an early stage of the innovation process, to the analytical methods at the operational level.

Flexibility in financial management. If cost estimation is performed once, only at the beginning of the process of innovation, require the freezing of funds for the implementation of the all process. Cost estimation carried out for each of the phases of the innovation process can specify separate funds for each of them. This allows for better and more flexible financial management by collecting funds according to needs. Do not freeze the whole amount for the implementation of the process but only the part needed for completion of the phases of the process. This is particularly important for innovation for the long term horizon time.

Standardization. The same approach to estimating costs for each of the processes of innovation in the enterprise to unify procedures for managing these processes.

Table 1: Characteristics of the selected techniques for cost estimation Cost Estimation Techniques

Key Advantages Innovative design approach

Limitations Dependence on past cases

Can provide optimized results

Time‐consuming

Case Based Systems

Intuitive Cost Estimation Techniques

Qualitative Cost Estimation Techniques

Decision Support System

Rules Based Systems Fuzzy Logic Systems Expert Systems

Analogical Cost Estimation Techniques

Handles uncertainty, reliable estimates Quicker, more consistent and more accurate results

Regression Analysis Models

Simpler method

Back‐Propagation Neural‐ Network (BPNN) Models

Deal with uncertain and non‐linear problems Utilize cost drivers effectively

Parametric Cost Estimation Techniques Quantitative Cost Estimation Techniques

Analytical Cost Estimation Techniques

Feature‐Based Cost Models

Features with higher costs can be identified

Activity‐Based Cost (ABC) Models

Easy and effective method using unit activity costs

Estimating complex features costs is tedious Complex programming required Limited to resolve linearity issues Completely data‐ dependent, Higher establishment cost Ineffective when cost drivers can not be identified Difficult to identify costs for small and complex features Reąuire lead‐times in the early project stages

Source: (Niazi 2006)

Source: Author Figure 4: Cost estimation techniques in innovation process planning

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Piotr Chwastyk Providing reliable information is a guarantee of quality of decision making. Cost information can achieve this credibility by using more efficient estimation methods. The most accurate methods require data that are achieved only in the advanced stage of the process. But more valuable is the knowledge of the costs in the early stages of the planning process. Using expert methods is conscious acceptance of mistakes caused by subjective judgment. It is better to use a method analogous. They are more accurate but require appropriate reference material. Polish companies are focused primarily on incremental innovation. It is of great importance for analogous methods. Making many small innovation allows to collect a large number of data about implemented processes that can be used to search for similarities. The bigger is set of realized processes the more accurate the results. The proposed approach for estimating the cost of innovation processes is a response to the needs of businesses. The proposed gradual cost estimation increase the accuracy of the results, provides a basis to verify the process of planning and leads to making the right decisions in situations where deviations from the plans can threaten achievement of the desired objectives.

Acknowledgements Author would like to thank Polish Government Agency: National Science Centre for financial support of this research project (Nr 4025/B/H03/2011/40)

References Brimson, J. A. (1998) Feature Costing: Beyond ABC, Journal of Cost Management, No 12/1, pp. 6–12. Cavalieri, S., Maccarrone, P., Pinto, R. (2004) Parametric Vs Neural Network Models for the Estimation of Production Costs: A Case Study in the Automotive Industry, The International Journal of Production Economics, No 91/2, pp. 165–177. Chen, M. Y., Chen, D. F. (2002) Early Cost Estimation of Strip‐Steel Coiler Using BP Neural Network. Proceedings of 2002 International Conference on Machine Learning and Cybernetics, Beijing, Piscataway, NJ, Vol. 3, pp. 1326–1331. Christensen, C. M. (2005) The Innovator’s Dilemma, Collins Business Essentials Cooper, R. and Kaplan, R. S. (1988) How Cost Accounting Distorts Product Costs. Management Accounting, No 69/10, pp. 20–27. Cooper, R. G., Edgett, S. J., Kleinschmidt, E.J. (2003) Best Practices in Product Innovation: What Distinguishes the Top Performers, whitepaper available at the Product Development Institute website (www.prod‐dev.com) Frambach, R.T. and Schillewaert, N. (2002) Organizational innovation adoption: A multilevel framework of determinants and opportunities for future research, Journal of Business Research, No. 55, pp. 163–176. Gatignon, H. and Robertson, T.S. (1989) Technology diffusion: an empirical test of competitive effects, Jurnal of Marketing, No. 53 (1), pp. 35–49. George, L. K. (1998) Rational choice theories Contributions and limitations, Journal of the American Society of CLU & ChFC, 52, (5), pp. 32‐39. Jurczyk‐Bunkowska, M. (2012) The Role of Planning In Innovation Success: Experience of Leading Polish Enterprises. Proceedings of the 7th European Conference on Innovation and Entrepreneurship, Published by Academic Publishing International Limited Reading, UK, 2012, pp. 90‐96 Hair, J. F., Black, W. C., Babin, B. J. and Anderson, R. E. (2010) Multivariate Data Analysis, 7th edition. Prentice Hall: New Jersey. Lewis, J. (2000) Metrics Mapping Cuts Estimating Time. Design News, No 55/18, pp. 107–110. Maguire, S. (2002) Discourse and adoption of innovations: A study of HIV/AIDS treatments, Health Care Management Review, 27 (3), pp. 74‐89. McCardle, K. F. (1985) Information Acquisition and the Adoption of New Technology, Management Science, 31 (11), pp. 1372‐1389. Nordern Ireland Assembly, Research and Library Service (2010) Methods of Budgeting, Research Paper 06/10. Oliva, T. A. (1991) Information and Profitability Estimates: Modeling the Firm's Decision to Adopt, Management Science; May 1991; No. 37,Vol. 5, ABI/INFORM Global p. 607. Rogers E.M. (1995) Difusion of innovations, The Free Press, 4th ed., New York. Rothwell R. (1992) Successful industrial innovation: critical factors for the 1990s’, R&D Management, Vol. 22, No. 3, pp.221–39. Sundgren, M. and Styhre, A. (2004) Intuition and pharmaceutical research: the case of AstraZeneca, European Journal of Innovation Management, No 7(4), pp. 267‐279.

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Platform Strategies for Open Government Innovation Brian Cleland, Brendan Galbraith, Barry Quinn and Paul Humphreys Department of Management and Leadership, University of Ulster, UK brian_cleland@yahoo.com b.galbraith@ulster.ac.uk b.quinn@ulster.ac.uk pl.humphreys@ulster.ac.uk Abstract: The concept of Open Innovation, that inflows and outflows of knowledge can accelerate innovation, has attracted a great deal of research in recent years (Dahlander and Gann, 2010; Fredberg et al, 2008). At the same time there has been a growing policy interest in Open Government, based in part on the assumption that open processes in the public sector can enable private sector innovation (Yu and Robinson, 2012). However, as pointed out by Huizingh (2011), there is a lack of practical guidance for managers. Furthermore, the specific challenges of implementing Open Innovation in the public sector have not been adequately addressed (Lee et al., 2012). Recent literature on technology platforms suggests a potentially useful framework for understanding the processes that underpin Open Innovation (Janssen and Estevez, 2013; O'Reilly, 2011). The paper reviews the literature on Open Innovation, e‐Government and Platforms in order to shed light on the challenges of Open Government. It has been proposed that re‐thinking government as a platform provider offers significant opportunities for value creation (Orszag, 2009), but a deeper understanding of platform architecture will be required to properly exploit those opportunities. Based on an examination of the literature we identify the core issues that are likely to characterise this new phenomenon. Keywords: open innovation, e‐Government, platforms

1. Introduction 1.1 Background The growth of interest in open innovation since Henry Chesbrough’s publication in 2003 of Open Innovation: The New Imperative for Creating and Profiting from Technology has been well documented (Dahlander and Gann, 2010; Fredberg et al, 2008, Huizingh, 2011). While the majority of the literature focuses on private sector activities, a parallel surge of interest in the innovation potential of open government has been attracting much attention from policy‐makers and commentators (Noveck, 2009; Robinson et al., 2009), triggered by renewed interest in the role of technology in the public sector and by initiatives within the White House, EU and elsewhere (Yu and Robinson, 2012). The primary vehicle for the open government agenda has the online publication of public sector information – the so‐called “open data” movement. This internet‐centric approach has meant that the discussion around open government has merged to some extent into the e‐Government debate. It has even been suggested that this new emphasis on openness, co‐creation and digital technologies represents the next stage in the evolution of e‐Government (“e‐Government 2.0”) (Chun et al., 2010; Baumgarten and Chui, 2009; Mergel 2010). The question of how these proposed changes to governance might be implemented has inspired increased interest in the lessons that can be learned from web‐based businesses such as Google, Facebook, Amazon, eBay and Wikipedia (O’Reilly, 2011, Fishenden and Thompson, 2012). It has been noted that these private sector organisations have adopted a platform structure in order to sustain a vibrant ecosystem of external innovators. Following this approach, it has been proposed that e‐Government might become a platform for private sector and citizen‐centred innovation. Many issues have yet to be resolved, however. For example, the distinctive characteristics of public sector platforms have not yet been clearly defined; i.e., in what respect might they resemble or differ from their industry counterparts? Generally, there appears to be a gap between the research and the practical guidance required by public sector managers (Huizingh, 2011; Heeks and Bailur, 2007; Meneklis and Douligeris, 2010). Furthermore, the platform literature is complex and multifaceted, encompassing as it does research from at least three diverse fields (i.e., product management, software development and economics). Finally, the

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Brian Cleland et al. appropriateness of the platform concept as a metaphor for government is not universally accepted (DiMaio, 2009).

1.2 Structure The structure of the paper is based on three research streams: open innovation, e‐Government and platforms. These topics were selected for their relevance to the issue at hand (open government innovation) and the breadth and depth of the available literature. For each field we provide a brief overview and then identify key themes from the research, with a particular emphasis on recent studies that suggest inter‐topic linkages. The order of discussion is: open innovation, followed by e‐Government, and finally platforms. We then discuss the sub‐themes which connect these areas of research, and propose a theoretical framework that allows us to encapsulate the most important findings. Finally, we highlight gaps in the literature and propose some questions for future research.

2. Open innovation 2.1 Overview Much evidence has been provided to support the proposal that innovation is a key driver for competiveness, profitability and sustainable growth (Drucker, 1988; Christensen, 1997). One model of innovation management that has gained much attention and popularity in the last decade is based on the assumption that companies should open up their innovation processes and integrate the products of internal and external innovation. The concept of open innovation was first defined by Henry Chesbrough as: “the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and expand the markets for external use of innovation, respectively”. (Chesbrough, 2006) Chesbrough (2003b) illustrates his ideas by contrasting the so‐called traditional “closed innovation model” with the new paradigm of open innovation, stating that factors such as the increased mobility of knowledge workers and the development of new financial instruments have caused the boundaries of the innovation process to start breaking up. It has been proposed that open innovation encompasses a diverse range of practices, such as customer and supplier integration, innovation clustering, innovation across industries, trading intellectual property and investing in global knowledge creation (Gassmann and Enkel, 2004).

2.2 Criticisms of open innovation Despite its popularity, Chesbrough’s work has not been without its critics. One of the criticisms has been that it is merely “old wine in new bottles” (Trott and Hartman, 2009). Trott and Hartmann point to the history of research in R&D management, where Chesbrough’s ideas were pre‐empted by Alan Pearson and Derek Ball over 30 years ago (Pearson et al., 1979; Griffiths and Pearson, 1973), and by the network model of innovation management (Rothwell and Zegveld, 1985) which was developed over 20 years ago. Trott and Hartmann accuse Chesbrough of erecting a “straw man argument” in the form of “closed innovation systems” that he can easily demolish and refute. In order to illustrate this, they go through each of the “principles” of closed innovation and compare them to the literature, thus attempting to demonstrate that Chesbrough’s “false dichotomy” does not really exist in industry. Similarly, Huizingh (2011) states that “it is clear that the roots of open innovation go far back in history” – a claim supported by Christensen et al. (2005). Mowery (2009) suggests that closed innovation – assumed by Chesbrough (2003) to be the dominant model ‐ might have actually been the exception in a history characterized mostly by open innovation practices. Galbraith and McAdam (2011) point out that a great deal of research still needs to be done to create a ‘consistent open innovation theory’. They state that Chesbrough’s model is overly broad in its current form, and on this basis it should be revisited and amended.

2.3 Popularity of open innovation If Chesbrough’s model suffers, as is claimed, from both overly‐simplification and a lack of originality, then how does one explain its current popularity among researchers? After all, his 2003 book gained more than 1,800 citations in just seven years and a wide range of disciplines, including economics, psychology, sociology, and even cultural anthropology have shown interest in it (Huizingh, 2011).

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Brian Cleland et al. According to Dahlander and Gann (2010) there are at four main reasons for its common currency: (1) it reflects social and economic changes in working patterns; (2) globalisation allows for an increased division of labour; (3) improved market institutions such as intellectual property rights, venture capital, and technology standards allow for organisations to trade ideas; (4) new technologies enable collaboration across greater geographical distances. Huizingh (2011) explains its attractiveness to scholars and practitioners in the following way: (1) Chesbrough assigned a single term to a collection of already existing activities; (2) the timing coincided with the increased interest in outsourcing, networks, core competences, collaboration, and the internet; (3) Chesbrough’s work offers opportunities for theoretical extension, which in turn further stimulate proliferation; (4) Chesbrough connected the processes of acquiring external knowledge and exploiting internal knowledge externally by placing them both under the open innovation umbrella.

2.4 Free revealing and open innovation Although Chesbrough remains a key thinker within this field, other researchers have begun to redefine the concept of open innovation. One important trend is the evolving theory on the role of intellectual property, and on the various mechanisms of innovation diffusion. While Chesbrough and much of the early literature focused on intellectual property as a core asset and its applications within technology transfer and spin‐ out/spin‐in (Fredberg et al, 2008), the scope of research has broadened in recent years. Ideas drawn from Open Source Software have become increasingly important (Gruber & Henkel, 2006; West & Gallagher 2006), and the term itself is still under debate. One of the more influential ideas has been the concept of "free revealing" as developed by Von Hippel and Von Krogh (2006) as part of their research into User Innovation. They suggest that free revealing is practised far beyond the confines of open source software development. Henkel (2006) argues that smaller firms with less internal resources are more likely to make use of revealing, and that the "selective revealing" is deployed to minimise competitive loss. Some, including Badem (2008), have asked whether there is a tension between openness and the protection of ideas. An idea closely‐related to free revealing, that appears in the literature on business networks and clusters, is that of “knowledge sharing between firms through the medium of untraded interdependencies ‐ knowledge exchanged informally and without explicit compensation” (Tallman et al., 2004). Storper (1993,1995,1997) introduced the idea of “untraded interdependencies” as “socially driven exchanges” which no market mechanism exists. Kogut, et al. (1994) suggest that firms and their suppliers share not only tradable resources, but they also share knowledge that is integral to the social community ‐ a “public good” for all members. It is notable that von Hippel’s conception of free revealing also requires than information is treated as a “public good” (Baldwin and von Hippel, 2010; Harhoff and von Hippel, 2003). Dahlander and Gann (2010) recognise this dimension of open innovation research by suggest that open innovation practises can be either pecuniary or non‐pecuniary, where non‐pecuniary open innovation is defined as that which presents no immediate financial rewards. They thus present an analysis of open innovation in two dimensions: inbound versus outbound, and pecuniary versus non‐pecuniary. These two dimensions of open innovation are used to produce a framework with four types of openness: acquiring, selling, sourcing and revealing. Where, then, do the research gaps exist? A review of the literature shows that the primary focus to date has been on open innovation in the private sector, with limited research having been been done on the public sector (Lee et al., 2012). To understand the context in which such research might take place, the following section will consider how the e‐Government has evolved to embrace openness as a driver for public sector innovation.

3. E‐Government 3.1 Background and definitions According to Yildiz (2007), early researchers into government technology treated technological factors as “peripheral”, outside of the primary management function. The role of technology from this perspective was

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Brian Cleland et al. to support improved decision‐making (Simon, 1976). Independent adoption of technology by government bodies lead to a “stovepipe” architecture (Aldrich et al., 2002). While academic interest in this area continued to grow throughout the 1970s and 80s (Danziger et al., 1982; Bozeman and Bretschneider, 1986), it was not until internet access became commonplace that the e‐Government concept really emerged (Ho, 2002). It has been argued that the events of September 11, 2001 triggered a change in perception of e‐Government – whereby the role of technology in strengthening national security became a core focus (Halchin, 2004; Seifert & Relyea, 2004). A number of authors have pointed out the tension between this security‐focused approach and the original principles of e‐Government (Doty and Erdelez, 2002; Halchin, 2004; Hernon, 1998). Perhaps unsurprisingly, no single definition for e‐Government has been universally adopted (Halchin, 2004). E‐ Government is defined by the UN as “utilizing the Internet and the World‐Wide‐Web for delivering government information and services to citizens” (UN & ASPA, 2002). Hernon describes it as “simply using information technology to deliver government services directly to the customer 24/7”, where “the customer can be a citizen, a business or even another government entity” (Duffy, 2000). Brown and Budney (2001) have broken down e‐Government actions into three categories: Government‐ to‐Government (G2G), Government‐ to‐Citizen (G2C), and Government‐to‐Business (G2B). Yildiz (2003) adds two more categories: Government‐to‐ Civil Societal Organizations (G2CS) and Citizen‐to‐Citizen (C2C).

3.2 From e‐Government to Open Government It has been suggested that the next stage in the development of e‐Government (“e‐Government 2.0”) involve adopting the principles of open innovation and user participation (Baumgarten and Chui, 2009; Chun et al., 2010). It is worth pointing out, however, that the concept of “open government” predates the internet era. Yu and Robinson (2012) argue that the idea of open government emerged as a result of the American “peacetime dividend“ following World War 2. The first published explanation of the term open government was Wallace Parks’ 1957 article, The Open Government Principle: Applying the Right to Know Under the Constitution. Almost ten years later, in 1966, the US Congress passed the Freedom of Information Act, and in 1974 it noted that “[o]pen government has been recognized as the best insurance that government is being conducted in the public interest.” (Yu and Robinson, 2012). The current resurgence of interest in open government has largely been driven by the information‐ sharing potential of the internet. Yu and Robinson (2012) suggest that recent policy has been characterized by a tendency to use the term open government in an ambiguous way – so that it refers to both technological innovation (as exemplified by the “open data” movement) and to political accountability (the original meaning of the phrase) ‐ and that this ambiguity threatens to undermine both ideals. The innovation potential of open government has been strongly promoted by the Obama administration. The administration’s emphasis on technology and innovation may be connected to a presidential campaign that successfully leveraged online networks and data‐driven fundraising methods (Kreiss, 2012). In recent years the open government / open data policy agenda has been promoted within the US through the Open Government Directive, and internationally through the Open Government Partnership (OGP, 2013). Related efforts, such as the European Union’s 2003 Directive on the Re‐use of Public Sector Information (Janssen, 2011) and the UK government’s Power of Information Taskforce Report (Mayo and Steinberg, 2007) demonstrate that other governments also recognise the value of open government data.

3.3 Open Government platforms A related trend, identified by Dunleavy and Margetts (2010), has been the shift within government away from new public management (NPM) (James and Manning, 1996; Cochrane, 2000; McNulty and Ferlie, 2004) towards what some have called digital era governance (DEG). A key aspect of DEG is the digitisation of government ‐ including technological innovations such as cloud computing, social networks and open data (Dunleavy et al., 2005). Fishenden and Thompson (2012) argue that an open platform architecture will be required to deliver DEG, and that inspiration should be drawn from platform businesses such as Google and Facebook. The theme of open government platforms has also been explored by O’Reilly (2011), who argues that “government is, at bottom, a mechanism for collective action” and that government 2.0 should be “an open

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Brian Cleland et al. platform that allows people inside and outside govern‐ ment to innovate. O’Reilly (2011) presents the platform model as an alternative to “vending machine government” (Kettl, 2002). Similarly, the core principles of what Janssen and Estevez (2013) call “lean government” include public involvement, platforms and orchestration. They argue that government’s role as orchestrator is to “control the platform and associated resources to coordinate the activities of the many stakeholders”. Others, however have pointed out potential flaws in the “government as platform” model, including issues related to the regulatory environment, public sector motivations, and the dual role of government as both platform provider and platform consumer (DiMaio, 2009). This recent focus on government platforms for open innovation suggests that we need to consider in more detail the extensive literature on platform architectures. This topic defines the third and final research stream for our study.

4. Platforms 4.1 Theoretical contexts The platform concept has been used to inform theoretical analysis in at least three distinct fields: product development (Wheelwright and Clark, 1992; Kogut and Kulatilaka, 1994; Kim and Kogut, 1996; Sawhney, 1998), software‐based business strategies (Bresnahan and Greenstein, 1999; Gawer and Cusumano, 2002) and economics (Rochet and Tirole, 2003; Parker and Van Alstyne, 2005; Evans, et al., 2006; Eisenmann, 2008; Hagiu, 2009). Baldwin and Woodard (2009) have argued that the term has a consistent meaning across these different domains ‐ whereby a platform is a system defined by three aspects: (1) a stable, low‐variety "core", (2) a changeable, high‐variety set of "complements", and (3) the interfaces which allow core and complements to operate as a single system. In this section we review some of the key concepts that have emerged from the literature.

4.2 An architecture for innovation? The term "platform architecture" has been interpreted in various ways by different authors. Ulrich (1995) defined product architecture as "the scheme by which the function of a product is allocated to physical components", and specifically included interfaces within this definition. In their discussion of modular systems, Baldwin and Clark (2000) consider architecture as a description of the relationship between modules and functions, and suggest that architecture, interfaces and standards together comprise the "design rules" of such a system. Whitney et al. (2004) state that architecture includes (1) a list of functions, (2) the components required to carry out those functions, (3) the connections and interfaces between the components and (4) a description of the system's operation under changing conditions. Tiwana et al (2010) define platform architecture as "a conceptual blueprint that describes how the ecosystem is partitioned into a relatively stable platform and a complementary set of modules that are encouraged to vary, and the design rules binding on both". A common rationale for platform architectures is that such structures enable higher rates of innovation. It has been argued that modular systems in general are particularly supportive of innovation (Baldwin and Clark, 1997) by allowing for more rapid trial‐and‐error‐learning (Nelson and Winter, 1977) and greater autonomy (Chesbrough and Teece, 2002), although the generalisability of such claims have been challenged by Miozzo and Grimshaw (2005). Furthermore, Kirschner and Gerhart (1998) argue that the conservation of core processes in biological systems facilitates evolution by supporting complementary processes that allow for variation and adaptation. Baldwin and Woodard (2009) argue that this biological principle should apply to platform designs generally, and that partitioning should reduce the cost of innovation in man‐made systems. The benefits of platform design generally come at a price, however ‐ as Langlois (2002) points out, “there is no free lunch". According to Baldwin and Clark (1997), "modular systems are much more difficult to design than comparable interconnected systems". A major challenge for the platform architect is knowing where the boundary between core and complements should lie ‐ in other words, "which components should remain stable and which should vary" (Baldwin and Woodard, 2009). Langlois (2002) highlights the difficulty of defining encapsulation boundaries in a dynamic environment, where it is impossible to effectively partition tasks in advance due to the fact that knowledge is constantly changing (von Hippel, 1990).

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4.3 Platform regulation Apart from the partitioning problem, a key challenge in platform design is the effective use of regulation in order to influence participants and thereby drive value generation and capture. A number of studies have referred to the regulatory role of platform owners (Rochet and Tirole, 2004; Iansiti and Levien, 2004; Farrell and Katz, 2000). Boudreau and Hagiu (2008) consider in detail at the use of non‐price instruments in a variety of multi‐sided platforms (MSPs) and conclude that regulation involves a wide range of legal, technical, informational and other instruments, often applied in concert. Tiwana et al (2010) propose that platform governance can be considered from three distinct perspectives: (a) decision rights partitioning, (b) control, and (c) proprietary versus shared ownership. In their analysis of government platforms, Janssen and Estevez (2013) suggest that "orchestration" is key, by which they mean the "arrangement, coordination, and management of complex networks in which public and private parties conduct tasks". Effective regulation (or governance/orchestration) requires an understanding of the dynamics of user communities. Boudreau and Lakhani (2009) state that a key question for platform owners is whether external innovators should be organised as a competitive market or a collaborative community, and identify three factors for consideration in this decision. Issues of motivation are also considered by Antikainen et al (2010), who note that the majority of existing reward mechanisms appear to increase participation but not collaboration. It is important to note that motivational mechanisms must be chosen carefully. For example, Frey et al (2011) suggest that intrinsic motivation leads to more substantial contributions than extrinsic rewards. Inappropriate reward systems may be counter‐productive, or even damaging. There is strong evidence, for example, that extrinsic rewards can have a negative effect on intrinsic motivation (Deci et al 1999).

4.4 Ownership and value The issue of ownership has also been identified as an important concern for platform providers (West, 2003). Tiwana et al. (2010) point out that decision rights for the platform need not belong exclusively to the owner, and that decision rights for modules need not belong exclusively to module developers. The challenge, they suggest, is to balance autonomy for external innovators with the need for a coordinated ecosystem. Decisions around access and control can also affect the type of user that is attracted to the platform (Belenzon and Schenkerman, 2008), and the overall rate of innovative activity (Boudreau 2010). Connected to the idea of ownership is the question of how to ensure that value generated by the platform can be suitably appropriated. Chesbrough (2003b) states that platforms can "combine internal and external innovations in ways that create value". He claims that just as value creation is vital for platform adoption, so value capture is necessary for platform sustainability. According to Baldwin and Woodard (2009), the ability of platforms to generate value depends on the "option potential" in the complementary modules. It is argued that external innovators will be drawn to the platform is there is option value in the complements, unless excessive appropriation of value occurs. Iansiti and Levien (2004) describe excessive value capture as a "dominator strategy" which runs the risk of starving and destroying the platform's ecosystem.

4.5 Platform evolution In their review of platform‐based innovation models, Boudreau and Lakhani (2009) emphasise that strategies should not be "cast in stone", highlighting the example of the iPhone App Store, which achieved success by converting a community of external innovators into a centralised and controlled marketplace. Tiwana et al (2010) propose a detailed framework for analysing platform evolution. Specifically, they consider the impact on platform evolution of three coevolving factors: (1) platform design, (2) platform governance and (3) environmental dynamics. Evolution is not solely the responsibility of the platform owner, however, and the role of customers in co‐creating modules and driving platform evolution is highlighted by Pekkarinen and Ulkuniemi (2008). It is also worth bearing in mind that the most attractive and durable systems often develop through an "unselfconscious" process, where "the rules are not made explicit, but are, as it were revealed through the correction of mistakes" (Alexander, 1964).

5. Emerging themes Based on our research we have identified four cross‐cutting themes that are likely to influence the design and governance of open government platforms:

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5.1 Information flows and interfaces Information flows are central to the definition of open innovation (Chesbrough, 2003a). Directionality is important ‐ flows can be inside‐out, outside‐in or coupled (Gassmann and Enkel, 2004). Similarly, the development of e‐Government models has been defined by the direction of communications (Layne and Lee, 2001; Schelin, 2003) between various categories of stakeholder (Brown and Budney, 2001; Yildiz, 2003). Multi‐ sided platforms can be said to mediate transactions between stakeholders (Rochet and Tirole, 2003; Baldwin and Woodard, 2009).

5.2 Regulatory mechanisms Mechanisms for identifying the best solutions to a given problem and for rewarding contributors,have been explored by various authors in the context of open innovation (Terweisch and Xu, 2008; Antikainen et al., 2010; Bakici et al., 2010). Mechanisms for promoting trust, participation and communication have also been addressed within studies on e‐Government (Linders and Wilson, 2011; Lim et al., 2011; Fishenden and Thompson, 2012). Platform researchers have examined related issues in depth (Tiwana et al., 2010; Parkes, 2007).

5.3 Value generation, measurement and capture Chesbrough (2003b) focuses on the importance of the open innovation business model to ensure that value can be captured and that the innovation process is sustainable. It has been claimed that platforms create value through the provision of real options (Fichman, 2004) and that they can capture value through various appropriation mechanisms (Baldwin and Woodard, 2009; Iansiti and Levien, 2004). In the context of e‐ Government, questions relating to measuring and capturing value are arguably more complex, as evidenced by debates over the meaning of public sector value (Irani et al., 2005; Heeks, 1999; Bannister, 2001) and the role of government‐owned intellectual property rights (IPR) (Reichman and Samuelson, 1997; Suber, 2009).

5.4 Ownership and partitioning Related to the debate over IPR and value capture is the question of ownership. Platforms for open government need not be government‐owned – they may be community‐owned (e.g., as an open source project) (Hogge, 2010) or privately owned (e.g., by a commercial open data platform provider). Indeed, open innovation studies indicate that the intermediary function is often carried out by a third party (Gassman et al., 2010). One justification for open government platforms is that they partition the stable, government‐controlled core from the dynamic ecosystem of private innovators (O’Reilly, 2011), but defining natural boundaries is a challenge for any platform architect, particularly in a changing environment with limited knowledge (Langlois, 2002). For public sector platform designers, the difficulty may be compounded by controversies over the proper size and scope of government (O’Reilly, 2011; Janssen and Estevez, 2013).

6. Further research 6.1 Theory vs practice The gap between theory and practice in e‐Government has been highlighted by a number of studies (Yildiz, 2007; Heeks and Bailur, 2007; Meneklis and Douligeris, 2010). Huizingh’s review of the literature on open innovation emphasises the need of managers for practical frameworks (Huizingh, 2011). Future investigations into government platform strategies should consider addressing this gap.

6.2 Public vs private platforms Within the literature on both open innovation and platforms, the focus has been predominantly on the private sector. The public sector provides a very different context, including regulatory requirements (DiMaio, 2009), cultural norms (Borins 2001), questions around value measurement (Irani et al., 2005) and value capture (Reichman and Samuelson, 1997), and other factors. Empirical research on the differences between emergent e‐Government architectures and established industry models would cast a useful light on these issues.

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6.3 Design, governance and environment Tiwana et al. (2010) describe a tripartite model of interacting dynamics – design, governance and environment ‐ that influence platform evolution. A distinctive mixture of endogenous and exogenous factors will shape the development of government‐owned platforms in ways that have yet to be fully explored. Questions of how to match architecture to governance (internal fit) and internal decisions to external conditions (environmental fit) will be important to ensure government platforms provide sustainable public value (Moore, 2005).

7. Conclusion The aim of this analysis was to understand the issues affecting platform strategies for open government from three distinct theoretical perspectives. These perspectives were chosen based on relevance to the core topic and the depth of existing research. We explored the major themes from each research area and subsequently identified four key questions for academics and practitioners. We also highlighted three important gaps in the literature where further research might contribute to both theory and practice. By drawing together these perspectives and highlighting emergent issues we hope to facilitate a deeper analysis of the role of government as an active participant in innovation ecosystems.

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Small and Medium Enterprises (SME) and Competitiveness: An Empirical Study Teresa Costa1 and Luísa Carvalho1, 2 1 Economics and Management Department, Business School, Setúbal Polytechnic Institute, Portugal 2 Center for Advanced Studies in Management and Economics (CEFAGE) University of Évora, Portugal teresa.costa@esce.ips.pt luisa.carvalho@esce.ips.pt Abstract: Globalisation and competitiveness affected the way of enterprises undertake innovation, particularly in the case of Small and Medium Enterprises (SME). According with European Commission (2013) in Europe 99% of the enterprises are SME. SME all over the world are considered as the lifeblood of the economies. The importance of this research is justified by the predominance of SME that represents the majority of enterprises in Portugal. SME contribute to the creation of jobs, as well as to the competitiveness of the economies, specially, in crisis time. This study has two main objectives; firstly propose a literature review focused on competitiveness of SME. Secondly analysis a sample of 23 enterprises identified as leaders of Portuguese SME in 2012. The data considering a ranking list of the largest 1000 Portuguese SME in 2012, published by Exame (2013). This analyze consider some SME features such as, sales, market share, dimension and sector. Additionally this research present a SME case included in this database. Through the application of a questionnaire the study provides a complementary micro perspective of the factors that influences enterprises competitiveness. The questionnaire is divided into 3 parts: part 1 refers to the characterization of the enterprise, part 2 assess the entrepreneurial competitiveness, considering 9 questions to assess performance, 6 questions to assess internal processes and 4 questions to understand the relations with customers, and part 3 analyse the diffusion of innovation through 3 questions. Finally the study provides important clues relevant for the development of public policies that can support the innovation and competitiveness of SME. Moreover the discussion highlight some variables approached in literature review considered as pertinent in the case of innovative SME due their contribution to exports and to economic growth. Keywords: competitiveness; diffusion of innovation; performance; SME

1. SME and competitiveness Competitiveness is a popular concept across different levels of studies and involves different disciplines such as comparative advantage and/or price competitiveness perspective, strategy and management perspective, as well as historical and socio‐cultural perspective (Nelson, 1992; Waheeduzzaman and Ryans, 1996). This concept is also understanding as the ability to increase market share, profit, growth, value added and to stay competitive for a long term (Ramasamy, 1995). Studies developed for O’Farell et al. (1992) research the relationship between sources of competitiveness and firm performance, considering price, quality, design, marketing and management. Additionally Slevin and Covin (1995) measuring the "total competitiveness" of SMEs, attending to several factors, such as, firm’s structure, culture, human resources, and product/service development. Other theoretical approaches (Stoner, 1987; Bamberger, 1989; Pratten, 1991; Chaston and Mangles, 1997) highlighted a number of firm specific factors respectively, financial, human and technological resources, organizational structure and system, productivity, innovation, quality, productivity, image and reputation, culture, product/service variety, flexibility and customer services. SMEs represent more than 90% of the enterprises in many countries (Gunasekaran et al, 2011; Poon and Swatman 1999, Cull et al. 2006, Ozgulbas et al. 2006). Furthermore, most of SMEs experiment a lack of market power and market turbulent and becomes more vulnerable to external influences than larger firms. Also internal sources of competitiveness are stressed in literature, specifically the human factor, i.e., the role played by the owner/manager and their skills and experience (Stoner, 1987). However, Salavaou et al, 2004 point out some advantages of SMEs over large companies due to its size and flexibility in adapting to change such as, market and learning‐oriented and when facing strong competition, tend to be more innovative and resilient.

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Teresa Costa and Luísa Carvalho Figure 1, presents some factors that influence the competitiveness of SME. The factors influencing competitiveness of SMEs can be divided into two groups, external and internal factors. Measuring competitiveness is a difficult task, because few values, indicators or features can be quantified and are accessible. Most of them are not quantifiable or accessible and have to be identified at corporate level.

Source: authors Figure 1: SME competitiveness Additionally, literature identified other factors that affect SME, Egbu et al. (2005), emphasize succession planning in the case of family business. Levy et al. (2003) argue that SME are excellent knowledge creators, but reveal limitations in the knowledge retention. Jorgensen and Knudsen (2006) refer other factor relevant to competitiveness of SME, their capabilities to action in global markets. For instance, the markets for semi‐manufactured goods become more global, and SME are more and more integrated into global value chains. Is consensual the role of SME in the national economy, and their contributes to GDP and to job creation. Globalization highlights the role of the global markets that could increase the opportunities for SME (Gradzol et al, 2005, Karaev et al. 2007). Though, to compete in the global market, SME have to enhance their individual competitiveness (Fassoula 2006) and as well as obtain advantage and synergy effects by cooperative relations with other SME and related partner institutions. Also other factors can be found in literature that reveals important limitations concerning SMEs research. Although the significant importance and SME and their contribution to economic growth, SMEs are still faced with numerous challenges. These challenges are related with the access to finance or poor management skills which is a result of lack of adequate training and education. These factors contribute to the high rates of business failure and represent limitations in their entrepreneurial growth. The background of the top management team is considered as a key factor that influences SME survival and development (Lu and Beamish 2001; Stoian et al., 2010). Nevertheless, research about Portuguese SMEs is more focused in some fields, such as internationalization (Oliveira and Teixeira, 2011), innovation (Trigo et al 2009) or in capital structure and profitability (Nunes et al, 2010; Serrasqueiro and Nunes, 2012). This gap justifies the purpose of other empirical studies applied to SMEs considering other relevant fields of management studies.

2. Empirical study 2.1 Methodology In order to accomplish the research purpose, an empirical study was developed considering two main parts:

Firstly study a sample of 23 enterprises identified as leaders of the 1000 Portuguese SMEs in 2012.The data was collected by Exame (2013) and includes the biggest 1000 Portuguese SMEs in 2012;

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Secondly, analyse a specific case of one enterprise from the data of 23 leaders SMEs, and applied a questionnaire in order to collect micro information considering a set of variables relevant to the research. The questionnaire is divided into 3 parts: part 1 refers to the characterization of the enterprise, part 2 assess the entrepreneurial competitiveness, considering 9 questions to assess performance, 6 questions to assess internal processes and 4 questions to understand the relations with customers, and the part 3 analyse the diffusion of innovation through 3 questions. The questionnaire uses a Likert scale with 7 degrees (1 represents very lower and 7 very higher). All questions were made considering the comparison of the analysed SME with the other competitive SME from the same sector in the last three years. The questionnaire was sent and receipt during March of 2013.

As already referred the first empirical research uses data collected in 2013 considering a ranking list published of the largest 1000 Portuguese SME (Exame, 2013). The 1000 largest portuguese SMEs were selected based on the following criteria’s:

Less than 250 employees;

Sales less than or equal to 50 million Euros;

Liquid assets equal to, or less than 43 million Euros;

Not to be detained for more than 50% by another company unless that mother company is also SME;

Does not belong to the financial sector.

Enterprises were classified into 27 branches of activities and considered several indicators, such as:

Localization/region: C‐Centre, LVT‐Lisbon and Tagus Valley, N‐ North; Aç‐Azores;

Gross Added Value for sales: measures contribute of the enterprise to the economy for each euro sold, in percentage.

Gross added value: refers to the sum of sales and services, work for the company, changes in production, subsidies for exploration and additional revenue less intermediate consumption and supplies and services;

Sales: Sales of products and services;

Sales growth: refers to the increased sales and services between the current and previous year in percentage;

Labour productivity: respect to gross value added per worker. Measures the efficiency of enterprises in the use of human resources.

2.2 SME leaders description This section presents a characterization of the Portuguese SME leaders in each sector, considering: region, sales; sales growth; net profit; GVA/sales; gross value added; productivity and number of employees. Attending to sales growth 19 SME reveal a positive growth and 4 of them present a negative growth. However, a high percentage of these enterprises refers to service sector with value of 227,8%, 65,66% and 52,88%. The absolute values of the sales are in the most SME between 10 and 15 millions. In generally the SMEs with a large number of employees present lower values of productivity (lower than 100). Concerning other financial indicators it is not possible to find patterns to group SMEs. Table 1: Relevant indicators to SME leaders

Region Sector C m LVT s C m C m LVT s N m N m LVT m

Sales 30464 27250 25591 20257 18057 18850 22803 22433

Sales growth

Net profit

4,7 44,9 52,88 19,19 31,21 13,68 13,88 6,3

1812 223 8774 428 383 939 2345 5392

GVA/sales 26,4115021 3,442201835 49,49787035 35,36061608 3,50002769 26,12732095 20,75604087 65,568582

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Gross value Number of added Productivity employees 8046 43 187 938 39 24 12667 264 48 7163 44 163 632 158 4 4925 31 159 4733 93 51 14709 108 136

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Region Sector C m LVT s N s N m C s N s LVT s LVT m LVT s N m AÇ s LVT s N s LVT m C m

Sales 16779 15366 14867 14483 14122 13979 11906 11690 11153 11000 10486 10423 10290 10213 10211

Sales growth

Net profit

42,69 3,81 65,66 ‐43,78 ‐9,99 227,76 ‐6,28 92,31 4,88 10,03 4,63 11,53 17,61 ‐25,41 4,49

1370 3113 1567 2299 1480 744 954 798 1132 3424 462 263 150 1413 792

GVA/sales 19,68532094 52,7853703 36,83325486 23,19961334 11,81843931 10,01502253 25,64253318 16,50128315 21,54577244 48,91818182 27,68453176 44,01803703 25,22837707 25,43816704 34,9035354

Gross value Number of added Productivity employees 3303 165 20 8111 213 38 5476 66 83 3360 560 6 1669 238 7 1400 27 52 3053 38 80 1929 48 40 2403 89 27 5381 163 33 2903 29 100 4588 42 108 2596 19 140 2598 649 4 3564 30 120

Source: Exame, 2013 Figure 2 presents the distribution of the SME and its possible to note that 39% of Lisbon and Tagus Valey and 31% are situated in North. This tendency follows national distribution of the enterprises in Portugal, where mostly enterprises are situated in Metropolitan areas of Lisbon and Oporto (north of the Portugal).

Source: Exame, 2013 Figure 2: Region Figure 3 presents the distribution of the firms according with the sector (manufacturing and services) cross by size. The size included the division attending the number of employees: Microenterprises (less than 10 employees); Small enterprise (between 10 and 49 employees) and Medium enterprise (between 50 and 249 employees). The figure 2 allows noting that most of the SME in the data are medium enterprises in both sectors.

Source: Exame, 2013 Figure 3: Size by sector

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2.3 A micro analysis of a SME In this section the paper present some results applied to a case from the 23 leaders SMEs. The case aims to allow the understanding of some aspects related with SME competitiveness in a micro perspective. The micro perspective allows a better understanding of some phenomenon and behaviour not detected in macro studies. Complementarily, the micro perspective allows a frame of an enterprise and proposes some clues and explanations that justified the performance indicators presented in table1 of the last section. The questionnaire was divided in 3 parts The first part present the description of the SME studied. This enterprise belong to manufacturing sector and are included in chemical industry, produce and distribute medicines. Is located in region of Lisbon and Tagus Valley, exports about 12% of their products and the main export market is Spain and don’t have investment in R&D. The second part refers to assess of the entrepreneurial competitiveness considered performance measures attending to apprenticeship and growth, internal process and clients. Table 2 presents in average the values grouped according with the dimensions of competiveness studies. It’s important to note that the higher average value refers to clients with a value of 4, 5 and the lower refers to internal process with 3, 5 (lower than 4, the median of the scale), the other values are very close with the median. Table 2: Results of the answers in average (scale 1‐7)

Source: Information collected by the authors Additionally attending to the answers it is important point out some outliers for each part. Concerning to apprenticeship and growth, the experience of their human resources and the lower turnover rates of the employees reveals values of 6 in the scale, also the productivity present a value of 5, higher than the median. In this part the lower value concerns to the infrastructures and facilities to support R&D and innovation. The results to internal process, also presents some outliers, the lowers with the value of 2, refers to investment in R&D and patents and the highest with value of 5 in both of them respect to marketing innovation and customer services. In section of the question related with clients, satisfaction with service and customer loyalty point 5 in the scale, revealing the preoccupation of the firm with clients and demand side of the business. Finally the third part analyse the diffusion of innovation and present an answer with a higher value 5, respecting to cooperation with other partners and institutions to develop R&D.

3. Concluding remarks In summary, it’s consensual that globalisation and competitiveness affected the way of enterprises undertake innovation, particularly in the case of SMEs. These enterprises play an important role in several economies and the studies about SME and competiveness are extremely suitable. This research proposes an empirical study that analysis a sample of 23 enterprises identified as leaders of Portuguese SME in 2012. Additionally the empirical study applied a questionnaire to an enterprise in order to have a micro perspective of the factors that influences competitiveness. The results of the empirical study to the 23 leaders are divided almost in two equals parts in two sectors manufacturing and services, respecting performance indicators reveals similar patterns and most of them located in urban regions, are medium enterprises and are situate in similar intervals with respect to the sales, sales growth or productivity. Concerning to the size is important to note that inside the 1000 SME of the data the leaders are the largest, suggesting that the scale could be crucial to sustainability and competitiveness of Portuguese SME.

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Teresa Costa and Luísa Carvalho The additional microanalysis allows a better understanding of some process inside a SME and reveals some aspects important to a future reflection. It was possible to understand the low auto perception of the management concerning the internal process and resources affect to R&D and patents. This SME produce mainly generic medicines and this strategy can justify the lower scores related with internal process due with their outsourcing strategy. The product development and R&D investment are low because they are focused on manufacturing medicines developed by other enterprises with a high concern about lower costs and higher quality. Moreover, the studied SME reveal a higher concern with clients (satisfaction, loyalty and services) and assumes that develop marketing innovation directed to the market. These results suggest the dependency of this kind of enterprise with the demand and maybe a push innovation model is our perception that inside the data most of them could reveal similar behaviour. Finally, is also interesting highlights the model of cooperation to develop innovation, assuming the importance of the cooperation with other institutions and research centres. SMEs are drivers of economic growth. A healthy SME sector contributes prominently to the economy through creating more employment opportunities, generating higher production volumes, increasing exports and introducing innovation and entrepreneurship skills. Future research aims to enlarge the number of SME inquired and compare results using a multivariate analysis to search similar patterns and behaviours and segmented according size, sector and region.

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Teresa Costa and Luísa Carvalho Pratten, C. (1991), The Competitiveness of Small Firms. Occasional Paper 57, Department of Applied Economics, University of Cambridge. Cambridge, UK: Cambridge University Press. Ramasamy, H. (1995), "Productivity in the Age of Competitiveness: Focus on Manufacturing in Singapore", Productivity in the Age of Competitiveness. APO Monograph Series 16, Asian Productivity Organization. Ruzzier, M.; Hisrich, R.; Antoncic, B. (2006), "SME internationalization research: Past, present, and future", Journal of Small Business and Enterprise Development, 13 (4): 476‐497. Salavou, H., Baltas, G., and Lioukas, S., 2004. Organizational innovation in SMEs: the importance of strategic orientation and competitive structure. European Journal of Marketing, 38 (9–10), 1091–1112. Serrasqueiro, Z., P.M. Nunes (2012), "Is age a determinant of SMEs’ financing decisions? Empirical evidence using panel data models", Entrepreurship Theory and Practice, 36(4), 627‐654. Slevin, D.P.; Covin, J.G. (1995), "New Ventures and Total Competitiveness: a Conceptual Model, Empirical Results, and Case Study Examples, Frontiers of Entrepreneurship Research, 574‐588. Stoner, C. (1987), "Distinctive Competitive and Competitive Advantage", Journal of Small Business Management, 25(2), 33‐ 39. Trigo, V.; Calapez, T.; Santos, M.C. (2009) “SMEs and internationalization: an empirical study of SMEs in Portugal”. Economia Global e Gestão [online]. 2009, vol.14, n.3, 9‐24 . Available from: <http://www.scielo.gpeari.mctes.pt/scielo.php?script=sci_arttext&pid=S0873‐ 74442009000300002&lng=en&nrm=iso>. ISSN 0873‐7444. Waheeduzzaman, A.; Ryans, J. (1996), "Definition, Perspectives, and Understanding of International Competitiveness: a Quest for a Common Ground", Competitiveness Review, 6(2), 7‐26.

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Innovation in Energy Sector – a Comparative Study in Brazil and Portugal Teresa Costa1, Luísa Carvalho2, Geciane Porto3 and Priscila Rezende da Costa4 1 CITIS; Lusíada University, Portugal, Economics and Management Department, Business School, Setúbal Polytechnic Institute, Portugal 2 CEFAGE‐ University of Évora, Portugal and Economics and Management Department, Business School, Setúbal Polytechnic Institute, Portugal 3 Management Department, School of Economics, Business and Accountancy of Ribeirão Preto, University of São Paulo, Brazil 4 Management Department, Academic Coordinator of the University July Nine, São Paulo, Brazil teresa.costa@esce.ips.pt luisa.carvalho@esce.ips.pt geciane@usp.br priscilarc@uninove.br Abstract: The energy sector is a strategic vector for the competitiveness of countries. It is consensual that this sector plays a crucial role in the context of the global economy, assuming a key factor in terms of economic growth and development. We considered important to understand how this sector can be important in countries with different stages of development and how companies from this sector lead with different threats and opportunities and develop innovation strategies to assure competitive advantages. The current study analyzes innovation in energy sector, studying the largest companies from Brazil and Portugal, focusing on different dimensions, such as investment in R&D, R&D activities and cooperation for innovation. Through a case study methodology, the study point out some differences and similarities from these two countries with different stages of development (Brazil and Portugal), considering the dimensions of innovation studied. Keywords: energy sector, innovation activities, R&D, cooperation for innovation

1. Literature review 1.1 The importance of energy sector Sustainable growth is one of the priorities within the Europe 2020 Strategy of the European Union, through which it aims to promote an economy that is not only more competitive but also more efficient in terms of resource use, ie more environmentally friendly. The European Union (EU), as the rest of the world, is faced with major challenges as regards energy and the environment, these include: ever‐increasing global demand for energy, volatile prices, rising emissions of the greenhouse gases responsible for climate change, and unstable oil and gas supplies, with reserves concentrated in just a few countries. So it is required efforts in order to prevent the worldwide energy situation from getting even worse. The development of new energy technologies can play a decisive role and help EU's to achieve the goals of reducing energy consumption and greenhouse gas emissions by 20% until 2020 and increasing by 20% the share of renewable sources in Europe's energy mix (European Commission, 2002; European Commission, 2006).

1.2 Innovation and competitiveness The majority of innovation studies differentiate innovation from invention. “Invention is the first occurrence of an idea for a new product or process, while innovation is the first attempt to carry it out into practice" (Fagerberg, 2005). Innovation is a process that includes invention, commercialization and diffusion with a multidimensional and nonlinear track. Innovation has been an important issue in several studies in economics, management, technology, sociology, with different interpretations (Arrow, 1962; Pavitt, 1984; Cohen and Lewin 1989; Urban, 2009). Several authors recognise that R&D facilitates the firm improvement in terms of efficiency (Cohen and Levinthal, 1989; Lucas, 1993; Hewitt and Wield, 1992; Mody, 1993; and Audretsch, 1995). They believe that R&D generates not only new information, but also develop the firm’s capability to incorporate and exploit the

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Teresa Costa et al. existing information. Consequently, the productivity effect of knowledge may depend on the firm’s own investment in R&D or worker training. Some studies confirm this relationship between R&D and productivity. For example, Griffith et al. (2004) use a panel of industries across 12 OECD countries and find evidence that R&D investments increase technology transfer by improving firms’ absorptive capacity and conclude that industries in countries that lag behind the productivity frontier can catch‐up particularly fast if they invest heavily in R&D. Also Klette (1996) finds some evidences, in Norwegian manufacturing plants that confirms that R&D investments in the past have higher productivity growth. Finally, Griliches (1979 and 1986) concludes that R&D contributes considerably to productivity growth, and that privately financed R&D expenditures have a larger effect on private productivity and profitability than federally financed R&D. Also cooperative activities for innovation, as well as strategic technological alliances, became important issues of many theoretical and empirical studies in the 1980s and 1990s. After the mid‐1980s, several studies paid particular attention to cooperation in innovation, including strategic technology alliances (Doz and Hamel, 1997), collaborative activities for R&D (Fusfeld and Haklisch, 1985) and innovation networks (Freeman, 1991; Beimans, 1992). According to Tether (2002:949), “Innovation cooperation means active participation in joint R&D and other technological innovation projects with other organizations”. Several studies point out the positive economic impact of cooperation on the competitiveness of firms (Powell et al., 1999; Hagedoorn et al., 2000; Cassiman and Veugelers, 2002), on performance and knowledge spillover and on success in the development of new products (Miotti and Sachwald, 2003; Sivadas and Dwyer, 2000). For some authors cooperation for innovation must assure absorptive capacity in order to firms benefits from external spillovers and increase the profitability of R&D cooperation (Cohen and Levinthal, 1990 and Cassiman and Veugelers, 2002) and contribute to increase firm’s capability and their ability to benefit from future cooperative R&D projects (Mark and Graversen, 2004).

2. Research methodology and data collection The empirical research applies the case study methodology. According with Yin (1994) “how” or “why” questions have better explanatory power in case studies since “such questions deal with operational links needing to be traced over time, rather than mere frequencies or incidence” (1994, p. 6). Yin (1994) defines the case study research method as an empirical inquiry that investigates a contemporary phenomenon within its real‐life context; when the limits between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used (Yin, 1994, p. 13). This exploratory study adopted an iterative process of data collection in conducting two cases built on the results of a semi‐structured interviews applied to key‐informers from Portuguese and Brazilian energy sector – Petrobas and Galp Energia. This methodology is applied to study innovation in organizations (Bjelland and Wood, 2008; Lakhani, 2008; Di Gangi and Wasko, 2009).The interviews were applied to key‐informers during st the 1 trimester of 2013. The research questions explored are: (1) Why Brazilian and Portuguese energy sector companies invest in R&D? (2) How Brazilian and Portuguese energy sector companies develop R&D activities? (3) How and why Brazilian and Portuguese energy sector companies develop cooperation for innovation? (4) What are similarities and differences in R&D investment, R&D activities and cooperation for innovation process between Brazilian and Portuguese energy sector companies? Besides semi‐structured interviews, documental data was collected in companies websites, journals and other documents.

3. Case studies: Petrobas and Galp Energia Petrobras is a Brazilian and transnational capital intensive, which works seamlessly in exploration and production, refining, marketing and transportation of oil and gas, petrochemicals, distribution of oil, electricity, biofuels and other renewable energy. The company operates on all continents, has commercial, operational or technological forecasting in 27 countries (other than Brazil). Founded in 1953 with the objective of performing the activities of the oil industry, in Brazil began operations in 1954 with the refineries Mataripe (BA) and Cubatao (SP). With an initial production of 2,700 barrels, equivalent at that time to 1.7% of national consumption.

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Teresa Costa et al. An activity that marked the history of the company was the R&D and development of new technologies. The beginning of this process occurred in 1957, with the creation of CENAP (Improvement and Research Center of Petroleum), replaced in 1966 by CENPES (Center for Research and Development Leopoldo Américo Miguez de Mello), now meet the technological demands of the company. In early 1985 has PROCAP, the Training Program Deepwater Technology in partnership with STO ((Science, Technological Institucions), to improve the company's technical competence in the production of oil and gas in water depths up to 1000 meters. The PROCAP 1000 marked the beginning of exploration in the Offshore segment, from 1986 to 1991. In 1993 it created the PROCAP 2000 (in partnership with STI), extending the technological effort to explore the depth of 2000 meters. In the second phase of the program, 20 projects were developed in the network, with a budget of about 573,6 million euros. In 2000, was instituted PROCAP 3000, also in partnership with STI. As a result of the cumulative action of CENPES, its network of innovation, the three versions of PROCAP and other technology programs of the company, have completed the first ultradeep drilling as early as 2005, with a well of 6,915 meters in the Santos Basin, 200 km from Rio de Janeiro. A year later, the company's value exceeded US$ 100 billion and Brazil won self‐sufficiency in oil and gas with the entry into operation of the P‐34 and P‐50. Galp Energia was established on 22 April 1999 as the result of the merging between Gas de Portugal and Petrogal. Nowadays, Galp Energia includes a group of companies. With internationalization, Galp Energia has evolved from a domestic company to an Iberian company in an initial phase, and an international company in a second phase. Today Galp Energia, has similar presence in Portugal and Spain, is located in the "upstream" and "downstream" in Africa, in the "upstream" of Latin America, particularly in and Brazil, and in "upstream" in Asia (East Timor). Galp Energy exports to 55 countries but the most important markets are USA, Mexico, the Netherlands and Britain. In 2012, Galp Energy presented a turnover of 18,507 million euros, representing an increase of 10% compared to 2011. Had earnings before interest and taxes (EBIT RCA) of 585 million euros, 48% more than in 2011 and a net profit RCA of 360 million euros, ie 43% more than in 2011. The company has built a strategy for R&D and innovation supported on cooperation with SCT (Scientific and Technological System) entities, creating a flexible network of partnerships that allows to share important skills. The three main foundations of the strategy for R&D and innovation are: 1‐ Closer linkages with the SCT and with customers; 2‐ Development of differentiation in the markets where the company is present, supported in the creation of new services in order to answer needs and expectations of the customers; 3‐ Active participation in the development of sectoral policies, which strengthen the future development of the energy sector.

4. Analysis and discussion of the cases In the following section we analyze the two five cases of energy companies according with three main dimensions in order to answer to the questions of the study. Why Brazilian and Portuguese energy sector companies invest in R&D? The alignment of strategic and technological enterprise for the next 10 years resulted in the prioritization of some actions, such as the acceleration of technological development, the expansion of national capacity and performance in the network involving the internal structure of R&D and technology partners abroad. Specifically, the company's technological guidelines are grouped into three key axes: Expanding the Boundaries; Diversification and Value Addition of Products, and Sustainability. In turn, these axles address the strategic issues for the company that should guide the R&D internal and external, both integrated and coordinated by CENPES and, more directly, by Petrobras Technological System.

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Teresa Costa et al. Among the strategic goals of Petrobras, presented in the Business Plan 2012 to 2016 stand out the programs listed below which provide investments of 180,6 billion euros.

Program for Increasing Operational Efficiency (Proef) Operating Units and the Campos Basin in Rio de Janeiro: seeks to increase the reliability of delivery of oil production through interventions and maintenance platforms and subsea systems, improving levels of operational efficiency and preserving the integrity of production systems

Optimization Program Operating Costs (Procop): aims to increase cash generation on the horizon of 2012‐ 2016 PNG, increase the productivity of their activities from internal and external benchmarks and strengthen the management model focused on efficiency costs

Content Management Program‐Local Prominp Petrobras: aims to make the most of the competitive capacity of domestic industry of goods and services to meet the demands of PNG 2012‐2016 with adequate time and cost to market best practices.

Program Divestitures (PRODESIN): aims to raise funds to finance the 2012‐2016 PNG and optimization of the portfolio of assets of Petrobras.

Program Optimization of Logistics Infrastructure (Infralog): aims to plan, monitor and manage projects and actions in an innovative way to meet the needs of the company's logistics infrastructure by 2020. The analysis of integrated logistics solutions enable the exploitation of synergies and cost reductions in all businesses of the Petrobras System, contributing to capital discipline.

Galp Energia has developed a great effort in order to ensure its competitiveness and sustainable growth. The investment in R&D in different fields of company´s operation allowed the company to get a higher efficiency in its operations, namely in refining and in the marketing of oil products and natural gas, as well as in the exploration potential of concessions. The company’s growth potential is also a reflection of its efforts in terms of qualify and develop human capital, as well as in a continuous‐improvement policies in what regards health, safety, the environment and sustainability. These efforts allow the company to be prepared to the technological and innovation challenges, through the allocation of resources to research and development projects and to a multiplicity of advanced training programmes. This investment in R&D and the development of the several research projects are determinant for the achievement of the targets that will provide the sustainable growth of Galp Energia in short, medium and long run:

The development until 2010 a production capacity of 300 kboepd;

The insurance additional resources that will allow the company to reach and sustain a production level of 400 kboepd;

The operation of refining base in accordance with the highest standards of safety, efficiency and reliability;

The development of the trading of crude and oil products;

The achievement of a minimum 15% share in the Iberian market for oil products;

The achievement of sustained growth in the African market for oil products, aiming to sell, in the long term, a material volume of those products;

The development of a minimum capacity for the trading and supply of natural gas and liquefied natural gas (LNG) consistent with our equity natural gas stakes and with the dimension of the market where we operate;

The grow of sales activities in the Iberian market for natural gas in order to keep, at the very least, the current market share;

The participation in the market for biofuels through a vertically‐integrated approach;

The promotion of energy efficiency solutions and the insurance of the sustainability of company operations;

The development of Galp Energia’s corporate centre, in terms of skills and responsibilities, considering the geographical dispersion of company activities;

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The promotion of policies for innovation, sustainability, health, safety and the environment, permanently meeting, in anticipation, the needs of our different operations;

The strengthens of an advanced training programme of human resources that will provide company with the human capital required to answer the challenges to come.

Finding 1: Brazilian and Portuguese energy sector companies invest in R&D in order to obtain a better performance in terms of reduction of costs, of higher efficiency, of an increase of sales and profit, and naturally, of an improvement in terms of sustainability, and safety. These factors allow assure the important market share and a sustainable growth of both companies. The literature review reinforce the relationship between R&D, productivity and efficiency (Cohen and Levinthal, 1989; Lucas, 1993; Hewitt and Wield, 1992; Mody, 1993; and Audretsch, 1995, Kettle, 1996). Additionally also Griliches (1979 and 1986) confirmed the association between R&D and profitability. How Brazilian and Portuguese energy sector companies develop R&D activities? Petrobras invested 0,8 billion euros in research and development (R&D) in 2012. The management of these resources is coordinated by CENPES, the largest research complex in the Southern Hemisphere and private use of Petrobras. From these resources 693 million euros were invested in universities and institutions of national science and technology for the realization of projects of R&D, qualification of technicians and researchers, and the expansion of laboratory infrastructure. The partnership with suppliers, especially in projects related to the pre‐salt, which led to the installation of R&D centers and laboratories in the Technological Park of Rio, including the actors: LabOceano ‐ Laboratório de Tecnologia Oceânica; NUTRE ‐ Núcleo Tecnológico de Recuperação de Ecossistemas; Neo; CEGN ‐ Centro de Excelência em Gás Natural; Instituto Global para Tecnologias Verdes e Emprego – GIGTec; LAMCE – Laboratório de Métodos Computacionais em Engenharia Schlumberger; Baker Hughes; FMC Technologies; Halliburton; Tenaris Confab; BG; EMC²; Siemens; General Electrics; V&M; Georadar. Here are some innovative actions and results recently achieved by Petrobras: 1) Discovery Microfossil kind of knowledge that contributed to more accurate positioning of reservoirs at different depths; 2) Completed lab tests for the injection of CO2 as fluid oil recovery; 3) Completed basic design of floating liquefied natural gas shipped to the utilization of natural gas pre‐salt Santos Basin; 4) Applied new way to anchor that meets specific pre‐salt; 5) Developed equipment for emergency repair during operation of pipelines transporting liquid without interrupting the flow; 6) New formulation for diesel Podium;7) Developed catalyst for use in production of high density polyethylene material having high mechanical performance; 8) Creating a core experimental Bahia to test separation technologies, CO2 capture and storage; 9) Completion of new geological model of the Brazilian Atlantic Continental Margin; 10) Update model for the geological evolution Parnaíba Basin; 11) Completion of three‐dimensional seismic velocity model for the discovery of Jupiter in the pre‐salt Santos Basin; 12) Applying the latest technology in simulators and analyzes developed in Petrobraswhich assisted in the drilling of the first horizontal well in the pre‐salt; 13) Installation of the first intelligent completion systems in the pre‐salt; 14) Start of operation of subsea multiphase pump more hélico‐axial currently operating in the world; 15) Start of operation of subsea system injection of seawater ; 16) Preparation of Basic Design and Technical Documentation for bidding platforms P‐74, P‐75, P‐76 and P‐77 oil fields of the Assignment Agreement.; 18) Start of operation of the first unit of industrial hydrodesulfurization of cracked naphtha technology with Petrobras in Capuava Refinery. Investment in Galp Energia, 2012 was 940 million euros, with about 70% of the total allocated to the Exploration & Production. The Refining & Marketing business, which by the end of 2011 was the major focus of investment in 2012 represented only about 20% of the total. Investment in Exploration & Production totaled 653 million euros (more € 354 million than in 2011) which was mainly allocated to development activities of block BM‐S‐11 in Brazil, which accounted for € 306 million. About 40% of the investment in the segment allocated to exploration activities, highlighting the investment in Mozambique which totaled about 79 million euros. The investment in the business segments Refining & Marketing and Gas & Power totaled 284 million euros, 412 million euros less than the previous year. This decrease was due to completion of investment in refinery conversion project

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Teresa Costa et al. Investment in Research and Development is understood as strategic and across the entire value chain of Galp Energia, with particular focus on activities involving higher technology. Regarding the capture and sequestration, Galp Energia participates in COMET, a project that aims to identify an infrastructure of transport and storage of CO2, covering the area of the western Mediterranean. In the field of E&P, Galp Energia is also developing some projects, such as the project modelling and characterization of fractured reservoirs and the seismic imaging project in reservoirs beneath canopies of evaporites. In the field of refinig, as part of the PhD Program in the business (EngIQ) some R&D projects are being developed: 1) Lonic liquids for extracting mercaptans; 2) Optimization of Parex unit; 3) Development catalyst hidrodesmetalização; 4) Oligomerization of Olefins C5 ‐ C8.; 5) Improved Alkylation; 6) Technology for NMR characterization of crude oils and some current procedural; 7) Ginseng project.. In the field of capture and sequestration, Galp Energia is also developing several projects of R&D. The most importante is COMET, an integrated infrastructure for the transport and storage of CO2. This project aims to identify a CO2 transport and storage infrastructure on the Mediterranean coast. This infrastructure will cover the West Mediterranean area, in particular the Iberian Peninsula and Morocco, and will identify locations with the capacity to store CO2 in geological formations Moreover, Galp Energia is also developing new products and services related with energy and sustainable mobility, namely the project Smart Galp. Finally, some projects related with the improvement of energy efficiency, we being developed, highlighting the programme Galp 20‐20‐20, the largest scholarship programme for applied research in energy efficiency (with the participation of IST, UA‐ Universidade de Aveiro and FEUP‐ Faculdade de Engenharia da Universidade do Porto), the creation of two R&D projects (industrial PhD) in partnership with UA and the programme that promotes energy efficiency in Palácio de Belém, in partnership with EDP and LNEG (national lab of engineering ang geology). Finding 2: Brazilian and Portuguese energy sector companies develop R&D activities through the development of several projects research in different fields, such as exploration and production (E&P), refining/capture and sequestration, through the development of programme of advance training and shared investigation, through the development of new products and services. According with international studies it is crucial that EU's achieve the goals of reduce energy consumption and greenhouse gas emissions as well as increase the share of renewable sources in Europe's energy mix (European Commission, 2002; European Commission, 2006). The activities identified allow both countries to contribute to the achievement of these sustainable goals. How and why Brazilian and Portuguese energy sector companies develop cooperation for innovation? To strengthen technological skills to face the internal and necessary developments, Petrobas develop a comprehensive system of partnerships over the years. Currently, the company have a total of 7 regional centers, 3 in Rio de Janeiro, one in Bahia,one in Sergipe, one with the Holy Spirit and one in Rio Grande do Norte, and 50 thematic networks. Petrobras is a Brazilian company that invests more in R&D, and in the period 2006 to 2010, its total investment in R&D got to the total of 0,9 billion euros, placing the company among the eight largest investors in the industry worldwide energy in that area, and specifically in 2010, the company invested 0,68 billion euros in R&D (PETROBRAS, 2010). About the company's total expenditure on R&D, infrastructure projects and considering, there is a total of US$ 2.6 billion in the period from 2008 to 2010, about five times the average for the period 2001 to 2003. Of the total of these expenditures, 44% resulted solely from internal R&D, 29% of partnerships with national ICTs, 8% of ICT and partnerships with overseas companies and 19% of partnerships with national companies (PETROBRAS, 2010).

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Teresa Costa et al. The history of the company's investments in R&D over the last seven years is due in part to the enactment of Resolution No. 33/2005 which regulates the investment of at least 1% of gross revenue in R&D for companies successful in bidding rounds of ANP, being 50% of the funds invested in internal R&D and 50% invested in projects and programs developed in partnership with ICTs previously accredited in ANP (PETROBRAS, 2010). Another important point of the innovation performance of the company was the realization of 705 projects of R&D from 2006 to 2010, with prior authorization from the ANP, representing about 99% of total investment during the same period, when considered all oil dealers that operate in Brazil and are subject to mandatory investment in R&D. In result, the investment of Petrobras, in partnership with ICT, grew nearly tenfold from 2004 to 2010, reaching 229,1 million euros in 2010. Also in Galp Energia the investment in new knowledge is determinant to creating a culture of sustainable innovation and create an important source of differentiation, essential in a competitive market. So, the development of R&D and innovation strategy is crucial for Galp Energia. For this purpose the company created several linkages and cooperative relations with SCT in a permanent network that share skills and knowledge. Some of the more significant collaborative partnership for innovation develop by Galp Energia are:

The creating of a digital platform of relationship with Scientific and Technological System. In 2010 the number of registered scientists, technologic entrepreneurs, partners and suppliers quadrupled an achievement (480 members). Additionally, the interaction between the members of this network and the adoption of this channel to present innovative proposals to Galp Energia increased significantly.

The development of 20‐20‐20 programme aims to promote the participation of MsC students with 30 studies in the area of rational energy systems and behaviours applicable in industry and buildings. This programme started at 2007 and already involved the participation of 53 entities, state‐owned or private.

The promotion of open innovation. Galp Energia Challenge is one of the open innovation channels either STS. The aim of this programme is to challenge university community and technology‐based companies for the presentation of proposals of technological solutions to solved existing problems in the company.

Also the main R&D projects already presented are developed in partnership with several universities and other entities (COMET project, ENGIQ programme of training and PhD‐refining, R&D projects related with energy efficiency and mobility).

Finding 3: Brazilian and Portuguese energy sector companies develop several collaborative partnerships with universities, institutes, researcher centres and national and multinational companies. This collaborative partnership allows both companies to shared skills and knowledge essential for an innovation culture, as well as, to the development of a differentiation strategy. Also the literature review reveals the importance of cooperation activities for innovation as well as strategic technology alliances and innovation networks (Fusfeld and Haklisch, 1985;Doz and Hamel, 1997; Freeman, 1991; Beimans, 1992). What are similarities and differences in R&D investment, R&D activities and cooperation for innovation between Brazilian and Portuguese energy sector companies? In order to analyse possible similarities and differences concerning the several aspects analysed during our study it was developed comparative analysis. Table 2 presents the summary results of this analysis. Finding 4: Brazilian and Portuguese energy companies revealed more similarities than differences concerning the subject proposed by this study. According with European Commission (2002, 2006) most countries all over the world have similar challenges, concerns and needs related energy resources. This may justify the similar strategies concerning innovation activities followed by energy companies in order to achieve more efficiency, productivity and competiveness.

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Teresa Costa et al. Table 2: Comparative analysis between Petrobas and Galp Energia Petrobas

Galp Energia

Public company

Private company

Transnacional company

Intensive capital

Leader in Bovespa Companies characteristics Integrated corporate strategy for growth, profitability and environmental responsibility

Large investments in R&D

R&D and innovation

Reasons of the investment: • expansion of national capacity; • cost optimization; • adding value; • product diversification and sustainability; • improved levels of operational efficiency Several developments in innovation and development of several R&D projects in E&P, refining, capture and sequestration In order to strengthen technological competencies the company develop various partnerships with universities, research centers, technological conpanies, suppliers and competitors

Leader in PSI20 Corporate strategy of sustainable value creation, development and expansion of activities and corporate responsibility in economic, environmental and social dimension as a catalyst for innovation and how to improve the satisfaction of their stakeholders. Large investments in R&D Reasons of the investment: • increase competetiveness; • get higher efficiency in its operations; • increase production; • guaranty highest standards of safety an quality.

Similiarities

Differences

√ √ √ √

√ √

√ Several developments in innovation and development of several R&D projects in E&P, refining, capture and sequestration In order to strengthen technological

√

competencies the company develop various partnerships with universities, research centers, technological conpanies, suppliers and competitors

√

5. Conclusions The present study analyzes innovation in energy sector, studying the largest energy companies from Brazil and Portugal. Our findings based on these two cases, that are representative of the energy sector studied, allow understanding why and how these firms invest and develop R&D activities, as well as why and how they cooperate to undertake these activities. Confirming the theoretical framework of our study, the empirical study suggests the important role of R&D concerning the improvement of efficiency, increase production, guaranty highest standards of safety a quality and the important achievements in terms of firms competitiveness. These developments are possible through cooperation between several stakeholders and share resources, such as natural resources, skills, competencies, knowledge or technology, technological. The study also confirms the importance of the energy sector and the cooperation between the developing countries and developed countries, since problems related with limited access to energy sources, the very widespread use of traditional biomass and dependence on imported energy sources constitute a significant obstacle to social and economic development. Finally the comparative analysis between the companies studied, considering its characteristics and aspects related with the form and reasons to develop innovation, suggests that these companies have essentially similarities, enlarging a great effort in terms of R&D development and cooperation for innovation, being, not only competitors but manly partners in several projects, sharing the same vision, mission, objective and implementing the same type of strategies.

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Innovation and Entrepreneurship by Academic Spin‐Offs: The UNITI Business Case Renata Paola Dameri, Federico Fontana and Roberto Garelli Department of Economics, University of Genoa, Italy dameri@economia.unige.it fontana@economia.unige.it rgarelli@economia.unige.it Abstract: The aim of this research is to analyze the academic spin‐offs like companies able to drive innovation and entrepreneurship and to fast the technological transfer from the academic research to the business. The research method includes both a literature review, to clarify the meaning of academic spin‐off, and an empirical investigation. The authors selected a set of academic spin‐offs settled in Genova during the latest years, thanks to the UNITI project. 17 spin‐offs have been examined, to understand their nature and their role in the economic context. The data for the empirical analysis were collected from the spin‐offs balance sheets. The results of this survey are useful to better define the nature and the functioning of academic spin‐offs and their role in technological exploitation and value creation. Keywords: technological transfer, entrepreneurship, academic spin‐off, innovation

1. Introduction Innovation and entrepreneurship are two critical success factors to improve the effectiveness of industry and economic policies, especially when regarding hi‐tech business and start up companies. One of the most profitable economic policies is technological transfer, that is, the faster and focused transformation of research results in business initiatives. Indeed, technological transfer permits to improve the quality of products, services and processes, aiming at several different and linked goals such as: more efficiency, less environment footprint, higher employment, better knowledge in workplace and in business, and so on. However, technological transfer is not easy, because to transfer the research results to the business poses several risks, for example: the lack of direct relationships among researchers and business, the lack of funding, the high failure rate that discourages entrepreneurship in innovative initiatives. A winning economic policy is academic spin‐off. An academic spin‐off is a start up settled by academic researchers, with the aim to directly transfer the results of their scientific research into business initiatives. An academic spin‐off can overcome most of the obstacles met by generic start up, if a specific business model is applied and if there are specific public policies aiming at academic spin‐off development. Indeed, academic spin‐offs permit to create a direct link between research and production, and to create start ups especially conceived to apply a specific research result. An academic spin‐off has the aim to translate the research into business and to produce the higher economic value from a scientific idea. Therefore, an academic spin‐off is the more efficient and effective mean to transfer knowledge from the research to the business. Moreover, academic spin‐offs can have success, if they pursue a specific business model, aiming for the first to transform a theoretical scientific idea into a marketable product or service and, after that, they could be acquired by a larger company for a faster growth. Finally, academic spin‐offs often enjoy specific public funding programs, just aiming to support the business start up and the technological transfer. The UNITI project is an Italian public program, aiming to support academic spin‐offs and technological transfer. Indeed, even if Italy is at the eighth place in the world ranking for patents and papers published in peer review scientific journals, its capacity to transform research results in economic value is still low. The UNITI program, thanks to the support to academic spin‐offs, permitted to create several start ups. In this paper, the authors analyse the academic spin‐offs phenomenon and its evolution, and the general characteristics of academic spin‐offs like start up initiatives. Afterwards, thanks to an empirical investigation

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Renata Paola Dameri, Federico Fontana and Roberto Garelli on a set of academic spin‐offs, they analyse the economic impact of UNITI program on technological transfer and economic value creation by start up initiatives.

2. Academic spin‐off definition During the latest years, the academic spin‐off has been an increasing phenomenon, widespread all over the world and especially in most industrialised countries with the most important universities. The idea of spin‐off was born in USA, at the end of Sixties, around some eminent universities such as Stanford and MIT. These universities, specialised in high tech research, were the source of knowledge that spread over the surrounding area. Sylicon Valley and Route 128 are the first cases of territorial development based on academic research outputs. The first definition of spin‐off is by Schumpeter (1934); he defines a research spin‐off as an innovative enterprise that continuously invests in research; for these companies, research is the key resource for development and competitiveness, this attracts more spin‐offs and produces an evolution process able to positively impact on the whole economic environment. However, an academic spin‐off is different from spin‐offs tout court, because it refers only to a specific type of enterprise, with some characteristics that qualify it. At present, a clear and generally accepted definition of university spin‐off is not available. Spin‐off itself is a fuzzy concept, regarding a wide set of enterprise typologies and university spin‐off is only a small part of them. Pirnay et al. suggest this definition of university spin‐offs: “new firms created to exploit commercially some knowledge, technology or research results developed within a university”. Already in 1982, McQueen and Wallmark identified three distinctive characteristics of academic spin‐off: subjects, activity and knowledge transfer.

Spin‐off subjects should be academic members: researchers and professors. Smilor et al. (1990) specify that in an academic spin‐off scholars should be entrepreneurs, both leaving the parent university or maintaining their position inside it (Pirnay et al., 2003). However, if the entrepreneurs are students or researchers leaving the university, probably the original link with the academy will gradually reduce, transforming the academic spin‐off into a normal enterprise, even if highly committed in research and innovation processes (Clarysse et al., 2000, Freitas et. al. 2012).

Spin‐off activity, the aim of the academic spin‐off should be to produce and sell products and services on the market, aiming at financial returns just like each other enterprise. Therefore, an academic spin‐off is not a private research organization; research results should be effectively transferred in products and they should be sold on the market, looking for potential customers and a demand for these products. The specific economic role of an academic spin‐off is just the technological transfer and, by this way, the increasing of products quality, innovation rate and value for customers (Klofsten and Jones‐Evans, 2000, Clausen and Rasmussen 2012).

Knowledge transfer is therefore the core business of an academic spin‐off (Smilor et al., 1990; Bellini et al., 1999; Rappert et al., 1999; Calvo et al., 2012). Knowledge transfer is mainly performed by people, that is, the researchers choosing to dedicate a part of their academic career to the concrete use of the research outputs in business. By this way, knowledge is directly transferred to business thanks to the entrepreneurial role assumed by the researchers, and therefore intellectual property is not a crucial resource, as intellectual capital is pervasive in the company, its people and its processes. Actually, sometimes patents are obtained after the settle up of the spin‐off, as a crucial part of its development and first phase of activity (Colombo and Piva 2012).

Finally, an academic spin‐off should be a new business, especially settled to exploit the research outputs implemented in production processes and products sold on the market (Weatherston, 1995). This aspect open a debate regarding the whole life cycle of an academic spin‐off. Indeed, what happens when a spin‐off has been settled? Which are the paths of its development, growth, innovation? And which exit strategies are conceived, to transform an academic spin‐off into a normal business, when the innovative impulse of the research results has finished? At present, this path is not clear and exit strategies are not defined, to gain the final value produced by the research results transfer into business.

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Renata Paola Dameri, Federico Fontana and Roberto Garelli If university spin‐offs have their motherland in USA, also in Europe this phenomenon has been increasing in the latest ten years. The main reason is the strong commitment of European Union in supporting knowledge economy in Europe. Lisbon Conference in 2000 and the Green Book on Innovation in 2005 strongly incentivize the university spin‐off creation. Lisbon Conference pointed the need to face globalization with higher investments in research and knowledge production and diffusion, to support a more competitiveness economy based on innovation and products quality. It requires the enforcement of knowledge transfer from universities to industries and by this way transform research into economic and social benefits for citizens and countries. Knowledge transfer could both qualify a higher product quality for customers, and create employment. The Green Book on Innovation (2005) outlines the backwardness of European universities in creating virtuous and stable relationships with industries, and especially the underdevelopment of spin‐off initiatives. It depended also by the lack of an adequate legislation aiming at supporting knowledge transfer to the product market. Also Italy has the same problems of the other European countries. However, during the last years, a change has been starting, with a higher focus on knowledge transfer and stringer links between universities and industries (Salvador, 2011). Also the spin‐off phenomenon is more studied, supported and regulated. Indeed, a survey on Google Scholar shows 2410 Italian papers regarding spin‐off, 2060 of them published after 2000. Almost of these contributes depicts this instrument like a good opportunity for our country, to create value by the research outputs. Indeed, Italy is at the eighth place in global score regarding scientific papers, but few of these knowledge results are effectively transferred to business (Piccaluga, 1991). An important stimulus for university spin‐off derives from the new law about intellectual property of universities and researchers and the possibility for them to use their own research outputs within spin‐off. Even if Italy is de facto a follower in university spin‐off strategies, we can distinguish an Italian way for university spin‐off creation and development (Cesaroni et al., 2005). It emerges from several data, such as:

a lower number of university spin‐off, with smaller dimensions, respect to USA (Pellicano and Monetta, 2007);

a lower default rate for Italian university spin‐off (Netval, 2012);

a higher university spin‐off rate in service industry, respect to products production;

less financial instruments and subjects like venture capitalists, business angels, and so on, to support the university spin‐off settlement and a higher financing by the public sector (government or local public agencies) (Boschetti et al., 2011);

the lack of a specific exit strategy, especially to drive the acquisition of university spin‐off by medium and large companies.

3. The spin‐offs of the UNITI project The University of Genoa has recently launched the UNITI program, which aims to support the creation of academic spin‐offs from the results of scientific research. The project, which also receives the support of local authorities, has not only led to the creation of 17 academic spin‐offs, but also to the spreading of a greater business culture within the University of Genoa. This in itself is a stimulus for technology transfer and the creation of innovative enterprises. Beyond the specific results of the project, its effects are in fact spreading into new business initiatives that promise to establish a permanent link between academic research and its application in various businesses of the Liguria region. As noted in the literature (Wright et al., 2004), academic spin‐offs have a composite nature. This is due to both the diverse origins, motivations and roles of their proposers, which has consequences in terms of available resources and expertise, and to the nature, size and destination of the business that will benefit from them, which has consequences in terms of the strategic orientation of the company. This means that academic spin‐ offs are a very heterogeneous set (Druilhe and Garnsey, 2004; Beraza and Castellanos, 2012) and the Genoan case is no exception to this rule.

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Renata Paola Dameri, Federico Fontana and Roberto Garelli The spin‐offs arising from the UNITI project, while sharing some common features, differ indeed in many respects, making up a relatively articulate framework. The common features are specifically the stance and attitude that the University of Genoa has kept throughout the process and the profile of their initiators, which allow to qualify them as ‘academic’ spin‐offs not just formally but also substantially. These are in fact initiatives that originated from an active and deliberate policy of the University of Genoa ("push spin‐offs", according to Pirnay et al., 2003), aimed at promoting and supporting the launch of new businesses stemming from the outcomes of the scientific research carried out by its academic scholars, rather than voluntary initiatives pursued independently by them ("pull spin‐offs"). With regards to the profile of the proponents, they are for the most part university researchers and professors, though they are sometimes assisted by students and neo‐graduates. Having regard to the motives of the proponents, these academic spin‐offs see the effective commitment and direct – although not exclusive – involvement of their initiators ("orthodox" or "hybrid spin‐offs", to use the logical categories of Nicolaou and Birley, 2002) in the management of the resulting company, rather than a mere transfer of technology ("technology spin‐off"). Consequently, the start ups are formed and guided by the academic proponents ("inventor‐led spin‐offs", according to Shane, 2004), who can be differentiated in terms of function and level of commitment, and not by contractors or investors ("shopper‐led” or "investor‐led spin‐offs"), who might be directly or indirectly interested solely in the commercial exploitation of the relative technological innovations. In other words, the economic enterprise that results from these academic spin‐offs can be traced back to its academic initiators ("intrapreneurial spin‐offs", using the definition of Van Dierdonck and Debackere, 1988), rather than to subjects that are external to the university ("extrapreneurial spin‐offs"). The latter, if present, participate in a partnership that can still be important and that has varying degrees of formalization. Indeed the presence or not of strategic partners is the first element of differentiation among the spin‐offs generated by the UNITI project. More precisely, 4 initiatives (less than a quarter of the total) were activated in the absence of previous business partnerships, and 13 (about three quarters of the total) started when specific relationships with technology or business partners were already identified and sometimes formalized. Within this second group, in 6 spin‐offs (about one third of the total) the external partners structured their relationship with the company by becoming major shareholders ("external equity backed spin‐offs", using the terminology of Lockett and Wright, 2005). This is an important aspect, since the presence of strategic alliances signals, on the one hand, the relational skills developed by the initiators and, on the other hand, the positive assessment by the market of the quality and potential of the initiative. It also encourages, at the very start, the economic and competitive success of the specific spin‐off. A further significant advantage, especially in the presence of structured partnerships, can be found in the contribution of commercial, administrative and managerial skills, which are sometimes lacking in the academic initiators. As for the profile of the partners, the situation is quite varied, including self‐employed professionals and entrepreneurs (also as business angels), public authorities (mostly local governments), small and medium‐size enterprises operating at the regional and/or national level, large business groups and multinationals that are industry‐leaders worldwide. In this regard, especially for the partnerships activated with large players, it is possible to observe that along with the opportunity of a more rapid and penetrating market entry there may be threats in terms of exclusivity of the business relationship and dependence on the strategies of the partner with the higher bargaining power. In any case, all spin‐off companies in their business plan declare their intention to maintain close working relationships with the research centers where their proponents come from. This is another important aspect, which guarantees that the level of innovation of the spin‐off initiatives will continue throughout time, tending also to strengthen ties between the University and its economic and business context.

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Renata Paola Dameri, Federico Fontana and Roberto Garelli Additional elements of differentiation that are found across the UNITI spin‐offs, which are also correlated to the type of partnerships they activated, concern the legal protection (through the registration of patents, copyrights and the like) of the results of the scientific research they stem from and the type of activity performed by the companies. As for the first of these aspects, by looking at the documents prepared for the launch of each individual business initiative, four of them (equal to about one quarter of the total) were already backed by specific industrial patents ("assigned technology‐based spin‐offs", according to Grandi and Grimaldi, 2005) and for eight other initiatives (a little less than half of all the cases) evaluations were underway (with the support of the Innovation and Technology Transfer Service of the University of Genoa) about the possibility of acquiring legal protection (since they were based on codified – or at least codifiable – knowledge). Of the five remaining initiatives (just over a quarter), two were not able to be backed by enforceable legal protection, since they were based only on tacit knowledge; for the other three, the proponents reserved the right to assess the activation of forms of legal protection in the future, once the possibility of developing codified knowledge would become a reality. This represents another significant aspect of the analyzed spin‐offs, as the legal protection of such innovations, if on the one hand would make their content public, on the other hand would lock in their economic value, representing, at least temporarily, a potential source of competitive advantage. Moreover, to keep defending this advantage, a systematic effort in research and development is required and is all the more important in view of the progressive contraction of the duration of the life cycle of new technologies. As previously pointed out, this fact reinforces the importance of the partnerships that the spin‐ off companies can activate and consolidate with both the research departments they come from and the leading actors of the business sector where they go to operate. It is to the possible strategic alliances and the protection of intellectual and industrial property rights that the type of activity performed by the spin‐off companies is connected (Stankiewicz, 1994). In this regard, the UNITI spin‐offs, which are practically all engaged in business to business markets, are ideally classified into two major classes: the first one is made up of 9 companies (more than half of the total) that provide services, especially of a consulting nature; the second class consists of 8 companies (less than half of the total) that produce goods (5 of them), technologies and software solutions (3 of them), and provide support services to the product or to the client (1 of them). Also in terms of the innovativeness of what they propose to the market, the UNITI spin‐offs are evenly distributed between those who propose new products/services and those that pursue the improvement of existing products/services (7 in both cases), along with three businesses that combine the two types of offer. With regard to the sectors of activity, the UNITI spin‐offs can be grouped as follows: 5 are engaged in research and development, 4 are related to the field of biotechnology, 4 to the information technology field and the last 4 to different business areas, mostly services. Finally, having regard to the strategic objectives they pursue, the UNITI spin‐offs are primarily – and prudently – aimed at the local or national market (precisely 14 of them, equal to more than four‐fifths of the total), which also reflects the entrepreneurial motives of their proponents ("lifestyle spin‐offs", according to the European Commission, 2002). Only 3 spin‐offs aim to grow on the international market ("growth spin‐off"). Not coincidentally, this second group consists of companies that include industrial partners among their founders and main shareholders. To conclude, we can say that the academic spin‐offs generated by the UNITI project, although too recent to allow for a reliable assessment of their impact, seem nevertheless to represent an interesting experience of business valorisation of the scientific and technological expertise developed in the context of university research.

4. The performance of the Uniti project spin‐offs The 17 companies resulting from the Uniti project, set up during the period 2009/2011, show the following situation (data in Euro/000). The data has been taken from the latest financial statements presented and approved (year 2011). See table 1.

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Renata Paola Dameri, Federico Fontana and Roberto Garelli Table 1: Data summary for the 17 spin‐off companies N. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Year 2009 2011 2010 2009 2010 2010 2011 2010 2010 2009 2010 2010 2009 2010 2009 2010 2009

Fixed assets 7 1 23 22 13 7 2 8 13 8 8 22 26 2 18 18 25

Capital 8 9 12 10 12 20 29 37 49 13 12 34 26 10 35 16 152

Sales 30 0 96 68 13 17 5 34 102 59 34 73 38 1 50 20 252

It is evident that 6 companies were set up in 2009, 9 in 2010 and only 2 in 2011. In brief, attention is drawn, on the basis of data found 1 , to the fact that all the companies considered share the following elements (with only one exception – spin‐off company 17 – which has a particular situation):

a limited amount of invested capital, of which the fixed assets play an important role;

a low amount of equity capital;

a low amount of long term liabilities.

The fixed assets are entirely made up of costs for the purchase of computer and other hardware. The costs for intangible fixed assets are practically irrelevant. To analyse the economic‐financial performance, attention is drawn, in this case, to the composition of investments and financing as well as their use and finally on the conditions of profitability. In this case the following indicators are used: F/K = rigidity; N/F = coverage; N/K = financial independence; ROE = return on equity; ROI = return on investment. From a structural point of view it can be noted that the percentage of the fixed assets of the capital invested (F/K) varies from 6.62 to 61.57 showing very different situations that are all united by the fact that the capital (K) is positioned on generally low values (only in 3 out of 17 cases does it rise above 100 thousand euro). All the companies show an elevated level of capitalization (N/K) the values of which vary between 7.28 and 90.18; 15 companies show values of N/K above 30% and 8 companies out of 17 above 50%. See fig.1 – diagram a). With regard to the profitability it can be noted, for each company, ROE and ROI values that are basically aligned (and both positive or both negative); nevertheless, the values for the profitability are both negative in only 4 out of 17 cases. In one individual case a ROE is postive and a ROI is negative (following a particular entry in the accounts of an extraordinary income item). With reference to the cost items in the profit and loss account it’s possible to note the low incidence of operating costs and the unflattering positioning of the amount of sales. See fig.1 – diagram b). At a later time the individual entities (spin‐off) were placed in the industry sector that they belonged to using the ATECO codes and the analysis was carried out comparing the principal indicators of economic‐financial performance with those of average Ligurian companies belonging to the same sector. The data used is relative to 375 companies subdivided in the different sectors as defined by the ATECO codes, having their registered office in Liguria and with a financial statement filed in 2011. The discrepancies relate to the comparison of the results of the spin‐off companies (grouped by sector) and those, appropriately selected, belonging to the same 1

The data used has been extracted from the Data Bank AIDA (Bureau Van Dijk).

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Renata Paola Dameri, Federico Fontana and Roberto Garelli sector. The comparison was done omitting 3 of the 17 spin‐offs (i.e. those set up in 2011 and at the end of 2010). The ATECO sectors referred to are the following: 1 = electric motor production, 2 =software production, 3 = consultancy 4 = other IT services, 5 = biotechnology R & D, 6 = R&D other sectors, 7 = university and post university education, 8 = geological studies, 9 = restoration of works of art. See table 2. Diagram a)

Diagram b) 1

1 100,00 17

100,00 17

80,00

40,00 20,00

‐100,00

6 12

7 11

ROI

ROE

‐150,00

N/K

‐50,00

F/K

0,00

7 11

8 10

0,00

60,00 15

50,00

8 10

Figure 1: Structure and profitability of the 17 spin‐off companies Table 2: Comparison between the performance of the spin‐offs versus Ligurian companies in the same sector (ATECO) ATECO sector N. spin off Ligurian companies F/K N/K ROE ROI

1 1 17 -40 -16 -2 0

2 1 259 -27 63 59 49

3 1 39 -2 65 36 51

4 1 4 -1 9 8 4

5 4 7 6 5 -7 -1

6 3 18 2 29 13 7

7 1 8 -41 9 11 -1

8 1 9 35 40 14 20

9 1 14 23 -2 -25 -11

The following points have emerged from the comparison carried out. The low value relative to the fixed investment (considerably less than the average in 4 out of 9 sectors) should be considered physiological and is connected to the limited tendencies to invest in long‐term assets, above all intangibile ones. Almost all the spin‐off companies (88% of the studied units) finance the fixed capital by using exclusively their original capital; in 8 out of 9 cases the fixed assets financed by capital of property is significantly higher than those of the other companies in the same sector (this should also be interpreted in light of the low average amount of capital invested). With regard to the composition of the sources it can be noted a particularly favourable level of financial independence which ranks, in almost all the examined companies (12 out of 14) and in 8 out of 9 sectors, values considerably higher than average. This aspect, appropriately investigated with specific questionnaires, has shown that the bank – spin‐off company relationship is always limited to current accounts: the absence of long‐term debts can be translated as an advantage both in terms of financial independence and in the impact of interest paid on the economic results. With regard to income aspects the situation is notably heterogeneous. The gap relative to the economic performance does not seem to be attributable to elements which characterise the spin‐off companies. However, some common elements can be noted, attributable to: absence or low incidence of employee costs, the low incidence of depreciation, the low incidence of financial components both active and passive and rare presence, in general, of uncharacteristic components. The results in terms of variances of profitability show values that tend to be aligned with ROE and ROI. Significantly postive variances emerge (greater than 20%) only in 2 sectors, attributable also to the low

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Renata Paola Dameri, Federico Fontana and Roberto Garelli incidence of the spin‐off companies’ original capital invested. Only one company showed results significantly lower than those of the sector.

5. Conclusion Academic spin‐offs are an interesting policy to support technological transfer from the research field to the business. This policy is really effective to support new enterprise settlement and a direct involvement of researchers in commercial activities. That is, spin‐off policy is an effective instrument to create a higher inclination of researchers to entrepreneurship; this means a faster and more effective transfer of knowledge to products and services and therefore a higher and faster value creation for people thank to the research results. The analysis of the spin‐offs resulting from the UNITI program allows us to briefly reflect on the characteristics, performance, and especially on the future of business arising from academic research. There are some positive elements to be highlighted: the heterogeneity of the economic sectors involved indicates that the spin‐off tool can be useful for technology transfer in all fields of research; the capitalization level and the good performance since the early years of life are promising signs for the spin‐off as a means to value creation. But there are also some negative elements: the low amount of invested capital prevents from operating in areas that require expensive facilities and equipment; the number of people involved is small and there is no growth strategies to foster development and employment opportunities; lack of exit strategies giving the spin‐off the ability to grow and develop, or be acquired by larger companies. To conclude, we can say that the academic spin‐offs generated by the UNITI program seem to represent an interesting experience of business valorisation of the scientific and technological expertise developed in the context of university research. However, researchers don’t have a good entrepreneurship competence; they are not aware about the role of equity or intellectual capital in business development in the medium and long term. Therefore, academic spin‐offs risk to suffer a blocked development, because they could lack the fundamental resources – capital and knowledge – to support their success and progression. Consequently, spin‐off strategy needs to be refined, for example introducing better training for researches‐ entrepreneurs or imaging some partnership between researchers, sharing their knowledge, business angels, putting on capitals, and managers, with their competence in business management.

References Bellini E., Capaldo G., Edström A., Kaulio M., Raffa M., Riccardia M. and Zollo G. (1999), “Strategic Paths of Academic Spin‐ offs”, 44th ICSB Conference, Naples, 20–23 June. Beraza J.M. and Castellanos A.R. (2012), “Tipología de las spin‐offs en un contexto universitario: una propuesta de clasificación”, Cuadernos de Gestión, 12(1):39‐57. Boschetti C., Grandi A. and Grimaldi R. (2011), “Risorse, competenze e incubatori d’impresa”, Sinergie, 61‐62:327‐349. Calvo M, Varela‐Candamio L., Soares I. and Rodeiro D. (2012), “Critical analysis of the role of universities in the creation and survival of university spin‐offs”, Advances in Management and Applied Economics, 2.2:53‐82. Cesaroni F., Moscara P. and Piccaluga A. (2005), “Le imprese spin‐off della ricerca in Italia”, Piccola impresa‐Small business, 276(1). Clarysse B., Heirman A. e Degroof J.J. (2000), “An Institutional and Resource based Explanation of Growth Patterns of Research based Spin‐offs in Europe”, in Reynolds P.D. et al., Frontiers of Entrepreneurship Research, Babson College, MA: Center for Entrepreneurial Studies, Babson College. Clausen, T. H., & Rasmussen, E. (2012), “Parallel business models and the innovativeness of research‐based spin‐off ventures”, The Journal of Technology Transfer, 1‐14. Colombo, M. G., & Piva, E. (2012), “Firms’ genetic characteristics and competence‐enlarging strategies: A comparison between academic and non‐academic high‐tech start‐ups”, Research Policy, 41(1), 79‐92. European Commission (2002), University spinouts in Europe. Overview and good practice, Luxembourg, Office for Official Publications of the European Communities. Druilhe C. and Garnsey E. (2004), “Do Academic SpinOuts Differ and Does it Matter?”, Journal of Technology Transfer, 29:269‐285. Freitas, J. S., Gonçalves, C. A., Cheng, L. C., & Muniz, R. M. (2012), “Structuration aspects in academic spin‐off emergence: A roadmap‐based analysis”, Technological Forecasting and Social Change. Grandi A. and Grimaldi R. (2005), “Academics’ organizational characteristics and the generation of successful business ideas”, Journal of Business Venturing, 20(6):821‐845. Klofsten M. and Jones‐Evans D. (2000), “Comparing Academic Entrepreneurship in Europe”, Small Business Economics, 14:299‐309.

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Renata Paola Dameri, Federico Fontana and Roberto Garelli Lockett A. and Wright M. (2005), “Resources, capabilities, risk capital and the creation of university spinout companies”, Research Policy, 34(7): 1043‐1057. McQueen D.H. and Wallmark J.T. (1982), “Spin‐off Companies from Chalmers University of Technology”, Technovation, 1:305‐315. Nicolaou N. and Birley S. (2002), “Academic networds, exodus and university spinout structure”, Frontiers of Entrepreneurship Research – Babson College Conference. Pellicano M. and Monetta G. (2007), “Sinergie relazionali per il successo degli spin‐off accademici”, Economia e diritto del terziario, 3:669‐691. Palumbo R. (2010), “Dall’Università al mercato – Governance e performance degli spin‐off universitari in Italia” Franco Angeli, Milano. Piccaluga A. (1991), “Gli spin‐off accademici nei settori ad alta tecnologia”, Sinergie, 25‐26. Pirnay F., Surlemont B. and Nlemvo F. (2003), “Toward a Typology of University Spinoffs”, Small Business Economics, 21:355‐369. Rappert B., Webster A. and Charles D. (1999), “Making Sense of Diversity and Reluctance: Academic‐Industrial Relations and Intellectual Property”, Research Policy, 28(9):873‐890. Salvador E. (2011), “How Effective Are Research Spin‐off Firms in Italy?”, Revue d'Économie Industrielle 133:99‐122. Shane S. (2004), Academic Entrepreneurship. University Spinoffs and Wealth Creation, Cheltenham, Edward Elgar Publishing Limited. Schumpeter J. (1934), The Theory of Economic Development, Cambridge, Harvard University Press. Smilor R.W., Gibson D.V. and Dietrich G.B. (1990), “Spin‐out Companies: Technology Start‐ups from UT‐Austin”, Journal of Business Venturing, 5(1):63‐76. Stankiewicz R. (1994), “Spinoff companies from universities”, Science and Public Policy, 21(2):99‐107. Van Dierdonck R. and Debackere K. (1988), “Academic entrepreneurship at Belgian Universities”, R&D Management, 18(4):341‐353. th Weatherston J. (1995), “Academic entrepreneurs: Is a spin‐off company too risky?”, 40 International Council on Small Business, Sydney. Wright M., Birley S. and Mosey S. (2004), “Entrepreneurship and University Technology Transfer”, Journal of Technology Transfer, 29:235‐246.

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Students’ Gains in Entrepreneurial Self‐Efficacy: A Comparison of ‘Learning‐By‐Doing’ Versus Lecture‐Based Courses Luc De Grez and Dirk Van Lindt Faculty of Economics & Business, Hogeschool Universiteit Brussel, Brussels, Belgium Luc.degrez@hubrussel.be Dirk.vanlindt@hubrussel.be Abstract: Entrepreneurial education has become increasingly important in higher education. It is therefore a challenge to find the most effective instructional method and learning environment for this entrepreneurial education. In this paper we focus on one aspect of entrepreneurial education: the enhancement of self‐efficacy. Earlier research suggested that ‘learning by doing’ programs can raise students’ entrepreneurial self‐efficacy. This situational self‐confidence is very important because it ensures that students actually practice what they learned. Self‐efficacy can be stimulated in the first place by enactive mastery experiences. But also modeling and verbal persuasion can raise self‐efficacy. Mastery experiences are very evident in ‘learning by doing’ courses and that is why it is hypothesized that ‘learning by doing’ courses will enhance self‐efficacy more than lecture‐based courses. It was also investigated whether personal or environmental variables have an impact on this increase. These research questions were examined with 213 economy students from a Belgian university. Two subgroups attended a learning by doing course and a third subgroup took lecture‐ based courses. A single group pretest‐posttest design was used with questionnaires at the beginning and at the end of the courses. Questionnaires contained subscales about entrepreneurial self‐efficacy and the Big Five personality questionnaire. Data about educational background of the participants and about some socio‐economic variables were also collected. Results showed differences between the three subgroups for personal characteristics, work experience and academic results. The three groups had for instance a different initial self‐efficacy level. The group consisting of professional Bachelor students had, at the start of the course, a lower self‐efficacy than the two groups from the academic program. This changed after following the different courses: the self‐efficacy of the two ‘learning by doing’ groups was raised significantly while the self‐efficacy of the lecture‐based courses group even diminished (but not significantly). There was also a gender effect with a lower entrepreneurial self‐efficacy for female participants. Variables related to educational and professional background such as student’s success rate and work experience had only a limited influence on entrepreneurial self‐ efficacy. Further qualitative and quantitative research is (certainly) needed in order to unravel the complicated, but intriguing process of stimulating entrepreneurship in educational settings. Keywords: entrepreneurial education, higher education, learning by doing , entrepreneurial self‐efficacy

1. Introduction The pressure on Higher Education to stimulate entrepreneurial learning is intensified by the economic crisis. Entrepreneurial education should, according to many, become an even more important part of higher education (Crayford, Fearon, McLaughin and van Vuuren, 2012). The broad concept of entrepreneurial education has been translated in a very wide range of types of courses, as illustrated in the review paper of Martin, McNally and Kay (2013). Courses with emphasis on ‘learning by doing’ or experiential learning are promoted particularly because of their effect on student motivation (Haase and Lautenschläger, 2011). Results of previous studies (De Grez and Van Lindt 2012) show that ‘learning by doing’ programs, in which students are provided with real‐world experiences, can raise entrepreneurial self‐efficacy of students. Self‐efficacy is a very important motivational construct which refers to “beliefs in one’s capabilities to organize and execute the courses of action required to produce given attainments” (Bandura, 1997, p.3). Learners need both skills and self‐efficacy beliefs to perform as what they learned. Self‐efficacy is always linked to specific realms of functioning. The literature about entrepreneurship suggests that self‐efficacy is essential for entrepreneurs to have and that people with higher entrepreneurial self‐efficacy have higher entrepreneurial intentions (Drnovsek, Wincent, and Cardon, 2010). We can stimulate self‐efficacy by providing learners with opportunities to exercise, because “enactive mastery experiences are the most influential source of efficacy information” (Bandura, 1997, 80). However, a vicarious experience or modeling and verbal persuasion can also enhance self‐efficacy. The latter two sources of self‐efficacy are also present in lecture‐based teaching courses. It can be hypothesized from the presence of mastery experiences that learning by doing courses enhance self‐ efficacy more than lecture‐based economics courses. However, even learning by doing courses differ in the number of opportunities to practice. Consequently. Comparing different types of courses is also encouraged by Martin et al. (2013).

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Luc De Grez and Dirk Van Lindt The main research question leads to a few additional questions: Is this gain in self‐efficacy the same for every student? How important is for instance the working experience many students have through student jobs? Which personality traits are important? It is important to raise these questions, not because entrepreneurship is a fixed and inborn personality trait, but because it is possible to develop traits favourable to entrepreneurship depending upon the predisposition of the individual (Haase and Lautenschläger, 2011). Research questions We investigated (1) whether ‘learning by doing’ programs can increase entrepreneurial self‐efficacy more than lecture‐based courses can, and (2) whether personal or environmental variables have an impact on this increase.

2. Research method 2.1 Participants Two hundred and thirteen students of a Belgian university college from two different economics departments (mean age = 22.18, 104 female) participated in the study. Originally the group contained 223 participants, but six questionnaires were incomplete or anonymous, two participants filled out two questionnaires and two participants were exchange students. The first group contained third (= last) year students from a professional bachelor in Business Science (n = 135, mean age = 22.4, 61 female) from three different programmes: Operation Management, Office Management, and Applied Information Technology. They had an internship (15 weeks) in a company during the last semester of their study. This is the Learning By Doing internship group (LBD internship). The two other groups were third‐year Bachelor students of Business Administration (n=78, mean age = 21.76, 43 female): The students from the second group (n = 46, mean age = 21.8, 25 female) were enrolled in a course in which where they worked on a project in a company during one semester (one day a week). This is the Learning By Doing project group (LBD project) The third group consisted of students (n=32, mean age = 21.8, 18 female) enrolled in lecture‐based theoretical courses (Lecture‐based Courses Group).

2.2 Measures Entrepreneurial self‐efficacy was measured by twenty‐two items on a ten‐point Likert scale (Chen, Greene and Crick 1998). The short version of the Big Five Personality questionnaire consisted of 15 items on a seven‐point Likert scale (Van Emmerik, Jawahar and Stone, 2004). The following socio‐economic variables were also obtained: gender, age, work experience (did you have a student job during the whole year or only during a part of the year, for instance the holidays, the weekends or some evenings). Finally, data about participants’ educational background were gathered: study track attended in high school and students’ success rate in higher education (in terms of credits acquired).

2.3 Method A single group pretest‐posttest design was used. A first questionnaire about self‐efficacy was presented at the start of the second semester of the program. The second questionnaire was administered at the end of the second semester and contained the self‐efficacy questionnaire together with the Big Five questionnaire. We assumed a stability concerning the Big Five for at least the duration of the study (12 weeks) when using pretest and posttest data in the analysis All the questionnaires were filled out online.

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3. Results In the first part of the analyses the differences regarding personal characteristics, work experience and the academic results between the three subgroups were investigated. Using ANOVA‐tests (all the data were normally distributed) the subscales Openness to Experience and Agreeableness of the Big Five Model were significant. Students of the Lecture‐based Courses group had a lower score on Openness to Experience than the other students who took a learning by doing program (F=7.012, p=0.001, n=213). The same conclusion could be drawn for Agreeableness (F=9.734, p<0.001, n=213). The variable Work Experience indicated if the students had a student job during the whole year or only during a part of the year (for instance the holidays, the weekends or some evenings). A higher percentage (59.7%, n=135) of Bachelor students in Business Science worked during the whole year in comparison with the students in Business Administration (46.2%, n=78). X2‐ tests showed that these differences in work experience between the students of Business Science and Business Administration were significant (X2=7.993, p=0.018). The averages of the academic results in students’ last year in higher education were compared for both groups in the program Business Administration. The academic result was measured by the student’s success rate which was indicated by the ratio of the ECTS‐grades obtained in the last academic year and the total number of ECTS‐grades for which students enrolled in that year. An Independent‐Samples t‐Test proved that the mean result (mean student’s success rate = 79.72%, n=46) for the students of the LBD project group was significant lower than the mean result (mean student’s success rate = 88.16%) for the students of the Lecture‐based Courses group (t=2.162, p=0.034, n=32). As mentioned before, entrepreneurial self‐efficacy was measured by a scale variable composed of 22 items. The internal consistency of this variable was indicated by the high value of Cronbach’s Alpha (α = 0.932).The relation between entrepreneurial self‐efficacy and educational program was investigated. At the start of the second semester the average level of the entrepreneurial self‐efficacy for the students in Business Science (LBD internship) was 5.975 (SD=1.315, n=135), for the students of the LBD project group 6.690 (SD=0.746, n=46) and for the students of the Lecture‐based Courses group 6.361 (SD=1.047, n=32). The ANOVA‐test indicated that these differences in the average levels were significant (F=6.745, p=0.001). Bonferonni’ test showed that the average level of the entrepreneurial self‐efficacy for the students in Business Science was lower than for the students in Business Administration. This effect of the educational program was confirmed by a multiple linear regression model controlling for the personal variables, the socio‐economic variables and the variables related to the educational background of the students. Selected predictors, regression coefficients and significant levels are presented in Table 1. The variables Lecture‐based course group and LBD‐ project are two dummy variables with the group of LBD‐internship as reference category. Table 1: Multiple regression model of entrepreneurial self‐efficacy (pretest) Variable

Tolerance

Lecture‐based course group

0.544

2.276

0.024

0.829

LBD‐project

0.787

3.907

<.001

0.881

Gender

‐0.380

‐2.342

0.020

0.925

Work experience

‐0.269

‐1.782

0.076

0.897

Openness to Experience

0.236

2.927

0.004

0.786

Conscientiousness

0.148

1.969

0.050

0.852

Introversion

‐0.073

‐1.170

0.243

0.883

Neuroticism

0.025

0.382

0.703

0.895

Agreeableness

‐0.02

‐0.205

0.838

0.717

Student’s success rate

0.239

0.544

0.587

0.918

Constant

4.783

5.596

<.001

This regression model explained 16.4% of the variation in (pretest) entrepreneurial self‐efficacy (R = 0.405, F = 3.955, p < .001) and the tolerance levels were much higher than .64, so multicollinearity problems were

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Luc De Grez and Dirk Van Lindt avoided. The dummy variables Lecture‐based course group and LBD‐project were significant at a 0.05 level. Variables related to educational and professional background such as student success rate and work experience had only a limited influence on entrepreneurial self‐efficacy. From the different dimensions of the Big Five model, Openness to Experience and Conscientiousness had a positive correlation with entrepreneurial self‐efficacy. The three other dimensions of the Big Five had no significant correlation. Finally, the average level of entrepreneurial self‐efficacy for the male students was 6.314 (SD=1.205, n=109) and for the female students 6.054 (SD=1.203, n=104). The regression coefficient of the variable gender was significant (T=2.342, p=0.020). In the second part of the survey the effects of ‘learning by doing’ programs on entrepreneurial self‐efficacy were investigated. The evolution in the entrepreneurial self‐efficacy is presented in Figure 1.

Figure 1: Comparison of entrepreneurial self‐efficacy: pretest versus posttest At the end of the second semester the average level of the entrepreneurial self‐efficacy for the students in Business Science (LBD internship) was 6.504 (SD=1.359, n=135), for the students of the LBD project group 6.991 (SD=1.078, N=46) and for the students of the Lecture‐based Courses group 6.211 (SD=1.344, n=32). The ANOVA‐test indicated that these differences in the average levels were again significant (F=3.801, p=0.024). Bonferonni’ test showed that the average level of the entrepreneurial self‐efficacy for the students without a ‘learning by doing’ program was lower than for the students in Business Administration with a project assignment. This conclusion was confirmed by a second multiple linear regression analysis. Table 2: Multiple regression model of entrepreneurial self‐efficacy (posttest) Variable

Lecture‐based course group

‐0.012

‐0.050

0.96

LBD‐project

0.671

3.336

0.001

Gender

‐0.636

‐3.927

<.001

Work experience

‐0.081

‐0.535

0.593

Openness to Experience

0.504

6.264

<.001

Conscientiousness

0.226

3.010

0.003

Introversion

0.017

0.274

0.784

Neuroticism

0.047

0.719

0.473

Agreeableness

‐0.168

‐1.718

0.087

Student’s success rate

1.052

2.394

0.018

Constant

3.221

3.771

<.001

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Luc De Grez and Dirk Van Lindt This regression model explained 29.9% of the variation in (posttest) entrepreneurial self‐efficacy (R = 0.546, F = 8.559, p < .001). The students of the Lecture‐based Courses group lost their advantage on entrepreneurial self‐ efficacy compared with the students of Business Science. The two groups of students in the ‘learning by doing’ program were able to realize a growth in entrepreneurial self‐efficacy. The significant regression coefficients of the pretest model were confirmed in the posttest model. The only exception was that students with a higher academic performance achieved also a higher effectiveness in terms of entrepreneurial self‐efficacy.

4. Conclusion It is important to note that following our results ‘learning by doing ‘programs raise self‐efficacy significantly and lecture‐based courses do not seem to do so. This is in accordance with the theoretical framework of Bandura (1979) according to which a mastery experience is the most powerful source of self‐efficacy and this source is prominently present in learning by doing programs. The students from the LBD internship group showed the biggest raise in self‐efficacy (from 5.975 to 6.504) but at the same time also had after all the lowest pretest self‐efficacy. An important limitation to this research should be mentioned and incite us to handle these results with care. It was not possible to work with a randomized assignment to treatment and control groups. This is a limitation often encountered in studies about entrepreneurial education. Martin et al. (2013) reported that only 6 studies included in their review study used this randomized assignment. In our study all the students of the professional bachelor in Business Science were obliged to do an internship and this made it impossible to work with a control group for this group. The third‐year students of Business Administration can choose between several programs and only some of these programs contain a project course. Unfortunately, results show that different programmes attract students with different profiles. Again, it is impossible to work with control groups. It is remarkable that results show on the one hand, differences between LBD groups and the lecture‐based course group and on the other hand differences between the two departments. The two groups of third‐year Bachelor students of Business Administration (LBD project and the lecture‐based Course group) had for instance a different initial average amount of self‐efficacy level. It is, however, possible that students starting the learning by doing course already felt already more confident because the learning by doing course is highly regarded by students because they are convinced that it will help them a great deal to become a successful economist. Consequently, it is possible that the face validity of this course could be higher and cause a higher self‐efficacy at the start of this course. The self‐efficacy of the third group is lower than the two other groups. It is plausible that students from the professional bachelor are less confident about their abilities than students from an academic bachelor are. But self‐efficacy is not the only difference between the groups. The students of the professional bachelor have for instance more work experience. This is important because this experience could provide the students with models that enhance self‐efficacy. Results from the regression model though show that work experience has only a limited influence on entrepreneurial self‐ efficacy. Students’ educational success rate also have a limited influence. As in earlier research we are unable to detect a big impact from personal or environmental variables on self‐efficacy (De Grez and Van Lindt, 2012). The positive correlation of entrepreneurial self‐efficacy with Openness to Experience and Conscientiousness is also a confirmation of earlier results (De Grez and Van Lindt, 2012). Students of the Lecture‐based Courses group have a lower score on two Big Five subscales (Openness to Experience and Agreeableness). They also had better study results in the last academic year. Further research is needed to investigate why certain programmes attract certain student profiles. Results also show a gender effect on self‐efficacy. Drnovsek et al. (2010) report that the literature on entrepreneurial self‐efficacy shows mixed results on this gender issue. Several conclusions can be drawn from the study presented. First of all, the potential of learning by doing courses to enhance self‐efficacy is confirmed. Secondly, it is also clear from this study that there is no such thing as a general profile of an economics student and that future research has to take into account individual characteristics such as different initial self‐efficacy levels. Not every student reacts in the same way to an instruction.

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Luc De Grez and Dirk Van Lindt Further research with bigger groups is certainly needed. This research could shed light on the processes underlying the enhancement of self‐efficacy through mastery experiences and modeling. Bar Nir, Watson and Hutchins (2011) already pointed at the complicated relationship between role models, self‐efficacy, entrepreneurial career intention and gender. Quantitative studies could be supplemented with qualitative studies in order to unravel the complicated, but intriguing process of stimulating entrepreneurship in educational settings.

References Bandura, A. (1997) Self‐efficacy: the exercise of control, Freeman: New York Bar Nir, A., Watson, W. and Hutchins, H. (2011) “Mediation and moderated mediation in the relationship among role models, self‐efficacy, entrepreneurial career intention, and gender”, Journal of Applied Social Psychology, Vol. 41, No. 2, pp 270‐297. Chen, C., Greene, P. and Crick, A. (1998) “Does entrepreneurial self‐efficacy distinguish entrepreneurs from managers?”, Journal of Business Venturing, Vol. 13, pp 295‐316. Crayford, J., Fearon, C., McLaughlin and Van Vuuren, W. (2012) “Affirming entrepreneurial education: learning, employability and personal development”, Industrial and Commercial Training, Vol. 44, No.4, pp 187‐193. De Grez, L. and Van Lindt, D. (2012) “The Influence of a ‘Learning‐by‐Doing’ Program on Entrepreneurial Perceptions of Economics Students”, Proceedings of the 7th European Conference on Innovation and Entrepreneurship pp 156‐162; Santarem (Portugal); 20‐21 September 2012. Drnovsek, M., Wincent, J. and Cardon, M. (2011) “Entrepreneurial self‐efficacy and business start‐up: developing a multi‐ dimensional definition”, International Journal of Entrepreneurial Behaviour & Research, Vol. 16, No. 4, pp 329‐348. Haase, H. and Lautenschläger, A. (2011) “The ‘teachability dilemma’ of entrepreneurship”, Int. Entrep. Manag. Journal, Vol. 7, pp 145‐162. Martin, B., McNally, J. and Kay, M. (2013) ”Examining the formation of human capital in entrepreneurship: a meta‐analysis of entrepreneurship education outcomes”, Journal of Business Venturing, Vol. 28, pp 211‐224. Van Emmerik, IJ., Jawahar, I. and Stone, T. (2004) “The relationship between personality and discretionary helping behaviors”, Psychological Reports, Vol.95, pp 355‐365.

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Rewards Work? Researching the Relation Between Monetary Reward and Employee Innovativeness Stan De Spiegelaere 1, Guy Van Gyes 1 and Geert Van Hootegem 2 1 HIVA‐KULeuven, Leuven, Belgium 2 CESO‐KULeuven, Leuven, Belgium Stan.despiegelaere@kuleuven.be guy.vangyes@kuleuven.be geert.vanhootegem@soc.kuleuven.ac.be Abstract: As organizations try to steer and direct the behaviour of employees, they frequently introduce reward schemes to align the employee behaviour with the companies interests. Yet, while these reward schemes can result in people working hard, the question is whether they also enable employees to work smart. In this paper we therefore study the relation between two different sort of financial reward schemes (individual and collective based) and their relation with the Innovative Work behaviour (IWB) of employees. Building on job design and intrinsic motivation literature, we expect to find both positive and negative relations, depending on the work context of the employee. Using survey data on 927 employees from five Belgian industries, we find that indeed individual financial rewards are both associated with more and less IWB, depending on the degree of autonomy of the employee. Rewards work in poor autonomy jobs, but have a negative association with IWB in high autonomy jobs. As for collective rewards, the faint positive relation is greatly enhanced when group‐communication is effective. We conclude that reward systems for innovation are no quick win and that the work organization should be taken into account. Keywords: innovative work behaviour, reward, job, collective reward, flexible pay

1. Introduction Both policy makers, managers and academia are increasingly aware of the importance of employee creativity and innovativeness (European Commission 2010; EUWIN 2012). As organizations are under pressure to continuously reinvent their products and production processes, the employee contribution in this process of continuous innovation is progressively acknowledged. Academic research frequently stressed that in order to boost the creative performance of employees, one should focus on boosting their intrinsic motivation (motivation coming from the task itself, because the employee enjoys doing it). As such, Hammond et al. (2011) recently identified job characteristics as the main trigger of employee innovativeness in their meta‐ analysis. Notwithstanding the relative consensus in academia about the primary importance of intrinsic motivation for employee innovativeness, HR managers on the field still quickly turn to extrinsic, monetary reward policies in order to promote certain employee behaviour. The role of these monetary rewards is nevertheless heavily disputed. Monetary rewards would increase the extrinsic motivation of employees (motivation rooted in the desire to obtain some outcomes of the work, such as reward or status), which could actually result in lower levels of intrinsic motivation (Amabile 1988; Deci & Ryan 2000). Others nevertheless found opposing evidence which suggest that giving extrinsic rewards could actually increase the creative performance of employees (Eisenberger & Shanock 2003). Some years ago, Baer, Oldham and Cummings (2003) studied these contradicting findings and discovered that the relation of extrinsic rewards on creativity is not linear, it depends on other characteristics which are related to the intrinsic motivation of employees. As such they found that for employees in complex, challenging jobs extrinsic rewards have a negative relation with their creative performance. Yet, for employees in non‐challenging simple jobs, extrinsic rewards stand in an opposite, positive relation to employee creativity. Since then, the research literature on employee innovativeness progressed rapidly. As such, the concept of ‘innovative work behaviour’ (IWB) and its dimensions related to idea generation and implementation has become more popular. In this article, we study the relation between extrinsic monetary rewards and employee innovativeness. In doing so, we distinguish between two large categories of extrinsic reward policies frequently used by organizations: individual performance related pay (PRP) and collective performance related pay. As will be shown in this article, these two kinds of extrinsic reward policies have very different relations with employee innovative outcomes. As such, this article makes a bridge between the literature streams of industrial psychology and organizational sociology by combining concepts and research traditions of both fields. In what

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem follows, we first define and describe the concepts of innovative work behaviour (IWB). We continue with a discussion of the difference between individual and collective forms of PRP and their relation with employee outcomes. Afterwards, we discuss the methodology and results of the analyses.

2. Literature 2.1 Employee innovative behaviour In this study, the main dependent variables are Innovative Work Behaviour (IWB) on the one hand and incremental & radical creativity on the other. Innovative work behaviour is here defined as: “all employee behaviour directed at the generation, introduction and/or application (within a role, group or organization) of ideas, processes, products or procedures, new to the relevant unit of adoption that supposedly significant benefit the relevant unit of adoption”. IWB thus includes behaviour of employees that directly and indirectly stimulates the development and introduction of innovations on the workplace. Employee creativity can be defined as the production of novel and useful ideas or solution in the workplace (Amabile 1988). The definition of IWB and creativity are very similar, yet cover distinct realities for two main reasons. First, creativity focuses exclusively on the generation of ideas, while IWB encompasses all employee behaviour related to different phases of the innovation process (Kanter 1988). Second, creativity traditionally refers to the creation of something absolutely new. IWB on the contrary focuses on something new, for the relevant unit of adoption. Employees who take the initiative to copy successful work habits from other departments, for example, are clearly staging important ‘innovative behaviour’, while not at all engaging in workplace creativity. As already stated, IWB makes an explicit reference to the distinct parts of the innovation process. A problem is recognized, a idea for a solution is generated and developed, the idea is proposed, defended and eventually implemented in the organization (Kanter 1988). Therefore, researchers on IWB frequently distinguish between two subdimensions of IWB: idea generation and idea implementation (De Jong & Den Hartog 2007).

2.2 Monetary rewards & employee innovativeness The relation between giving employees financial incentives and employee outcomes in terms of motivation, productivity or creativity has been the subject of fierce debates, both in industrial psychology and organizational sociology literature. In industrial psychology, the discussions are focused on the roles of intrinsic motivation at the one hand, and extrinsic motivation at the other hand. Intrinsic motivation refers to a motivation to work, rooted in the work itself. Employees can be motivated because they find the work interesting and challenging. Intrinsically motivated employees would be more creative as they are generally more be more curious, flexible, persistent and have an internal drive for optimizing the work process (Baer e.a. 2003; Shalley & Gilson 2004). Extrinsic motivation refers to a motivation rooted in the desire to obtain some outcomes of the work, such as reward or status (Amabile 1993). Installing performance related incentive systems would increase the attention of the employees to the rewards and thus increase their extrinsic motivation. Whether this increase in extrinsic motivation occurs at the detriment of the intrinsic motivation or is added up is one of the focal points of debates between the friends and foes of providing incentive rewards. Empirical findings tend to find evidence for both the argument that extrinsic rewards stimulate (Eisenberger & Rhoades 2001; Ramamoorthy e.a. 2005) or deter creativity/innovativeness (e.g. Kruglanski et al., 1971). Building on these contradictory findings Baer et al. (2003) studied the effect of extrinsic reward on employee creativity, taking into account the role of first job complexity and second the cognitive style of the employees. His data suggested that reward has very different (and opposing) relations with creativity, depending whether the employee has a simple or complex task. They related their findings to the previously mentioned idea that when intrinsic motivation is high (complex job), extrinsic rewards will ‘outcrowd’ the intrinsic motivation and reduce the creative performance of employees. Yet, when intrinsic motivation is low (simple jobs), extrinsic rewards will give a certain degree of control to the employees which will lead to higher levels of creative performance. The same inconclusiveness is reflected in the organizational sociology field. Here, reward systems are discussed in the context of what is called ‘High‐Performance Work Systems (HPWS)’, which are HR practices that would lead to supreme company performance through the stimulation of the employee motivation, productivity and innovativeness. Nevertheless, when it comes to performance related reward systems, the overall evaluation is mixed. Empirical studies focusing on the direct effect of incentive schemes on organizational innovativeness mostly find insignificant effects (Michie & Sheehan, 1999; Shipton, Fay, West,

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem Patterson, & Birdi, 2005; Shipton et al., 2004; Zoghi, Mohr, & Meyer, 2010), while some find positive (Nielsen & Lundvall, 2003) or mixed effects (Walsworth & Verma, 2007). Just as in the industrial psychology literature, important interaction effects are nevertheless mentioned. As such, the effect of a performance related reward system generally increases when combined into ‘bundles’ or ‘systems’ with other HR practices (Laursen & Foss, 2003).

2.3 Individual and collective PRP Under the general term of ‘Performance‐related pay’ (PRP), organizations introduced a wide variety of systems in which employees receive a monetary reward contingent on the performance of an individual, group or company as a whole (Aumayr e.a. 2011). Building on organizational research, we know that the selection of the indicators, the process of evaluation, the frequency and the height of the reward all have their influence of the effectiveness and success of the reward system (Thierry 2011). A major distinction can be made between individual and collective PRP. The first refers to PRP systems where the reward is contingent on the individual performance of the employee, whereas collective PRP is linked to meeting collective performance indicators on the level of the department or company. When it comes to employee outcomes, both have very different rationales and consequences as the focus is or on the individual, or on the group. Individual PRP (implicitly or explicitly) introduces a form of competition between workers while collective PRP (implicitly or explicitly) introduces an incentive for cooperation while at the same time risks to stimulate ‘free rider behaviour’.

2.4 Individual PRP & employee innovativeness Building on the previously discussed theoretical and empirical literature, we suspect to find no significant linear relations between individual PRP and employee innovativeness. As was demonstrated by Baer et al. (2003) the effect of reward on creativity is dependent on the job context of the employee. As such, we suspect to find a significant interaction effects between job resources, individual PRP and employee creativity/innovativeness. Job resources is defined here as “those physical, social, or organizational aspects of the job that may do any of the following: (a) be functional in achieving work goals; (b) reduce job demands and the associated physiological and psychological costs; (c) stimulate personal growth and development” (A. B. Bakker & Demerouti 2007) and is closely related to how Baer et al. (2003) see their ‘job complexity’. As they stated, providing extrinsic rewards in complex jobs tend to negatively affect individual creativity (through depressed levels of intrinsic motivation). At the same time, providing extrinsic rewards in simple jobs is related to higher levels of individual creativity (as employees are given a basic sense of control in jobs with which are not intrinsically motivating). Hypothesis 1: There is no direct linear relation between individual PRP and employee innovativeness. Hypothesis 2: The relation between individual PRP and employee innovativeness will be interacted by the degree of job resources enjoyed by the employee in such that individual PRP will be positively related to employee innovativeness when job resources are low and negatively when job resources are high. We nevertheless suspect that this relation will be weaker for idea implementation as idea implementation is likely to suffer more from the competition element related to individual PRP. Hypothesis 3: This interaction effect between individual PRP and job resources will be particularly strong for idea implementation.

2.5 Collective PRP and employee innovativeness Very little is known about the impact of collective PRP on the motivation or creativeness of employees. Advocates of collective reward systems refer to the increased cooperation and feelings of ownership or commitment of employees to state that collective reward systems can positively contribute to the motivation and performance of employees (Bartol & Srivastava 2002). Adversaries on the other hand point to the problem of ‘free rider behaviour’ of employees (Gerhart e.a. 1995). Empirical studies are rare, yet one study performed by Hanlon, Meyer and Taylor (1994) studied the effect of the elimination of a gainsharing plan. After the elimination of this collective reward policy, the researchers observed higher levels of job satisfaction, commitment, but also of idea generation. Other studies on the other hand note that through forms of collective PRP, employees have an incentive to share ideas and knowledge that they would otherwise keep for

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem themselves (Bartol & Srivastava 2002). Also the empirical studies on the organizational level find weak positive relations between collective forms of PRP and innovation (Zoghi e.a. 2010), while others find insignificant results (Michie & Sheehan 1999). At last, studies on the year‐old ‘Scanlon Plan’ are revealing (Welbourne & Mejia 1995). According to these case‐studies, the introduction of a form of collective reward, combined with a organizational structure in which employees can effectively influence the companies’ performance will result in an overall increase of employee motivation and firm profitability, through the optimal mobilization of the innovative and creative ideas of employees (Massoud e.a. 2008; Thierry 2011; Wren 2009). Building on these last insights, we suspect that the relation between collective PRP and the individual innovative behaviour of employees will depend on their evaluation of the influence they have on the group outcomes. If employees feel they can effectively communicate their ideas and complaints to the group, the collective PRP will strongly affect the employees’ innovative performance. We further suspect that the influence of the collective PRP will predominantly affect the idea implementation behaviour as this type of IWB is more strongly linked to group dynamics than the idea generation. Hypothesis 4: There will be a positive relation between collective PRP and IWB. This relation will be stronger for idea implementation. Hypothesis 5: Effective group communication will interact in the relation between collective PRP and IWB where the combination of both collective PRP and company resources will result in the highest levels of IWB.

Figure 1: Hypotheses and model

3. Method Data collection and sample. The data used in this article is based on an employee‐level face‐to‐face data collection based on standardized surveys. The sample consisted of Flemish unionized workers from five different industries: banking, retail, hotels & restaurants, chemical industry and the social sector. It concerns an a‐select sample taken from the membership databases of the two primary unions organized in these sectors. As such, the sample consisted of employees from a multitude of organizations and HR policies. In total 927 surveys were collected with an overall response rate of 49%. Measures. The presence of individual and collective forms of performance‐related pay was measured using dummy variables. Employees were asked whether a part of their wage was dependent on their individual performance first. Second, employees were asked whether their wage (on a monthly, yearly or other basis) was dependent on the group level performance or company performance (profit sharing, gain sharing and occasional collective bonuses). Innovative work behaviour, was measured using the IWB scale developed by De Jong & Den Hartog (2010). Respondents indicated how much a certain characteristic occurred in their job, ranging from “very rarely” to “very frequent”. Examples are: finding original solutions for work related problems and developing innovative ideas into practical application. An exploratory factor analysis showed that a two‐factor solution was to be preferred. This factor solution separated the IWB scale in a idea generation and idea implementation dimensions with high reliability (Cronbach α: 0.88 & 0.94). Job resources was measured using a series of 7 questions which referred to job autonomy (e.g. I can arrange my own work pace’ and ‘I can decide for myself how I perform my work’) and 7 questions related to learning opportunities at work (e.g. I have the opportunity to develop my professional skill and through my work, I learn new stuff). Following Schaufeli & Bakker (2004), we calculated a single variable of all these items with a high reliability

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem (Cronbach α: 0.87). The measure for group communication was based on a 3 item scale including questions like ‘in my company people can express clearly when they disagree on a topic’, and ‘in my company, one can react on decisions coming from above’ (α: 0.84). Further, control variables were included such as educational level, sector of employment, age, size of company and type of employee.

4. Results 4.1 Descriptive results Table 1 and 2 give some descriptive statistics of the data. We first see that the overall reliability of the scales used in this research was satisfactory. The scales were calculated based on the factor scores of the items. Consequently, all variables were centered around a mean of zero. As we expected, the correlations of the job resources and group communication variable with the employee innovativeness are all positive and significant. Table 1: Descriptive statistics ‐ correlations

Cr a

Job Resources

0,87

Group Communication

Idea Generation

Idea Implementation

St Dev 0,94

0,84

0,327*

0,93

0,88

0,507*

0,190*

0,95

0,94

0,97

0,445*

0,221*

0,767*

* p: <,01

Table 2 gives an overview of the relation between the various variables and the PRP policies. As can be seen, a sufficient fraction of the sample was subjected to individual or collective PRP policies. The regarding some dependent and independent variables are mostly relatively small and statistically not significant. Regarding individual PRP we see a significant difference when it comes to group communication (which has a higher value when there is an individual PRP system) and the two dimensions of IWB. Regarding collective PRP the only observed bivariate difference is found regarding the job resources. Employees who fall under a collective PRP system tend to have more resources in their jobs. Table 2: Descriptive statistics ‐ individual & collective PRP

Resources

Group Communication

Idea Generation

Idea Implementation

Individual PRP 340 Yes

0,04

0,84

0,10

0,82

0,17

0,85

0,11

0,91

587

‐0,03

0,99

‐0,06

0,99

‐0,10

0,99

‐0,07

Sign diff. Collective PRP

not sign.

1,00 **

Yes

177

0,16

0,77

‐0,08

0,92

0,11

0,83

0,02

0,87

736

‐0,04

0,98

0,02

0,94

‐0,03

0,98

‐0,01

0,99

Sign diff.

not sign.

* α:0,05; ** α:0,01

4.2 Regression results The results of the regression analysis are given in Table 3. We first of all notice that our model has a relative strong explanatory value for the two IWB dimensions (R2 between 0.28 and 0.35). Next, we see that job resources stand in a strong positive linear relation with all dependent variables in this research. This finding is in line with the literature on the importance of job resources of employee innovativeness (Hammond e.a. 2011). The linear relation between group communication and our dependent variables is nevertheless more ambiguous. Where group communication is positively related to idea implementation, it is not related to idea generation. This findings confirms that idea implementation is, more than idea generation, an form of employee behaviour that is affected by group dynamics.

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem Table 3: Regression results

Idea Generation

Model 1

R square

Idea Implementation

Model 2

0,34

Model 1

0,35

Model 2

0,28

Beta 0,40

p val. <,01

Beta 0,44

p val. <,01

Beta 0,34

p val. <,01

Beta 0,36

p val. <,01

Group Communication

0,03

0,31

‐0,01

0,67

0,09

0,01

0,05

0,15

Collective PRP (0: no PRP)

0,30

<,01

0,29

<,01

0,27

<,01

0,26

<,01

Individual PRP (0: no PRP) Coll PRP* Group Resources

0,03

0,68

0,08

0,31

‐0,02

0,77

0,01

0,93

0,15

0,02

0,11

0,09

Ind PRP*Job Resources

‐0,23

0,01

‐0,13

0,14

Job Resources

Model controlled for age, education, sector, company size & hierarchical status

Turning to our hypotheses, we see that our first hypothesis is fully confirmed. There’s no linear relation between the presence of an individual PRP system and the individual employee behaviour. Nevertheless, the interaction (hypothesis two) of individual PRP with job resources on the dependent variables was significant for idea generation. For ease of interpretation, we plotted these interaction effects in figure 1.

Figure 2: Interaction of Individual PRP and job resources on idea generation As we hypothesized (hypothesis two), the relation of individual PRP shifts, depending on the level of job resources. When employees have ‘high resource jobs’, the individual PRP is not, or even negatively related with the generation of ideas. For employees in low resources jobs, on the other hand, the relation between individual PRP and idea generation is positive. Regarding the relation of individual PRP on idea implementation, none of the studied relations (direct and interaction) were significant. As not all the interaction effects were significant, we conclude that our second hypothesis is only partially confirmed. The third hypothesis on the other hand is fully confirmed. Individual PRP and the interaction with job resources is particularly important for idea generation. Regarding collective forms of PRP, we suggested that there would be a positive relation between collective PRP and the employee outcomes, and that this relation will be particularly strong for idea implementation. As can be seen in Table 3, collective PRP indeed stands in a direct positive relation with idea generation and idea implementation. The strength of the relation with idea implementation is not significantly different from the relation with idea generation which refutes the second part of our fourth hypothesis. Our fifth hypothesis suggested that the relation between collective PRP and our dependent variables will be particularly outspoken when the subjective appraisal of group communication in the company is high. This hypothesis could only be confirmed for idea generation (figure 2) and shows the pattern we hypothesized. For all other dependent variables, this interaction effect was insignificant.

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem

Figure 3: Interaction of collective PRP and group level resources on idea generation

5. Discussion As managers try to influence the behaviour of their employees, they frequently turn to monetary incentive schemes to do so. Yet, monetary rewards schemes are mostly known for their complexity, not their effectiveness. Moreover, giving people financial rewards can well undermine their intrinsic motivation and negatively affect their innovative and creative performance. Earlier studies showed that the relation between rewards and creativity is complex (Baer e.a. 2003) and this study builds on these insights to further untangle this relevant research question. In doing so, we use recent insights on the diverse nature of both employee innovative behaviour. Further, we chose not to use subjective evaluations of reward, but objective indicators regarding the absence or presence of both individual and collective PRP systems. Our analysis first showed what is generally known fact in the innovation research: more than rewards, the work content is a crucial factor for explaining employee innovativeness. Job resources such as autonomy and learning opportunities are strongly related to all dimensions of IWB. Regarding our main object of study, individual and collective PRP, the findings mostly confirmed our hypothesis. Individual PRP is mostly unrelated to employee innovative or creative behaviour. For idea implementation, no relation was between the two variables. For idea generation on the other hand, the interaction between job resources and individual PRP was significant. Analysis of the pattern showed that, in line with previous findings (e.g. Baer et al., 2003), individual PRP is positively related with the dependent variables when the job resources are low, yet negatively when job resources are high. Although our data cannot establish causal relation, it appears that giving individual rewards to employees is no managerial ‘quick win’ for employee innovativeness. On the contrary, blind individual reward policies can potentially undermine the innovative performance of employees and therefore the performance of the company at large. Contrary to the complexity of individual PRP, collective PRP was found to be directly and strongly related to both dimensions of IWB. For idea generation, we also found a significant interaction with effective group communication on ideas and complaints which amplified the positive relation of collective PRP. This last finding confirms the year old case‐study findings on the implementation of so‐called Scanlon Plans: effective employee innovation comes from the combination of collective reward with effective participation of employees. The findings on first individual PRP and collective PRP could hardly be more contrasting. Where individual PRP asserts itself as a complex, potentially negative policy option for stimulation employee innovativeness, the relation between collective PRP and employee innovativeness is straightforward and simple. This observation stands in contrast with the very scant attention that went collective reward in both the industrial psychology and organizational sociology literature.

6. Conclusion As Jeffrey Pfeffer (1998) noted in his article in the Harvard Business Review, performance related pay policies are very popular with managers cause, “It's simpler for managers to tinker with compensation than to change the company's culture”. Yet, while implementing reward systems might be relatively easy, assessing their

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Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem outcomes is not, definitely not when it comes to employee innovativeness. As we have shown in this article, when it comes to individual PRP, both negative, positive and insignificant relations are found. All depends on first the outcome variable and second, the degree of resources enjoyed by the employee. When the job is challenging and resourceful, individual PRP undermines employee idea generation. Yet, when resources are low, individual PRP can actually enhance their innovative behaviour. Where the individual PRP is marked by ambiguousness and complexity, collective PRP has a strikingly straightforward and strong relation with employee innovative outcomes. As has been shown by this article, reward matters for IWB. Yet, the size and direction of the relation all depends on the job of the employee and on the organization.

References Amabile, T.M., 1988. A model of creativity and innovation in organizations. In B. M. Staw & L. L. Cummings, red. Research in Organizational Behavior. Greenwich: J.A.I. Press, pp. 123–167. Amabile, T.M., 1993. Motivational synergy: Toward new conceptualizations of intrinsic and extrinsic motivation in the workplace. Human Resource Management Review, 3(3), pp.185–201. Aumayr, C., Welz, C. & Demetriades, S., 2011. Performance‐related pay and employment relations in European companies, Dublin: Eurofound. Baer, M., Oldham, G.R. & Cummings, A., 2003. Rewarding creativity: when does it really matter? The Leadership Quarterly, 14(4‐5), pp.569–586. Bakker, A. B. & Demerouti, E., 2007. The job demands‐resources model: State of the art. Journal of Managerial Psychology, 22(3), pp.309–328. Bartol, K.M. & Srivastava, A., 2002. Encouraging Knowledge Sharing: The Role of Organizational Reward Systems. Journal of Leadership & Organizational Studies, 9(1), pp.64 –76. Deci, E.L. & Ryan, R.M., 2000. The “What” and “Why” of Goal Pursuits: Human Needs and the Self‐Determination of Behavior. Psychological Inquiry, 11(4), pp.227–268. Eisenberger, R. & Rhoades, L., 2001. Incremental Effects of Reward on Creativity. Journal of Personality and Social Psychology, 81(4), pp.728–741. Eisenberger, R. & Shanock, L., 2003. Rewards, Intrinsic Motivation, and Creativity: A Case Study of Conceptual and Methodological Isolation. Creativity Research Journal, 15(2/3), p.121. European Commission, 2010. Europe 2020. A European strategy for smart, sustainable and inclusive growth, European Commission. EUWIN, 2012. Dortmund/Brussels Position Paper: Workplace Innovation as Social Innovation. Gerhart, B.A., Minkoff, H.B. & Olsen, R.N., 1995. Employee compensation: Theory, practice, and evidence. CAHRS Working Paper Series, p.194. Hammond, M.M. e.a., 2011. Predictors of individual‐level innovation at work: A meta‐analysis. Psychology of Aesthetics, Creativity, and the Arts, 5(1), pp.90–105. Hanlon, S.C., Meyer, D.G. & Taylor, R.R., 1994. Consequences of Gainsharing A Field Experiment Revisited. Group & Organization Management, 19(1), pp.87–111. De Jong, J. & Den Hartog, D., 2007. How leaders influence employees’ innovative behaviour. European Journal of Innovation Management, 10(1), pp.41–64. Kanter, R.M., 1988. When a Thousand Flowers Bloom: Structural, Collective, and Social Conditions for Innovation in Organisations.". In B. M. Staw & L. L. Cummings, red. Research in Organizational Behavior. Greenwich: J.A.I. Press, pp. 93–131. Kruglanski, A.W., Friedman, I. & Zeevi, G., 1971. The effects of extrinsic incentive on some qualitative aspects of task performance1. Journal of Personality, 39(4), pp.606–617. Massoud, J.A., Daily, B.F. & Bishop, J.W., 2008. Reward for environmental performance: using the Scanlon Plan as catalyst to green organisations. International Journal of Environment, Workplace and Employment, 4(1), pp.15–31. Michie, J. & Sheehan, M., 1999. No innovation without representation? An analysis of participation, representation, R&D and innovation. Economic Analysis: Journal of Enterprise and Participation, 2, pp.85–97. Pfeffer, J., 1998. Six Dangerous Myths About Pay ‐ Harvard Business Review. Harvard Business Review, pp.108–119. Ramamoorthy, N. e.a., 2005. Determinants of Innovative Work Behaviour: Development and Test of an Integrated Model. Creativity and Innovation Management, 14(2), pp.142–150. Schaufeli, W.B. & Bakker, Arnold B., 2004. Job demands, job resources, and their relationship with burnout and engagement: a multi‐sample study. Journal of Organizational Behavior, 25(3), pp.293–315. Shalley, C.E. & Gilson, L.L., 2004. What leaders need to know: A revieuw of social and contextual factors that can foster or hinder creativity. The Leadership Quarterly, 15, pp.33–53. Thierry, H., 2011. Beter belonen in organisaties, Assen: Van Gorcum. Welbourne, T.M. & Mejia, L.R.G., 1995. Gainsharing: A Critical Review and a Future Research Agenda. Journal of Management, 21(3), pp.559–609. Wren, D., 2009. Joseph N. Scanlon: the man and the plan. Journal of Management History, 15, pp.20–37. Zoghi, C., Mohr, R.D. & Meyer, P.B., 2010. Workplace Organization and Innovation. Canadian Journal of Economics, 43(2), pp.622–639.

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Significant Competitiveness Factors of Companies in the Czech Part of the Euroregion Neisse‐Nisa‐Nysa Jaroslava Dědková and Denisa Skrbková Technical University of Liberec, Liberec, Czech Republic jaroslava.dedkova@tul.cz denisa.skrbkova@tul.cz Abstract: If a company wants to maintain its competitive advantage, it is forced to constantly observe and monitor the market situation, react on the changing market conditions and be prepared to rapidly and efficiently produce, develop and advertise a wide range of quality products and to accelerate its innovation cycles. It is possible to assume that the company which wants to be successful in the market has to develop particularly its flexibility, innovation and competitiveness. The flexibility of the company is based on its ability to quickly react on customer´s requirements and competitor´s strategy. The firm should be able to produce at the lowest level of production costs while achieving high productivity and innovation processes. The main objective of this paper is to identify the significant factors of companies competitiveness in the Czech part of the Euroregion Nisa based on the evaluating primary obtained data. For the evaluation is used the factor analysis and factors are sorted according the significance of action. The authors discuss the question of which factors are important for companies and how to increase the competitiveness of enterprises. These factors are called “key factors” of competitiveness. The importance of these key factors depends on many conditions, such as the scope of the business, on the business field, on size of the business, on the requirements of the owners and customers, on the priorities of management, etc. The purpose of this research is to find which key factors are dominant and have the biggest influence on how competitive the company is. This research is going to study besides other things the new categories of competitiveness factors, which are identity, integrity, mobility and sovereignty of the firms which are not studied as much as the other factors. The companies are constantly trying to identify and measure factors of competitiveness. Current theories do not have one specific indicator, which could determine whether the firm is competitive or not. Keywords: competitiveness, research, competitive advantage, innovation cycle, competitive factors, Euroregion Nisa

1. Introduction All economic markets are currently affected by fast, dramatic changes. Globalisation and the interconnection of multinational cooperation has led to unforeseeable turns of events, the rise of competition and changes in customer preferences. A company that wants to succeed must always be able to respond flexibly to these factors and must be competitive. (Filo, 2005) Increasing a company’s level of competitiveness is central to its success or failure on the market. This ability (to be competitive) is an important condition for a company being able to remain on the market and further stabilise its operation on that market.

2. Competitiveness The term competitiveness is difficult to define because it is used in different ways in many different contexts and in different concepts. We can compare the competitiveness of individual states, regions or companies. (Turok, 2003) According to the Commission of the European Communities (2003), competitiveness is “the ability of an economy to provide its people with a rising standard of living and a high level of employment for all those that want to work on a sustainable basis”. This paper will be, however, primarily concentrate on the competitiveness of individual companies. The competitiveness and competition do not have any unambiguous definition in economic theory. Kotler (2007) deals with a question of how can be the company successful in such a competitive environment. He is also looking at the competitive position of the company and discusses the strategies of competing. The work of J. A. Jirásek (2001) has been important in formulating characteristics and analysing the concepts of company advantages and competition. He defined competitiveness as “a term that expresses the market potential of individual companies, sectors or countries in the market position fight with other companies, sectors or countries.” Čichovský L. (2002) defines competition as an “opened‐set of competitors creating in a given time and territory of competitive environment the functional many‐factors effect connected with achieving an influence against other members of the competition."

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Jaroslava Dědková and Denisa Skrbková As Porter (1998) says, being competitive means a company knowing how to assert itself and knowing how to compete with local companies on world markets. Fischer and Schornberg (2007) are of a different opinion, considering competitiveness the ability of a company to obtain and maintain a position on the market over the long‐term. This aspect of competitive advantage is elaborated by Miklošík, Hvizdová and Žák (2012), who introduce and analyze new factors affecting the sustainability in the present turbulent markets. According to Feurer and Chaharbaghi (1994), the term competitiveness is truly universal and means something different to each and every organisation. Some see strength in persuading customers of the quality of their products, whereas others consider improving individual production processes within a company to be most important. Research has being conducted not only on internal processes; in the same time the growing importance of Information Management, namely the interaction with customers is often demonstrated as an important source of competitiveness. (Tislerova, 2012). Beneš (2006) considers the term competitiveness of a company to indicate a certain “ability to successfully compete on markets”. The sections, that follow, aim to discuss what successfully competing on markets actually means and how this competition can be compared.

2.1 Measuring competitiveness There is currently no uniform study on how to measure competitiveness. All authors look at competitiveness from a different angle. Some (Suchánek, Špalek, 2009) suggest the indicators of financial analyses as the best instruments for measuring competitiveness. According to them, the “starting criterion of competitiveness is the financial success of a given company”. In contrast to this, Donaldson and Preston (1995) consider a company to be a complex unit created on the basis of variously interconnected and joined individual interest groups. When measuring competitiveness, this so‐called stakeholder approach requires the inclusion of financial indicators and indicators that encompass the performance and controlling of human resources. What is of prime important to such an analysis is to properly determine the groups involved. According to Donaldson and Preston, these are the company owners, its employees, investors, suppliers, customers and the general public. It is also important to identify individual causal relations and the interconnection between financial and non‐financial indicators. Individual indicators must thereafter satisfy the conditions of having the unambiguous capacity to inform, of being meaningful and of being applicable for feedback. (Marinič, 2008)

2.2 Factors of competitiveness Mikoláš (2005) claims that competitiveness is traditionally considered according to four attributes. These attributes are human and financial resources and the technological and commercial potential of the company. A different view of the issue of finding the factors that influence the competitiveness of a company can be inferred from Porter's diamond of the competitive advantages of individual states. Rasoul Shafaei (2009) also looks at the issue of the diversity of approaches to evaluating competitiveness in his work. Shafaei, along with Chi (1999), says that we can mark out nine individual factors that affect competitiveness. These factors are the ability to come up with a realistic forecast, the quality of products and services, the innovative and marketing abilities of the managers of the company, the company image, the ability to effectively use information technology, the ability to know how to sustainably manage the financial side of the company, the capacity to control international commercial processes and the ability to recognise and know how to use human potential and talent. (Shafaei, 2009) In general, we can divide the factors of competitiveness into two groups – internal and external or specific and non‐specific. Included in the specific factors is the ability of a company to effectively assert its products on the customer market, meaning on the product and service market. We can understand this effectiveness to be the maximum use of input (material, labour, capital) for one unit of output. When comparing effectiveness, we must take into account the size of production costs, the price of competition and the quality of products. Another factor is the ability of a company to effectively look for and obtain investors and financial resources on the capital market. The principal matter assessed in this regard is the appreciation in value of assets and capital for investors. The third important factor is the ability of a company to effectively hire new employees on the labour market. The standard of the social programme and security for employees, the level of pay and remuneration and the possibilities for professional and personal development among employees are assessed

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Jaroslava Dědková and Denisa Skrbková within this factor. Such non‐specific factors include the company’s image and its relationship to the environment and to the economic and social development of the region. (Gregar, 2001) One of the main factors to influence the position of small and medium‐sized businesses is the use and improvement of modern technology. (Anonymous, 2010) The problem of introducing new technology and innovations is that it is very expensive, meaning that most companies cannot afford it. As is clear, it is impossible to assess individual factors in isolation, meaning that we must observe them as an interconnected whole. We cannot assess only technology and neglect customer‐related or stakeholder‐related values. If a company wants to succeed, it must try to achieve the very best results at all levels of its activity. (Feurer, Chaharbaghi, 1994)

2.3 The modern concept of competitiveness As already said, the economic market changes very quickly and companies need to respond to this and adjust how they behave adequately, quickly and flexibly. (Feurer, Chaharbaghi, 1994) The production is becoming more exacting and the sales are more complicated in this time.(Skála, 2010) It is absolutely clear that the concept of “competitiveness” also changes over time and that what was once enough to maintain a position on the market has now become clear to other companies as well. According to Mikoláš (2005), it is therefore important when considering a company to take into account factors other than only those that have been thought of as primary until now. These include the identity, integrity and sovereignty of the company, as depicted in the following Figure 1.

Source: Mikoláš, 2005. pp. 85 Figure 1: The competitiveness scheme By finding its own identity, a company is essentially finding its own individuality. Determining this individuality is something that proceeds based on the company’s pre‐defined and determined aim and purpose. Identity can be taken as a set of ideas or thoughts that provide a picture of the essence of a company’s existence. This is also taken from the location, design, individual types of communication in operation at the company, the traditions and rituals in place and the overall ability to innovate and adapt to changes. All these characteristics genuinely define the company’s position in relation to its surroundings. The integrity of the company is based on the cohesion of its units, which in this case means its employees, who should, however, be flexible and dynamic as separate units in themselves. Just as individual employees are adaptable, so too must the company as a whole be able to adapt. (Plchová, 2011)The way in which a company is able to respond to changes both inside and out and to adapt to new conditions is termed the mobility of the company.

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Jaroslava Dědková and Denisa Skrbková The final dimension on which Mikoláš feels the need to concentrate is the sovereignty of the company. To a company, sovereignty in the business environment means having a genuinely realistic chance of taking decisions on its own fate and of then implementing such decisions. Being able to unambiguously determine all factors that we can use to precisely consider the competitiveness of a company is practically impossible. Each and every author sees company potential in a different area and considers this to be the most important distinct factor. According to Veber (2000), a company cannot focus solely on its own internal operation, meaning that it is necessary to take the above‐mentioned outside factors into consideration and build a company image. This theoretical knowledge acted as the source material we used in putting together 22 variables, of which the 4 most important factors that constitute competitiveness among the companies active in Euroregion Nisa were evaluated by way of factor analysis.

3. Characteristics of Euroregion Neisse – NISA – NYSA This Euroregion lies in the border areas of three countries – the Czech Republic, Germany and Poland. All three parts of the region are united by many common problems and interests arising from similar system transformations and many years of common history. The unifying element of the area as a whole and the traditional symbol of mutual cooperation is the River Nisa, which forms the border between Germany and Poland. The conference founding the Euroregion, which was known as Euroregion “TRIPOINT”, the first cross‐border structure in Central and Eastern Europe, was held in the German town of Zittau in 1991. The profile and role of the Euroregion have undergone certain unavoidable changes over the 22 years of its existence. More than 1.7 million people live within the Euroregion, with the most important areas of common activity involved in trilateral cooperation currently including:

the development of the economy and balancing standards of living;

building and adapting infrastructure to needs not confined by borders;

cooperation on land‐use planning;

cooperation in the development of public transport and tourism in border areas;

cultural exchange and care for the common cultural heritage, improving interpersonal relations.

The driving force behind cross‐border cooperation is primarily the search for common or bilateral economic interests and advantages. Emphasis is placed on strengthening competitiveness and regional economic bases by way of cooperation, with special consideration for interaction between small and medium‐sized businesses and in support of developing new business opportunities. Small and medium‐sized businesses in border regions are faced with particularly unfavourable conditions arising from their position on the peripheries of national economic systems.

3.1 The Czech part of Euroregion Nisa The Czech part of Euroregion Nisa encompasses Česká Lípa, Jablonec nad Nisou, Liberec, Semily and the northern part of the Děčín district (around Šluknov) and covers around 4.5 % of the area of the Czech Republic. This part of the Euroregion is home to 135 municipalities (figure taken from 2011) and concentrates mainly on glassmaking, engineering, metallurgy, textiles, clothing, building and the food industry. The new market conditions saw considerable development of the small and medium‐sized business sector, mainly in car production, building and services according to market demands. There was a clear influx of foreign companies, particularly in the second half of the 1990s, building on the traditions and qualified workforce in the region, in particular in prospective industries such as the manufacture of glass and costume jewellery, the production and processing of plastics, engineering and the motor industry.The number of economic entities by number of employees in Euroregion in 2011 is shown in Table 1.

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Jaroslava Dědková and Denisa Skrbková Table 1: Business entities by number of employees in the districts of Euroregion Nisa in 2011 District Česká Lípa Jablonec nad Nisou Liberec Semily Total

Total number of entities

By number of employees 0‐9 employees

10‐49 employees

50 employees and over

1) Czech part

23,695 24,171 51,573 19,327 118,766

23,311 23,742 50,649 18,944 116,646

293 328 717 298 1,636

91 101 207 85 484

Source: http://www.czso.cz/xl/redakce.nsf/i/130123_zsuern

4. Evaluation of marketing survey This section examines and evaluates the quantitative information taken from a questionnaire survey. It is divided into two smaller parts, the first characterising the profile of respondents and the second concentrating on factor analysis. A total of 170 companies from the Czech part of Euroregion Nisa completed the questionnaire.

4.1 Methodological procedure of marketing survey The methodology used in the empirical investigation of the competitiveness of companies is based on the definitions, expectations and principles set out in the introduction to the paper. A quantitative form of collecting data in a written questionnaire was chosen as the method of obtaining the information we required, this questionnaire taking the shape of an electronic survey created using the tools available at Google.com. The survey was carried out in January and February 2013 in the Czech part of Euroregion Nisa and was anonymous. A uniform, standardised, structured questionnaire was used to gather data in which the wording and order of questions were precisely set out. Closed‐ended, multiple‐choice questions were mostly used when putting together the questionnaire. A set of variables that influence the competitiveness of a company was assembled based on the theoretical knowledge available and space given to respondents to rate these individual variables. Our expectation was that the survey would serve to confirm the views of the authors as to the ambiguity of meaning of the "competitiveness” of companies.

4.2 The structure of respondents For the purposes of considering the economic base, the Czech part of the region was divided into the districts of Liberec, Jablonec over Nisou, Česká Lípa and Semily. A database was created of 250 companies active in the districts of Euroregion Nisa in question. These companies were contacted by telephone and subsequently sent an electronic link to the questionnaire in the Google.com system. One hundred and seventy questionnaires were subsequently processed. The opening questions 1 to 5 in the questionnaire were designed to identify the sample of respondents. Ninety respondents came from the Liberec district, around 53 %, 23 respondents from Jablonec nad Nisou (almost 14 %), 23 respondents from Česká Lípa (around 14 %) and 34 respondents from Semily (20 %). This spread of companies corresponds to the size of the districts in question. Twenty‐four companies have less than 10 employees (14 %), 18 respondents (11 %) gave an answer of between 10 and 20, the same number have 21 to 50 employees, 41 companies (24 %) employ between 51 and 100 members of staff, 23 companies (14 %) have between 101 and 200 employees and 46 (27 %) have more than 200 employees. Of the 170 companies questioned, 29 % were joint stock companies (49 respondents), 2 were associations (1 %), 5 were natural persons (10 respondents), 6 were state enterprises (4 %) and 103 were limited liability companies (61 %). The next question identified 119 companies without foreign capital, meaning 70 %. Another 4 companies have a share of foreign capital of up to 24 %, 9 companies a share of foreign capital of between 25 and 50 %, 11 companies between 51 and 76 % and 27 companies, around 16 %, have a share of foreign capital in the company of more than 76 %. Core business activities differed greatly and were divided into the categories of

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Jaroslava Dědková and Denisa Skrbková industry, services, trade and transport and other to help us process the information. Eighty‐nine companies were classified under industry (building, engineering, glassmaking, food production, textile industry), meaning 52 %, 77 were classified under services, trade and transport (45 %) and the rest, almost 3 %, are part of another branch.

4.3 Factor analysis Respondents were given the task of grading a total of 22 variables in order to map out the factors of competitiveness. Grading used a scale of 1 to 5, with 1 meaning a considerably better rating than a competitor and 5 a considerably worse rating than a competitor. Grading was very diverse. However, the essence of a great many attributes is not clear from the values. For this reason a factor analysis was conducted, the aim being to clarify the dimensions that influence the competitiveness of companies. A factor analysis was conducted at a total of four stages because the first, second and third analysis identified attributes with a correlation coefficient value of less than ± 0,5, which were for this reason discarded. The aim of this procedure was to reduce the number of variables and find the “optimum level” factors, meaning the factors that play the biggest part in the competitiveness of companies. Table 2 summarises selected results of the four stages of factor analysis. Table 2: Results of factor analysis

Cronbach’s alpha 95 % confidence interval Kaiser‐Meyer‐Olkin measure Bartlett’s test of sphericity

Number of variables entering FA Number of factors Number of variables included in factors Cumulative percentage of variability

Stage 1 of FA

Stage 2 of FA

Stage 3 of FA

Stage 4 of FA

0.617

0.75154 (0.69851, 0.80458) 0.6497 0.6656

0.603

Chi‐squared Degrees of freedom Significance level

1078.5 231 0 22

507.1 91 0 14

344.4 55 0 11

245.94 36 0 9

12 14

5 11

4 10

63.1

59.3

60.7

60.1

Source: Author´s elaboration Cronbach’s alpha is fulfilled because it exceeds a value of 0.7. The structure of the confidence interval serves to find the interval which a random value falls within with a pre‐determined degree of high probability of 1‐α, which applies in this case. The condition of achieving the Kaiser‐Meyer‐Olkin measure, i.e. a KMO value of higher than 0.5, applies to all stages. Bartlett’s test of sphericity was fulfilled at all stages. The resulting matrix for the four steps is presented in Table 3. Table 3: Resulting matrix 7. Market share 8. Know‐how, technology 9. Company management 14. Company identity 15. Integrity, cohesion 17. Company sovereignty 19. Innovative activity 20. Labour costs 21. Other costs 22. Image (brand) Percentage of variability Cumulative % of variability

Stage 1 ‐0.103 ‐0.025 0.035 ‐0.112 0.114 0.032 0.267 0.996 0.468 0.138 25.5 30

Source: Author´s elaboration

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Stage 2 0.880 0.120 0.058 0.081 0.052 0.255 0.123 0.027 0.005 0.586 13.2 38.7

Stage 3 ‐0.042 ‐0.039 0.226 0.563 0.712 0.464 0.324 ‐0.008 0.013 0.249 11.1 49.8

Stage 4 0.209 0.484 0.605 0.185 0.024 0.336 0.534 0.052 ‐0.018 0.131 10.2 60

Jaroslava Dědková and Denisa Skrbková Factor analysis identified four factors, which were named according to the individual variables which they contain. The following factors were identified:

Cost competitiveness;

Market share and company image;

Relationship to surroundings (identity, integrity, sovereignty and cohesion of the company);

Innovative processes (know‐how, technology, management and innovative activities at the company).

The first factor, named cost competitiveness, consists of two variables, with cumulative variability of 25.5 %. Respondents made it clear that the main competitive factor across all branches was costs, among these labour costs and all other costs. No difference was identified here between individual categories of industry, services or other. This conclusion substantiates the importance of price as a crucial factor of success, one that rests on the competitive advantage of low costs. The second factor is the size of market share and company image. These variables, with variability of 13.2 %, draw on tradition, connections and the action of the company in the region. The third factor encompasses all variables associated with relationships to surroundings and makes up 11.1 % of variability. These include newer competitiveness variables, meaning the identity, integrity and cohesion of the company, as Mikoláš (2005) describes in his work. Companies in order to build and sustain their competitive advantage reorient their operations towards the improvement of their CRM performance by creating and delivering superior customer value. (Simová, 2010) The fourth and final factor, innovative processes, encompasses know‐how, technology, company management and the company’s own innovative activities. The variability here is 10.2 % and this factor shows that respondents are aware of the importance of innovative activities in combination with management knowing how to obtain finances to introduce technological innovations that could contribute towards the company's competitiveness. Nonetheless, the Czech Republic lags behind the European th Union average in terms of innovations, occupying 18 position in the relevant table. This all ensues from a report published by the European Commission, according to which the EU performance in terms of innovation has improved as a whole in spite of the crisis. The Commission placed the Czech Republic in the largest group, “moderate innovators”, in 18th position overall. The Czech Republic was ranked 17th last year. Among those in the same group are Slovenia, Cyprus, Greece, Estonia, Italy, Portugal and Slovakia. The Commission drew on 24 indicators to concern, for example, research and development, investment in research, number of patents, scientific publications abroad, innovations placed on the market, number of employees in the knowledge economy and its share in exports. (Czech News Agency ‐ ČTK) Last, but not least, we were interested in whether Euroregion Nisa is able to influence the competitiveness of a company or its development. A total of 129 respondents, almost 76 %, said that Euroregion Nisa had no effect on the development of their companies. Six companies (4 % of those asked) said that Euroregion Nisa had a decidedly positive influence on company development, 33 respondents (19 %) said that it's influence was more positive than negative and the remaining 2 companies (1 %) said that Euroregion Nisa had more of a negative influence on company development. This is all shown in Figure 2.

Source: Author´s elaboration Figure 2: Influence of Euroregion Nisa on company development

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Jaroslava Dědková and Denisa Skrbková

5. Conclusion The aim of the paper was to analyse and formulate the key factors that support the competitiveness of a company from the theoretical perspective of various authors and the perspective of primary research in the Czech part of Euroregion Neisse ‐ Nisa ‐ Nysa. The results of our investigation help the development of theory, to be applied in the teaching of university students, and are useful to participants in research in business practice, in particular to those companies that took part in the investigation. The investigation showed that cost variables, the basis of the optimum price of an end product, had the greatest influence, followed by market share, relationships to surroundings and last, but not least, innovative processes, without which it is impossible to remain a competitive company. It is quite clear that the secret of success and high levels of competitiveness is not simply in the assets and tradition of a company, but in the greatest possible number of competitive advantages that the company is able to offer. In conclusion, we confirm recognition of the ambiguity of the factors of competitiveness, since the result of the factor analysis shows 10 variables as part of the competitive advantage of the companies within Euroregion Nisa. Each individual factor at a company could be a factor that conditions competitive advantage and competitive ability, but no individual factor can offer a company dominance in competitiveness. Only a perfect combination of all factors and using them in the right way in the external conditions in place provide the key to success. Only companies that develop and maintain these competitive advantages will be able to survive in the medium‐term. The ability to manage basic activity, knowledge, innovation and information and to transfer this into the company strategy is the key element of competitiveness in the global economy. This article was written with financial support for a specific research project under TUL Student Grant Submission No. 38001/2013: Identification of factors of competitiveness among companies in the Czech part of Eurorgion Neisse‐Nisa‐Nysa.

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Towards Sustainable Business Models: Necessity, Opportunity or Challenge? Nikolay Dentchev1 and Jan Jonker2 1 University of Brussels (VUB) and HUBrussel, Belgium 2 Nijmegen School of Management (NSM), Radboud University Nijmegen (RU), Holland nikolay.dentchev@vub.ac.be j.jonker@fm.ru.nl Abstract : In our collective memory, the double‐dip economic crisis of 2008/9 and 2011/12 would be remembered as the result of respectively the subprime financial crisis and the unbalanced government budgets in various countries of the European continent. However, we illustrate with the evolution of commodity prices that there is definitely another, additional reason for the challenges of our modern economies. Spikes in commodity prices seem to coincide with the timing of the recent economic downturns. And we argue that these spikes are the result of our unsustainable, consumptive behavior, fueled by recent rising planet population. This paper contributes with an analysis to support sustainable business model necessity that goes beyond the often very broad and general attention paid to certain added‐on social and environmental issues. Instead, we argue, based on conventional business models, that the explanations for the recent economic crises significantly overlook the impact of our commodity hunger. Hence, the opportunity rises for business models that mitigate operationally the risk of resource dependence. Keywords: sustainable business models, corporate sustainability, sustainable development, resource depletion, resource dependence, resource regeneration

1. Introduction Fortunately, a growing number of people around the globe are convinced that sustainable development is important and urgent. Constant reminders of global warming, the melting ice‐cap of the North Pole, the next tsunami, earthquake or flood continuously alarm us about the necessity of sustainable life. The surge in interest regarding sustainable development is significantly underpinned in the media and propagated by scholars, famous TV stars, politicians or businessmen with names that need no introduction, e.g., Al Gore, Gro Harlem Brundtland, Leonardo Di Caprio, Madonna, Bono, Bill Gates, and Warren Buffet, among many others. Moreover, sustainability has been on the agenda of fundamental research and of international organizations for decades. The United Nations (e.g. The Rio Summit, The Kyoto Protocol, The Global Compact) and the Club of Rome, among others, provide platforms that propagate sustainable development. However, even with so many alarming signs about the need for sustainable development, why is there little or nothing done in effect about the sustainability of our planet? Unfortunately, there is, according to the theory of planned behavior, a difference between being convinced (intentions) and translating those convictions into reality (action), (Ajzen, 1991). Hence, the vicious cycle of comfortable, old activity patterns needs to be broken in order to make space for new habits, new ways of living, and new economic systems. Our argument to this is that a new generation of so‐called ‘sustainable’ business models can substantially contribute to breaking the vicious cycle and translating intentions into sustainability actions. In the words of Birkin et al (2009, p. 65), sustainable business models embrace not only the “business case” but also the “nature case” and the “social case” of a business venture (Birkin et al., 2009). This paper contributes with an analysis to support sustainable business model necessity that goes beyond the often very broad and general attention paid to certain added‐on social and environmental issues. Instead, we argue, based on conventional business models, that the explanations for the recent economic crises significantly overlook the impact of our commodity hunger. Our collective attention is exaggeratedly focused on problems such as a subprime crisis and government deficits. The spikes of commodity prices in recent years vividly illustrate our argument. Hence, we emphasize the growing need for sustainable business models as an opportunity to reduce our commodity addiction and to mitigate and temper the market risks associated with the volatility of commodity prices.

2. The necessity for a new generation of business models It initially seems absolutely unnecessary to propagate the necessity for sustainability. We all are convinced, so why bother to once again stress that fact? In effect, we do not want to plead in favor of sustainability but,

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Nikolay Dentchev and Jan Jonker instead, in favor of sustainable business models. The former is to be perceived as a result of the latter. Business models are composed of individual interests and motivations that all result in human activity (Magretta, 2002). Sustainable business models are associated with business activities that consider “(a) consumers as individuals with a complex set of needs that consumption of products only partially satisfies and as members of a larger community with complex interdependencies; (b) today’s underrepresented communities; and (c) tomorrow’s communities, i.e., the generations of individuals and communities that will follow our own and which depend critically on our current decisions and behaviors” (Esslinger, 2011) p. 401). In this instance, sustainable business models are approached from a holistic perspective, embracing the complexity of needs of primary and secondary stakeholders, while others explicitly draw the attention of sustainable business models of social issues and the natural environment (Birkin et al., 2009). Building on these scholars, sustainable business models are defined here as financially viable business activities that can be developed on a self‐sufficient resource basis without negative social or environmental externalities. These business models generate value not only in financial terms, but also in non‐quantifiable social and environmental terms. Product and service quality are central in the total value chain of the business activity so as to guarantee a multi‐facetted, value added (financial, social, environmental) of an activity. Examples of sustainable business models are cradle‐to‐cradle, (some) renewable energy types, recycling, and bottom of the pyramid innovations. It is necessary to plead in favor of sustainable business models as they are anything but self‐evident activities. They are not those easy‐going business constructs with an activity focused only on cash generation. They are more complex, taking into account multiple stakeholders’ interests and aiming at value generation throughout the entire life‐cycle of the product and services of the business. As humans, we may intend to act according to the principles of sustainability, however, it is apparently not in our inherent nature to embrace the complexity of sustainable business models and translate our good intensions into decisive action. A good example for our overall neglect to sustainable action the double‐dip in the economic cycle of 2008‐ 2012. In the beginning, there were the sub‐prime mortgages of North‐America. Sub‐prime is an intriguing term from a banking perspective indicating borrowers with lower quality than the prime clients. While prime clients are considered to have sufficient repayment capacity to service their credit (interest and principal), sub‐prime clients have insufficient repayment capacity to service its debt. Sub‐prime clients should not receive lending based on conventional banking principles as they cannot repay it. However, they did receive funding as it was speculated that housing prices would continuously grow, and the repayment capacity would grow from the positive price difference. A fictive example illustrates best the mechanism of a subprime mortgage: Tom has a net monthly income of 2.000,00 USD (annually 24.000,00 USD), and finds his dream real estate: a house in a good neighborhood at the cost of 300,000.00 USD. If Tom does not need to repay capital during the tenor of the loan (i.e. bullet repayment), it is perfectly conceivable for him to repay an interest of, say 4 %, on an annual basis. This interest generates an expense of 12,000.00 USD per year, or 50 % of Tom’s net income. If real estate prices increase, such a luxury house is a good idea for Tom. He has to pay interest comparable to rent, and after few years he can sell the real estate at a higher price than initially lend. After transaction costs, Tom earns a good amount on the whole transaction. But … What if real estate prices decrease? Interest rates are a reflection of the risk for a bank, and falling real estate prices do automatically reduce the value of the credit collateral. Increasing risk implies an increase in interest rate and assuming an increase to 5 % could cost 15,000.00 USD (62.5 % of net income) while an increase to 6 % results in 18,000.00 USD (or 75 % of net income). As a result, Tom will have additional expenses that endanger his normal living activity. Not to mention that houses require maintenance, and unexpected expenses may occur. And what happens if Tom’s salary is reduced, he becomes ill, or becomes unemployed. The probability to default on his sub‐prime credit is relatively high. Unexpectedly, markets did the reverse, and the housing bubble in the USA exploded with prices much lower than initially expected. The so‐called sub‐prime clients, as one could expect, had difficulties in servicing their loans, the collateral of the mortgage was much lower due to the plummeted real estate prices, and banks began to accumulate losses. However, this was not the full story. The sub‐prime mortgages were syndicated in packages and sold to other banks outside the USA, mostly to European banks. Hence, there was a contamination effect of the North‐American sub‐prime crisis on the European continent. The sub‐prime crisis led to a credit crunch, banks lost all confidence and stopped lending to each other, which then led some financial institutions to liquidity problems with casualties. Certain icons of the financial sector such as Lehman Brothers went bankrupt or, in the case of Bear Sterns and the Royal Bank of Scotland, needed to be rescued. In

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Nikolay Dentchev and Jan Jonker addition, many other banks were saved after nationalization or substantial state loans and guarantees. European governments undisputedly contributed to save the economy from a severe recession in 2008 as banks have a systemic function that provides the necessary capital for the economy. However, the same European governments are the main reason for the faded confidence in the economic markets during the summer of 2011. Greece was unable to function (i.e. pay state‐officials, pensions, or bills) without the support of other EU countries and the IMF. Ireland found itself in less precarious situation, but with rather weak public finances. As a result of increasing public debt, speculative rumors targeted Portugal, Spain, and Italy. The grimy public finance of the above mentioned countries gave birth to the term PIGS countries, an acronym based on their first letter and denoting the potentially dirty financial situation of their governments. In addition to all of this, France and Belgium came under the same speculative rumor. The former’s AAA rating was canceled, and there was speculation that its banks had substantial exposure to PIGS public debt, while the latter faced difficulties in federal government formation that spanned 1,5 years (more precisely 541 days from June 2010 till December 2011). Overall, the summer of 2011 will be remembered with its nervous financial markets, with a new negative, vicious circle of the economy, with no confidence in the public finance, with a drying‐up of inter‐banking lending, and economic slowdown. In summary, we will remember the sub‐prime mortgage crisis and the European public debt as the main reasons for the double‐dip crisis of 2008‐2012. Are we not missing something? We argue that our collective attention is very much shortsighted and that we are overlooking, arguably, the most important reason for the current economic challenges. In its fundamentals, the economy is suffering from its unsustainable fundamentals, which becomes apparent when focusing on (i) consumption patterns, (ii) growing commodity prices, and (iii) growing world population.

2.1 Consumption Consumption is a central concept of current societies. Lack of consumption is generally considered as problematic for the economy as it leads to a slowing down of economic growth or even to economic depression. Our desire to consume is without limits, and we readily desire the next object very soon after we already possess everything we have dreamed for. This desire to consume or dream to possess even better items was explained more than half a century ago by the pyramid of needs of psychologist Maslow (Maslow, 1954). First, we seek to fulfill a fundamental need, e.g., the need for transportation, by tram‐bus‐train‐bicycle or a small car. As we earn more, we seek to fulfill our safety, social, esteem or self‐actualization needs with the purchases of, perhaps, an SUV, luxury car, or even a private jet. Consumption has become an end to itself and is, to many, no longer a means to an end. Our collective obsession to consume results in modern diseases, such as obesity, shopaholics, obsessive plastic surgeries, etc. Without realizing it, we are addicted to consumption, and we measure our wealth by consumption instead of cherishing other human values such as honesty, quality, love, happiness, friendship – to mention a few – which are less material and difficult to measure but of greater importance for the sustainability of our societies. Addicted to cheap consumption, our goods (and sometimes services) are transported thousands of kilometers to a final destination. In fact, we consider the direct factors of production such as labor cost, raw materials, production facility and transport, and we remain blind to the hidden costs, or externalities, of our urge of consumption. After so many years, we have not even effectively succeeded to take pollution into consideration as the cost of our human activity. We have no problem flying, driving cars, and using environmentally unfriendly technologies, and most do not appear to feel that pollution is their problem. It is much easier to benefit from relatively cheap consumption, not pay directly for pollution, and argue that our individual action is impossible due to the complexity of the problem. But this is shortsighted. We pay much more as pollution causes diseases, costs human lives, causes natural anomalies such as global warming, melting of the ice cap, tsunamis, tornadoes, and earthquakes. As scientists, we cannot prove the direct link between consumption, pollution, health and natural disasters, and we do not want to enter in scientific fields outside of my competences, hence, the honor of discovery and proof is left to scientists in the fields of medicine, geology, and meteorology. However, we can convincingly argue in the following sections that there is logic demonstrating the economic effects of our unsustainable consumption habits.

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2.2 Growing commodity prices The rise of commodity prices, one would argue, is a simple equilibrium between supply and demand (higher demand leads to higher prices). Additionally, raw materials are scarce, and our excessive consumption increases prices. In regard to scarcity, two mechanisms are worth mentioning. The first is related to the limited capacity to extract or produce raw materials. With the increased extraction/production, a new production facility is required. In essence, scarcity is not the challenge here. The challenge is how to calculate capacity needs and how flexible this capacity is in order to adapt to our current needs. Various types of infrastructure are a good example, e.g., ports, airports, highways, or railways. However, capacity is also an issue for any production facility and service organization, and capacity challenges are here to stay! Why? Because any organization has boundaries, i.e., limits of its activity. Yet, the most alarming aspect related to commodities is their scarcity. The price of crude oil is quite illustrative. 30 years ago, in 1982, a barrel of crude oil was USD 33,23‐, while, in October 2012, its price is 103,39‐ (commodity prices retrieved from www.indexmundi.com, consulted on 13.10.2012). To illustrate the full range of price development, it is interesting to note that the lowest price per barrel in that period was USD 10,41 in December 1998 while the highest price was USD 132,55 in July 2008. While there may still be discussion whether “peak‐oil” is a reality or a myth (Lutz et al., 2012), there are some indications signaling limited oil reserves such as extracting from deep water reserves or tar sands. The economic impact of “peak‐ oil” is described as being comparable to the economic crisis of 2008/9 (Lutz et al., 2012), while the transformation from our fossil fuel addiction to sustainable and climate change neutral consumption is expected to take decades (Murray and King, 2012). In the meanwhile, individual consumers, households and firms are feel budgetary pressure from high fuel prices. It is a curious coincidence that the economic crisis of 2008 coincided with the highest ever crude oil price in July of that year, yet, crude oil prices are not the only suspect of the evil that caused the economic crisis. Let us take a look at other commodities. Iron ore had a price tag per dry metric ton of USD 14,05 in October 1982 compared to USD 113,95 in October 2012 with a peak of USD 187,18 in February 2011. Hot rolled steel per metric ton: USD 260,00 in October 1982 compared to USD 800,00 in June 2012 with a peak of USD 1.000,00 in the period June 2008 and February 2009. Aluminum per metric ton ‐ USD 951,48 in October 1982 compared to USD 1.974,30 in October 2012 with a peak of 3.578,10 in June 1988 but continuously high prices (in the range to ca. 2.500 to 3.000 USD) in the period October 2006 and September 2008. Zinc per metric ton ‐ USD 751,78 in October 1982 compared to USD 1.903,96 in October 2012 with a peak of USD 4.381,45 in December 2006. Now, let us take a look at other commodities than metals. Rubber, per 100 kg, rose from USD 85,10 in October 1982 to USD 320,40 in October 2012 with a peak of USD 619,04 in February 2011. Cotton, per 100 kg, maintained more or less its price of USD 154,79 in October 1982 vs. USD 180,69 in October 2012, but note the peak of USD 506,34 in March 2011. Hard sawn‐wood, per cubic meter, rose from USD 203,98 in October 1982 to USD 873,36 in October 2012 with a peak of USD 973,60 in August 2011. We could continue like this, but more importantly, commodity prices inflate the cost structure of businesses (and households), which cannot be always passed through to the customers in order to compensate increasing costs with increasing income. Stated otherwise, spikes in commodity prices form a plausible reason for economic crises. Such peaks are indicative of our collective unsustainable behavior. Our economies are built on the consumption of commodities with insufficient attention paid to the regeneration of resources. We seem to be addicted to cheap products produced in low cost countries (e.g. China) that import raw materials and export finished products all over the world. Therefore, fast growing economies are currently lobbying to secure raw materials from various sources. China’s hunger for commodities such as crude oil, copper, iron ore, manganese, soy, wood and meat are sourced, according to Deutsche Bank research, primarily from Africa and Latin America (Deutsche_Bank, 2006). It is well known that China’s industrial development and growth rates require the above‐mentioned commodities. It is also known that each crisis softens the pain when commodity prices drop following each recession. The problem is not with the commodities and their prices; the problem is our collective addiction to them. However, industrial activity is only a segment of human activity. What about food prices? Maize per metric ton ‐ USD 90,94 in October 1982 compared to USD 321,63 in October 2012 with a peak of USD 332,95 in July 2012. Barley per metric ton ‐ USD 50,27 in October 1982 compared to USD 249,25 in October 2012 with a peak of USD 267,16 in Augustus 2012. Wheat per metric ton ‐ USD 146,61 in October 1982 compared to USD 358,20

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Nikolay Dentchev and Jan Jonker in October 2012 with a peak of USD 439,72 in March 2008. Beef per kilogram ‐ USD 248,02 in October 1982 compared to USD 400,23 in October 2012 with a peak of USD 428,49 in March 2012. Chicken per kilogram ‐ USD 75,29 in October 1982 compared to USD 211,29 in October 2012, and the latter is, at the same time, the peak in the period. Bananas per metric ton ‐ USD 299,40 in October 1982 compared to USD 959,04 in October 2012 with a peak of USD 1.151,43 in March 2012. It is not the intention to depict a comprehensive view on all food commodities, however, these few examples indicate increases in prices for food commodities where the spikes occur more recently (most in 2012) and, therefore, seem to be less related to previous economic crises than industrial commodities. It is important to note that forecasts of economic growth are largely expected in Asia, Africa, and Latin America; regions that represent ca. 83 % of the world population. To be more precise, IMF expects the following GDP growth rates for 2013: Russia 3,8 %, China 8,2 %, India 6 %, Brazil 4 %, Mexico 3,5 % and Africa, as a region, has variation between 3 % and 5,7 % (IMF, 2012) p. 3). Europe can be envious of these growth rates as the Euro Area growth is estimated at 0,2 % for 2013 in this same study. Overall, these growth rates are positive information and indicate economic revival in various regions in the world. Among them are also commodity rich countries that have benefited, and continue to benefit, from the elevated commodity prices. On the other hand, this does also indicate that we all need to refocus toward sustainable consumption.

2.3 Growing world population Since 2011, the Earth sustains seven billion people. In 1999, the number of people on Earth was six billion, and there are projections, reported with 83 % probability, that the number will be 8 billion in the period between 2022 – 2035 (Scherbov et al., 2011). Furthermore, the United Nations predicts that the number will reach 9,3 billion by 2050 and 10,1 billion by 2100 (UN, 2011). Predictions on the world population indicate the underlying dynamics within our consumptive societies. The dynamics of consumption are related to income. The higher the income a person possesses, the more that person is able to spend. The sky is the limit. Think of private jets, expensive yachts, or a bottle of wine with a price tag of USD 168.000 (for a bottle of 2004 Penfolds Block 42 Cabernet Sauvignon, dixit CNBC article of Kerima Green dd 28.06.2012), or a painting for USD 75 million (for “Royal Red and Blue” by Mark Rothko at auction of Sotheby’s dd 13.11.2012). Money is not spent on all of this out of necessity but because of our urge to consume, to feel important and satisfied. “Necessity” could not possibly be an explanation for the excessive spending, nor for the fact that some pets have to deal with obesities and undergo plastic surgery. In contrast to luxury excesses, the World Bank shows that 2,5 billion of the world’s population must survive with less than USD 2 per day. At the same time, the same poor people live in regions blessed with economic growth in the coming years. It is positive that economic activity revives in the poorest regions in the world, both from a moral and instrumental perspective. It is impossible to stop the human urge for a better life. Environmental or social arguments have inferior importance to people who must survive with USD 2 per day and now acquire the opportunity of relatively decent shelter and food. Their norm for natural environment and social issues (e.g. child labor) is not the same as our western norms (Donaldson and Dunfee, 1999). This is not due to not wanting these higher standards but simply because they have other priorities, i.e. the priority to survive. Indeed, we are concerned, together with others, that economic growth in developing countries could push their consumption rates comparable to Western Europe or North America. Not to speak about basic infrastructure: roads, railways, or houses. These types of pressure on commodity demand, not only for crude oil but also for a variety of commodities, can cause economic disruptions in the future. Together with Murray and King (2012), we believe that there will be decades of transition and, most likely, multiple economic crises. The reason for these would be our unsustainable business models that are primarily focused on consumption. Concurrently, the commodity challenge of our planet provides an enormous opportunity, i.e., the opportunity to embrace sustainable business models. We should embrace them simply because it makes perfect sense to do so, and not because the often argument of there is no alternative.

3. Sustainable business model opportunity In the above argumentation, we have illustrated the necessity for sustainable business models. However, the mere argument in their favor is insufficient, and enlarging the scope from the business case to environmental and social cases of a business activity (Birkin et al., 2009) provides insufficient guidance of the various

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Nikolay Dentchev and Jan Jonker orientations towards sustainable business models. Based on the above discussion, we elaborate on few aspects important to the sustainable business model concept. Sustainable business models provide the opportunity for risk management. Risk management is not about avoiding the risk, but rather about its mitigation (Brown, 2013). Risks are there to stay, and there are various risk factors that fuel these risks (e.g. human, technology, physical, economic, natural, political; for a comprehensive view of corporate risk analysis and rating systems cf. Jacobson et al., 2006, Treacy and Carey, 2000, or Basel III regulatory framework on counterparty credit risk) Although the volatility in commodity prices is has only economic risk factor as a background, it has further implication to technology, politics, and humanity. Hence, various spill‐over effects may multiply the risk factor of volatile commodity prices. Such volatility is actually an indication of market risk with an impact on cost structures and disruption of the overall business activity. One way to mitigate such risks is through the use of hedging volumes and prices (i.e. fix volumes and prices through option or effectively for a transaction at a future date). However, this mitigation does not touch upon the fundamental problem, i.e. the scarcity of raw materials. In addition, it projects further uncertainties when a future contract on price and volumes is fixed, but the company suddenly realizes that demand levels vanished as a result of market depression. Hence, the main opportunity of sustainable business models is related, in our view, to the natural risk reduction of dependency on raw materials. Dependency reduction can be realized through business models that stimulate:

Reduction of resource needs: This can be realized by efficiencies that lead to reduction in the needed resource input factors. It can also be realized by the substitution with complementary resources. (e.g. energy efficiency)

Optimization of resource use: In this instance, we refer to increasing the efficiency in the resource utilization. For example, in the food industry, there is significant waste that can be reduced (e.g. agricultural production, distribution, consumption).

Regeneration of resources: The regeneration of resources refers to the transformation of abundant resources in valuable commodities (e.g. renewable energy).

Reutilization of resources: This can be realized either with giving second life to old products, or trough recycling them into new raw materials. Many goods maintain economic value when disposed of, and, on many occasions, can be a platform for social inclusion in poverty regions (e.g. old pc – mobiles – clothes to poor regions). Moreover, some resources can be perpetually used in the value chain (e.g. cradle‐to‐cradle, recycling, waste management).

Making resources obsolete: Of course, the best way for reduced resource needs is when resources are made absolutely unnecessary in the process of production and consumption (e.g. reading on pc vs. on paper, using public transport vs. car, meeting on Skype vs. travel, solar panels for water pumping, mobile phones to sell products).

Resource dependency reductions are possible thanks to technological advancement. On the technological side, much is possible and much can be developed in the near future. However, cooperation can also result in sustainable business models. Sharing resources and knowledge contributes better to the solution of the social and environmental challenges of our planet. Finally, the impact of human activity depends on the behavior of every one. Attitudes toward sustainability have changed and now behavior needs to follow.

4. Conclusion Based on the collective memory of the last economic crises – 2008/9 due to financial institutions and 2011/12 due to government deficits – we argue that the (un)sustainability impact on our economy is clearly underestimated. Conventional business models are focused toward commodity consumption, as illustrated with spikes in commodity prices preceding the mentioned recent economic crises. Hence, sustainable business models are not only necessary, but they can provide a natural hedge for companies. However, there are many challenges ahead. These challenges are associated with the extensive period of time that will be required to adapt our infrastructure in favor of sustainability. We do know what a successful sustainable business model looks like, what its building blocks are, and under which conditions it may prosper. Therefore, while there is growing awareness regarding the need for a new generation of business models, and it is time to invest in the development of sustainable business models.

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References Ajzen, I. (1991) "The theory of planned behavior", Organizational Behavior and Human Decision Processes, Vol. 50, No. 2, pp. 179‐211. Birkin, F., Cashman, A., Koh, S. C. L. and Liu, Z. (2009) "New Sustainable Business Models in China", Business Strategy and the Environment, Vol. 18, pp. 64‐77. Brown, J. (2013) "Creating an ERM culture requires people enterprise risk management", Financial Executive, Vol. 29, No. 3, pp. 61‐63. Deutsche Bank (2006). China's commodity hunger: Implications for Africa and Latin America. Donaldson, T. and Dunfee, T. W. (1999) Ties that bind: A social contracts approach to business ethics, Boston, Harvard Business School Press. Esslinger, H. (2011) "Sustainable Design: Beyond the Innovation‐Driven Business Model", Journal of Product Innovation Management, Vol. 28, No. 3, pp. 401‐404. IMF (2012) World Economic Outlook October 2012: Coping with High Debt and Sluggish Growth. Washington, DC. Jacobson, T., Linde, J. and Roszbach, K. (2006) "Internal ratings systems, implied credit risk and the consistency of banks' risk classification policies", Journal of Banking & Finance, Vol. 30, No.. 7, pp. 1899‐1926. Lutz, C., Lehr, U. and Wiebe, K. S. (2012) "Economic effects of peak oil", Energy Policy, Vol. 48, pp. 829‐834. Magretta, J. (2002) "Why business models matter", Harvard Business Review, Vol. 80, No. 5, pp. 86‐91. Maslow, A. H. (1954) Motivation and personality, New York, Harper & Row, Publishers. Murray, J. and King, D. (2012) "Oil's tipping point has passed", Nature, Vol. 481, No. 7382, pp. 433‐435. Scherbov, S., Lutz, W. and Sanderson, W. C. (2011) "The Uncertain Timing of Reaching 8 Billion, Peak World Population, and Other Demographic Milestones", Population and Development Review, Vol. 37, No. 3, pp. 571‐578. Treacy, W. F. and Carey, M. (2000) "Credit risk rating systems at large US banks", Journal of Banking & Finance, Vol. 24, No. 1‐2, pp. 167‐201. UN (2011) World Population Prospects: The 2010 Revision. Highlights and Advance Tables. New York.

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Standardization‐ the Source of Innovation and Sustainable Development of Companies in Romania Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka Politehnica University, Timisoara, Romania danc.dumitrescu@yahoo.ro ntrandafir09@gmail.com qualex.iso@gmail.com Abstract: The partnership between the UNICERT specialists of the International Group and a research team from the University "Politehnica" has result from a volume of information on sustainable development directions of companies that have implemented specific standardization s ystems. This paper presents the results of studies with reference to how the rigors of the implementation of standardization innovatively affect companies and how to ensure their sustainable development after implementation. Other examples are based on the results of monitoring carried out for various companies where standardization was implemented, the conclusions drawn highlighting the factors that ensure the sustainable development of companies through which they promote innovative elements, but also how to ensure leadership in order to achieve good results compared to previous periods of standards implementation’. The paper highlights aspects of how sustainable development can support social change, creating thus new economically sustainable values, all this after obtaining the certificate of conformity and by taking the reports of the first surveillance audit into consideration, audit that was held on a yearly basis, starting with the initial certification audit. Briefly, the study findings can be of relevance following the synthesis of observations made in several companies: The survey initially target ed 20 companies and has been extended to companies that have a functional system of minimum of 1year. The study was conducted for two months, during which advantages and possible issues arising from obtaining certificates of conformity have been identified. A common element for all studied companies, after the implementation of the Quality Management and Environment System (in various versions) is that they went through a transitional period in order to assimilate the new conditions imposed by the new quality system, this period was different (between 2.5 months to 6 months), taking into account several factors such as: the structure and complexity of the manufacturing process, the quality of the human resources used, the leadership that was promoted in order to obtain positive results from the implementation of the quality system, the employees compensation system, the manufacturing and program structure of delivery deadlines. From the point of view of the end results of this period, the following was noticed: a stagnation and a decrease in production volumes assortment, a stabilization and reduction of costs that define the products’ quality, a performance spill over effects based manufacturing system (a positive individual attitude to the general goals of companies, participation and active involve mentain concrete problems due to the increase in labour productivity in the workplace. The transitional period was followed by a period of enhanced value generating processes, because working methodologies that comply with the provisions imposed by the quality system implementation have been assimilated by work stations; moreover, where the synergistic effect of new assimilation working methods could be compared, the results were well above expectations of the management team. Keywords: standardisation, quality management system (QMS), services, structure fabrication, sustainability, audit

1. Introduction Managers have always wanted to ensure a high level of quality of products and services for sales, at minimal manufacturing costs. However, particularly strong forces opposed and oppose this requirement. Thus, the necessity to plan continuously developing strategies has emerged, to obtain the desired quality level, which resulted in a very dynamic and demanding economic environment. With the industrial revolution additional strategies were developed which included among others: written specifications on materials, technologies, finish‐ goods and control at different levels, standardizing in many forms. The 20th century brought with it an explosive growth of goods and services both in terms of their complexity as well as in the production volume over time. Giant Systems of energy providers were developed, means of communication, transport options and information processing that have become increasingly demanding in terms of quality, particularly in terms of product reliability and maintainability of equipment and services in order to ensure their continuity in action .(Juran, J.M. 1992) It was remarkable how the Japanese managed to solve existential problems more through trade than through military means in the post‐war period; they have placed particular emphasis on developing the concept of

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Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka quality by introducing quality management courses management at all levels, and also for companies’ employees. The Japanese have decreed the quality improvement process as a continuous process involving employees nation wide. The result of the Japanese "Quality Revolution" was generated by massive exports of goods in all areas throughout the world and especially in the USA.( Juran, J. M. 1989) The need to consider the quality of life behind barriers’ has appeared, especially publicly, because of the convergence of several aspects that were generating social‐economic damages, such as damage to the environment, the imposition of strict liability related to economic labour pressure coming from economic organizations to ensure a higher products’, services’ and environmental quality and an increase of the public understanding to wards the role of quality in the international competition, the fear of imminent occurrence of major disasters.

2. Standards, management systems, auditing The society’s reactions to this issue were various, starting with the social ones ‐creating state‐level committees for policies and concrete action plans on product safety, or the development of quality audits to ensure continued fulfilment of the established objectives and policies. An embodiment of the society’s reactions to the seis sues was to strength en its roleby addressing quality‐ based processes, and while selecting relevant common, representative within the synthesis items which allowed the introduction of standardisation, in order to ensure sustainability over time. The standard means a rule which establishes mandatory requirements regarding the quality, size, and other elements that define a product and is applied to unify the manufacturing and product consumption. Standards are developed for some analysis method or for the use of certain systems of scientific concepts, symbols and units. Technical standards for products shall be established, that have an important place in social production and for the general regulations for the technical field (i.e. ISO 9001). The development and implementation standards, at the level of a single company, have several objectives:

To stabilize the manufacturing systems in time, in order to make it possible to achieve good technical and economic features as stable and identical in terms of manufacturing costs as constant as possible;

To ensure a level of easy communication with suppliers by using the standardized references on process resources (raw materials, energy, fuel, equipment);

To ensure an open communication for the end consumers, through the assimilation of standardized performance elements.

With the entry into force of the ISO 9001, ISO140001, OHSAS 18001, ISO22000 and other standards, a new period in terminology quality begins; these standards have been designed for all users on the basis of uniform principles and criteria as the requirements formulation is general.

Checking the right fullness of the standards appliance in manufacturing processes, and especially checking of the constancy of the processes’ quality characteristics ensured through the implementation of QMS; they are designed as a set of elements that characterize decision making, organizational, informational and motivational management organization in order to achieve effective and efficient processes that take place within the structure of manufacturing. (DM). Time dimensions of process efficiency/effective nessis verified through QMS aiming audits. Audit means a trained reviewing approach of the process or actions in certain areas to determine the extent to which they comply with certain principles, requirements, rules, streamlining key decisions, actions and involved behaviours (Nicolescu, O. 2011) The main types of audit are management audit, environmental audit, audit joint venture. In terms of how to perform, several types of audit can be identified:

Internal audit: Performed within the audited company by a team of their own specialists.

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The structure: it shall comply with the general policy and strategy of the organization, of which it is part and to comply with the internal audit law of Romania. I.A. activity: is continuous, diverse, planned and conducted according to the results obtained in the risk analysis.

External audit: The team consists of specialists who have performed the certification of the company. It is legally independent; undergoing certification period is predetermined by mutual agreement with the management team of the audited company. The external audit takes place according to a precise methodology, standardized and based on analysis, comparisons, reports, and evaluations of the internal control systems.

Ethical audit: Audit category that consists of a set of external audit services, which prevails in the market recently, offered by consulting companies, which has as objective the improvement of the governance at company level, the improvement of internal control, the improvement of the investor protection, and others; the provided services are in accordance with the law, they cover the operational training plan within the company’s ethical business behaviour, including the implementation of a code of ethics.

The audit’s role is to verify and certify the accuracy of the quality management systems implementation in the manufacturing system, namely, the accuracy and effectiveness of the internal control, of the financial control, of inspections and audits of manufacturing processes. The recommendations made by auditors are optional; they only establish a state of affairs, which can be changed or maintained by the management team of the audited company.

3. The effects of certification ‐ case study 3.1 QMS implementation in the services area A feature of the last three decades is that while increasing the manufacturing of goods, both from the assortment as well as in the volume of production, a development of services related to those goods, and an increase in service‐oriented aspects specific such as: ensuring equipment reliability, maintenance, redundancy and availability took place. In addition to the significantly increasing number of employees working in the services area, specific areas for sales of goods and services to customers even within companies were developed, areas that, until recently, had the exclusive domain of manufacturing activity. The main problem encountered at that point was related to the quality of services, because an integrated approach of quality enabled consumers and providers with the possibility of knowing their expectations; thus the possibility of a direct offer of services to meet the highest expectations, to satisfy consumer demands and to gain their confidence existed. Direct links to customers ensure manufacturers a higher satisfaction level due to the immediate response to existing needs and expectations. The direct connection ensures permanent revising activities, and their regulation, while increasing self responsibility and self‐control. Third, through the close relationship established with customers, one can gain a competitive advantage due to the continuous improvement of services, and sustainability assurance on the services market. To maintain the competitiveness and sustainability under the requirements of the market, the services providers are to focus on the quality improvement. One option in this regard is the specific implementation of QMS in each company. But the reappears to be a paradox: Despite the fact that the services providing sector substantially contributes tot he overall economy, and that worldwide an economy is considered to be more efficient as its volume has a wider range of services, there are much fewer concerns about the concept of services’ quality than those related to product quality and to the quality of manufacturing. (Bogan, C. and Michael, J.1994)

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Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka This is because of the followings differences: the technical, physical product that can be clearly determined and the characteristics of the services related to products, which of ten are unknown and cannot be evaluated. Therefore, there has to be a difference in the quality of products, processes and services’ quality.

3.2 Case study The “Qualex” company, specialized in the design and implementation of QMS, has worked with companies specialized in the manufacturing of food, consumer goods, but also with services companies specializing in various areas, in order to be able to determine the effects resulting from the application of QMS. The study has covered20companies and has been extended to organizations that have a functional system for at least 1year, from the moment the certification was granted. The covered areas were:

Processing industry, mining, machinery –equipment ‐ gear ‐ 6 companies (31%)

Industrial companies ‐ 5 companies (25%)

Professional services ‐ 4 companies (20%)

Food industry ‐ 3 companies (12%)

Other areas ‐ 2 companies (12%)

TOTAL‐ 20 companies 100%

The structure of the companies, according to the services area is shown in figure 1.

Figure 1: Structure areas addressed The object of the study was to determine the effects of implementing specific standards for QMS and to draw conclusions on the sustainable development of companies by implementing the quality management system. The analysis was focused on two aspects:

The analysis of the effectiveness of the measures following the grant of the certificate of conformity.

The analysis of the conclusions of the first surveillance audit reports, which took place about 1 year after the initial certification audit.

During the study, possible advantages and disadvantages or difficulties arising from the certification process were identified. A first group of questions aimed the reason, motivations which have led to the implementation of the QMS. Responses were grouped as follows:

The consent to participate in domestic and international tenders

6 companies30%

The elimination of scrap from the manufacturing process

2 companies10%

A better internal organization of the manufacturing processes

3 companies15%

Continuous training, continuous in crease awareness of staff to wards processes

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5 companies25%

Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka

The Improvement of the company image

3 companies15%

Otherc auses

1 company5%

Total

20companies100%

The answer provided by companies regarding the motivation behind the QMS implementation, the main causes, is given in figure 2:

Figure2: Motivation implementation, QMS, cause related In order to analyze the economic efficiency of activities und retaken before and after the certification needed to establish trends for future activities, the information from table 1was used. Table 1: Dynamics of manufacturing value achieved before and after implementation of the QMS No. crt P1.1 P1.2 P1.3 P1.4 S1.5 S1.6 S2.1 S2.2 P2.3. P2.4. P2.5. S3.1. S3.2. A3.3. S3.4. P4.1 S4.2 S4.3 S5.1. S5.2.

Process type Manufacturing Manufacturing Manufacturing Manufacturing Services Services Services Services Manufacturing Manufacturing Manufacturing Services Services Services Services Manufacturing Services Services Services Services

Q 50234 83500 101250 261320 73254 82163 43.888 52.235 597841 64544 44326 203000 280025 71456 91347 450225 150324 356894 353648 647890

Q1 21226 80124 85200 200624 70132 82006 42900 51490 498200 60980 44090 203900 267980 70678 89368 360620 150007 309539 350480 607365

Q2 20120 80227 88103 230189 71265 83720 42932 51644 472539 61831 44134 198777 278555 71156 88900 375090 150568 340124 341268 612490

Q3 21989 81678 92124 240990 75250 84625 43123 52650 473134 62569 44256 210234 275341 72167 89324 402156 150988 367458 346780 627750

Q4 31023 82880 102450 250327 76040 84890 43670 52785 498256 63889 44698 215356 280001 72980 89454 430679 152650 367580 347902 634557

Q5 38156 84720 104421 262017 76260 85999 44669 52700 523890 65.721 44765 225335 289354 72887 90124 460135 167549 369200 349796 656589

Trend ↔ ↔ ↔ → ↑ ↔ ↔ ↔ ↔ ↔↑ ↓↔ ↓↔ ↔ ↔↓ ↔ ↔ ↓↔↑ ↔ ↓↔ ↔ ↔

Where: ValueUnit

Q =output value achieved before the implementation of QMS( month ) Q1, Q2, Q3, Q4, Q5=value of production in he first, second, third, fourth, fifth month after the implementation ValueUnit

of the QMS( month ); Symbols representing trends: ↔‐ stability; ↑ ‐increase, ↓ ‐decrease. A range of five months was selected as a minimum interval to determine the trend followed by every company, after a period of two months, adjusting to the new working system.

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Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka These results have led to the graphical output of the monthly production growth, for manufacturing companies (Figure3) apart of services providing companies(Figure 4) 1800000 1600000 1400000 P4.1. 1200000

P2.5. P2.4.

1000000

P2.3. P1.4.

800000

P1.3. P1.2.

600000

P1.1. 400000 200000 0 1

Figure 3: Dynamics of production value, manufacturing companies’ profile The analysis of the graph in figure 3 shows the following:

All companies register a reduced production value in the early months after the implementation of the QMS.

Companies of the manufacturing industry, mining (P1.1, P1.2, P1.3, and P1.4) have quickly adapted to the new provisions of the QMS, so that after only one month of the implementation of the QMS, production volumes registered an upward trend and after three months they reached the same level as before the implementation of the QMS.

The production value is higher, so its reduction after implementation of the QMS is substantial.

The period of adjustment with the QMS rules takes one to three months, after which the activity is stable and there is also an increasing tendency in the manufacturing beyond the existing value before implementing QMS.

Implementation of QMS. The companies belonging to the industrial construction (P2.3., P2.4., P2.5.) needed an adjustment period of about four months, after which they went in to a stabilized activity phase; the causes that generated this situation were many: inability to use unskilled labour, production processes needed to adapt to customer requirements diversification, the need for flexible management for diverse work phases of different corporate objectives.

Regarding the food manufacturing company (P4.1.): It took about five months for it to go under a stable, safe operation, because when implementing QMS on food products‐ISO22000 /HACCP advanced gear and equipment was needed, and the qualified personnel was trained to fulfil the safety standards set by the standardizations. 700000 600000

S1.5. S1.6. S2.1.

500000

S2.2. S3.1.

400000

S3.2. S3.3

300000

S3.4. S4.2.

200000

S4.3. S5.1.

100000

S5..2.

0 1

Figure4: Dynamics of production value, services providing companies profile

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Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka The analysis of figure4 shows:

Reducing the production capacity of services providers, after the implementation of QMS, did not visibly affect the value of the services provision.

Even if the decrease occurred, its maximum length and duration was of six weeks after the activity showed a positive trend or a stationary one.

Exceptionally, the company specializing in professional services(S3.2) after a period of operation with a stationary trend was forced to change it score business and has seen a decline in the value of services rendered far below original.

4. In conclusion

Implementing a QMS, regardless of the area the company runs its activities in, has a positive effect in the sense that, after an appropriate time to assimilate the rigors of the QMS, the company starts working in a safe, stable environment, generating additional benefits. This trend is observed in the analysis of individual development of the companies(last column of Table 1).

Out of the20 analyzed companies, only 1resultednot proving to be sustainable in the initial market segment, other companies have developed, based on the QMS implementation, innovation strategies that enabled them to achieve the level required to maintain sustainability in their market segment.

Services providing profiled companies have assimilated in a much shorter time provisions imposed by QMS, which led to the irrelevant decrease of the value of provided services and their sustainability in relation to customer requirements.

The survey also revealed that in companies that are active the industrial field, the uptake of QMS provisions was done more easily, because the operators worked more with products specific documentation and according to the manufacturing processes. There were situations where operators participating in the implementation of the QMS, in conjunction with the quality assurance responsible employee have improved some more complex procedures, initially only generically presented.

In services providing companies, QMS uptake encountered issues when implementing the expanded working points: either lacked the necessary equipment or the training meaning they were not trained to fulfil the conducted tasks.

One of the generally presented issues by trained staff was that of very complex documents, sometimes difficult to be absorbed in a short time. An analysis of the financial results revealed that, despite the implementation costs, after about seven months of implementation, an increase in production by 6‐145 was obtained, compared to the situation before implementation, which pleads for the sustainability of companies in their market segment.

5. Acknowledgements “This work was partially supported by the strategic grant POSDRU 107/1.5/S/77265 (2010) of the Ministry of Labour, Family and Social Protection, Romania, co‐financed by the European Social Fund – Investing in people.”

References Bogan, C. and Michael, J. (1994) Benchmarking for Best Practices, McGraw‐Hill, New York Juran, J.M. (1992) Juran on Quality by Design, Original English edition, Juran Institute, Inc.. Juran, J. M. (1989) Juran on Leadership For Quality, Original English edition, Juran Institute, Inc. Kemp S(2006)Quality management‐demystified‐a self teaching guide‐Mc GRAW – Hill Inc.Toronto ISBN 0‐07‐‐129‐882‐5 Nicolescu, O. (2011) Dictionary of Management, Prouniversitaria Publishing House, Bucharest, ISBN 978‐973‐129‐882‐5 YvanAllaire(1998)Strategic management business success strategies‐ Economical Ed. Bucharest 1998‐ ISBN973‐590‐040‐8

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Employee‐Driven Innovation in a Higher Educational Institution: Organisational and Cultural Influences Smile Dzisi1, Joshua Ofori‐Amanfo2 and Benjamin Kwofie3 1 School of Business and Management Studies, Koforidua Polytechnic, Koforidua, Ghana 2 Leeds University Business School, University of Leeds, Leeds, UK 3 Center for Communications Media and Information Technologies, Aalborg University, Copenhagen, Denmark afuasmile@yahoo.com bnjoa@leeds.ac.uk benjaminkwofie@gmail.com Abstract: Employee‐driven innovation is yet to receive sufficient attention in the literature. Although some studies have been done on organisational innovation, very little is still understood about employee‐driven innovations. Of particular research interest is employee‐innovator’s source of innovative ideas, their drive for the innovation and the process of initiating, adopting and implementing the innovation. In this paper, we take a step at advancing knowledge on the concept through a study of four employee‐driven innovations in a higher educational institution in Ghana. These innovations were examined within the context of the institution’s organisational and cultural attributes. The study fundamentally addresses the research questions: (1) what is the nature of employee‐driven innovations and how are they initiated? (2) what motivations drive employee‐driven innovations? (3) what organisational and cultural challenges impact on employee‐driven innovations? An in‐depth case study methodology was adopted for the study where Individuals, groups and top‐ management involved in the investigated innovations were identified and interviewed. Findings from the study contribute to our understanding of EDI and there are ongoing efforts to develop EDI theory and organisational learning through the identification and clarification of the nature of employee‐driven innovation. Keywords: employee‐driven innovation; organisational influences; motivation, higher educational institution, innovation process

1. Introduction Innovation is considered as the lifeblood of every enterprise and entrepreneurship scholars recognize the critical role of innovation in the success of organisations. The 21st century has witnessed rapid innovations in both product and business processes facilitated by advances in technology which invariably have intensified business competitions. Remaining competitive and profitable in this global and dynamic business environment is now a major concern to most organisations. Organisations are compelled to constantly scan their internal and external environments for opportunities to innovate their products, process and practices in order to maintain their visibility and market share. Innovation is, therefore, emerging as a key dimension of organisational competitiveness. The role of innovation and its importance as a driver of competitiveness, profitability and productivity of organisations have been confirmed in literature (Fazlzadeh and Moshiri 2010; O’Regan, Ghobadian and Gallear 2006). Although formal organisational structures like the research and development (R & D) units are created and tasked with the duty of generating and developing organisational innovations particularly in manufacturing organisations, such formal structures for innovations are quite rare in higher educational institutions within the developing world. In such educational institutions, the main source of innovations are individuals who in most cases hold key positions in the institution as well as in the government policy directive. Employees in some organisations have often been credited with brilliant innovative ideas and have been identified to champion some innovations introduced by the management. Employee‐driven innovations therefore impact significantly on institutional reputation and visibility. In spite of the critical role that employee‐driven innovations play in higher educational institutions, not many such institutions are aware of the importance of employee‐driven innovations and formally recognize, encourage or take advantage of the vast potential of this form of innovation. This oversight may be attributed to the general lack of understanding of the concept as it appears to be an understudied area of organisational innovation. This study, therefore, fills the gap by contributing to the enhancement of the understanding of employee‐driven innovation in the context of organisational influences within higher educational institutions in Ghana.

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2. The case institution The case institution is a higher educational institution providing post‐secondary education in business, applied science and technology and engineering in Ghana. The institution has employee population of over 650 members of staff including administrators and faculty members. The institution has a student population of about 5000. The institution engages in teaching, research and community services geared towards development. Over the last ten years many innovative initiatives have been introduced, some of which have been successful and thrive till date. These innovations which mainly come in the form of new academic programmes originated from particular individuals within the institution. It is four of such innovative academic programmes that were selected for study in this research. Although some of these programmes are currently not being run, useful lessons can be learnt from the experience which will contribute to theory building in employee‐driven innovation. Below we describe the initiatives.

2.1 Evening school programme In 2002, an evening school programme was established alongside the regular school programme. The programme was designed for workers who wanted to pursue academic qualifications on part time basis. This programme offers students the opportunity to attend classes at the close of work from 5pm. Another objective for the establishment of the programme was to help generate funds for the institution’s developmental agenda as the government subventions were inadequate. The programme ran parallel to the regular day programmes with revenue from the initiative shared between the institution and faculty members. Till date, the programme continues to run successfully and represents a major source of income for the institution.

2.2 Door‐step programme This was another innovative educational programme introduced with the objective of taking the institution’s educational services straight to the door‐step of community members in remote towns. Two branches of the institution were opened in two towns in Ghana. Operating in a distant learning mode, faculty members were sent on every weekend to lecture in each of the two centres. Students were recruited and enrolled into different programmes. In 2012, the programme was closed down due to some constraints.

2.3 Modular programme The modular programme was introduced in 2008 with the aim of enabling students in the institution and from similar institutions completes additional semester requirements during the long vacations. This was to shorten their period in school from 3 years to 2 years since usually it was shown that students graduating with HNDs from polytechnics undertook top‐up programmes in the universities. The programme was limited to students with certain levels of achievement in terms of grade point averages. It was run for a year and later cancelled due to accreditation problems.

2.4 IODL programme This centre was recently introduced to provide distance education through the application of e‐learning. Currently the centre runs weekend distance programmes with plans far advanced to introduce online learning resources and support. The centre has become an institute coordinating all part time academic programmes including professional studies (ACCA, ICA), artisan training (beauticians, carpenters, etc.).

3. Literature summary Schumpeter is the economist who has most prominently drawn attention to the innovating entrepreneur. Schumpeter (1961) argued that innovation meant doing more with the same amount of resources available to anyone. Schumpeter also regarded the entrepreneur as the one who contributes significantly more than others to the economy by virtue of innovation. This innovation results in the loss of old products and processes. Schumpeter calls this creative destruction. Schumpeter stated that the term innovation fits into any of the five categories: the creation of a new product; a new method of production; the opening of a new market; the capture of a new source of supply or a new organization of industry. Schumpeter (1979) further argued that every innovation successfully introduced by firms, large or small, creates new demand for goods and services and therefore creates new wealth and success for the entrepreneur. Choi (1995) and Kirzner (1999), in supporting this perspective, added that although innovations can vary in their degree of radicalness,

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Smile Dzisi, Joshua Ofori‐Amanfo and Benjamin Kwofie innovativeness represents a basic willingness to depart from existing technologies or practices and venture beyond the current state of the art. Schumpeter’s perspective is strongly affirmed in business literature in that the choice of industry sector and the type of business activity undertaken has a direct effect on potential growth and success. Bhide (2000) also added that innovative business ventures that are not easily imitated are more likely to attract high patronage, and create wealth. In support of Schumpeter’s innovation perspective, Linder, Jarvenpaa and Davenport (2003) describe innovation as “implementing new ideas that create value”. This generic description refers to the various forms that innovation can take such as product development, the deployment of new process technologies or innovative management practices (Glynn 1996). From a practitioner’s perspective, this means the adoption of new products and/or processes to increase competitiveness and overall profitability, based on customer needs and requirements (Mone, McKinley and Bargar 1998; Zahra, Nielsen and Bognar 1999). Effective innovation therefore means that organisations need to maximize the creative resources that they possess (O’Regan et al, 2006). Innovation is widely recognized as an important engine of growth. The underlying approach to innovation has been changing or shifting away from models largely focused on Research and Development (R&D). The understanding of how organizations build their resources for innovation has thus become a crucial challenge to finding new ways of supporting innovation in all areas of activity. According to ILO (2008:10) Employee–Driven Innovation (EDI) means that “employees systematically and actively contribute to the generation of new ideas which create value when they are implemented”. EDI refers to the generation and implementation of new ideas, product and process‐including the everyday remaking of jobs and organizational practices – originating from interaction of employees who are not assigned to this task (Kesting & Whoi, 2010). The processes are unfolded in an organization and may be integrated in cooperative and managerial efforts of the organization. Employees are active and may initiate, support or even drive or lead the processes. In this conceptualization, EDI indicates a bottom‐up process in the organization. EDI begins at the job and at worker level. EDI may begin at the Job and worker levels, but turns out to be an interaction between many actors that may include employees and managers as well. Therefore it may be difficult to isolate EDI as a pure bottom up process in the organization, and the process may not be isolated from the management, but related to management. In some conceptualization of EDI, the management perspective seems to be dominant (Kesting & Whoi, 2010). Management plays a role in EDI, in several ways. Employees typically acquire exclusive and in‐depth and highly context‐dependent knowledge that managers often do not possess (Kesting & Whoi, 2010). Therefore EDI indicates that innovation emerges coincidentally among ordinary employees from shop floor workers, professional and middle managers across the boundaries of existing departments and professions (Kesting and Whoi, 2008). It may be possible for the employees in units of the organization – for instance in teams without interference from the management to continuously develop and remake their daily work practice and to conduct other kinds of innovations. But that also implies a threat: if the organization is overflowing with uncoordinated ideas and solutions from employees, this may threaten to tear apart the very order of the system, and the process of change from this perspective may therefore appear anarchic and unpredictable. Consequently, managers may be involved in EDI on 2 levels. First, they may join the process of EDI to coordinate and systematize the processes initiated by the employees, to use the resources of the employees and make these processes constructive to the organization. Second, managers may take the initiative in innovation by inviting employees to participate in innovative processes, and the involvement of employees in the innovation process may be formally organized. This is clearly a top‐down process. This understanding of the concept of EDI is prominent in approaches centered on the term participation, as in the approach by Kesting & Whoi (2010). Accordingly, EDI is understood as employee participation and involvement in innovation related activities and decisions (Kesting & Whoi, 2010). Cooperation between management and employees is thus essential (ILO, 2008:9). In effect, EDI represents a case of a mixture of both bottom‐up and top‐down processes in the organization (Teglborg, 2010). The new development trends that we are observing in the society, in the organization of companies and in the relationship between company and employee combined with the new ideas of innovation – contribute to creating the concept of EDI. The recognition of ordinary employees as being important and key to generating new knowledge, new ideas and solutions is fundamental to the understanding of EDI. Employees’ active involvement in the operations of the firm and their continuous remaking of their jobs comprises a new and a fruitful perspective on innovation in organizations. Furthermore, employees‐driven innovation may be

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Smile Dzisi, Joshua Ofori‐Amanfo and Benjamin Kwofie conceptualized as embedded both within working processes – the daily work practice‐ and within learning processes, especially workplace learning. It becomes clear that the concept of employee‐driven innovation covers a broad range of complex processes that can be related to a formal‐in‐down point of view.

4. Methodology The study employed the case study methodology for obvious reasons. Yin (1989) defines a case study as an objective, in‐depth examination of a contemporary phenomenon where the researcher has minimal control over events. Similarly, Eisenhardt (1989:534) describe the case approach to research as “a research strategy which focuses on understanding the dynamics present within single settings”. This type of research method enables investigation into one or a small number of social entities or situations using multiple sources of data and developing a holistic description through an iterative research process (Easton, 2010). Case studies are very useful research means for understanding “real world” events (McCutcheon and Meredith, 1993). Kesting and Ulhøi (2010:66) refer to employee‐driven innovation (EDI) as “the generation and implementation of significant new ideas, products, and processes originating from a single employee or the joint efforts of two or more employees who are not assigned to this task”. This definition highlights individuality and a sense of initiative as vital ingredients in EDI. This, the researchers thought could be better captured by employing a case research approach. Moreover, as research on EDI is still at the infancy stage, an understanding of the concept in relation to appropriate theory building is paramount. A case research may have different purposes but predominantly used to understand the why’s and how’s of social events (Yin, 1989: McCutcheon and Meredith, 1993). Stuart et al (2002) maintain that case studies offer an excellent research role of developing understanding of a social or organisational process. Developing understanding as a research role is particularly important in the field where the subject matter is very complex such as EDI. To this end, the researchers thought a case study approach will offer a better opportunity for exploring in detail, the researcher‐participant interactions in order to understand the ‘reality’ behind EDI. The choice of case research methodology for the study is grounded in the view that the methodology is both appropriate and essential where either theory does not yet exist or is unlikely to apply (Stuart et al, 2002) as the case of EDI may be. The case study methodology is also useful for the study of EDI due to the multiple data collection opportunity it offers. To comprehend the EDI process and develop a good picture of the phenomenon, one invariably requires multi‐source data collection methods (McCutcheon and Meredith, 1993). Among these are interviews, story‐telling, observations, document analysis etc. Thus the inherent flexibility of case‐based research enhances the usage of qualitative data collection methods which seems to be most appropriate for “sense‐making” of the EDI reality.

4.1 Data collection Construed within the context of a qualitative case study methodology, ten in‐depth interviews were conducted between November 2012 and February 2013. The interviews were open allowing respondents to use a story‐ telling approach to recount various incidents of EDI initiatives they were involved in. The interviewees were allowed to take the interviews to any reasonable direction in order to allow theory to freely emerge. The research participants were people who had initiated or were directly involved in the initiation of an EDI programme within the case study. The researchers employed purposive sampling to ensure that data was collected from people who were familiar with the phenomenon under study. All the interviews were voiced‐ recorded and transcribed for analysis. The total interview hours recorded was 18 hours, 20 minutes.

4.2 Data analysis The interviews were transcribed to a very high level of detail. The transcripts were then systematically coded using conceptual codes. The constant comparative method (Glaser & Strauss, 1967) was employed by the research team to compare and contrast conceptual codes and identify emerging themes within the transcripts. In order to create a picture of the interconnections and associations as well as the governing mechanisms among the conceptual codes, the narrative approach to analysis was employed. The narrative approach was therefore a useful approach to ‘sense‐making’ of the EDI situation in the case organisation. The application of the narrative approach to analysis is justifiable on the grounds that it can be applied to interview accounts in general (Bryman and Bell, 2003).

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5. Results 5.1 How the innovations were initiated The four innovations described above were all initiated and spearheaded by employees, who were members of faculty. With the four programmes under study, the originators of the idea were all at the time heads of department, had some degree of authority and were part of the highest decision making body in the institution, the academic board. A common characteristic that runs through these employees is that they were all in middle level management positions and as such had some level of influence in decision making. Whether this is an important consideration is yet to be determined as it raises questions about whether employees who are not in managerial positions can drive innovations successfully. The interviewees revealed that majority of these individuals are creative thinkers who are always challenged to move away from the status quo. One respondent commented: “Thinking and bringing out new ideas has always been part of me. I have achieved many things in life through thinking outside the box. The thing is I always ask myself the question, why must it always be done this way and not that way and I tell you, when you begin to question yourself this way, it’s amazing the sort of thoughts you are able to generate. I have always asked myself the question what I could do differently in my two year tenure of office……” (Case respondent 1). “This idea came to me one morning after I’ve had a phone conversation with my wife who lives and works in a remote town. I had always wanted to bring my wife closer to me so she could have access to higher educational facilities and upgrade herself education‐wise but her job wouldn’t permit. In these days of economic hardship, I couldn’t afford to ask her to terminate her job just for education, man must eat you know. So I asked myself how could I help her and that was when this idea of taking the institution’s programmes to such remote towns cropped up. Thank God it wasn’t a wishful thinking and today my wife is a graduate” (Case respondent 4). It is obvious from these quotes that these innovations resulted from employees who do not limit themselves only to thoughts around their job descriptions. Creative thinking by employees is thus a precursor to employee‐driven innovation. The analysis further revealed that creative thinking alone is insufficient to generate innovations. Personal involvement of these individuals in the operations of the institution and the subsequent recognition of such innovative efforts by the management were equally contributory factors to employee‐driven innovations as demonstrated in the quote below: “…..one thing I like about this school is that there is always somebody who will see the little efforts people make. This was not the case with my previous institution and that was the main reason why I left. I mean even though I have not been given any special financial reward, the mere fact that virtually everybody in this school knows that I am the originator of the idea for this programme, which is more than money for me. With my continual involvement, who knows what other ideas may come up in the future” (Case respondent 1). It is obvious from this expression that the support system provided by the institution contributes to employee creativity and innovativeness. The support system may have its challenges as may be seen later in the analysis, but its availability is an essential innovative factor.

5.2 Motivations for employee‐driven innovation Different sources of motivations emerged during the interviews. The analysis supports the proposition that employee‐driven innovations are influenced by personal desire of individuals in the organisation to satisfy a need as well as an empowering organisational environment. Relative to innovations driven by the desire to satisfy a personal need, are needs motivated by the desire to attain some recognition among management and staff of the institution, the quest to address personal concerns, or the desire of such individuals to introduce some differentiation into their organisations for competition. One employee‐innovator asserts that he was motivated by the need to make the institution unique. “…..it was a question of how do we get more students than other similar institutions and to do this it was obvious we needed to do something different from what the rest (other institutions) were doing. I felt this idea would be unique to this institution when I thought about it initially but

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Smile Dzisi, Joshua Ofori‐Amanfo and Benjamin Kwofie now it has been copied in many other institutions. At any rate we take consolation in the fact that we are the pace‐setters, no doubt about that” (Case respondent 9). “In fact, I wanted to be remembered as the one who introduced this programme in my term in office and I think I have achieved that aim” (Case respondent 2). All the four instances of innovations cited in the case description were tied to a prime motivation and therefore suggests that there is always a reason why employees may originate an idea. This may be in pursuant to a personal agenda or in an attempt to promote the wider interest of the institution. The study also revealed that a friendly and welcoming organisational environment engenders innovation and creativity among staff. Innovativeness thrives in a participatory type of environment. Where staff are encouraged and empowered to actively participate in the operations of the firm, employee creativity is engendered. In the case of the case institution, the management of the institution encourages individual employees or teams to put forward their conceived innovative ideas in the form of a proposal. The individual will then defend the idea before a committee after which it will be subjected to a thorough brainstorming session to assess risks and merits all with the active involvement of the originator. This process in itself helps to shape new ideas and assures staff that their proposals will be considered as long as it “makes some sense to the powers that be”.

5.3 Organisational and cultural factors influencing employee‐driven innovations Organisational and cultural practices were found to be key factors that promote employee‐driven innovations. The practice of recognising the contributions of individual members was found to be rewarding enough to encourage staff to be innovative. There was evidence from management which shows that each individual’s role is important for the success of the institution. This is clearly articulated in the institution’s mission statement. A key management staff expressed: “We are all in the same boat taking us to a never‐reaching destination. It is therefore the responsibility of everybody on board to ensure that the boat stays afloat and even though we don’t know our final destination, we have an idea of where we are going and so all must ensure that we are heading towards the right direction. If we sink, we sink together, not just management. This is why everybody is important and we recognise and appropriately reward such efforts” (Case respondent 8). Support and encouragement from the management subsequently appears to be an important organizational factor that influences employee‐driven innovations. The employees indicated that, had management not supported and encouraged their ideas by requesting the submission of a proposal for consideration, these innovations might not have seen the light of day. Such support and encouragement show the interest and commitment of the management which then inspires employees to continue until they realize the intended objectives for the innovation. There were, however, some negative attitudes that were discovered to impede creativity and innovation among some innovators. Some management staff who have worked for the institution since its establishment some seventeen years ago sees such innovations as a threat to their positions. In most cases these members of staff are included as committee members who evaluate innovation proposals. Their strategy is to frustrate the individual to give up his new idea. They do this by absenting themselves from scheduled committee meetings so that such meetings would be rescheduled. This practice leads to unnecessary delays in the evaluation of proposals and which eventually leads to the loss of interest by the originators of innovative ideas. “It got to a point that I nearly gave up but I encouraged myself with the thought that good things don’t come easy so I persisted and persisted because I strongly believed it was a workable idea. Even with that effort, it took over a year for the programme to be accepted and implementation strategy put in place. ……….There are some senior staff up there that are just there to frustrate you simply because the idea is not coming from them. I think it’s about time some of these old folks retired as they don’t seem to see anything good with ideas they are not familiar with” (Case respondent 2). There is no doubt that frustrations and delays such as the one articulated by case respondent 2 discourage employee‐driven innovations. Invariably, the important role played by institutional influences engendering or impeding employee innovativeness should be given a serious consideration.

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5.4 The impact of employee‐driven innovations The analyses point to the direction that employee‐driven innovations impact significantly on the operations of a higher educational institution. The employee‐innovations studies have become a major source of income funding many building and construction projects the institution is undertaking. These innovative academic programmes have also increased the visibility of the institution and enhanced its reputation and competitiveness. The benefits accruing from the employee innovativeness extend to individual members of staff as they earn extra income in addition to their salaries.

6. Managerial implications Every organisation is made up of individuals with different levels of intellectual and analytical abilities. Such innate abilities of the individual members of the organisation may not relate directly to their job description. However, these abilities which often remain untapped can be utilised to enhance the organisational competitiveness when appropriate structures are put in place. Kesting and Ulhoi (2008) contend that employee‐driven innovations emerge coincidentally and the probability of such innovations emerging is very high where there is availability of organizational support systems which this study has identified as an important ingredient in developing and sustaining new operational and strategic ideas. As part of the support system, employees should be made to feel as part of a process or a system and valued. Such an organisational environment represents a nurturing ground for employee‐driven innovations among employees from all levels of the organisation. O’Regan, Ghobadian and Gallear (2006) posit that the skilful utilisation of employee‐driven innovations will drive efficiency, productivity, competitiveness and profitability into the organisation, hence the need for a strategy to promote employee‐driven innovations.

7. Conclusion This study has enhanced our understanding of the concept of employee‐driven innovations. The case study has been useful in unpacking the motivations that drive employee innovative thinking. The study shows that employee‐innovations can be sourced to the desire of individuals to address a personal concern or a general desire to resolve a wider organisational challenge. The success of an employee‐driven innovation is however very much dependent on available organisational support systems which might influence or impede its success. A key limitation of the study is the use of only one case study to examine the phenomenon. Subsequently, a future research could employ a multi case study approach for the purposes of establishing the validity of the antecedents of employee‐driven innovations as found in this exploratory study.

References Bhide, A (2000) The Origin and Evolution of New Business, 1st edn, Oxford University Press, New York. Bryman, A., and Bell, E. (2003) Business research methods. Oxford, UK: Oxford University Press. Choi, Y (1995).The Entrepreneur: Schumpeter vrs Kirzner in IM Kirzner, (1999), Creativity and/or Alertness: A Reconsideration of the Schumpeterian Easton, G. (2010). “Critical realism in case study research”. Industrial Marketing Management, 39, 118‐128 Eisenhardt, K. (1989) “Building theories from case study research”. Academy of Management Review 14 (4), 532–550. Fazlzadeh, A and Moshiri, M. (2010) “An Investigation of Innovation in Small Scale Industries Located in Science Parks of Iran”, International Journal of Business and Management, Vol. 5, No. 10 Glaser, B. G. and Strauss, A. L. (1967) The discovery of grounded theory. Chicago: Aldine. Glynn, M.A., (1996) “Innovative genius: A framework for relating individual and organizational intelligences to innovation”, The Academy of Management Review, Vol. 21 No. 4, pp. 1081‐1111. International Labour Organisation (2008) World of Work Report, Geneva, International Labour Office. Kesting, P. & Ulhøi, J.P. (2010). “Employee‐driven innovation: extending the license to foster innovation”. Management Decision, 48, 1, 65‐84 Kesting, P. and Ulhoi, J.P. (2010) “Employee‐driven Innovation: Extending the license for fostering Innovation”, Management Decision, 2010, Emeraldinsight.com Kirzner, IM (1999). Creativity and or Alertness: A Reconsideration of the Schumpeterian Entrepreneur, Review of Austrian Economics vol.11, pp 5‐17, Kluwer Academic Publishers. Linder, J.C., Jarvenpaa, S., and Davenport, T.H., (2003) “Towards an innovation sourcing strategy”, MIT Sloan Management Review, Vol. 44 No. 4, p. 43(7) McCutcheon, D.M. & Meredith, J.R. (1993) “Conducting case study research in operations management”, Journal of Operations Management, 11, 239‐256. Mone, M.A., McKinley, and W. Bargar, V.L. (1998) Organizational decline and innovation: a contingency framework, Academy of Management Review, No. 23, pp. 115‐132.

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Smile Dzisi, Joshua Ofori‐Amanfo and Benjamin Kwofie O’Regan, N., Ghobadian, A. and Gallear, D. (2006). “In search of the drivers of high growth in manufacturing SMEs”, Technovation, Vol. 26 No. 1, pp 30‐4.1 Schumpeter, J.A (1961) The Theory of Economic Development, Harvard University Press, Cambridge, Massachusetts. Schumpeter, J.A (1979), Capitalism, Socialism and Democracy, George Allen, Irwin, London, UK. Stuart, I., McCutcheon, D., Handfield, R., McLachlin, R. and Samson, D. (2002) “Effective case research in operations management: a process perspective”. Journal of Operations Management, 20, 419‐433 Teglborg, A. (2010) “Modes of Approach to Employee‐driven Innovation in France: An empirical Study”. European Review of Labour, SagePub.com. Yin, R.K. (1989). Case Study Research: Design and Methods. Sage Publications, Newbury Park, CA, rev. edn. Zahra, S.A., Nielsen A.P., and Bognar, W.C. (1999) “Corporate entrepreneurship, knowledge and competence development”, Entrepreneurship: Theory and Practice, Vol. 23, No.3, pp. 169‐189.

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Firm Capabilities, Complementarities and Innovation in the Latin American Coffee Sector Luis Figueroa University of Essex, Southend on Sea, UK lrfigu@essex.ac.uk Abstract: This research proposes a quantitative evaluation of the mutual impacts of innovation performance and technological capabilities in a context that has been scarcely explored in the previous literature: a mature low‐tech (agricultural) industry located in Latin American countries, particularly the case of the coffee farms in Costa Rica and Guatemala. The results confirm a strong positive relationship between innovation performance and technological capabilities. Also, the data shows that a high level of marketing capabilities increases this positive relationship, although a moderator effect cannot be detected. Finally, potential differences that may be attributable to the country of origin as well as other control variables are explored and tested, but they seem not to be significant. Keywords: technological capabilities, marketing capabilities, RBV, innovation, Latin America, coffee

1. Introduction The Resource‐Based View of the Firm (RBV) suggests that differences in business performances among firms could be explained by the heterogeneity of the resources that each company owns or controls (Barney, 1991; Wernerfelt, 1984). According to RBV, firm’s resources could represent a sustainable competitive advantage if they are valuable, rare and hard to be imitated or substituted (Barney, 1991; Dierickx and Cool, 1989; Hoopes et al., 2003; Prahalad and Hamel, 1990; Teece, Pisano and Shuen, 1997). Firm capabilities are a definition derived from the RBV theory. Afuah (2003) defines firm capabilities as the conjunction of assets and competences that generate value for customers. In other words, capabilities are the efficiency in which firms transform inputs in outputs (Dutta et al. 2005). In the literature, arguably there are two main types of firm capabilities: technological capabilities (Lall, 1995) and marketing capabilities (Vorhies and Morgan, 2005). The literature proposes the existence of synergies or complementary effects between different kinds of firm capabilities (Amit and Schoemaker, 1993). These complementary effects have been theoretically explored in the case of technological and marketing capabilities (e.g. Song et al., 2005; Prasnikar et al., 2008; Eng and Okten, 2011). Nonetheless, most of the previous quantitative research linking capabilities with business performance considers only one type of firm capabilities at a time (Prasnikar, et al., 2008). They consider either technological capabilities or marketing capabilities; but few of them consider both firm capabilities acting together. Therefore, the quantitative evaluation of the potential complementary effects between firm capabilities may be an interesting area for further exploration, and this is one of the purposes of this research. Previous studies also suggests a positive impact of firm capabilities on business performance (e.g. Isobe et al., 2008; Eng and Spickett‐Jones 2009; Merrilees et al., 2010; Nah et al. 2010), and specifically on innovation performance (Cohen and Levinthal, 1990; Zhou and Wu, 2010). However, most of the previous studies test the impacts of firm capabilities on financial performance or general performance. Consequently, the potential effects of technological capabilities on innovation performance may need further empirical research, especially in their extension to agricultural activities in Latin America. This study attempts to make a contribution to the research stream dealing with the relevance of firm capabilities for innovation performance. Its general purpose is to build on previous quantitative studies extending the innovation performance evaluations in the case of a mature low‐tech industry located in Latin American countries, specifically the agricultural coffee sector in Costa Rica and Guatemala. The specific research questions of this study are: What is the relationship between Innovation performance and Technological capabilities in the case of a mature low‐tech industry (agricultural coffee production) in Latin America? Given their differences at the national level, is this relationship stronger in the case of Costa Rica´s coffee growers in comparison to Guatemala´s?

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Luis Figueroa Does marketing capabilities have a moderating effect or any other influence on this relationship between Innovation performance and Technological capabilities?

2. The coffee sector in Latin America Coffee is produced in more than 50 countries and is particularly important for Latin America. In this region, coffee production represents a 58% of the world’s total, whilst Asia and Africa accounts 30% and 12%, respectively (FAO, 2011). Coffee is the second‐largest traded commodity in the world and the leading coffee exporting countries are Brazil, Vietnam, Colombia and Indonesia. The largest coffee markets in the world are European Union (66%), United States of America (22%) and Japan (7%) (ICO, 2011). The international prices for agricultural commodities, such as coffee, are particularly volatile. Supply shocks, in particular from large producers such as Brazil and Vietnam, could create huge price variations. After passing through a recent profound low‐price crisis, the global coffee industry is experiencing a better situation (ICO, 2011). Nonetheless, another coffee crisis is always a possible scenario and, precisely for that reason, to innovate for the development and commercialization of better or more differentiated products may be particularly crucial for the success, or even the survival, of these farmers (Gonzalez, 1998; Castro et al., 2004, Damiani, 2004). Indeed, in times of low prices, the premiums obtained by producing and selling more sophisticated products, such as certified coffees or specialty coffees, could be the difference between profits and losses at the farm level. This is the main reason why the coffee sector has been selected for this study about innovation. However, the rationale to study innovation in the Latin American coffee sector also includes other considerations. Firstly, there is a relative scarcity of previous studies about firm’s innovation performance in Latin American countries, and this situation is even scarcer for agricultural activities such as coffee. Secondly, the Latin American coffee sector is focused on selling their products in developed countries, where customers are particularly demanding and where innovation could be much more appreciated (ICO, 2011; ITC, 2011). Thirdly, coffee may have a huge potential for the implementation of business initiatives related to product and process innovation, as most of the coffee is traditionally exported as a low value‐added commodity (Gonzalez, 1998, Damiani, 2004). Lastly, the coffee business is still an important economic activity in many Latin American countries (ICAFE, 2009; SIB, 2011); therefore, a better understanding of the innovation phenomena in this sector could help to design policies that may improve the social and economic situation of many people in this region. This research focuses in two important Latin American coffee‐exporting countries: Costa Rica and Guatemala. The general differences between these two countries are significant, not only in regards of social, educational and economic development, but also in relation to the legal and institutional framework that rules the coffee activity in each country. On the one hand, Costa Rica enforces a strict regulation on its coffee sector by law (Castro et al., 2004). This regulation forces a clear separation of functions inside the value chain, under a scheme of profit sharing and social solidarity (Asamblea Legislativa, 1961). In fact, in Costa Rica, the international commercialization of this product is almost exclusively performed by other trade‐specialized companies and not by the farms themselves. As a consequence, the coffee growers in this country may not require of a high level of marketing skills in order to export their products efficiently. On the other hand, in Guatemala, the coffee farms have a higher degree of freedom for doing business. The Guatemala’s legislation could allow a certain degree of public interventions in the coffee sector, however that rarely happens. Due to the differences between these two countries, a comparative analysis is proposed in this research.

3. Conceptual framework The conceptual framework of this research builds on the previous studies that link Innovation performance and Technological capabilities. It also takes in consideration the potential additional effects of marketing capabilities in this relationship, and finally tries to test them quantitatively. Technological capabilities and innovation performance Lall (1995) defines technological capabilities as “the information and skills – technical, organisational and institutional – that allow productive enterprises to utilise equipment and information efficiently” (p. 261). Other more recent conceptualizations define technological capabilities as the firm’s effectiveness for creating,

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Luis Figueroa adapting or assimilating new technologies with the purpose to create new and more valuable products, services and processes (Wu et al., 2008; Krasnikov and Jayachandran, 2008). Lall (1992) classifies technological capabilities in three categories: a) investment capabilities, b) production capabilities, and c) linkage capabilities. According to him, investment capabilities are the skills needed before the implementation of a new technology: selection, evaluation, preparation, design, acquisition and staff training. Production capabilities are abilities related to the production process, their maintenance, adaptations and improvements, as well as their management and control. Finally, Lall explains that linkage capabilities are associated with the interrelations with other people and organizations, including companies, private consultants, and research institutions, among others. As stated before, previous studies suggest a positive impact of firm capabilities on innovation performance (Cohen and Levinthal, 1990; Zhou and Wu, 2010). Nevertheless, this assertion may need further empirical testing at least in the case of agricultural activities located in Latin American countries. Marketing capabilities and their potential moderating effect Another point to be tested in this research is the moderating effect of marketing capabilities on technological capabilities and innovation (Amit and Schoemaker, 1993; Teece, 1986). Although technological capabilities may be important for innovation, Teece (1986) suggests that companies may require more than their technological capabilities in order to achieve innovation results. According to him, a company may need also the support of other related capabilities, or “complementary assets”, in order to take advantage of its technological capabilities in the markets (Teece, 1986; Afuah, 2003). One of the key complementary assets identified by Teece is marketing capabilities. Nath (et al., 2010) describes marketing capabilities as “the integrative process, in which a firm uses its tangible and intangible resources to understand complex consumer specific needs, achieve product differentiation relative to competition, and achieve superior brand equity” (p. 319). The literature shows eight categories of marketing capabilities (Vorhies and Morgan, 2005): a) pricing; b) product development; c) channel management; d) marketing communication; e) selling; f) market information management; g) marketing planning and h) marketing implementation. Eng and Spicket‐Jones (2009) suggest an additional category: the use of IT technologies. Indeed, the use of Internet technology may be a useful tool for the successful commercialization of agricultural products, such as coffee, in the international markets. This research quantitatively tests the relationship between innovation performance and technological capabilities, applied to an agricultural activity located in Latin America. Moreover, the potential moderating effect of marketing capabilities on this relationship between innovation performance and technological capabilities is explored. A positive impact of technological capabilities on innovation performance is expected, as well as it may be possible a positive additional effect of marketing capabilities in this relationship.

4. Methodology Target population and unit of analysis The target population of this study is the coffee farms located in two important coffee‐exporting countries of Latin America: Costa Rica and Guatemala. The unit of analysis is the owners (or managers) of these coffee farms. Coffee producers of all sizes are considered; however, the majority of this population is composed by small farmers, i.e. farmers with a production area of 20 hectares or less. Accordingly, small farmers are predominant in the sample. Sample and data collection The sampling for this research relies on data sources identified in websites, databases and contact lists of business associations and other institutions related to the coffee sector in Costa Rica and Guatemala. The total population of coffee producers in Latin America is not known but this number may be in the order of the hundreds of thousands. The total number of coffee producers that could be identified through these data sources is 1,200.

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Luis Figueroa The data collection relies on a survey questionnaire deployed through two strategies. The first strategy is an Internet survey based on a specialized website for conducting online surveys (www.surveymonkey.com), although a very low response rate was expected. The second strategy is a field survey, applied either through personal interviews or in workshops offered by local support institutions. The sample is not a probabilistic one but a convenience sample, which is one of the limitations of this research. In the Internet survey, 46 responses were obtained: 9 from Costa Rica, 17 from Guatemala and 20 from other countries. A few responses were discarded because they were almost empty. The general response rate obtained for the Internet survey is close to 5%. Only the responses from Costa Rica and Guatemala are considered in this paper. In the field survey, 139 additional responses were collected: 86 from Costa Rica and 53 from Guatemala. Therefore, a total of 165 responses are included in this study, 95 (58%) from Costa Rica and 70 (42%) from Guatemala. Small producers (20 hectares or less) are the larger group in the sample, representing a 58% of the total. Also, most of the surveyed coffee producers (67%) have been working in this activity for more than 20 years. Measures The following are the measures proposed for this study, which are based on adaptations of previous scales found in the literature. Innovation performance In the literature, business performance is normally measured through accounting indicators, such as ROS, ROA and ROE (or ROI), and through market value indicators (Coombs and Bierly, 2006). However, these kinds of indicators may be of a doubtful applicability in Latin America, as many companies in this region are normally reluctant to share their financial information. This situation has been considered an important limitation in previous studies regarding business performance evaluations in other regions (Gruber et al., 2010). Davies and Ko (2006) propose the use of self‐reported qualitative scales instead of hard data as a solution for this limitation described by Gruber. Indeed, following a similar approach, Su, Tsang and Peng (2009) measure innovation performance evaluating the perceptions of managers through Likert scales in a self‐reported questionnaire. Following this approach found in the literature, the present study proposes the measurement of innovation performance through the use of self‐reported qualitative scales (5‐point Likert scales). The coffee producers included in the surveys are asked to compare themselves with other neighboring coffee growers in regards of their innovation performances and other variables. Four types of innovation performance are considered as sub‐indicators: a) Product innovation, b) Process innovation, c) Managerial/organizational innovation and d) Marketing innovation. Finally, a general indicator (index) for innovation performance is created by the simple average of the four sub‐indicators previously mentioned. Technological capabilities Technological capabilities is a broad and multi‐dimensional latent construct and it is not easy to quantify (Coombs and Bierly, 2006). The literature proposes to measure technological capabilities based on inputs proxies or outputs proxies. Input proxies include R&D expenditures both in absolute terms (US$) and in relative ones (% of sales). Output proxies consider the number of patents released and the citations, among others. Each of these proxies has their operational limitations, especially considering the business environment conditions in Latin America. In this region, R&D expenditures are rarely monitored or published by the companies themselves. Moreover, the use of patents in Latin America is not as common as it is in developed countries, probably due to a lack of confidence on the rule‐of‐law for intellectual property rights. Considering these limitations, a feasible alternative to measure technological capabilities may be the use of qualitative scales based on manager’s perceptions (e.g. Isobe et al., 2008 and Shan and Jolly, 2010). Indeed, Shan and Jolly (2010) implement this qualitative approach, using the three categories proposed by Lall (1992) in a multi‐item scale in their quantitative research about tech‐based companies in China. In the present research,

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Luis Figueroa Technological capabilities is measure as an index variable composed by three sub‐index multi‐item variables (self‐reported 5‐point Likert scales) in the three categories proposed by Lall (1992), following an adaptation of the multi‐item scale implemented by Shan and Jolly (2010) (see Table 1). Table 1: Technological capabilitiesindex and sub‐indexes Technological capabilities index Categories Sub‐index: Investment capabilities (6 items)

Sub‐index: Production capabilities (7 items)

Sub‐index: Linkage capabilities (6 items)

Items In‐house R&D Outsourced R&D Investment in tangible technology (machinery and equipment) Investment in intangible technology (patents, licenses, know‐how) Marketing of new or improved products Staff training in topics related to innovation Improvement and adaptation of production processes Improvement of product quality Design of changes in how the production is organized Imitation of technologies brought in by competitors Imitation of innovation in products developed by competitors Development of own technology (machinery, processes, etc.) Design of new products External relations with suppliers External relations with buyers External relations with competitors External relations with private consultants External relations with academic institutions External relations with public research organization

Source: Adaptation based on Lall (1992) and Shan and Jolly (2010, pp. 8‐9) Marketing capabilities Following Vorhies, Morgan and Autry (2009), a simplified scale to measure marketing capabilities is applied in this research. The simplified scale incorporates eleven 5‐point‐Likert‐scale items, adapted from the main categories suggested by Vorhies and Morgan (2005) and Eng and Spicket‐Jones (2009) (see Table 2). Table 2: Marketing capabilities Marketing capabilities Categories Marketing capabilities (11 items)

Items Price determination and administration New product development Channel management Marketing communication and promotions Public Relations Branding Selling Use of Internet in marketing activities Acquisition and implementation of market information Marketing planning and strategy Marketing implementation.

Source: Adaptation based on Vorhies and Morgan (2005, p .92), Eng and Spicket‐Jones (2009) and Vorhies, Morgan and Autry (2009) Models In the proposed models, innovation performance is considered as a dependent variable. Technological capabilities and Marketing capabilities are the main independent variables, but a selection of control variables is also included. A linear OLS regression is applied, as the normality test suggests that Innovation performance behaves like a normal variable. However, although a classification of dependent and independent variables is established, this study has no elements to test causality on these variables. Therefore, the results should be interpreted just as correlations and not necessarily as a cause‐effect relationship.

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Luis Figueroa Control variables The following dummy variables are selected as control variables:

Country of origin Costa Rica (dcr): it is 1 for producers from Costa Rica, it is 0 otherwise.

Small producers (dsmall): it is 1 for producers with 20 hectares or less, 0 otherwise.

Antiquity (dold): it is 1 for more than 20 years in the business, 0 otherwise.

Cooperative members (dcoop): it is 1 for members of coffee cooperatives, 0 otherwise.

Direct exports (dexport): it is 1 for direct exporters, 0 otherwise.

Brand (dbrand): it is 1 for producers with their own brand names, 0 otherwise.

Moderator (Moderating Variable) This research is testing a potential moderating effect of the variable Marketing capabilities in the relationship between Innovation performance and Technological capabilities. This is tested following the methodology proposed by Baron and Kenny (1986). Additionally, the potential influence of Marketing capabilities is also examined through the incorporation of a dummy variable (dmarkcap) that is 1 for coffee producers with a high level of Marketing capabilities (a value over 3 out of 5 in the standardized scale), and 0 otherwise. Validity and Reliability In this research, construct validity relies in the use of adaptations of scales and constructs used in previous studies. Moreover, face validity was tested, as all the constructs and items were checked with experts through personal and electronic interviews. In regards of reliability, Cronbach’s alpha results suggest a good internal consistency reliability in all the multi‐item constructs selected for this research, as all the Cronbach’s alphas are higher than 0.8 (Bryman, 2001).

5. Data analysis and results Using the transformed data set, an econometric data analysis is conducted with the assistance of specialized software: STATA IC 12. This section is referred to the results of this data analysis. Normality test for the Variables The results of the Skewness and Kurtosis test suggest that Innovation performance (index) could be considered as a normal variable and it could be included as a dependent variable in Linear OLS regression models. Common Method Variance An evaluation of Common Method Variance (Podsakoff et al, 2003) is performed following factor analysis, as the applied survey is a self‐reported instrument. When all the 63 Likert‐scale items of all the variables included in the survey are considered, the percentage of the variance explained only by the first factor is 33.33%, which may be regarded as an acceptable value. Regression results Linear OLS regression analysis is conducted to test potential impacts between Innovation performance (index) and Technological capabilities (Techcap). Moreover, six control variables are incorporated into the models as independent dummy variables (see Table 3). For all the models, the data suggests a high positive relationship between Innovation performance and Technological capabilities. However, the control variables seem not to be significant. Testing Moderation for Marketing Capabilities. Following the methodology suggested by Baron and Kenny (1986), the potential moderating effect of Marketing capabilities cannot be affirmed (see Model 9 in Table 4). Nonetheless, when a dummy variable for

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Luis Figueroa high levels of marketing capabilities (dmarkcap) is included (Model 10), the coefficient for this dummy variable is positive and significant. This may suggest that higher levels of Marketing capabilities increase the positive relationship between Innovation performance and Technological capabilities. Table 3: Linear regression (OLS robust): Innovation performance and technological capabilities Independent Variables Techcap .dcr .dsmall .dold .dcoop .dexport .dbrand constant N R‐sq adj. R‐sq

Model 1 0.686*** 1.346*** 142 0.257 0.252

Model 2 0.693*** 0.216 1.209** 142 0.270 0.260

Dependent variable: Innovation performance (index) Model Model Model 3 4 5 0.680*** 0.668*** 0.701*** ‐0.0684 ‐0.136 0.0578 1.404*** 1.500*** 1.259** 134 139 133 0.256 0.257 0.277 0.245 0.247 0.266

Model 6 0.691*** 0.0914 1.283*** 137 0.276 0.265

Model 7 0.672*** 0.247 1.352*** 135 0.285 0.274

*p<0.05, **p<0.01, ***p<0.001 Table 4: Testing moderation for marketing capabilities

Dependent variable: Innovation performance (index) Model Model Model 8 9 10 0.511* 0.209 0.523*** 0.216 ‐0.060 0.097 0.460* 1.192*** 2.008 1.577*** 136 136 136 0.305 0.3113 0.326 0.295 0.296 0.316

Independent Variables Techcap Markcap Markcap * Techcap .dmarkcap Constant N R‐sq adj. R‐sq

*p<0.05, **p<0.01, ***p<0.001 Regression diagnostics Regression diagnostics is performed considering normality of residuals, heterocedasticity and multicollinearity. No problems were detected.

6. Discussion The results suggest the existence of a strong positive relationship between innovation performance and technological capabilities in the case of the Latin American coffee farms considered in this study. In this relationship, the control variable for country of origin is non‐significant and this result is unexpected for the author. A difference in the relationship between innovation performance and technological capabilities among the coffee producers in Guatemala and Costa Rica had been suspected and expected, due to the better economic and social climate conditions that are predominant in Costa Rica and her rural areas. Moreover, the presence of a highly supportive legal and institutional framework in Costa Rica may require from these coffee producers a lower level of firm capabilities, in average, in order to achieve a particular level of innovation performance in comparison to their counterparts located in Guatemala. Nevertheless, the evaluations finds no statistical evidence of this expected difference between the coffee producers of these two countries in regards of their relationship between innovation performance and technological capabilities. Other examined control variables, such as being a small producer (20 hectares or less), having more than 20 years in the coffee activity, being a member of a coffee cooperative, being a direct exporter, or having their own brand name, seem not to be significant as well, when included in the proposed models.

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Luis Figueroa In reference to the potential moderating effect of Marketing capabilities in the relationship between Innovation performance and Technological capabilities, statistical evidence about this could not be found. However, the data shows that the positive relationship between Innovation performance and Technological capabilities turns stronger when the coffee producers also have a high level of marketing capabilities. This finding may suggest a complementary effect of Technological capabilities and Marketing capabilities in relation to their relationship with innovation performance, which could be considered as an empirical confirmation of the theoretical statements found in the Resource‐Based View (RBV) and firm capabilities literature but, in this case, applied to a much less explored situation of a mature low‐tech (agricultural) industry located in Latin America, specifically the coffee growers in Costa Rica and Guatemala.

7. Limitations It is a limitation that this research has no elements to test causal effects on the considered variables and only correlations are being evaluated. Also, as hard data related to business or innovation results is not available, a self‐reported scales obtained through a questionnaire is followed. However, the use of self‐reported subjective scales is suggested in the literature as a valid tool when hard data is not available (Davies and Ko, 2006; Isobe et al., 2008; Shan and Jolly, 2010; Su, Tsang and Peng, 2009). Another limitation is that a simplified scale for measuring marketing capabilities is applied, following Vorhies, Morgan and Autry (2009). Finally, this research is not using a probabilistic (random) sample, but a convenience sample, which is probably its most important limitation.

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Intellectual Capital Between Innovation and Innovative Adaptation‐ Opportunities to Obtain Performance Nicoleta Valentina Florea and Mihaela Badea Faculty of Economic Sciences, Valahia University of Targoviste, Romania floreanicol@yahoo.com, mihaela.badea@gmail.com Abstract: Organizations have realized that intellectual capital (IC) became the main aspect of business administration. The secret of success it is not only reside in technologies but also in ensuring that the team consists of people who give all the best to succeed. People are an essential characteristic of the effective organizations. To obtain efficient

products and services, technological innovation is needed and this can be achieved only through the efforts and enthusiasm of IC. Organization's success lies in attracting the best and better trained people. Innovation makes the world go round. Our lifestyles are the result of other people’s efforts to improve the human condition. They mixed ideas and inventions together. They work hard to create the must‐have and often taken‐for granted staff that surrounds us. The main purpose of the paperwork is to show the strategic role of IC in obtaining innovation, and/or innovative adaptation through commitment, motivation, trust and sustainable development. No organization can invent all the time, and from this perspective, it is recognized the IC limitation. Only studying the best practices, operating tactics and winning strategies of other organizations and individuals, organizations will achieve progress and improvements. Innovative adaptation means that people and organizations have looked into their external environment to find solutions. The smart organizations will keep innovating and the smart people know the difference between success and failure. We are beginning to understand how to increase our ability to improve together. We are learning how to move from individual invention to group innovation. Keywords: intellectual capital, innovation, innovative adaptation, benchmarking, performance

1. Introduction In the XXI century IC is the major source which gain competitive advantage and may be an important determinant in obtaining long‐term performance. Organizations have realized that their success depends on their ability to attract, develop and retain talented staff. Today, human beings are recognized as the central most precious business resource (Reed, 2001). The IC area is one of the most sensitive and delicate areas in any organization because it is the place where generally of the sensitive pieces of information are deposited and kept (Moore, 2008). All good ideas recognize opportunities and meet needs (McKeown., 2008). The only way that profit can be maintained is through innovation and the only way organizations can be innovative is through their creative people. Thus, what all organizations are desperately seeking is creativity. Maintaining innovative staff requires innovation in human resources management (HRM). Technological innovation requires well‐trained, motivated, experienced and dedicated manpower, because only human resource can innovate. In this regard, effective HRM is indispensable for organizational effectiveness and competitiveness. Organizational competitiveness and survival depends on the ways in which it draws on the past experiences, current culture and social norms to make its IC to be innovative. Creativity is the ability to produce unusual, uncommon, novel and quality ideas and products within an environment (Dauda, 2009).

2. About innovation and intellectual capital People invent solutions because they cannot always find a product which can satisfy their needs. The greater need the grater the incentive to invent (McKeown, 2008). All innovations are new, but they vary in their degree of newness (McKeown, 2008):

Incremental innovation involves small steps, minor improvements,

Radical innovations take big steps, creating major improvements,

Revolutions happen when groups of these innovations can together cause a huge impact.

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Nicoleta Valentina Florea and Mihaela Badea Technological innovation is regarded as changes in technology that significantly improves the performance, product enhancement, process improvement and delivery system, which goes beyond the existing state of art in technology, to produce viable products and services. These could only be possible through active participation of its HR. Technology occupies a critical position in the development of organizations and nations in the global economy, the absence of which makes organizational competitiveness and national progress difficult (Dauda, 2009). Researchers recommend that HR should be developed and be motivated to enable them to marshal and use their intelligence, knowledge and creative potential for technology innovation at all levels of organizations. The business formula of the future is: Over‐supply + commoditization= innovation (Reed, 2001). The only long‐term defense against the erosion of margins is to impress consumers with innovative products and services. To be successful in the modern economy, organizations must offer something new or different. Competition drives innovation in this age of changing needs consumer. In this era to reach its objectives, organizations must accept the change. HRM is intrinsically linked to the success of every business venture. They manage and support innovation within their own organizations, and it should be practices and policies within every HR department to encourage and react to innovation from all members of the organization. HR professionals can lead innovative practice, as well as respond to innovation from other sources. By pioneering creative strategies in attracting, recruiting, training and retaining key workers, innovative HR department can make a massive and measurable difference to the success of organizations. “Human resource is no longer about trying to smooth the ride for others; it is about navigating business into uncharted waters” (Reed, 2001). Many organizations recognize that people are the core of their successful activities: ‐“Abbey National is nothing without its people”‐Abbey National, ‐“We recognize that it is our people that make things happen”‐ BAE Systems, ‐“Everything we do rely on people”‐ BP Amoco, ‐“People are the key to the success of the business”‐ British Airways, ‐“We have continued to invest in our most important resource of all‐ our people”‐ Dixons, ‐“The difference between successful and less successful organizations ultimately lies in the quality of their staff”‐ HSBC. Managers are often under great pressure to improve the performance of their organizations. To improve performance, they need to constantly evaluate operations or process related of producing goods, providing services, and marketing and selling products. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a mean to improve performance and increase productivity, and are valuable when no objective or engineered standard is available to define efficient and effective performance. For this reason, benchmarking is often used in managing service operations, because service standards (benchmarks) are more difficult to define than manufacturing standards (Zhu, 2009).

3. Ways to obtain or improve innovation Strategic human capital management must be the centerpiece of any serious change in management strategy (Sistare, 2009). New technologies and workforce productivity are the critical drivers of the new global economy. Organizational transformations were linked, essentially to the HR creativity and innovation. The survival of any organization and nation depend on the extent it can develop in timely ways new technology for improved performance (Dauda, 2009).

Using team‐work to obtain innovation

Technology innovation needs to be supported by the work systems and organizational structure. In the recent years, teams and interpersonal relationship are becoming more and more important HR factors for organizational effectiveness of technological innovations.

There are three areas of new developments which need more empirical research and applications:

the globally distributed engineering and international technology entrepreneurship,

the IT innovation and e‐HR developmental approaches,

the professional services, and CRM modeling (Wang, 2005).

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Nicoleta Valentina Florea and Mihaela Badea Using strategic alliances to obtain innovation The globalization, the sophisticated needs of the customers, the innovation, the competition and the automatization have grown the complexity of world work. The complex work needs more knowledge and performant systems. Competitive advantage increasingly depends not only on a company’s internal capabilities, but also on the types of alliances and the scope of its relationships with other companies (Glaister, 2004). Inter‐firm collaborative activity, has a profound effect on the practicing managers. The strategic alliances are considered an aranjament of cooperation between two or more organizations where the partners want obtaining products, abilities, technologies and knowledge. Strategic alliances denote any medium to long term cooperative relationship between firms, whether based on an equity joint venture company that principals create or an contractual relationship entailing frequent interactions between the allied corporations (Contractor and Lorange, 2002). The knowledge transfer between organizations is difficult and the transfer of knowledge depends on the absorption capacity of knowledge and the cultural dimensions of the organizations (Cannavale and Canestrino, 2008). Strategic alliances, in their many forms, have become increasingly important over the past several decades. The greatest change, in the way business is being conducted, is the accelerating growth of relationships based not on ownership but on partnership (Inkpen, 2002). Strategic alliences, collaboration, joint ventures and other form of partnerships (as it is shown in Figure 1) have become more of a rule than an exception in modern industrial world (Contractor and Lorange, 2002).

One time very short arms‐length contracts

„Relational” contract (turn key, training)

alliances Medium term Medium to contractual long term relationship supply chain (licensing) relationship

Equity joint venture

Complete merger or acquisition or green‐ field subsidiary

Figure 1: A spectrum of cooperative arrangemets‐ adaptation after contractor and Lorange, 2002 . Alliances provide an ideal platform for learning. Two or more organizations are brought together because of their different skills, knowledge, and strategic complementarity. Alliances may generate knowledge, aptitudes and competencies, may acquire skills from its partner and can be the base for mutual value creation. Learning process is an important motive to create an alliance, that is why some alliances are classified as learning alliances (Inkpen, 2002). Using Knowledge Matrix to obtain innovation An organization might need tools, such as Knowledge Matrix to achieve competitiveness and to ensure success. Knowledge Matrix (Malhotra, 2001) contains:

Change management ‐ re‐engineering, outsourcing,

Development ‐ intranet, international information systems,

Relationship Management ‐ partnerships and strategic alliances, management software suppliers and customers,

Strategies ‐ strategic initiatives, developing a coherent vision of the business,

Policy modelling ‐ change the organization.

Without such a rigorous matrix, organizational change can seriously affect the organization and expansion of key skills. Using Knowledge Matrix is done in three steps:

Step 1 ‐ identifying partners;

Step 2 ‐ description of existing resources ‐ determine skills, intangible resources of each partner and the information held by them;

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Nicoleta Valentina Florea and Mihaela Badea

Step 3 ‐ granting the degree of importance of each resource defined ‐ in every cell of the matrix is defined resources strategically ‐ critical to the future success of the organization, critical to the organization's current business (support), critical to improve business and management (with possible strategic importance).

Important strategic HR planning is mapping the human capital of the organization: strategic value of employee skills, their uniqueness, diversity of knowledge and skills held and the split into different categories, such as: employees with unique knowledge base, employees with contracts work or associate (Bohlander G., S. Snell, 2010, p.98). Organizations have built an HR strategy to retain and develop employee skills to achieve organizational success. Organizations will seek to use this knowledge and skills in the creation of goods that can not be easily imitated competition. Probst et al. (2000), states that central dimension of competitiveness is the efficient transfer of knowledge organization. Solutions to implement KM in organizations:

Create a database record of knowledge, like "yellow pages" and a mapping of existing knowledge;

Establishing best practices for the creation and development of knowledge: seminars: manuals, databases, lists, best practices, training seminars: strategic planning, negotiations, strategic alliances, operational contracts, web‐sites and workshops; databases, reports, EDI, presentations and benchmarking analysis type, ITC e‐mail, newsletters, chatrooms, audio and video conferencing, specialized working groups, mailboxes, portals, intranets and the Internet.;

Job creation in organizations of the "chief officer ‐ chief knowledge officer".

Mapping knowledge ‐ use this technique helps the organization to build graphs, generate statements and statistics to design a complex website such knowledge,

Researched organizations should implement an array of knowledge to easily identify which HR will need at some point to internal recruitment.

Using HR data to track innovation Data on professionals’ skills, work, relationships, and productivity is an alternate or complementary source of information on industrial innovation. This is not merely because considerable data exist, but because technological advance depends on HR. In economic terms, technology is embodied in human as well physical capital, and the interaction of scientists, engineers, and technicians is a principal means of technology diffusion. Categories of data that might have a bearing on innovation and on which survey data are or could be collected (Merril and McGeary, 2002):

Training (educational qualifications, continuing education),

Employment and mobility (changing sectors, geagraphic movement),

Structure of work and affiliations (allocation of time among functions, participation in projects, coauthorship of scientific paper, other participations),

Output/productivity (patents applied, publications, citations, salaries and other income, fees).

Improving individual performance, automatically the organization will obtain performance (Becker, Huselid and Ulrich, 2001).

4. Definitions of benchmarking process Managers and employees are meeting with different challenges, such as the management of change, innovation, creativity, organizational learning, the speed or the reduction of production cycle, reengineering, and to satisfy rapidly the customers’ needs. To face these challenges the organization must low the costs, grow the profit, and to fulfill all the activities on term, must not remain isolated, it must study the good practices of organizations which learned to obtain performance even in critical situations (Bogan and English from Craig, 1996). When the organizations cannot innovate, Benchmarking is a way to obtain new ideas and evaluate the implementation of changes that may appear. Del M., CEO Dell Computer, say that “ideas are very useful, but

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Nicoleta Valentina Florea and Mihaela Badea very hard to put them on practice”. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a mean to improve performance, innovation and increase productivity (Zhu, 2009). There are many definitions of benchmarking concept, all trying to show its essence:

Benchmarking is an important tool in the search of success for organizations (Bramham, 2003);

Benchmarking facilitates the search of good practices, the innovative ideas and the efficient procedures necessary in obtaining performance (Craig, 1996);

Benchmarking is a learning tool, where imitating successful organizations, or avoiding the actions of unsuccessful ones, can enhance the capacity for and speed of learning (Jack, 2009);

Benchmarking is an important process used to discover and incorporate best practices into organization operations (Damelio, 1995);

Benchmarking is the process of comparing and measuring your organization against others, anywhere in the world, to gain information on philosophies, practices, and measures that will help organization take action to improve its performance (Coers et al, 2002);

Benchmarking is a continuing search for, and implementing of, performance improvement. It requires considerable effort, motivation, and good management to be effective but it does offer considerable payback (Scholes and Johnson, 2001);

Benchmarking is an evolutionary process; the organization may start with internal partners and see improvements, then can be extended to better‐practice partners (Wireman, 2004);

Benchmarking management process that develop during the twentieth century (Watson, 2007);

Benchmarking is a method of measuring and improving the organizational performance comparing with best organizations (Stapenhurst, 2009);

Benchmarking, like in sport, is based on the effort of the others, on enthusiasm, experience, innovation, creation and knowledge (McCabe, 2001);

Benchmarking involve making those steps, constantly, to get into the top (Harper, 1996). Benchmarking is a barometer of the state the organizations are going through and the effects of these processes on their performance.

Benchmarking, as any activity, appeared from necessity (Saul, 2006). The concept of benchmarking and the concept of competitiveness are related;

Benchmarking became a significant tool used in improving results (Kozak, 2004);

Benchmarking is a managerial tool, probably the most effective in the last few years, which help organizations to perform daily operations, in such way being the best operations (McCabe, 2001);

Benchmarking can help an organization stimulate innovation, increase impact, decrease costs, inspire staff, impress funders, engage boards and focus the mission (Saul, 2006).

Note that all these definitions share the same concepts:

continuity‐ benchmarking is a constant, never‐ending cycle of looking for new and better ways of doing things;

process‐ benchmarking is seeking to improve;

learning‐ benchmarking is a learning process, which studying other ways of doing things;

measuring‐ benchmarking requires comparison.

5. Innovative adaptation‐ using benchmarking analysis No organization can invent all the time, therefore, it is important to take into account the experiences of others. Organizations operating alone are doomed to "reinvention”. The innovations of others can be adapted to the circumstances of other business, and new innovations uncovered (Jack, 2009). Learning is a process which can involve experience, practice or insight and can occur through observing the actions of others and their consequences, providing the knowledge can be transferred to a different situation. Innovative adaptation

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Nicoleta Valentina Florea and Mihaela Badea has a very old history, the people studied the environment and than adapted it to their needs and the different situation. As a method we use in the paperwork the benchmarking study, because it can determine the way to access new ideas and evaluate the implementation of changes that may occur. So benchmarking is a learning tool, where imitating successful organizations, or avoiding the actions of unsuccessful ones, can enhance the capacity for and speed of learning. Benchmarking purpose is:

to help organizations identify what they need to change to improve their performance;

to provide a model or principles, to guide the implementation of practices and bridge the gap between goals and aspirations (Jack, 2009).

M. Dell, CEO Dell Computer, said that "ideas are very helpful, but hard to put into practice." Benchmarking involves those steps taken to reach the top constantly. "The second person who light the fire is actually the first who applied benchmarking”‐ Fred Bowers, Benchmarking CEO Digital Equipment Corporation. The managers and the employees are meeting with various challenges, such as change management, innovation, creativity, organizational learning, speed or reduction the production cycle, reengineering and to meet customer needs they must reduce costs, increase revenues, to accomplish all tasks on time. To achieve these objectives they must not remain isolated, they must study the best practices of the organizations, which have learned to get high performance even in critical situations. Benchmarking and competitiveness are closely related concepts. Benchmarking has become an important tool used to improve results (Kozak, 2004). As we can see, the reasons to use benchmarking are many (Figure 2), thus people must adapt best practices to help an organization to avoid being taken by surprise by changes. % answer Bladrige criteria educate professionals respond to management information needs understand strategies

set performance goals identify design options identifying gaps 0

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Figure 2: Reasons to use benchmarking‐ adaptation after Coers et al., 2002 So, benchmarking is a pragmatic approach that managing change and helps improve performance. As a conclusion, we may say learning by borrowing from the best and the adoption of these techniques to meet their own needs is the essence of benchmarking. Today's practice, being dynamic and progressive, will inevitably lead to achieve best practices, to innovation in the future; this analysis, called "evergreen" process, will lead the organization to renewal and performance. The major innovations in any sector come from outside the industry, yet many organizations have continued to look internally or within their industry for clues to achieve or maintain competitive edge. The need to develop an external perspective is crucial and benchmarking is the most powerful weapon in the strategic armor (Codling S., 1995). The spread of benchmarking throughout manufacturing, commerce and services is accelerating. In a complex, dynamic, fast‐changing environment organizations must strive for superiority in their core activities in order to survive. Competitive edge cannot be achieved or maintained by setting goals based on past, or even present, performance. Benchmarking is itself a process, which helps identify, compare with and emulate best practice wherever it occurs. The organizations must apply benchmarking to stay on the market (Kozak, 2004). Benchmarking is now internationally recognized, as a tool of quality improving.

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Nicoleta Valentina Florea and Mihaela Badea Benchmarking is rooted from the word "benchmark" ‐ the reference value and serves as reference point in determining the current position of an organization through surveys and observations. Benchmarking consists of two parts (Kozak, 2004), called:

"benchmarker" ‐ represents the organization which make the procedure, and

benchmarkee "‐ refers to the comparison organizations.

Beginning with 1970 the concept has evolved passing beyond the technical term, representing a term for business, which signify the process measurement to conduct activities through comparison. Any analysis of benchmarking consists in the following activities: planning and data collection‐ the study in domain shows that 50% of time is for planning phase, 30% to elaborate the study and 20% to analysis (Andersen, 1996). search for benchmarking partners and data entry‐ after finding the best in class it is formed the team and the members should participate to measure the team performance to ensure that the team is motivated enough. When the team is formed, this is starting to find the best‐in‐class partners and data entry starts. observing the best practices and evaluation report‐ understanding the processes and the partner practices; to understand the own processes it is necessary to create an evaluation report, necessary for the observation of the partner’s processes. finding the performance gaps‐ identification of performance gaps between the organization and its partners to obtain improvements. Gap analysis is often used as a fundamental method in performance evaluation and benchmarking (Zhu, 2009). As a result, some multifactor based gap analysis methods have been developed, such as spider charts, AHP maturity index, and Z charts. A gap analysis involves taking a look at how things are and comparing them to how you want them to be (Joint Report, no.585, 2007). adaptation and improvement plan‐ choosing the best practices and their adaptation to the organization in order to obtain improvement performance. Practically any activity can be analyzed with the benchmarking process. The success is not only resides in technologies but in assuring an efficient team, which is composed of people who give all the best to succeed. Human resources own the role to benchmark, because this process needs “champions” to put it into practice. The HR specialists have a greater opportunity then other departments test and consult the employees and to propose changes. Though, these resources become leaders for the future changes (Bramham J., 2003). People are that essential feature of performance organizations. In obtaining success and organizational performance are involved the three “P” (Hotten (1998) from McCabe, 2001): products, processes and personnel. He also believes that in obtaining success they are needed the skills of managerial team in obtaining the resources necessary for each “P”. Putting benchmarking into practice supposes:

preparing the list of activities that add value to customers and organization;

dividing the activities after their performance, though:

the biggest performance (maximum score= 5);

average performance (score between 2‐ 4);

lower performance (minimum score=1).

When the partners are found and are willing to benchmark, a questionnaire should be developed, based on the analysis conducted earlier. The questionnaire is sent to the partners, and site visits are conducted (Wireman, 2004). The information gathered in this process (Table 1) are compiled, and putted into an analysis with recommendations for changes, to improve the benchmarked process. Once the changes are implemented and improvements noted, the process starts over again. When one process is improved, it often generates

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Nicoleta Valentina Florea and Mihaela Badea improvements to other processes and the next process chosen for benchmarking may not still need improvement. Table 1: Benchmarking in practice. Gathering general information Activities

Add value

Worst or best 3

Source‐ adaptation after Bramham, 2003. Traps of benchmarking When benchmarking is used properly, it can improve its processes, and when is used improperly it can devastate an organization’s competitive position. Some of the improper uses of benchmarking include (Wireman, 2004): Using benchmarking data as a performance goal‐ when organizations benchmark their core competencies, they can easily fall into the trap of thinking a benchmark should be a performance indicator. Premature benchmarking‐ when an organization attempts to benchmark before the organization is ready, it may not have the data to compare with its partners. Copycat benchmarking‐ imitation benchmarking occurs when an organization visits its partners and, rather than learning how the partners changed their business, concentrates on how to copy the partners’ current activities. Unethical benchmarking‐ sometimes an organization will agree to benchmark with a competitor and then try to uncover proprietary information while on the site visit or by use of the questionnaire. This behavior will lead to problems between the organizations and will ruin any chance of conducting a successful benchmarking exercise at a later date. Another unethical benchmarking is about using the benchmarking partners’ names or data in public without receiving prior permission.

6. Conclusions “If you cannot measure something, you cannot understand it; If you cannot understand it, you cannot control it; If you cannot control it, you cannot improve it”‐ H.I.Harrington The survival of any organization and nation depend on the extent it can develop in timely ways new technology for improved performance. This could be achieved, sustained and maintained through the creation of supportive and cooperative environment, which motivates employees to energize themselves, and also enable them to set goals and performance targets. Such environment also provides possible behavior reinforcement, constructive feedback, and meaningful career development opportunities for employees. Single innovation may not bring tangible results but complex technology‐driven organizations combined innovative ideas of their skilled employees together to obtain performance. When organizations cannot innovate they could try innovative adaptation – Benchmarking‐ to solve problems, to achieve objectives, to improve processes, to innovate and to create strategies. Benchmarking is a process of measuring its own performance with the best organization and using this analysis to improve and compete with that. Benchmarking is a search process of the best practices to obtain higher performance in its adaptation and implementation in its own organization. The main goal is to identify the best operational practices and to obtain performance. If an organization improves a certain process, then it will improve its activities and will obtain performance – it will grow the productivity, the sales and it will obtain lower costs. That is why the managers, who look to obtain performance, will use the Benchmarking process.

References Andersen, B. (1996) The benchmarking handbook: step‐by‐step instructions, Per‐Gaute Petterson, Chapman &Hall, London, UK.

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Nicoleta Valentina Florea and Mihaela Badea Becker, B.E., Huselid, M.A. and Ulrich D. (2001) The human resources scorecard: linking people, strategy, and performance, Harvard Business School Press, USA. Bogan, C. (1994) Benchmarking best practices, McGraw Hill, UK. Bogan, C.E. and English, M.J. (1996) Benchmarking for best practices, from Craig R.L., The ASTD training and development handbook: a guide to human resource, McGraw Hill Co., Inc.. Bohlander, G. and Snell, S. (2010) Managing HR, 15th edition, Cengage Learning, Canada. Bramham, J. (2003), Benchmarking for people managers; a competency approach, CIPD House, Camp Road, London. Cannavale, C. and Canestrino, R. (2008) Entrepreneurship and knowledge transfer: a cross‐cultural perspective, Proceedings of the 5th European Conference on Knowledge Management. Codling, S. (1995) Best practice benchmarking, Industrial newsletters Ltd., Gower Pub.Ltd., Croft Road, England. Coers, M. et al. (2002) Benchmarking: a guide for your journey to best‐practice processes, American Productivity & Quality Center, 123 North Post Oak lane, USA. Contractor, F.J. and Lorange, P. (2002) Cooperative strategies and alliances, Int.Business &Management, Elsevier Science Ltd., UK. Craig, R.L. (1996) The ASTD training and development handbook: a guide to human resource, McGraw Hill Co., Inc.. Damelio, R. (1995) The basics of benchmarking, Productivity Press, USA. Dauda, Y. (2009) Labour, education and society. Managing technology innovation, Deutsche Nationalbibliothek, Frankfurt am Main, Germany. Glaister, K.W., Husan, R. and Buckley, P.J. (2004) Strategic business alliances: an examination of the core dimensions, Elgar E. Pub.Ltd., UK. Harper, K. (1996) Benchmarking: international clearinghouse plays matchmaker for companies that want to improve, Arkansas Business, vol.9. Hotten, J., from McCabe S. (2001) Benchmarking in construction, Blackwell Science, Oxford, J.Street, London. Inkpen, A.C. (2002) Learning, knowledge management, and strategic alliances, pp 267‐289, from Contractor F.J., Lorange P., Cooperative strategies and alliances, Int.Business &Management, Elsevier Science Ltd., UK. Jack, L. (2009) Benchmarking in food and farming: creating sustainable change, Gower Pub. Co., USA. Joint Report NCHRP (2007) Racial gender dibversity in state DOTs and transit agencies: a benchmark scoping, Report 585, Transportation Research Board of the National Academies. Kozak, M. (2004) Destination benchmarking: concepts, practices and operations, Cabi Pub., Wallingford, Oxon, UK; Malhotra, Y. (2001) Knowledge management and business model innovation, Idea Group Pub., USA. McCabe, S. (2001) Benchmarking in construction, Blackwell Science, Oxford, J. Street, London. McKeown, M. (2008) The truth about innovation, Pearson Edu.Ltd., UK. Merril, S.A. and McGeary M. (2002) Using HR data to track innovation, National Academy Press, Washington, USA. Moore, R. (2008) Benchmarking 100 success secrets, Springer Science, USA. Probst, G. et al. (2000) Knowing in firms‐understanding, managing and measuring knowledge, Knowledge as a strategic resource, Sage Pub., London. Reed, A. (2001) Innovation in human resources management: tooling up for the talent wars, CIPD House, Camp Road, London. Saul, J. (2006) Benchmarking for nonprofits. How to measure, manage, and improve performance, Fieldstone Alliance Pub. Center, Saint‐Paul, USA. Scholes, K. and Johnson, G. (2001) Exploring public sector strategy, Pearson Education Ltd., Edimburgh gate, England. Sistare, H.S. et al. (2009) Innovations in HRM, National Academy of Public Administration, USA. Stapenhurst, T. (2009) The benchmarking book: a how‐to‐guide the best practice for managers and practitioners, Butterworth‐Heinemann, Oxford, UK. Zhu, J. (2009) Quantitative models for performance evaluation and benchmarking, Springer Science, Worcester Polytechnic Institute, USA. Wang, Z. (2005) Organizational effectiveness through technology innovation and HRM strategies from International Journal of Manpower by Wang Z. and Chen J., volume 26, Number 6, pp. 481‐487. Watson, G.H. (2007) Strategic benchmarking reloaded with six sigma: improving your company’s performance using global best practices, J. Wiley & Sons Inc., USA. Wireman, T. (2004) Benchmarking best practices in maintenance management, Library of Congress, Industrial Press Inc., USA.

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SMEs’ Internationalisation Through Strategic Alliances: A Qualitative Study Mário Franco1, Heiko Haase2 and Sandra Figueiredo1 1 NECE‐Research Center in Business Sciences, Management and Economics Department, University of Beira Interior, Covilhã, Portugal 2 Center for Innovation and Entrepreneurship, Department of Business Administration, University of Applied Sciences Jena, Jena, Germany heiko.haase@fh‐jena.de mfranco@ubi.pt sandra.figueiredo@gmail.com Abstract: International strategic alliances are cooperative arrangements with cross‐border flows of resources and capabilities of the involved organisations. Such alliances offer both potential synergies and opportunities to better exploit local markets and to enter into foreign markets. In this way, strategic alliances between firms from different countries are considered to be an important part of firms’ internationalisation process. This is particularly relevant for small and medium‐sized enterprises (SMEs). In spite of the opportunities going along with international strategic alliances, there is only limited empirical evidence of their impact on the SME internationalisation process and vice‐versa. Over the last years, only a few studies have been made on cross‐border alliances established between SMEs. Consequently, the objective of our study is precisely to identify the reasons for the internationalisation of SMEs through strategic alliances and to understand how this internationalisation process evolves. For this purpose, we performed exploratory case studies of two SMEs in Portugal. We used primary sources of information, gathered through interviews using semi‐structured questionnaires. We also employed secondary sources through data taken from the firms’ web sites and the commercial register. Additionally, we applied data triangulation to check for reliability and validity, considering observations such as behaviour, attitudes and opinions of the interviewees. The organisation and interpretation of the data had the following sequence: (1) characterisation of the firms, (2) individual case analyses, and (3) cross case analysis. The SMEs subject to analysis have their principal business activities in traditional Portuguese cheese production and bottled water. We found that the countries for international activities have been chosen according to the connections the firms have, based on trust and reliability to decrease the possibility of failure. What the SMEs pursue in forming alliances is firstly reduced costs. Secondly, they prefer to learn safely and gain knowledge about the foreign markets and cultures, in order to develop more appropriate internationalisation strategies. Keywords: strategic alliances, small and medium‐sized enterprises, SMEs, internationalisation, Portugal

1. Introduction International strategic alliances are cooperative arrangements with cross‐border flows of resources and capabilities of the involved organisations (Miller et al., 2008). Such alliances offer both potential synergies and opportunities to better exploit local markets (Miller et al., 2008) and to enter into foreign markets (Suárez, 2002). In this way, strategic alliances between firms from different countries are considered to be an important part of firms’ internationalisation process. This is particularly relevant for small and medium‐sized enterprises (SMEs) (Sirmon and Lane, 2004). However, the specific characteristics of SMEs make international expansion more difficult than it is for their larger counterparts (Aldrich and Auster, 1986; Knight, 2001). Due to their ‘liability of smallness’ (Aldrich and Auster, 1986; Brüderl et al., 1992), firm size may be considered one of the biggest obstacles to SME internationalisation. This is because SMEs face severe constraints in gaining access to critical resources and capacities (Lang et al., 1997; Strandholm and Kumar, 2003; Hewitt‐Dundas, 2006). As a solution, Trigo et al. (2009) proposed that firms can acquire the necessary means to overcome this difficulty by forming alliances with others, allowing them to gain the resources and knowledge needed. Strategic alliances arose from the need to expand business and capture a greater market share of an increasingly sophisticated and internationally‐orientated customer base (Ohmae, 1985; ul‐Haq and Howcroft, 2007). Alliances facilitate entry into new markets allowing in particular SMEs to explore larger markets by being able to strengthen their market position and production in order to accompany new market demands.

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Mário Franco, Heiko Haase and Sandra Figueiredo In spite of the opportunities associated with international strategic alliances, there is only limited empirical evidence of their impact on the SME internationalisation process and vice‐versa (Leiblein and Reuer, 2004; Alvarez et al., 2006). Over the last years, only a few studies have been made on cross‐border alliances established between SMEs (e.g. Haase and Franco, 2011). Consequently, the objective of our study is precisely to identify the reasons for the internationalisation of SMEs through strategic alliances and to understand how such an internationalisation process evolves.

2. Literature review Spekman et al. (2000, p. 37) say that a strategic alliance “is a close, collaborative relationship between two, or more, firms with the intent of accomplishing mutually compatible goals that would be difficult for each to accomplish alone”. According to Suárez (2002), strategic alliances are used to enter other countries. Glaister and Buckley (1996) say that more than 50 per cent of strategic alliances are set up to pursue international expansion. Thus, strategic alliances are considered to be a very important part of firms’ internationalisation. It is difficult to determine and explain the beginning of this concept, but according to Arruda and Arruda (1998), international strategic alliances or partnerships became frequent in the 1990s. They are considered a complex topic as the conclusions reached by several authors sometimes diverge (e.g. Townsend, 2003; Ohmae, 1989). Their use as a strategic instrument has increased considerably over the last decades. Alliances between firms from different countries and different cultures offer both potential synergies and growth opportunities to exploit national markets (Glaister and Buckley, 1996; Miller et al., 2008). They also allow the firm to face the challenges of globalisation and technological development (Ohmae, 1989) and, in this way respond better to growing customer needs and the demands of a changing market environment (ul‐ Haq and Howcroft, 2007). The opportunity for SMEs lies in sharing costs, acquiring specific knowledge and achieving new capabilities (Sirmon and Lane, 2004). According to Haase and Franco (2011), establishing an international cooperative alliance may be the gateway to a whole network of complementary skills and resources, due to the positive influence of the knowledge gained from cooperation. In this way, it turns out that competitive advantage is replaced by collaborative advantage (Kanter, 1994). Arruda and Arruda (1998) acknowledge that firms can achieve organisational goals when working in markets abroad by establishing reliable relationships with foreign firms. In particular, for the process of SME internationalisation, Ellis (2000) and Harris and Wheeler (2005) consider alliances with foreign firms as influential, perhaps fundamental. However, cooperating with other firms from other countries is a serious commitment, and that is why this process must be properly planned and the allies carefully selected (O’Donoghue, 2005). The evolution of cooperation in strategic alliances is limited by the conditions when creating the alliance and influenced by the collaboration process that takes place subsequently (Doz, 1996). The most important phase when building a partnership is the beginning because the firm’s capacity to absorb knowledge from its alliance partners mostly depends on its delivery of relevant capabilities upon entering the alliance (Mowery et al., 1996). That is why knowing and gathering detailed information on the future partner as well as knowing what their objectives are is so important at the beginning of a strategic alliance.

3. Research methodology 3.1 Type of study and selection of cases This study adopts a qualitative approach as it intends to give answers to questions such as “how” and “why” (Yin, 2009) in order to better understand the internationalisation of Portuguese SMEs through strategic alliances. In this way, we decided on a case study approach. According to Godoy (1995), a case study is a type of research where the facts to be studied emerge from a real life context and in which the object is a unit to be analysed in depth. Given our research objective, we performed exploratory case studies on two SMEs in Portugal involved in internationalisation processes. The selection was therefore limited to firms with fewer than 250 employees (cf. European Commission, 2003/361/EC). The SMEs subject to analysis are located in inland, central Portugal. We selected them based on the criterion of having strategic alliances with other firms, whether Portuguese or not.

3.2 Data collection and analysis The unit of analysis was the firm as a whole. We used primary sources of information, gathered through interviews using semi‐structured questionnaires (Hjorth and Steyaert, 2004). Following the suggestion of

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Mário Franco, Heiko Haase and Sandra Figueiredo Holstein and Gubrium (1995), we designed an interview guide to engage thes respondent and establish the area of investigation. The interviews took place in August 2012 and lasted about an hour. Despite the possibility of recording each interview, this did not happen at the request of the interviewees, and notes were taken in order to collect all the information needed for completion of this study. Furthermore, we employed secondary sources through data taken from the firms’ web sites and the commercial register. Additionally, we applied data triangulation to check for reliability and validity, considering observations such as behaviour, attitudes and opinions of the interviewees. The organisation and interpretation of the data had the following sequence: (1) characterisation of the firms, (2) individual case analyses, and (3) cross case analysis.

4. Results and discussion 4.1 Characterisation of the firms Case 1 is a company based at the industrial estate in Fundão. It has operated since 1993 in the food sector, producing traditional Portuguese cheese. The company has about 40 employees and exports its products to countries such as the United States of America, Canada, France, Spain and Angola. Its exports represent about one third of its production. Case 2 is located in Castelo Novo, in the district of Fundão. The firm started its operations in the early 1990s in the bottled water business. After a decline in production, the company went out of business until 2011, when it was bought by a Portuguese group named Waterbunkers SGPS. It has 26 employees and is entering foreign markets such as China and USA. Table 1 shows the firms’ characteristics. Table 1: Characterisation of the cases Location Number of employees Market sector Time acting internationally Foreign markets

Case 1 Fundão industrial estate 40 Regional food (cheese) About 20 years USA, Canada, France, Spain, Angola

Case 2 Castelo Novo 26 Beverages (water) Just starting China, USA

4.2 Individual case analyses Case 1 Reasons for international strategic alliances Case 1 went international through exporting its products. According to the owner‐manager, this process started naturally and was somewhat unintended. However, from a practical point of view, according to the owner‐manager: “The creation of alliances allows our company to act in foreign countries, which is beneficial as it allows us to sell products internationally with fewer costs when compared to the option of opening an establishment in the importing country.” Alliances played a very important role in the internationalisation of this firm, and according to the interviewee: “By building alliances it was possible to learn new strategies and means to face the difficulties imposed by other countries, such as closing the cheeses in specialised vacuum recipients preventing them from releasing any odours or becoming contaminated. There was an opening for ideas for improvement suggested by partners and clients.” About this opportunity, the respondent mentions: “The use of alliances to obtain the intended goals has exceeded all expectations.” Internationalisation Process The firm’s alliances are with firms located in countries such as the USA, Canada, France, Spain and Angola. However, it began by casually building alliances with national firms that exported to other countries and some interest was shown in exporting some of its products. It was through this situation that the cheese produced by this firm began to be known internationally as it won first place in an international blind‐tasting contest in the USA. The firm has acquired a partner in the USA that exports products to several countries in the world. In Spain, through a visit of a member of the royal family to the fair in Trujillo, Case 1 began selling products in the

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Mário Franco, Heiko Haase and Sandra Figueiredo Spanish market. These and others were important steps towards the international acknowledgement of this firm. Additionally, the owner‐manager emphasises: “Our company participates in international fairs to let the brand and products be known worldwide.” Instead of locating in the destination country, Case 1 collaborates with other firms, confessing at the same time: “The idea just never came up but we do not ignore it as a possibility for the future.” The allied firms are responsible for providing the proper transport of the products, except for Spain due to its geographical closeness. Thanks to its partner firms abroad, Case 1 does not have the problem about which product would sell most as the partners selling its products are well placed in their home markets, with knowledge of how and what to sell. Nevertheless, a disadvantage of working internationally through alliances with other firms is: “There is no direct feedback that would allow us to have direct access to the opinion of our customers.” Regarding future markets, Case 1 intends to export to the Netherlands, Germany and Brazil. At the beginning, the firm considered there were not many difficulties in creating alliances and starting to act internationally. Nowadays, however, the difficulties are becoming more apparent, especially the legal paperwork hindering export activities. For instance, Brazil presented some major difficulties concerning customs arrangements. Case 2 Reasons for international strategic alliances The internationalisation of this SME is to combat the limited scale of the Portuguese market. According to the owner‐manager: ”Nowadays, there is also the fact that the national market is in recession due to lower consumption of the products. This implies that in 2011 the water market has shrunk by approximately 8%. So as not to restrain the growth of the company, internationalisation is the best measure not only relating to the economic situation of the market but also due to the image and perception that water has in Portugal.” Therefore, internationalisation comes as a way of developing water products from Portugal, fighting the above mentioned adverse factors by trying to introduce products into other markets that may need and value them. In this way, the interviewee stated: “Internationalisation allows the firm to become less and less dependent on the national market and its high distribution prices.” Some of the advantages of taking the national product into a foreign market are considered to be reducing the inherent risk of the national market with less dependence on it, more possibilities of commercialisation and obviously acknowledgement of the brand. However, some of the disadvantages may be less control over foreign markets and price fluctuation which will depend on transport costs. According to the owner‐manager: “Alliances are fundamental to the success of Portuguese firms, which may in this way reach other markets with innovative products at competitive prices and quality services.” Internationalisation process Case 2 intends to start acting internationally in three steps, as referred to by the owner‐manager: “One is the appearance in at least three international fairs and exhibitions; the other is by creating partnerships; and the third is by selling the products directly to foreign markets.” Acting together with other Portuguese firms is a means of reaching those markets more easily as it provides a wider range of products for customers and lowers the costs of foreign market penetration. Partner firms increase the power of negotiation by extending the diversity of products to internationalise as they have products already placed in international markets. To do so, it is necessary to study and frame the activity of the partner firms so that there are no misunderstandings. According to the owner‐manager:

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Mário Franco, Heiko Haase and Sandra Figueiredo “There is a contract to be signed between the partner firms regarding the rights and obligations of each company and the minimum goals intended to achieve.” In this regard, the respondents also added: “Most of the partnerships, in order to be maintained, depend most of all on positive results achieved by each partner but also on the empathy, trust and commitment formed.” The possibility to build an alliance with a company already located in the targeted market brings more knowledge of the market. There are always some difficulties, in particular concerning cultural barriers. The products to be introduced to foreign markets will be both premium branded and low priced, depending on the type of client to be targeted. Products will also be adapted to each market, with regard to the specific country’s laws and the best way for the product to be received and viewed. Nonetheless, it was also stated: “The initial difficulties when internationalising a product in a foreign market come from the fact that Portuguese firms do not have the habit of trying to enter other markets. There is still some reluctance to build partnerships.”

4.3 Cross case analysis Both cases chose the strategy of export to place their products in foreign markets. Although the firms had different motives leading to this choice, both conclude and agree that it was and still is the best method. It allowed them to place products in foreign markets at lower costs (Camisón and Villar, 2009), compensating the disadvantage of their size in a bigger market (Aldrich and Auster, 1986; Brüderl et al., 1992). The reasons that led Case 2 to internationalise are obvious and correspond to the findings of Hamel (1991) and Haase and Franco (2011). Both cases use direct export by means of a distributor located in the foreign country. Through this facilitator, the SMEs have more control over the market’s needs and specific marketing plan. However, Case 1 also uses indirect export, which means that products go through another company already placed in the foreign market. For Case 1, internationalisation was unplanned, beginning when a partner company contacted them about starting to sell their products outside Europe. It was also due to the product’s success at an international product contest. This was the starting point for initiating more alliances and increasing exports. For Case 2, internationalisation was an intended strategy in order to gain other markets and a way to guarantee sales outside the national economy being affected by crisis. Case 1 has been acting in foreign markets for about twenty years. However, just now it is trying to reach a broader set of international markets outside Europe, mainly through participating in international fairs in order to increase brand awareness. Case 2 is only beginning to internationalise the brand and products. However, in comparison to Case 1, Case 2 had a more reasoned and deliberated entry into the international market. This firm has not only built rational strategic lines, but also carried out studies to be able to respond to foreign customers’ needs and, in this way, determine in which markets they may be more successful. Both cases prefer to choose national firms to build alliances with. This may have to do with the fact communication is easier when cultural compatibility is high. It is also due to the fact that the allied firms were searching for other national products in order to answer their customers’ needs. Case 1 also cooperates with foreign firms. As for Case 2, the alliances are with national firms already acting in foreign markets. This provided the firm with the initial knowledge about the foreign markets in order to select certain countries to export to, better adapt its products and predict sales. With this information it was possible to save time and expenses, a frequently cited motive (ul‐Haq and Howcraft, 2007; Ohmae, 1985). In Case 1, the choice of markets was driven by the fact that Portuguese emigrants or descendants from similar cultures are located mostly in these countries, and in Case 2, the selection was made based on the need for and value of the product being commercialised. Hence, we deduce that Case 1 reaches national customers located in foreign countries, while Case 2 is trying to reach other people and cultures in foreign markets. Accidentally or on purpose, respectively, both cases chose to interact and build partnerships with national and foreign firms working in similar sectors such as traditional, regional food and beverages, and already connected to the import and export of products. This situation is due to the fact that each market sector has its own means and rules. Building alliances with firms that already have the means and knowledge of working across borders was evaluated as very helpful in the internationalisation process of the cases studied. According to the answers given, it is possible to conclude that both firms use strategic alliances to facilitate the export and commercialisation of their products and to avoid some of the risks this process implies. Neither firm has

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Mário Franco, Heiko Haase and Sandra Figueiredo considered expanding abroad by establishing a plant or store in the countries they are working with, mainly because of the costs involved in maintaining facilities and business there. Table 2 summarises and compares the main aspects of both cases regarding their strategic alliances and their internationalisation processes. Table 2: Comparison of the cases Preparations Alliances Future foreign markets Time acting in foreign markets Method of entering international Markets Reasons to enter foreign Markets Partner firms Final customer Choice of foreign markets Internationalised products Product

Case 1 No procedures taken initially National and foreign firms Netherlands, Germany, Brazil Acting for years in foreign markets

Case 2 Studies of markets and possible allies National firms (not mentioned) Just starting to act in foreign markets

Direct and indirect export

Indirect export

To sell products internationally with lower costs and to acquire knowledge Traditional and regional supply markets

To combat the limited scale of the Portuguese market National and foreign firms already placed and operating in the target markets People from other cultures appreciating water Need and value assigned to the product

Mainly Portuguese people living in other countries Preference for Portuguese regional food One product required more than others – Amarelo Cheese No need to adapt

All products for different market segments Possibility to adapt to different needs

5. Conclusion and implications The purpose of this paper was to analyse the reasons for the internationalisation of SMEs through strategic alliances and to understand how such an internationalisation process evolves. In doing so, we not only show how important, but also how complex and controversial this topic for SMEs is. The two firms selected for this study provided detailed information, giving the possibility of another insight into SME internationalisation. We show that the type of alliance and therefore type of export chosen by the firms can and will affect how the product reaches the foreign market and how feedback comes back to the Portuguese firms. Some reasons for engaging in international strategic alliances were identified by studying the two Portuguese SMEs. We found that the countries for international activities have been chosen according to the connections the firms have, based on trust and reliability to reduce the possibility of failure. What the SMEs pursue in forming alliances is firstly a reduction in costs that would be involved in commercialising their products in other countries, which is in line with Camisón and Villar (2009) and Suárez (2002). Secondly, they prefer to learn safely and gain knowledge about foreign markets and cultures, in order to be better prepared and develop more appropriate internationalisation strategies in the future. Regarding the implications, in spite of a considerable body of literature on strategic alliances in general, our paper represents an attempt to better understand the SME internationalisation process through alliances. In doing so, we defend the importance of costs and cross‐border knowledge flows. In our study, it was not only possible to study the SMEs and their strategic alliances, but also to analyse their specific efforts to internationalise, albeit in different business contexts. Our study intends to give an idea of how a simple strategy can be related to a firm’s development as well as to the success of some firms’ internationalisation and recognition. However, in line with Camisón and Villar (2009), we also provide evidence of the variety of internal and external motives for one firm cooperating with another. Finally, it should be noted that our study has some limitations. The great amount of information found during the theoretical research for this study showed that this is a topic that can and must be developed further, specifically in Portugal with its particular economic structure and climate. There will also be the possibility to complement or continue the study with a quantitative approach providing more substantial and reliable statistics supporting the insights already gained. Lastly, we hope the insights of our study will inspire other scholars, and the combination of this and future work will surely allow valuable comparisons to be made.

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The Business Model of the Entrepreneurial University Olaf Gaus and Matthias Raith Faculty of Economics and Management, Chair of Entrepreneurship, Otto‐von‐Guericke University of Magdeburg, Germany gaus@ovgu.de raith@ovgu.de Abstract: The advancement of science and technology is regarded as the driving force behind economic growth and social welfare in knowledge intensive societies. While the responsibility for the creation and dissemination of new knowledge typically lies with leading research institutions, such as universities, the translation of this knowledge into economic value is typically per‐formed outside of universities. Since universities increasingly depend on additional funds for new and expensive research, research groups are more and more considered to be ‘quasi firms’ ‐ a process which already has been described as “the invention of the entrepreneurial university” (Etzkowitz, 2003). In this paper, we acknowledge this orientation by revealing the logic of value creation within the university through its business model. We develop a general business model of the university as a research and teaching institution. Within this framework we contrast the private with the public university, and we are able to point out differences in their incentive structures, which are important for the fulfillment of their missions. We then include transfer as the third mission, which is fundamental for the entrepreneurial university. By changing the income structure, transfer affects the objective and incentive structure of the university. Within our business‐model framework, we are able to derive implications for the implementation of and the transition to the entrepreneurial university. In this paper, we acknowledge this economic orientation by revealing the logic of value creation by the university through its so‐called “business model.” Despite the popularity of the term today, it is, nevertheless, difficult to pin down a precise definition. We adopt the definition of Osterwalder & Pigneur (2010), according to whom “a business model describes the rationale of how an organization creates, delivers, and captures value”. However, they go one important step further than other authors by identifying nine interacting key components of a business model, which they logically organize in a graphical business‐model canvas. We extend this approach by decomposing the business model into separate value‐creation modules that are interrelated by a causal map, a further graphical tool that has successfully been used in the past, e.g., by Eden and Ackermann (1998) for strategy building. The combination of the business‐model canvas with causal mapping allows us to characterize the sophisticated business model of the university in a manageable form. Keywords: business model, value creation, entrepreneurial university

1. Introduction As we show initially in this paper the social effectiveness of a university depends on the university’s (financial) independence. In Section 2, we introduce the modular business‐model framework that we employ in our analysis. In Section 3, we then begin with the university’s oldest mission, teaching, and develop the business model of the university as a private school. By adding research as a further mission for value creation, we are able to contrast the business models of the purely private university, in chapter 4, and the purely public university, in chapter 5. The role of transfer as the university’s third and newest mission is analyzed in chapter 6, and the implications of this new orientation are developed in chapter 7. In section 8, we draw the conclusions from our analysis and point out aspects for further research.

2. The business‐model framework For a firm, the opportunity for value creation arises, whenever a problem can be solved, a specific demand met, or a need satisfied with a product or service. The created economic value can be measured by the difference between the value perceived by consumers and the firm’s unit cost of providing the good or service (cf. Besanko et al, 2009). If both the perceived value as well as the unit cost can be measured in monetary units, then so can the created value, although monetary value is not a prerequisite for value creation. For the firm, the crucial questions are with what, for whom, and how this value creation can be realized. The answers to these questions are given by what is commonly referred to as the firm’s “business model.” In this paper, we follow Osterwalder & Pigneur (2010) and characterize a business model by nine key components, which can be logically and graphically organized in a “business‐model canvas,” as depicted in Figure 1.

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Figure 1: Osterwalder & Pigneur’s nine key components of a business model Central to the business model is the firm’s value proposition, stating what form of value is provided. The economic relevance of this value depends on whom this value is created for, i.e., the customer segments. Their willingness to pay then generates the revenue streams for the firm. How well value is delivered depends on the firm‘s choice of distribution channels and the quality of its customer relationships. While the right‐hand side of the canvas focuses on value distribution, the left‐hand side is concerned with value creation. Most important for sustainable value creation are the resources of the firm (cf. Ndonzuau et al, 2002), which include its key competencies. Putting these resources to work appropriately enables the firm its value proposition. Hence, value creation requires key activities (cf. Porter, 1998) and typically also the support of partners (e.g., suppliers, networks) outside the firm. The accruing expenditures must then be weighed against revenues in order to determine whether or not the firm is able to capture its share of the value created and to see how profitable or at least economically sustainable the business model is.

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Figure 2: A causal map of the processes for creating, delivering, and capturing value A causal map connects the business‐model components in Figure 2, thereby characterizing different processes for creating, delivering, and capturing value. The solid arrows indicate the direction of argumentation between individual components (i.e., the nodes in the causal map), whereas the dashed arrow describes the transfer of a component, thus indicating a change of roles within the value‐creation process. The main difference between our characterization of a causal map in Figure 2 and the more traditional uses of causal or cognitive maps in political science or strategy making (cf. Eden, 1988; Eden and Ackermann, 1998) is that the nodes in our causal map are given by the predefined and, via the canvas, graphically prepositioned components of the

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Olaf Gaus and Matthias Raith business model, thus making the causal map easier to read and, consequently easier to expand to more complex settings. In the example business model, shown in Figure 2, the firm requires two key resources, X and Y, to be able to generate the two distinct value propositions A and B. While offer A is directed towards the specific customer segment 1, offer B addresses the firm’s two other customer segments, 2 and 3. With three distinct customer segments, the firm is able to generate three different revenue streams, which together determine the firm’s overall revenue. If revenues outweigh expenditures, then the firm is able to reap a positive share (i.e., the producer’s rent) of the value created. Suppose, however, that revenue stream 1 is relatively small com‐pared to revenue streams 2 and 3. As a consequence, the firm may be inclined to neglect customer segment 1, or simply to dispose of its value proposition A, with the same consequence. As Figure 2 shows, this could be detrimental for the whole value‐creation process, because customer segment 1 is less important for its revenues, but a crucial resource for the generation of value proposition B. In order to highlight this aspect of interdependent value‐creation processes, we separate the business model, described in Figure 2, into two value‐creation modules, as shown in Figure 3, where the relationship between the modules is characterized by the causal map. Partners

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Figure 3: The modular characterization of a business model The business model in Figure 3 is the same as in Figure 2, but the hierarchical structure of the value propositions and the asymmetric roles of the customer segments are now more visible. The relevance of customer segment 1 for the whole value‐creation process of value proposition B is emphasized by its transfer as a resource, indicated by the dashed arrow a in Figure 3. Moreover, the modular characterization of the business model also highlights a further important feature that is obscured by the aggregated characterization in Figure 2, namely that reve‐nue stream 1 is not sufficient to cover the expenditures of value creation, such that revenue streams 2 and 3 are required to subsidize the value‐creation process of value proposition A, which is depicted by the solid arrow b. In the following sections we will investigate the multidimensional value‐creation process of the university using such a modular approach. The individual modules will be identified with the help of the business‐model canvas described above. In order to understand the university’s business model, we disaggregate its multi‐ dimensional value proposition by first distinguishing between its core missions, teaching and research. More recently, universities are also expected to claim a third mission, viz. technology transfer, which we will discuss afterward.

3. The business model of the university as a private school We begin with teaching, historically the oldest mission of the university. The addressees of teaching are the university’s students at various levels. Their role within the business model, however, must be differentiated, in order to understand the multiple aspects of value creation. On the one hand students can be regarded as the university’s customers, to whom knowledge is sold. On the other hand, they can just as well be seen as (human) resources, which are trans‐formed by the education (production) process to marketable products (cf. Franz, 1998; Sharrock, 2000) as part of the university’s value proposition. We first take the latter perspective.

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Olaf Gaus and Matthias Raith Module SR: Students as resources The key resources for value creation are the professors, their key activity being teaching, supported by the university’s infrastructure. More sophisticated, though, is the role of the stu‐dents. Viewed as a production process, the value proposition of university education is the “value‐adding process” (cf. Christensen and Eyring, 2011) of transforming students (re‐sources/inputs) into high‐quality graduates (products), who are then hired (acquired) by private firms, the greater research community, or the government (in the role of an employer). The placement of graduates, alone for their sheer number, constitutes the greatest and most relevant form of knowledge transfer from the university to society. The following figure 4 illustrates the specification of all components of module SR. A crucial feature of module SR is that the university is confronted with customers from whom it does not receive any monetary revenues to cover the high expenses of the complete educational infrastructure. Although these customers do have a willingness to pay, their payments go only as salaries to the graduates that they hire. For the university, the main benefits are reputational (i.e., non‐monetary). Module SC: Students as customers A complementary perspective, strongly popularized by the increasing internationalization of higher education, is to view the students themselves as customers of the university, who are offered state‐of‐the‐art specialized knowledge and a job‐qualifying degree as a value proposition. This perspective is given by module SC, illustrated in Figure 4. The creation of this value requires the same process as in module SR, but since the customer segment of module SC differs, value is distributed within the university through different distribution channels and requires different forms of customer relationships. As students require several years of education before receiving a job‐qualifying degree, the value that they associate with the prospective acquired knowledge when entering the university is generated by the perceived value that future employers associate with the graduates that they hire. There is, thus, a direct causal relationship between the value proposition of module SR and that of module SC. In Figure 4 this is illustrated by the solid arrow labeled A.

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Figure 4: The university as a private school As they enter the university as customers, students at the same time enter as inputs to the education (production) process, willing to be transformed into high‐quality graduates. This transfer from one component of the business model to a qualitatively different component is depicted in Figure 4 by the dashed arrow B. The crucial aspect of module SC is: Can the students of the university be regarded as customers with a willingness to pay tuition (in Figure 4, this is indicated by arrow C), and, if yes, are the generated revenues sufficient to close (all modules of) the business model? If this is the case, as indicated by arrow D, then both

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Olaf Gaus and Matthias Raith modules, SR and SC together, constitute the closed business model of a university as a private school, where the term “closed” refers to a sustain‐able cyclical process of creating and capturing value.

4. The business model of the purely private university The business model of the previous section, to a large extent, characterizes the medieval university as a teaching institution, designed to preserve and pass on knowledge within society (cf. Etzkowitz, 2008). The more modern view of the Humboldtian university further acknowledges the importance of research as the crucial foundation for high‐quality teaching. In order to understand the value‐creation process of the research‐ oriented university, we, therefore, need to augment our business model by further aspects related to the university’s research activities. We capture these in a new module, which is depicted in Figure 5. Module RV: Research output as a value proposition As a research institution, the university’s value proposition is determined by the output of its research, ranging from publications to patents that document cutting‐edge research results. The university’s key resources for providing research products are its senior and junior scientists, whose key activity is research (cf. Ndonzuau et al, 2002). In addition, there is also the complete research infrastructure together with the supporting administration. The relevant customers are to be found mainly within the scientific community, with which the university collaborates in various partnerships, and which can be segmented into individual peers, peer groups, research institutions, and research funds that are addressed through different distribution channels. If students are paying customers, then the university receives revenues in the form of tuition fees. These revenues can be used to close the business model, if tuition not only covers teaching expenditures, i.e., finances modules SR and SC, but also research expenditures, thus subsidizing module RV as well. In Figure 5, which illustrates the interaction of all discussed modules, this subsidization of research is captured by arrow E.

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Figure 5: The business model of the purely private university

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Olaf Gaus and Matthias Raith Since students’ willingness to pay is determined by their expected future income, the higher this is, the higher the university can set the price for education and reap higher revenues to finance not only the teaching modules, but also the research module as well. Hence, the business model of the private university is driven by the interaction between the two teaching modules SR and SC. The research module RV, subsidized by module SC, in return, enhances the quality of teaching, as shown by arrow G. To what extent researchers can free themselves of subsidization by teaching, depends on much non‐teaching monetary revenues they can generate from research funds (arrow F in Figure 5). However, the model of the private university depends not only on students’ willingness to pay but also their capability of paying the tuition. The general criticism of this model is that not all potential students have access to the necessary funds. The private university may confront this deficit by means of price discrimination, i.e., by letting poorer students pay less than wealthier students. Although, rather than actually charging different prices, the university will typically fix the tuition, and instead grant (promising) poorer students scholarships, which are subsidized by (less promising) wealthier students.

5. The business model of the purely public university Within our business‐model framework, we treat the government that finances the university as a new customer segment. Figure 6 illustrates the corresponding module GC. Module GC: The Government as a Customer The value proposition offered by the university must be broad enough to encompass all its missions, i.e., teaching, research, and transfer (which we deal with in Section 6). In order to keep the analysis tractable, we include in module GC only the main components that are of interest for the complete business model. The value proposition offered to the government as a paying customer is a university system, designed in accordance with the government’s preferences. Figure 6 illustrates how the new module GC fits into the university’s business model. Without the financial revenues of student tuition the business model of the purely public university is closed with the public funds of the government (arrow H), which must now subsidize both teaching (arrow I) and research (arrow J). As Figure 6 reveals, the business model of the public university induces an incentive structure which is quite different than that of the private university. There is no driving module associated with the university’s core missions. Instead, it is the government that politically weights the university’s missions and distributes funds accordingly. In particular, the university itself has no incentive of its own to regard students as customers, unless the government as its customer demands this explicitly. Relevant for the flow of funds is, therefore, not students’ perception of the university’s value proposition, but rather the government’s view of the quality of education. Unfortunately, governments have limited possibilities to measure student satisfaction, therefore often relying only on the number of enrolled or graduating students. The switch from the students to the government as the main financing customer not only changes the incentive structure within the university. The qualitatively different nature of the two customer segments also affects the social effectiveness of the university. Although the purely private university depends mainly on the revenues accruing from students’ tuition, the students constitute a very large and diverse customer segment. The private university is, thus, able to choose its customers, find its individual niche with a specific profile or approach the mass market, but, most important, it can replace student customers, which increases its bar‐ gaining power and, thereby, its independence within society. The purely public university, in contrast, is mainly dependent on its one customer, its politically assigned, mostly regional, government, which it can neither select nor replace. In this state of extreme dependence, the university has little bargaining power, relying completely on the support of its government. As one can see in Figure 6, the only way for the public university to increase its independence in research is by raising its monetary revenues from research funds (arrow F).

6. The role of transfer as the third mission The reference to the entrepreneurial university is typically associated with the university’s third, more recent, mission, namely the transfer of marketable research results into society. In the past, universities have been quite successful in transferring knowledge, in general, through the placement of their graduates (cf. module

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Figure 6: The business model of the purely public university Module TV: Transfer as a Value Proposition Central to this module is a value proposition, which must be understandable for customers outside the ivory tower. The university as an R&D institution offers marketable rather than publishable research results. Accordingly, the customer segments are also active players on the market, who are interested in state‐of‐the‐ art R&D, and the university’s distribution channels as well as its customer relationships are those of a business firm. The creation of these marketable values, however, requires activities, such as product development, product marketing, business planning, or contracting, which are not common for the traditional university. Moreover, aside from the research results, that provide the foundation for value creation, the transfer‐ oriented (i.e., entrepreneurial) university requires a significant share of applied researchers and, in addition, professional transfer experts with market experience, market contacts, and juristic competences. The more professional this module is designed, the more costly it will be. On the other hand, if the variety of possible revenue streams is appropriately exploited, module TV can be developed to a driving force within the university’s value creation system. We begin with the business model of the purely private university, illustrated in Figure 5. The incorporation of transfer as further value proposition into this business model is shown in Figure 7.

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Figure 7: The business model of the private university with transfer For transfer to be successful, it must naturally augment the university’s value creation. This means that the marketable research results should consistently follow from the basic research process (cf. arrow K in Figure 12), rather than emerge from a separate division. Consequently, the basic research of the university’s professors must be complemented by market‐oriented R&D, conducted by a new group of applied researchers, which the university can readily recruit from its own graduates (cf. arrow L). Their qualification for these R&D jobs can be increased by integrating the market‐oriented activities of module TV into the teaching program (arrow M). In addition, the proactive placement of well‐trained graduates as transfer agents in innovative firms or start‐ups helps to enhance the firms’ interest in the university’s marketable research (arrow N). Arrows K, L, M, and N, thus, characterize the university as an interactive player within an entrepreneurial eco‐system. If the university’s market participation is successful, which may depend on “the age of the technical field, the importance of the market segmentation, the effectiveness of patents, and the importance of complementary assets” (Shane, 2001), and the accruing revenues (arrow O) are sufficiently high, then module TV can serve as an additional means of financing the university’s research (arrow Q) and, presumably to a lesser extent, also its teaching (arrow P). Note that arrows P and Q serve the same purposes as arrows D and E, respectively. Hence, transfer revenues, depending on their size, can be regarded as a substitute for tuition revenues. As they increase in importance, the new business customers of module TV are quite likely to affect the overall customer orientation of the university. This does not necessarily imply that the customer orientation towards students will decline.

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Olaf Gaus and Matthias Raith The integration of the transfer module into the business model of the public university, shown in Figure 6, follows the same pattern as the private university. The overall result, however, is qualitatively different, as Figure 8 illustrates. Arrows P and Q serve the same purposes as arrows I and J, respectively, so that transfer revenues can now be regarded as a substitute for government funds. However, the public university is not simply opening a new customer segment. The development of the transfer module and the expansion of transfer revenues liberate the university from its total dependence on its single customer, i.e., its responsible government.

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Partners

Activities

Researchers in other fields

Research

Researchers at other universities

Cutting-Edge Research Results

Resources Scientists Research Infrastructure

Expenditures

Value Proposition

Customer Relationships Conferences

Distribution Channels Journals Publishers Calls for Proposals

Customer Segments

Partners

Research Community •Peers •Research Institutions •Research Funds

Resources Research and teaching infrastructure

Value Proposition University system •Research •Teaching •Transfer

Customer Relationships

Customer Segments Government

Distribution Channels

Administration

Expenditures

Revenue Streams

Activities

Non-monetary revenues Expenditures for personell •Journal publications/editorships •Patents Costs of infrastructure and administration Monetary Revenues •Research Grants

Revenue Streams Public Funds

Figure 8: The business model of the public university with transfer As it gradually gains higher independence, the university is freer to determine and prioritize its own objectives. Moreover, as the position of the transfer module within the business model is strengthened (arrows K, L, M, and N), the university can expand its interdependence, in particular within the regional entrepreneurial eco‐ system. The business model, shown in Figure 8, specifies the synergetic interaction between the university, industry and the government, referred to by Etzkowitz (2008) as the “Triple Helix”. The crucial difference of our business‐model approach is that our view of this interaction specifically takes the perspective of the university, which enables us to derive targeted implications for the development of its entrepreneurial profile.

7. Implications for the entrepreneurial university As Figure 7 reveals, the installment of the transfer module can be considered as a significant business‐model innovation, both for the public as well as the private university. The additional value proposition for a new

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Olaf Gaus and Matthias Raith customer segment requires activities and personnel that are qualitatively new to the university. Understandably, traditional transfer offices, in charge of mainly information services for external stakeholders and university researchers, are generally unable to cope with the now relevant market‐oriented tasks (cf. Slaughter, Leslie, 2001). Some universities, therefore, choose to outsource the transfer module to an external transfer agency, i.e., a business firm operating by appointment outside the university. Most important for the success of the transfer module is its input of marketable research results. In Figures 7 and 8, this is characterized by arrow K, indicating the transfer of research results from module RV as resources to module TV, which can be regarded as the crucial life‐line of value creation through market‐oriented transfer. The organization and, in particular, the legal setting behind arrow K is a fundamental issue, which critically depends on the regulation of property rights within each specific university system (cf. Stephan, 1996, 2001, 2012). For example, if the transfer agency is a division within the university, then it could be assigned to exploit marketable research results emerging from module RV, e.g., by taking equity in research results, which generally yields higher profits than traditional licensing (cf. Bray, Lee, 2000). However, without additional funds, public universities are forced to initiate the transfer within their given infrastructure, i.e., with their present transfer personnel, whose previous tasks as an intermediary is now augmented by the market‐ oriented activities required in module TV (cf. Figure 7). Without the necessary professional support, the university is under pressure to quickly raise new revenues through market‐oriented transfer. A plausible reaction is, therefore, to redirect and concentrate its research funds on disciplines with the most marketable research results.

8. Conclusion The notion of the entrepreneurial university suggests viewing a research institution as a business. As we have argued in this paper, the main motivation for this perspective should be a deeper economic understanding of the process of value creation and distribution by the university. As we showed, the business model, precisely defined, is a useful tool for this exercise. Our approach of characterizing the business model by distinct modules of value creation, whose interrelations are graphically illustrated by causal mapping, enabled us to map the sophisticated business model of the university.

Acknowledgements The authors acknowledge financial support by the Ministry for Education and Research of the Federal Republic of Germany (BMBF) through the research project Uni:prise: Universities as Enterprises.

References Besanko, D.A., Dranove, D., Shanley, M. and Schaefer, S. (2009) Economics of Strategy, John Wiley & Sons. Bray, M.J. and Lee, J.N. (2000) “University revenues from technology transfer: Licensing fees vs. equity positions”, Journal of Business Venturing, Vol. 15 (5‐6), pp. 385–392. Christensen, C.M. and Eyring, H.J. (2011) The Innovative University, Jossey‐Bass. Eden, C. (1988) “Cognitive Mapping”, European Journal of Operational Research, Vol. 36, pp.1‐13. Eden, C. and Ackermann, F. (1998) Making Strategy – the Journey of Strategic Management, SAGE Publications Ltd, London. Etzkowitz, H. (2003) “Research Groups as ‘quasi‐firms’: the invention of the entrepreneurial university”, Research Policy, Vol. 32, pp. 109‐121. Etzkowitz, H. (2008) “The Triple Helix – University‐Industry‐Government Innovation in Action”, Routledge, New York. Franz, R. S. (1998) “Whatever you do, don't Treat your Students Like Customers!”, Journal of Management Education, Vol. 22 (1), pp. 63–69. Ndonzuau, F.N., Pirnay, F. and Surlemont, B. (2002) “A stage model of academic spin‐off creation”, Technovation, Vol. 22 (5), pp. 281–289. Osterwalder, A. and Pigneur, Y. (2010) Business Model Generation, Self Published. Porter, M. (1998) “Competitive Strategy: Techniques for Analyzing Industries and Competitors”, Free Press. Shane, S. (2001) “Technology Regimes and New Firm Formation”, Management Science, Vol. 47 (9), pp. 1173–1190. Sharrock, G. (2000) “Why Students are not (Just) Customers (and other reflections on Life After George)”, Journal of Higher Education Policy and Management, Vol. 22 (2), pp. 149–164. Slaughter, S. and Leslie, L.L. (2001) “Expanding and Elaborating the Concept of Academic Capitalism”, Organization, Vol. 8 (2), pp. 154–161. Stephan, P.E. (1996) “The Economics of Science”, Journal of Economic Literature, Vol. 34 (3), pp.1199–1235. Stephan, P.E. (2001) “Educational Implications of University–Industry Technology Transfer”, The Journal of Technology Transfer, Vol. 26 (3), pp. 199–205. Stephan, P.E. (2012) “How Economics Shapes Science”, Harvard University Press, Cambridge, MA.

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National Innovation System and Public Innovation Policy: Theory and Practice Problems Oleg Golichenko and Svetlana Samovoleva Central Economics and Mathematics Institute Russian Academy of Sciences, National Re‐ search University Higher School of Economics, Moscow, Russia golichenko@rambler.ru svetdao@yandex.ru Abstract: Bounding strength and intensity of networking provides the integrity of the national innovation system (NIS). The integrity allows the system to perform its fundamental functions of production, storage, diffusion and economic use of new knowledge. The primary factors of system dysfunctions caused by systemic failures include the following: a shortage of actors’ incentives for activities in NIS, lack of absorptive and innovative capacity and shortage of competency of actors, insufficient resources and a lack of partners providing the performance of NIS processes, disruption of interaction coher‐ ence and bounding strength, a complexity and failures of the framework conditions. The second‐row factors, i.e. ones in‐ fluencing the factors listened above, could be defined as the system imperfections. The system dysfunction resulting from the action of the factors induces public policy makers to intervene into formation and development of the NIS. To select and specify the NIS components that public policy should address, policy tools are bound to the NIS horizontal and vertical decompositions. During the horizontal decomposition, the NIS is presented in the form of three interrelated macroblocs. They are business environment and markets, environment producing new knowledge, knowledge transfer and diffusion mechanisms. During the vertical decomposition, a macrobloc should be divided into NIS subprocesses. Besides, the in‐ vestment‐driven and innovation‐driven stages are taken into account. The public policy on the former stage has to facili‐ tate a switch to competition driven by low costs and improvements of consumer properties of products on the base catch‐ ing‐up processes. Special measures shape the technology push policy of this stage. The essential feature of the latter stage is a radicalization of innovations. On this stage, the government continues to develop technology push policy, but it places a significant emphasis on the market‐pull policy focused on the end of an innovation cycle and establishment of non‐linear network interactions. Keywords: innovation system, dysfunction, decomposition, public policy, stages of development

1. Dysfunctions and failures of the innovation system According to traditional economic reasoning, public policy should intervene in the economy if a competitive market fails to allocate resources efficiently (Arrow 1962), i.e. the market failures take place. The market fail‐ ures can also be attributed to innovation activity. Under neoclassical assumptions, the innovation stems from the new codified information that is obtained during research and development (R&D). Therefore, following the logic of the linear model of innovation, which largely had prevailed until the NIS conception appeared, the main task of public innovation policy that the market failures determine is a financial support for R&D. The appeared conception of NIS has expanded a basis for public policy and given a new rationale for government intervention in activities of actors of the system (Mylteka and Smith 2002, Sharif 2006). Like any other system, the NIS may have dysfunctions. The analysis of emerging systemic dysfunctions allows us to identify systemic factors requiring public policy intervention to mitigate or eliminate their actions (Smith, 2000). Many publications of various authors deal with them. Among the authors are Carlsson and Jacobsson (1997), Edquist et al. (1998), Johnson and Gregersen (1994), Smith (1997). These authors often assign many impediments and imperfections to system failures, but they are more likely to be associated with the factors of these failures (see also Klein Woolthuis et al., 2005). Below, the failure of the NIS is thought of as an inability of the system to fulfill completely its main functions (creation, storage, diffusion and economic use of knowledge) through interaction of actors. The primary factors of these dysfunctions include the following:

insufficient incentives for activities in NIS;

lack of absorptive and innovative capacity and shortage of competence of actors,

a shortage of resources and partners providing the performance of NIS processes;

disruption of interaction coherence and low linkage strength;

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Oleg Golichenko and Svetlana Samovoleva

complexity and failure of framework conditions.

The following group of imperfections encountered in scientific literature could be taken as second‐row factors, i.e. ones influencing the factors listed above. 1. Insufficient force and incompleteness of motivational basis. The former leads to low levels of compensation of innovation activity risks. It noticeably reduces actors’ activities. The latter results in risk aversion and in‐ duces many participants of innovation processes to avoid significant activity. The absence or lack of motivation forces is often a consequence of institutional failures. 2. Low mobility of highly qualified personnel. It often does not allow organizations to satisfy current demand for human resources. 3. Failures of institutions (rules of game). These mean imperfections of existing formal institutions, i.e. failures of regulation and general legal system (Smith 1999) or informal (soft) institutions such as political culture and social values (Smith 1999, Carlsson and Jacobsson 1997). The imperfection or shortage of institutions can lead to poor compatibility of different NIS components, particularly to mutual inconsistency of incentives for joint actions of market and non‐market institutions, e.g. institutions of business and public research and develop‐ ment (OECD 2010). Some institutions performing fundamental NIS functions may be missed. 4. Institutional rigidity, communication gaps and underdevelopment of networks. Institutional rigidity (OECD 1999) may result in prohibition of certain types of linkages. Thereby, actors often are not able to have outside interactions, track new trends in an external environment and include new participants in networks. The ex‐ cessive rigidity of linkages and network failures of weak interactions (Carlsson and Jacobsson 1997) decrease an opportunity for actors to use interactive learning and participate in complementary processes of innova‐ tion. It is also worth noting that infrastructure inadequacies are also an important factor of underdevelopment in networking and communications (Smith 1999, Edquist et al. 1998). The blocking of transition to new technologies for both firms (Smith 1999) and socioeconomic systems (Perez 1983) is often a consequence of the effects listened above.

2. Public policy and its decomposition Systematic methods of horizontal and vertical decompositions must be used to select and specify the factors contributing to NIS dysfunctions. During the horizontal decomposition, the NIS breaks in three interrelated macroblocs (Golichenko 2011). They are business environment and markets, environment producing new knowledge, knowledge transfer and diffusion mechanisms. Under the vertical decomposition, each macrobloc may be divided into NIS subprocesses. The division includes the following groups: enterprises of manufacturing activities at different levels of technological intensity; size classes of organizations (i.e. ones united in classes in accordance with the number of employed people); property classes of organizations (i.e. ones clustered ac‐ cording to property types); economic operators united in groups according to their belonging to certain re‐ gions. The key policy tools tailored to liquidate and mitigate market failure and NIS dysfunctions are bound to the vertical and horizontal decompositions. Besides, the stages of development called by Porter (1990) as re‐ source‐based, investment‐driven stages and innovation‐driven one should be taken into account. It is worth noting that during the investment (catching‐up) stage institutions and resource base for transition to the next stage should be brought into being. According to Fagerberg and Godinho (2006: 522), “policies and institutions that worked well during the catch‐up phase may not be equally well suited when this phase is completed and the former catch‐up country has to compete with other developed countries on an equal foot‐ ing”. Besides, the country’s long orientation only towards problems of technology catching up can result in essential deterioration of creative facilities of the nation, particularly it concerns human resources in science and technology (HRST). In other words, there is a need for a mixed policy implementing in some proportions the institutions and institutional instruments corresponding to both the current stage driven by investment and the future stage based on innovations. Finally, the areas of this mixed policy must be grouped according to the following tasks (Golichenko 2010b):

providing conditions for increasing business innovation activity;

extending processes of knowledge diffusion and cooperation;

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supporting science and its orientation to solve problems of innovation development.

3. Entrepreneurial environment and market The goal of the policy in this area is to create a competitive business environment whose subjects have strate‐ gic thinking, learning ability, knowledge and management capacity to acquire and use new knowledge.

3.1 Investment‐driven stage, catching‐up model Framework conditions. On the stage, framework conditions are of vital importance. The problems of creation of favorable macroeconomic environment and conditions for business doing, particularly tax and investment climate, come to the fore. The framework conditions must liquidate corruption roots, separate business and authorities at all levels of governance (see table 1, row 4, columns 1 and 2) and assist to create an effective owner having incentives to innovate. The development of effective regulatory environment facilitates the solu‐ tion of these problems. Particularly for companies, which are active in absorption and adaptation of catch‐up technologies, modern empirical studies (Johansson et al. 2008) show that there is a negative effect of many corporate tax rates determined by law. The reduction of regulatory and administrative barriers restricting new firm's creation (OECD 2006a) and the effective system of firms’ access to finance are of considerable impor‐ tance. There is a need for reforms which could reduce institutional rigidities. To contribute significantly to achieving and maintaining reasonable competitive pressure, it is necessary (Jaumotte and Pain 2005) to opti‐ mize antitrust laws, lower the barriers to market entry and exit (OECD 2008). The foreign direct investment (FDI) may be an important element of economic development on the stage (Guellec and van Pottelsberghe 2001). To make a significant contribution to improving the absorption capabilities of NIS actors, it is important to pro‐ vide public and business investing in the highly skilled labour force and technologies. The development of sec‐ ondary, higher and vocational education is one of the basic factors for passing the stage. Besides, the availabil‐ ity of the highly skilled workforce and the quality of knowledge institutions in the country has a considerable impact on foreign direct investment (Erken et al. 2005). Special conditions. During the stage, there must be a switch to competition driven by low costs and improve‐ ments of consumer properties of products. These improvements are a result of catching‐up processes in inno‐ vation including incremental improvements of imported technologies and products. The essential factor of the stage is demand and supply of HRST. The demand‐side policy aims to enhance em‐ ployment and development of highly qualified staff through regulation of labor markets, tax incentives to in‐ vest in R&D and encouragement of exacting consumer demand. In turn, the supply‐side policy requires gov‐ ernment support for education and training and conditions for transformation of "brain drain” into “brain cir‐ culation”. The increasing dependence between innovation processes and R&D intensity give evidence for growth of in‐ vestments in high and medium‐high technology industries. If a country has rather significant HRST, the intro‐ duction of incentives to manufacture technologically complex products could leverage innovation activity (see table 1, row 3, column 1 and 2). These incentives may include tax reliefs, privilege credit conditions for equip‐ ment and licenses import, stimuli for international cooperation in R&D. General measures to stimulate innovative demand, supply processes are in need of development. The supply (push) stimulation policy, above all, aims to shape a sufficiently complete and consistent government system of indirect and direct financial incentives, e.g. target grants and tax incentives for R&D. Innovative activities are usually distributed unevenly among various size classes of enterprises. Therefore, public policy should aim at both overcoming the innovative passivity of large companies and increasing the weight of innovative‐active small and medium enterprises. At the beginning of this stage, the demand‐pull policy is rather simple due to a certain degree of the rigidity and scarcity of production and market systems. Its content is largely technology‐ oriented government procurement, which makes demands on qualitative products in the framework of gov‐ ernment contracts.

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3.2 The national innovation‐driven stage of development On the stage, following the success already achieved during the previous stage (see table 1, row 4, column 4) the monitoring and evaluation of barriers to competition and entrepreneurship are taking place. Efforts are being made to overcome identified barriers. Calls for decentralization of decision‐making processes in the economy become urgent. Meeting new challenges, the access to capital for fast growing companies including new technology based firms is expanded. The flexible market of qualified and mobile labour becomes available for enterprises. Growth of incomes, educational level and consumer's qualification can provide a basis for advancing facilities of high and medium‐high technology industries, implantation of innovative‐active firms in kinds of economic activities. The special conditions for innovation growth include encouraging the private and public investment aimed at the HRST development and facilitating the creation and promotion of disembodied and dual‐use technologies (OECD 2006b). On this stage, the government continues to develop a technology push policy, but it places a significant emphasis on the market‐pull policy focused on the end of innovation activity phases. Demand be‐ comes a driving force, which manages resources and innovative capacity to meet emerging societal or market needs (Schmookler 1966, Rosenberg 1969). The essential feature of this stage is radicalization of innovations. While there does not usually exist a problem of the diffusion of incremental but radical innovations (Bower and Christensen, 1995). In order for the radical innovations could be adopted quickly by consumers, the mar‐ ket demand often needs to be enhanced by public policy, for example through lead‐market initiatives including tax credit, rebates for consumers of new technologies, regulations and standards (OECD 2011a). The firm’s innovation activity can move to a new more profitable value‐added chain. The types of activities may be en‐ couraged by competition processes and fragmentation of value chains (Pavitt 2006, Golichenko 2011). The necessary conditions of giving rise to the activities are vertical cooperation and partnership, greater coherence of innovative resources and high mobility of highly qualified personnel.

4. Mechanism of knowledge transfer and diffusion The mechanism creates the opportunity for knowledge transfer and diffusion through open information chan‐ nel, channel of transforming open knowledge in pre‐competitive and competitive one and channel of commer‐ cial knowledge transfer (Golichenko 2008).

4.1 Investment‐driven stage, catching‐up mode On this stage, catching‐up countries achieve increases of productivity and improvements in welfare not from R&D performance and commercialization of their results but mainly due to absorption of already‐known‐to‐ the world technological knowledge (OECD 2009). In order for the absorption takes place, actions are necessary to involve and support all eligible channels of knowledge diffusion, to focus efforts on the fast growth of ab‐ sorption capacities of enterprises (see table 1, row 2.2., column 1 and 2). Aside from the strong improvement of the quality and scales of technical education in higher school, the organization of professional and special intra‐firm training takes place. For development of this form of vocational training, it is useful to leverage FDI. As the experience of China shows, the strong government bargaining power may assist to involve foreign in‐ vestors in processes of intra‐firm training of domestic enterprises (OECD 2009). Development of the traditionally understood diffusion of disembodied and embodied technologies requires a well‐run commercial knowledge transfer channel (see table 1, row 2.1., column 1 and 2). If this is the case of commercial knowledge of foreign origin, the substantial factors of this process are international trade, FDI and intellectual property rights. The acquisition of foreign technology companies by enterprises plays a certain role. Diaspora, if it is rather widespread, can also be involved in these processes. The domestic markets of countries with relatively low income per capita do not usually contain drivers of economic development. The countries need to strengthen competition through strong export orientation of domestic firms and open the domestic market to foreign competitors. Nevertheless, it must be borne in mind that excessive strong competition might cause irreversible far‐reaching negative consequences for national industry. Aghion et al. (2005, 2009) proposed and empirically proved the hypothesis that, in industries with a large gap between foreign technology leaders and domestic laggards, do‐

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Oleg Golichenko and Svetlana Samovoleva mestic innovative firms are forced to leave market due strong foreign competition. The intensive competition may discourage the emergence of new industries and make a negative impact on the national economy as a whole (Dixit and Stiglitz 1977, Romer 1990, Grossman and Helpman 1991). At the same time, the classic pro‐ tectionism maintaining high barriers to entry for foreign companies preserves backward technological struc‐ ture and thus provides serious obstacles for economic development. In other words, there is a need to achieve a careful balance between processes of foreign competition and public support of domestic enterprises.

4.2 National innovation‐driven stage of development On the stage, there is a switch from supporting individual firms and organizations to setting up system‐ integration and network models of continuous innovation, i.e. development of clusters of interconnected firms and research organizations. Faced with increasing global competition and rising R&D costs, companies can no longer survive on their own R&D facilities, and they look for opener new modes of innovation. The government encourages cooperative interaction between universities, public research organizations and industry. The bridges to pass Death Valley by new technology base firms are constructed and supported. The human capital mobility, systems of disembodied technology transfer (see table 1, row 2.1 and column 3) and fertile “breeding and growth grounds” for technology‐oriented spin‐offs are desirable for transition to the innovation‐driven stage. The cooperative processes take two dimensions. The first reflects a move away from traditional supply‐push policies towards a model based on joint development including public‐private partnerships and networks of firms and actors outside national borders. The second dimension is associated with the market‐pull or contrac‐ tual relationship between public research and demand from the business sector (OECD 2011b). On the stage, the lack of business motivation to search new knowledge sources can be a major obstacle to the linking of business performance and R&D. The special programs to accelerate technology diffusion in areas of nascent demand assist in solving problems of increasing technological and organizational firm capabilities. There is also a need to remove obstacles and create incentives for horizontal and vertical interaction and de‐ velopment of networking between enterprises and organizations of different ownership forms. Technology platforms can play a significant role in shaping this stage.

5. Environment producing knowledge The policy goal is to maintain and develop research environment, ensure knowledge production, to orient re‐ searchers towards meeting manufacturers’ needs for innovation and encourage for cooperation with business communities.

5.1 Investment‐driven stage, catching‐up mode On the investment‐driven stage, the innovation activity mainly has a catching up character. Moreover, the ap‐ plied research and engineering are of greater value than basic sciences. However, in order to achieve the stra‐ tegic goals of the next stage driven by innovation, the arrangements for encouraging R&D should already occur on the stage (see table 1, row 1, column 1 and 2). The most important of these arrangements are the following developments:

creating an attractive environment for carrying out R&D, in particular enhancing the prestige of scientific activity and increasing the effective researcher’s income above the average industry‐level wage;

setting up the modern engineering base for carrying out R&D including not only well‐qualified people, but also high‐quality scientific facilities.

in order to find new fields of research and focus in the areas of global R&D, the equilibrium between port‐ folio of R&D related to the national priorities and complementary fields of research should be reached.

5.2 The national innovation‐driven stage of development In order to facilitate the transition to this stage, the country needs to stimulate a transfer of the final and in‐ termediate R&D results from public organizations to industry (see table 1, row 1, column 3), pursue a monitor‐ ing and eliminate obstacles constraining a legal transfer capacity of public research organizations. Public policy should boost knowledge production and supply to accelerate knowledge spillovers and externalities (Jones and Williams 1998).

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Oleg Golichenko and Svetlana Samovoleva Considerable public and private efforts build conditions and incentives for joint orientation of government R&D sector and industry and their cooperative relations. The appropriate stimuli enabling domestic entrepre‐ neurs to advance high technology manufacturing and enterprise’s research base are necessary (see table 1, row 1, column 4). In areas of traditional responsibility of public authorities (defense, medicine, ecology and so on), reforms of programming processes are needed to achieve greater openness of procedures of program formation and their results estimation.

6. Conclusions Thus, in addition to market failures, the rationales for government innovation policy are dysfunctions of the national innovation system. The vertical and horizontal decompositions of the NIS are needed to differentiate policy measures and to identify areas of their influence. To make policy effective, the policy measures must be articulated with the economic stage of country development. On the investment‐driven stage, the public policy facilitates a shift from the mobilization of primary factors to technology leapfrogging driven by the sharp increase of utilization and up‐grade of imported technologies and incremental improvements of products. An important part of this policy is the introduction of economic incen‐ tives to leverage technological absorptive capacities by integrating in the global economy and diffusing global knowledge. The high quality of secondary and higher education and vocational training must underpin neces‐ sary processes of technology absorption. Special measures shape the technology push policy of this stage. It is worth noting that there is a danger that a country copes largely with phases of investment stage but then fails to transit to innovation‐driven one. Therefore, there is a need to create preconditions for transition to innova‐ tion‐driven stage. On the innovation‐driven stage, the principal policy purpose is to promote the formation of post‐catching up NIS capable of generating radically new products and processes (see table 1, row 3 and column 3). Among the potential problems, support of public and private investment in HRST and development of flexible markets of highly qualified labour is of great importance. The government continues the technology‐push policy to gener‐ ate disembodied and dual‐use technologies. At the same time, it should increase emphasis on the market‐pull policy involving incentive schemes focused on the end of innovation cycles. Besides, significant efforts must be directed at providing conditions and stimuli for reinforcement the cooperative relationship of government R&D sector and industry and establishment of non‐linear network interactions including public‐private part‐ nerships. The research has been supported by the Russian Humanitarian Scientific Fund (project 11‐02‐ 00426а). Table 1: The comparison of innovation tax incentives

1. Environment producing new knowledge R&D tax credit rate based on Expenditures vol‐ ume Incremental ex‐ penditures R&D allowance Additional R&D incentives

Investment‐driven stage

1 China

2 Russia

Transition to the national innovation‐ driven stage 3 South Korea

‐

1 25% / 6%

130% / 225%2

‐

50% / 40%

‐

150% of expenditures

‐

Investment tax credit

Expenses equal to 3% of taxpayer revenue3 Investment tax credit for R&D equipment

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National innova‐ tion‐driven stage 4 UK

Cash credits for SMEs

Oleg Golichenko and Svetlana Samovoleva

2. Mechanism of knowledge transfer and diffusion 2.1 Knowledge transfer

2.2. Providing con‐ nections between the elements of Innovation System

3. Entrepreneurial environment and market

4. Framework con‐ ditions The standard rate of corporate tax Corruption Percep‐ tions Index, Rank (2012)

Investment‐driven stage

1 China Business tax exemption for the transfer of qualified technology Income from technol‐ ogy transfers below RMB 5M is exempt from income tax. In‐ come in excess of RMB 5M is taxed at a 50% reduced rate4 Exemption on import duty, VAT and con‐ sumption tax on im‐ 4 port of equipment The corporate tax rate to Technology Ad‐ vanced Service Enter‐ prises was reduced to 15%. These enterprises must be located in designated cities with over 50% revenue de‐ rived from providing qualified technology advanced services out‐ sourced by foreign entities Reduced to 15% corpo‐ rate tax rate and a tax holiday for companies granted High and New Technology Enterprise status Tax incentives for Technology/Soft‐ware Companies (e.g., ex‐ emption from enter‐ prise income tax)

2 Russia VAT exemption for revenue from sales of IP or license rights VAT exemption for Non‐Profit Educational Organizations Tax deduction of ex‐ penditure on the pat‐ enting and the acquisi‐ tion of exclusive IP rights5

Transition to the national innovation‐ driven stage 3 South Korea Tax credit in the amount of 7% of the IP purchase price (for SMEs)

National innova‐ tion‐driven stage 4 UK Lower rate of Corporation Tax to profits earned from its patented inventions and certain other innovations. It must be equal to 10%.

Tax incentives for Skolkovo and residents of Technology Devel‐ opment Areas (e.g., property tax exemp‐ tion, reduced to 14% rate social security contributions)

n/a

0% corporate tax for sale of high technology sector shares

Tax credit on current R&D expenses for the New Growth Engine Industry or Original Source Technology programs

n/a

25 %

20 %

from 11% to 24.2%

from 20% to 26%

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Notes. 1 Small firm/ large firm. 2 Currently the R&D tax credit scheme in the UK is structured as an enhanced deduction. 3 For first year. Taxpayer is required to add the R&D reserve deduction back into income in three years. 4 For Technology and Soft‐ware Companies. 5 The incentive is applying under simplified tax system.

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Involving Students in Ideas Generation – a Bulgarian Case Elissaveta Gourova1, Tzvetelina Teneva 2 and Tsvetoslava Kyoseva3 1 Telecommunications Department, New Bulgarian University, Sofia, Bulgaria 2 The Business Institute, Sofia, Bulgaria 3 Mobiltel EAD, Sofia, Bulgaria egurova@nbu.bg tzteneva@thebusinessinstitute.eu dikovska@mobiltel.bg Abstract: It is widely accepted that in the knowledge‐based economy, knowledge and information have become key factors for success and competitiveness. At policy level in Europe are taken specific measures to boost research and innovation, and to take advantage of technology development world‐wide. A long way was passed since the first innovation concepts emerged, and we are witnessing today rapid changes of business models of enterprises, changed perceptions and activities of users. With the development of Web 2.0 and Web 3.0 applications, companies have many opportunities to gather opinions and ideas from their users and other interested stakeholders for the development of new products and services, as well as to get insight on users’ behaviour and preferences. This helps organisations to take advantage of the ‘wisdom of the crowd’. The changes in innovation models, and in particular the concept of open innovation attract the attention of researchers and practitioners. Many studies are devoted to these topics, whereas some focus on lead users involvement, others consider the living labs approach, while third present the ideas generation practice. The ideas competitions often focus on involving young people in innovation and taking advantage of their creativity and talent. This often requires collaboration of different stakeholders.The aim of this paper is to make the researchers community familiar with the approach for involvement of students of the Technical University – Sofia with ideas generation in a special Innovation Lab created by a leading Telecom operator. At the same time, it is a best practice example of the university – business collaboration in innovation, involving also partners of the Telecom operator as mentors and facilitators. Such collaboration model needs to be explored and multiplied for strengthening stakeholders’ collaboration and fostering building a real national innovation system. Therefore, the paper tries to present the case focusing in particular on the structure and roles in the Innovation Lab, and the methodology followed by the students’ teams. Keywords: open innovation, ideas generation, students involvement

1. Introduction Knowledge and innovation have become essential factors for sustainable development and competitiveness of organisations world‐wide. Organisational learning through exploration of new knowledge and usage of the existing one is behind entrepreneurship of companies (Hayton 2005). The knowledge‐intensiveness of economy today, the market volatility and the pace of technology change are among the main reasons for researchers to consider that organizational competitiveness depends to a greater extend on intangible resources, and knowledge in particular (Singh 2008). It is not surprising that many organisations have launched Knowledge Management (KM) projects in order to ensure their success – to innovate faster then competitors; to increase their efficiency and productivity; to enhance intellectual capital; and to preserve knowledge of employees in time of high workers’ mobility (Du Plessis 2005), (Greiner et al. 2007), (Nunes et al. 2006). Recent trends in Information and Communication Technology (ICT) development have provided organizations and individuals with new opportunities for creativity, collaboration and knowledge transfer. The emergence of Web 2.0 and the Semantic Web (Web 3.0) has reflected in changes of business and innovation models. Nowadays, social media is increasingly supporting knowledge transfer and creativity, and actually, is behind most open innovation processes. The trends towards Internet of Things (IoT) and the wide use of new Internet‐ based applications have faced ICT companies with enormous challenges. Telecom operators, in particular, need not only to provide high‐quality communication services, but also to consider how to preserve their competitive position on a market with high volatility, and to grasp the opportunities of the Future Internet. Looking into the future, companies avail themselves on the creativity and ideas of the users, and especially young people. Many competitions are organized for students world‐wide, and on a national scale. In Bulgaria, for example, ICT students regularly attend Intel and HP contests (Gourova et al. 2012). Local operators are also looking for fresh ideas coming from the computer‐savvy generation.

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The aim of this paper is to present the open innovation practice at Bulgarian Telecom company and its approach to involve students in ideas generation. The paper provides initially an insight into the concepts of living labs and ideas generation as discussed by researchers, and then, focuses on the innovation activities of the company, and its practice in streamlining students’ creativity and innovation for its own benefits. A special emphasis is given on the methodology used in the ideas generation and the results achieved so far.

2. The concepts of ideas generation and living labs The shift from vertical to a horizontal production model has changed the innovation process towards open innovation, where end‐users and external stakeholders provide additional benefits to organisations (Leven et al. 2008), (West et al. 2010). The concept of ‘open innovation’ reflects the strong emphasis on involving external actors together with organization employees in the innovation process, and thus, using the creativity of the ‘crowd’. As Chesbourgh (2003) points out, ‘open innovation is paradigm that assumes that firm can and should use external and internal ideas, and internal and external path to market as firms look to advance their technology’. West et al. (2010) consider that organizations are looking how to enable users innovation, and how to streamline it to meet organisational goals for development of new products. The added‐value for organizations comes from the fact that their customers ‘know different things than the producers’ (Zwass 2010). Many organizations have launched ideas competitions in order to gather users innovative ideas in the early phases of new product development (Gourova et al. 2009). Ideas competitions are a well‐elaborated method for active involvement of users and integrating them in the organizational innovation and problem‐solving activities for limited time duration. Irrespective of the way of implementation (online, offline or mixed), individuals or groups of them are encouraged to propose ideas, sometimes evaluate them, and the most active participants and the best ideas are rewarded (Ebner et al. 2009). The advantage for organizations is that they collect many new ideas without involving much internal resources (Riedl et al. 2010). Students are often the main target group of organizations by launching ideas competitions. On the one side, young people turned to be more creative and innovative then the older users. On the other side, organizations benefit also from the opportunity to find new talents and prospective employees, as well as to increase the awareness of young people on their own products (Ebner et al. 2009). One of the most difficult issues is to evaluate ideas, whereas some of the widely used criteria for measuring ideas quality include (Blohm et al. 2010):

novelty – assessed as original, unique/rare, uncommon/surprising, revolutionary, radical or trendy

relevance – might provide clear customer benefit, attractive market potential, competitive advantages

feasibility – if the idea is technically feasible, economically feasible or fits the initiator’s image, more generally to be easy transformable into a commercial product

elaboration – the idea should be precise, complete and exactly described, mature and well understandable.

Living labs represent a user‐centric innovation methodology which could be deployed at all phases of the innovation process – product idea, concept, prototype or marketing. In living labs are utilised several methodologies and creativity techniques (Figure 1) whereas the collaboration is taking place predominantly face‐to‐face rather then using technologies for Collaborative Work Environments (CWE) as stressed by Mulder et al. (2010). The living labs, despite the methodology used, facilitate the innovation and refining complex solutions in multiple and evolving real life contexts, and are characterized by (Kviselius et al. 2008), (Svesson et al. 2009), (Almiral 2008), (Leven et al. 2008):

variety of stakeholders – involve users, technology developers, researchers, use also own staff creativity in an open innovation environment in which they can interact and become co‐producers of each other’s value creation processes.

ideas and problem‐solving focus – facilitate new idea generation, identification of problems and solutions coming from users, and process them against predefined criteria.

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testing, experimentation and evaluation focus – grounded and linked to real‐life settings and requirements.

approaches – make products/technology available to users at their homes or create a home where users could stay.

Figure 1: Living Labs Methods (Mulder et al. 2010)

3. Ideas generation in Bulgaria 3.1 Mtel innovation lab The students’ ideas generation is recently introduced in Bulgaria by Mobiltel (Mtel), a leading telecom operator in the country. The company follows the overall trends in telecommunications and offers to its clients the best quality. Faced with the strong competition on the local market, the company looks for opportunities to offer its clients a bigger diversity of services which could facilitate their everyday life and work. The company has a special Innovation Centre which guides its work on developing new products and applications. Some of them support the access to electronic books, and others look how to make smarter cities. At the same time, the company is open to partnerships with other stakeholders for developing their innovative ideas into real products. In its Test Zone it engages many citizens in providing their views on the tested new products (Mtel 2013). For developing new ideas the company is taking advantage of students creativity as well (Vladkov, 2012). In 2011 it launched a new Innovation lab at the Faculty of Telecommunications of the Technical University – Sofia (TU). In the Lab are equipped 4 working places to support students developing their ideas. The major goal of the operator is to help and support TU activities related to innovation, research and development in the field of advanced telecommunication and information technologies and services. Common mission of the university and the Telecom operator is the encouragement of good students to develop themselves as leading specialists and professionals, by enriching their knowledge and enhancing their creativity and innovative thinking, giving them the opportunity to work with up‐to‐date and advanced technologies and tools under the tutorship and guidance of leading professors and specialists from the business and the university. The roles in the Lab, based on the intrapreneurship principles, are as follows:

Initiator – with role on ideas generation to prototype: Students

Manager/Champion – managing and coordinating, motivating teams: Mentors, Tutors

Sponsor – defining working approach and goals: Company Innovation Centre

Supporter – practical guidance and mentoring: The Business Institute, TU the company business partners,

Judge – monitoring project progress and key indicators: Company Decision Making Positions

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Mtel defines the patterns of work and the goals in details, follows the key phases of the implementation, provides and manages the funding of the project. It participates in defining the objectives at macro‐level, monitors key performance indicators, and gives critically opinion and corrective to the project. Mentors and tutors are facilitating the work of the students and are providing them theoretical knowledge and practical guidance. The Business Institute and other business partners of the company are also supporting the work of the students (Mtel, 2012). In the Innovation Lab work 4 teams, each consisting of 4 students, one company mentor and one company tutor (Figure 2). At the beginning of the programme, the company defines a topic for all 4 groups to work on ideas generation and development. The group work is facilitated by 2 representatives of The Business Institute, as a partner of the Lab.

Figure 2: Mtel Lab Organisational structure (Mtel 2012) Students are selected on bases of an open competition with thematic focus. In 2011, the topics were Remote Personal Health Systems, Multi sensor networks at home, Future Internet and Apps and Games, while in 2012 the focus was on “Connected world" and improving the everyday life using modern technologies such as Cloud, Mobile Applications, Big datа, Social Networking, Green technology.

3.2 Ideas generation methodology Generally, the approach for developing a new product in the Lab comprises business and technology development (Figure 3). The process in the Innovation Lab is divided in 3 main stages taking in total 11‐12 months (Figure 4):

Stage 1: Idea generation, assessment and ‘go’ or ‘no go’ decision

Stage 2: Customer development of the chosen ideas

Stage 3: Prototype development of the chosen ideas

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Figure 3: Mtel Lab processes (Mtel 2012) After each stage, the students’ teams present their development so far. The presentations after Stage 1 and Stage 2 address representatives of Mtel and TU. The presentations after Stage 3 are open for outside audience and media.

Figure 4: Innovation Lab stages (Mtel 2012) The methodologies for Stage 1 and 2 are proposed and managed by The Business Institute in the role of facilitator of the business part of the Lab. The roadmap and the methodology are based on the following prerequisites:

Numerous and various entrepreneurial workshops, delivered by The Business Institute as a representative of the Cisco Entrepreneur Institute;

Practical entrepreneurial and intrapreneurial education in Masters Degree in Entrepreneurship and finance;

Coaching and mentoring sessions by The Business Institute team as a strategic partner of LAUNCHub start‐ up investment fund (JEREMIE programme).

Methodology of Stage 1: Idea Generation and Assessment Stage 1 is for ideas generation and assessment, based on which Mtel takes decision which of the ideas will go on to Stage 2 to be further developed. The format of Stage 1 includes series of workshops in which all working groups (students, mentors, tutors) participate, and as facilitators act representatives of The Business Institute. Each workshop consists of three main parts:

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Introduction of the topic and the tools used – explanation, practical examples by The Business Institute Faciitator (30% of the time)

Practical work on the ideas by the teams (40% of the time)

Discussion and feedback – practical discussion on the result of the groups work (30% of the time)

The workshops are based on a roadmap of a business methodologies and tools, selected and mixed by The Business Institute team for the purposes of the Innovation Lab. The roadmap underpins the Stage 1 programme (Table 1). Methodology of Stage 2: Customer Development Stage 2 is devoted to the development of the chosen ideas in business aspect. It is facilitated by The Business Institute representatives, based on the Customer Development methodology by Steve Blank, Stanford University (Figure 5). Precisely, Stage 2 is focused on the first two parts of the methodology – Customer Discovery and partially Customer Validation. Customer Development is provoked by the statistics that more start‐ups fail from a lack of customers than from a failure of product development. The main goal of the methodology is to prove the “product‐market fit” early enough before financial investment in the venture. The methodology is suitable both for entrepreneurial and intrapreneurial ventures. Customer Discovery is focused on “market‐product fit”. It is designed to prove that the hypothesis of the market problem solved, the product idea and the target segment of the business model are correct. Subsequently, the methodology encompasses iterations of meetings “inside the building” and such “out of the building” with market representatives, mostly customers. Stage 2: Customer Development partially overlaps with Stage 3: Prototype Development, based on the prescriptions of the Customer Development methodology. Table 1: Roadmap of business methodologies and tools Topic Business Ideas Generation Business Idea Evaluation Business Model Options Business Environment Analysis Target Customers Insight and Channel Business Ideas Development Scenarios – Assessment of the Potential Innovative Business Models and Competitive Advantage Financial Model and Analysis

Business methodology/tools Creative techniques Business Idea Mandala methodology and tools Business Model Canvas methodology and tool (Osterwalder and Pigneur, 2010) PEST Analysis, 5 Forces Analysis (Porter 2008) The Empathy Map tool, XPLANE PEST Analysis, 5 Forces Analysis Business Model Canvas methodology and tool (Osterwalder and Pigneur, 2010) Business Model Canvas methodology and tool (Osterwalder and Pigneur, 2010) Financial Model Canvas tool

Figure 5: Customer development methodology

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At the Innovation Lab, based on the Customer Development, the following steps are implemented:

Articulate Business Model Canvas (BMC) hypothesis – refine the results of Stage 1

Problem – test the problem hypothesis with iterations of meetings “out of the building” with market representatives (mostly customers) and meetings “inside the building” with The Business Institute facilitators to analyse the results and refine the BMC

Product – test the product (Value proposition) hypothesis with iterations of meetings “out of the building” with market representatives (mostly customers) and meetings “inside the building” with The Business Institute facilitators to analyse the results and refine the BMC

Customers – test the Customer Segments hypothesis with a clear focus on early adopters (lead users) with iterations of meetings “out of the building” with market representatives (mostly customers) and meetings “inside the building” with The Business Institute facilitators to analyse the results and refine the BMC

Minimum Viable Product (MVP) – define MVP based on the iteration and test it with potential customers At each step the groups are guided by The Business Institute facilitators’ team, which provides report to Mtel representatives after each meeting about the development of the process, positive and negative outcomes with proposals for adjustment of the next steps. With the aim that students get quick access to market representatives and customers, Mtel supports the process with contacts to its business partners in the respective areas. The latter meet the working groups for interviews and further identify and connect the teams with other suitable respondents.

3.3 Results The Innovation Lab approach turned to be mutually beneficial for all participants. TU professors consider that “Such cooperation between academia and business is important and beneficial not only for academia but also for the Bulgarian society”, and believe that this best practice example could facilitate the university‐business collaboration and be a bases for future joint initiatives in research and innovation. For Mtel as well, this is an approach to shorten the distance between the business and the university, as well as assisting students’ community developing its potential and implementing brave ideas. Actually, within 12 months the students gained new theoretical knowledge and practical skills – to generate ideas, develop models for ideas evaluation and analysis, concept formulation, presentation and defense of concepts, building hypothesis, preparing questionnaires, interviewing experts and potential users, etc. While many of them were motivated by their future career prospects, the impact was greater than expected – gaining new interdisciplinary skills, following the whole process from the idea to the real product and seeing how their ideas evolve (Mtel 2012). The work of the Lab in 2011 gave already its results: the educational game “Magic Heros” (Figure 6), which is in Bulgarian and is appropriate for children over 3 years is already tested on “Mtel Test Zone” (http://testzone.Mtel.bg/) and can be downloaded from App store Google Play.

4. Conclusions The paper provided an overview of the practice in a newly created Innovation Lab at the Technical University – Sofia by Mtel. Actually, the Lab has many elements of a Living Lab as it involves a users group in many phases of the open innovation. However, as the main actors are students and the objectives of the ideas generation are not only innovation, but also better preparing the future employees, the emphasis of the paper was to present the main processes and results of the Innovation Lab work. At the same time it should be stressed that young people are a prospective target group for open innovation. In fact, the feedback of the Innovation Lab participants points out that for students the creative challenge, the training, as well as the contacts with Mtel and the prospect for career, are with higher value then possible monetary rewards. Obviously, young people devote time and efforts in creative activities with the aim of developing the skills required by employers, but also for their personal satisfaction in realizing their ideas.

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Figure 6: The prototype (Mtel 2012) While companies are involving students in ideas generation for taking advantage of their creativity and talent, universities need to take advantage of the opportunities to establish stable long‐lasting collaboration with the business community. The paper presents a best practice example of recent joint activities, which unfortunately are rare in Bulgaria, but have traditions at the Technical University ‐ Sofia. Similar practices need to be examined and made publicly known in order to be multiplied. This is especially important for Bulgaria, where business – university collaboration according to several reports faces many barriers, and is limited mainly to education, whereas joint research and innovation projects are extremely rare.

Acknowledgements The authors gratefully acknowledge the support provided by the Innovation Lab team for preparing this paper.

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Emancipatory Māori Entrepreneurship in Screen Production: Theory and Application Ella Henry Auckland University of Technology, Auckland, New Zealand ella.henry@aut.ac.nz Abstract: This paper presents findings from the author’s PhD (Henry, 2012), which explored entrepreneurship in screen production, with a focus on Māori, the indigenous people of New Zealand, and the ways those findings are being incorporated into Māori media education, to stimulate and nurture Māori entrepreneurship. Māori are more likely than any other ethnic group in New Zealand to be incarcerated, under‐employed, under‐educated and living in low socio‐ economic communities. However, there is one arena in which Māori have flourished in recent decades, as part of the evolution of the Māori screen industry. The PhD, entitled ‘Te Wairua Auaha: emancipatory Māori entrepreneurship in screen production’, explored, analysed and developed theory about Māori in screen production, and how the identity and experiences of participants combined to shape their careers and entrepreneurial intent. The study comprised two phases, an on‐line survey of a sample of Māori practitioners, which explored their backgrounds, career pathways, entrepreneurial intent, influences, and levels of cultural identity and self‐efficacy. The second phase involved in‐depth interviews with ten Māori producers who owned companies that had produced a significant body of Māori‐centric work, including in the Māori language. It was found that both groups of participants had been influenced by people and places that had nurtured their self‐belief, their passion for telling stories and their desire for self‐determination. That is, taking control of Māori story‐ telling in screen production by creating organisations in which they could enact authentic identities and inwardly‐derived values. The outcomes of the research comprised a written PhD thesis and documentary, which enabled participants to share their narratives in their own words. Wairua Auaha, which means ‘creative spirit’, was found to embody the creative and entrepreneurial spirit of Māori in screen production, and is manifest in the desire to take control of the story‐telling process and to participate in the revitalisation of Māori language and culture, both of which have diminished over the last two hundred years. The findings of the PhD study have implications for those involved in educating Māori for screen production, who believe they have a role to play enhancing the self‐belief, story‐telling skills and capacity for self‐ determination of Māori students, coming from under‐privileged and impoverished backgrounds. This paper looks at the ways that Te Ara Poutama, the Faculty of Māori Development at Auckland University of Technology (AUT), are incorporating the findings of the PhD, the principles of Wairua Auaha, into the curriculum of the Bachelor of Māori Development, Māori Media major, preparing students to work in the Māori screen industry, which in 2012 generated approximately $50 million worth of film and television production, employing approximately one thousand Māori. Thus, this paper contributes to our understanding of how theory can be directly applied to education and training for Māori in screen production. Keywords: Māori entrepreneurship, indigenous, screen production, theory and application Māori

1. Introduction This paper presents findings from the author’s PhD (Henry, 2012), which explored entrepreneurship in screen production, with a focus on Māori, the indigenous people of New Zealand, and the ways those findings are being incorporated into Māori media education, to stimulate and nurture Māori entrepreneurship. It discusses the ways that theory is informing practice in the delivery of a Māori media programme at Auckland University of Technology (AUT). First, the paper provides an overview of Māori people, society and history. The author is a Māori woman, with experience as a screen industry practitioner, who is both the author of this research on Māori entrepreneurship in screen production, and the Programme Leader of the Māori media programme at AUT.

2. Māori society and history Māori are the indigenous people of Aotearoa New Zealand, one of the Polynesian peoples who traversed the South Pacific over thousands of years, using knowledge of astronomy, winds, weather, and bird migration, without recourse to written text or mathematical equation, and bolstered by the sturdy outrigger canoe (Davidson, 1984). Whilst Māori brought with them an existing Polynesian language and culture, over the centuries, both of these were adapted to the new and often harsher environment. Maori society was tribal, a kinship‐based society, founded on a political economy which Mauss (1990) described as one of gift exchange and reciprocity. Traditional beliefs honoured kinship, spirituality and guardianship, values that exemplified the connectivity between all living things, and ancestral linkages to the

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Ella Henry gods from whom humankind originated. Māori communities existed around the community centre, the Marae, which was the gathering place where all community business was conducted (Henare, 2001). Kaupapa Māori is a term that is used by Māori to describe this specifically Māori‐centric philosophy and worldview. It can be viewed as both a set of beliefs (that which is tika, or true), and concomitant social practices (tikanga). For example, the importance of the collective is exemplified by whanaungatanga, which means kinship, and is practiced as a set of tikanga, protocols to enhance kinship and solidarity. The intimate relationship with the spiritual dimension is reflected in wairuatanga, spirituality, expressed in a wide range of tikanga, including karakia (communion) and acknowledgement of wāhi tapu (sacred places). Other key elements of Māori philosophy include tapu (sacredness), mauri (life force) and mana, or power and prestige (Henry and Pene, 2001). Marsden stated that, “We can be nothing; we can do nothing, without mana, or power. Our mana is actualisation, the realisation of our tapu... All the mana of the human person can be seen as coming from the three sources‐ mana whenua from the power of the land, mana tangata from our bond with the people, and mana atua, from our bond with the spiritual powers” (cited in Shirres, 1997, p. 18). It has been estimated that at the time of first contact, the population of Māori was approximately 100,000 (Wilson, 2012). The first recorded arrival was Dutchman Abel Tasman in 1642. Captain James Cook arrived in New Zealand in1769. Whilst in Tahiti, Cook had taken on board Polynesian navigator, Tupaia, who facilitated communications with Māori (Druett 2011). Two months after Cook, Frenchman De Surville arrived, bringing pigs and chickens, nails, axes and other tools previously unknown to the Māori, which would have been a strong incentive to maintain good relations with these pale‐skinned visitors. Wilson (2012) states that, “From the 1790s, Māori produced pork and potatoes for this trade”. The first settlement of Europeans was Kororāreka, now known as Russell. Overall, relationships between Māori and th Pākehā flourished in the early 19 Century. One missionary in New South Wales, Samuel Marsden was keen to set up a permanent mission in New Zealand. He wrote that the Māori possessed, “many excellent qualities of the heart that would do honour to the most civilised people” (Nicholas, 1817, p.8). After meeting Northern Chief, Hongi Hika in 1814, in Sydney, the Reverends Marsden, Kendall, Hall, King and Nicholas were dispatched to New Zealand. By the 1830s Māori were actively engaged in international trade. According to Petrie (2002), in 1830, 28 ships made 56 voyages between Sydney and New Zealand carrying Maori agricultural produce. In 1835, a consortium of chiefs requested the British Crown to recognise their national flag and acknowledge their Declaration of Independence, as symbols of nationhood, and to ensure protection of their vessels in international waters. The British Parliament did so in 1836 (Henare, 2001). Then, four years later, Governor Hobson arrived to promote a Treaty with Māori, guaranteeing protection of New Zealand as a formal British th Colony. A Treaty was signed on February 6 , 1840 at Waitangi, the founding document of New Zealand. The Māori language version of the Treaty ceded ‘governorship’ (kawanatanga) to Queen Victoria. The English language version ceded ‘sovereignty’. It is the opposing language of these two versions of the Treaty which has resulted in outright warfare between Māori and the Crown and an ongoing legacy of antipathy and grievance between Māori and Pākehā. The breakdown in relations between the tribes and the early governors of New Zealand is well recorded (Scott, 1975; Adams, 1977; Orange, 1989; Durie, 1998). It was only a matter of months before the chiefs realised their relationship with the British Crown was not to be the mutually beneficial partnership they had envisaged, but instead one of British control over trade, legislation, jurisdiction and all other social institutions. Māori protest eventually resulted in the Land Wars of the 1850s‐1860s (Belich, 1987). Whilst Māori proved to be worthy opponents, ultimately the sheer force of the British Crown wore down Māori resistance. From the late 1800s until the mid‐1900s Māori progressively suffered the consequences of a colonised and conquered people. The economic dominance of the new settlers was reinforced by repressive legislation, military and judicial might, which combined to undermine the collective ownership of resources, and served to individuate and expropriate Māori lands. The results of this economic oppression have been devastating for Māori. However, more subversive and odious has been the socio‐cultural oppression. This has resulted not just in the loss of land by stealth, and the loss of people through disease, poverty and despair, but the loss of language and diminution of culture. Over the same period, European settlers grew in wealth and opportunity, on the backs of the expropriated land and the diminishing mana of the Māori (Walker, 1990).

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Ella Henry In the aftermath of World War II, Māori began an unprecedented urban migration. Whilst this further served the needs of assimilation it also introduced increasing numbers of traditionally isolated and rural Māori to the institutions, technologies and opportunities of the Post War economy. Māori became educated, embourgoisened and empowered to the extent that by the 1970’s the Māori Renaissance was borne. The Māori struggle was founded on demands for Māori sovereignty, acknowledgement of the Treaty of Waitangi as the constitutional basis of New Zealand society, and demands for acknowledgement of Treaty grievances (Awatere, 1984). A Māori Land March in 1975 brought together diverse groups of activists and Māori organisations to highlight the plight of Māori people. In the same year, the National government created a Tribunal to look at Treaty grievances. However, it was not until the Labour government of 1984 that the Waitangi Tribunal was given the power to look retrospectively to 1840. Since 1985 successive New Zealand governments have devolved hundreds of millions of dollars to tribes, for settlement of grievances arising from breaches of the Treaty of Waitangi. Māori have grown in political strength and unity, particularly since the introduction of proportional representation in 1996. However, the majority of Māori still languish economically, socially and culturally (Census, 2006). There is, however, recognition by growing numbers of New Zealanders that an understanding of Māori society and culture adds to, rather than detracts from New Zealand society. It is out of this milieu that the Māori screen industry has evolved (Henry and Wikaire, 2013).

3. The Māori screen industry The New Zealand Government remains committed to Māori broadcasting as a consequence of the outcomes of a Treaty grievances taken to the Waitangi Tribunal. The findings of the Māori Broadcasting Claim (WAI 176) and Te Reo Māori Claim (WAI 11) have been pivotal in the Crown accepting their responsibility for the revitalisation of Māori language and culture through broadcasting. According to the WAI 176 Summary Report (1994), “The claimants alleged Treaty breaches by the Crown in its broadcasting policies, and they sought, inter alia, that the Broadcasting Act 1989 and the Radiocommunications Act 1989 be amended to ensure that Māori, their language, and their culture had a secure place in broadcasting in New Zealand”. Since 1986 a number of recommendations have been implemented by successive governments. For example, in 1996 Aotearoa Television Network (ATN) was set up, as a national television channel, but survived for less than two years, closing in a shroud of accusations and acrimony. In the aftermath of the dissolution of ATN, the then National Government consulted with the Māori broadcasting community, which resulted in a series of recommendations to ensure a more robust Māori Television Strategy (Māori Television, 1998). Finally, in March 2004, the Māori Television Service was created, and it produces over 1,000 hours of programming annually, to protect and enhance ‘te reo me ngā tikanga Māori’, Māori language and culture. Māori have had a varying relationship with screen production. In the earliest years of film, Māori were more likely to be the objects of European curiosity, which was reflected in the images of Māori culture and society that were conveyed to the wider world. It was not until the 1940s that Māori began to tell our own stories on film. It was similar in television, which was first introduced to New Zealand in 1960. Again, in the early years, Māori were more likely to be the objects of enquiry, rather than the authors of our stories. It was the work of stout‐hearted individuals, who broke down the barriers, often with the help of supportive Pākehā in positions of power, which has created the domain we can now refer to as the Māori screen industry. According to the 2006 Census, there were almost one thousand Māori employed in the screen industry, approximately 10% of the industry, whilst Māori comprise approximately 15% of the New Zealand population. The Screen Industry Survey (Statistics, 2007) noted that: “In 2007, total revenue for the New Zealand screen industry was $2,447 million, a decrease from $2,581 million in 2006. Television broadcasting was the most significant sector in 2007, accounting for $1,081 million of total revenue, a slight increase compared with $1,071 million in 2006”, (2007, p.3). Whilst the abovementioned report provides an invaluable overview of the industry, there is little specific data about Māori screen production and capacity. That information has to be synthesised from other data, including the amounts contributed by funding agencies for the Māori Television Service and other Māori film and television projects. According to Akuhata‐Brown & Henry (2009) in 2007 approximately $43 million of Crown funding had gone into projects produced by a Māori‐owned production company, and/ or written and directed by Māori, for film or television. So, Māori screen production is a very

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Ella Henry small part of the total screen industry. However, it can still be viewed as a significant contributor to Māori economic development, and more importantly to aspirations for revitalisation of language, culture and authentic Māori authorship.

4. Te Wairua Auaha This study was the first in‐depth analysis of Māori in screen production, in which an exploration of entrepreneurship was a primary objective. The author conducted the research between 2009 and 2011. It involved analysis and theory development about Māori participation in screen production, and how Māori identity and experiences combined to shape their careers and entrepreneurial intent. The literature review drew together a disparate range of philosophical and intellectual disciplines. Kaupapa Māori literature informed the cultural context and research paradigm (Smith, 2001). Māoritanga is seen as the foundation of Māori knowledge and belief systems (Royal, 2003). The ‘insider research’ literature was explored because the researcher was both an academic and a screen industry practitioner (Wicks & Rowland, 2009). Other important contributions were drawn from identity theory (Houkamau, 2007), career and boundaryless career theory (Moore, 2000; Arthur et al, 1999), and entrepreneurship theory (Dees, 1998; Wadeson, 2006). The latter led to a more extensive review of social (Martin & Osberg, 2007), indigenous (Peredo et al, 2004; Frederick & Henry, 2005; Dana & Anderson, 2008), and emancipatory entrepreneurship O’Neill and Ucbasaran (2010). This body of knowledge provided the framework for those things that were, and were not known, about Māori entrepreneurship in screen production, and a pathway for the research design and methods. The research comprised two phases, complementary quantitative and qualitative components. The first involved an on‐line survey of Māori screen practitioners. This quantitative study provided an unprecedented insight into the backgrounds, influences, career pathways and entrepreneurial intentions of a broad sample of participants, identified through the personal networks of the researcher, and from existing databases (e.g. The Brown Pages, 2008). The database yielded a pool of 182 potential participants, and 51 completed surveys. This is, to date, the largest quantitative study of Māori screen practitioners. Major findings of the demographic data include:

Participants were predominantly female

Though they came from a wide variety of tribal and regional backgrounds, the majority lived and worked in either Auckland or Wellington

Most had worked extensively in both film and television

Those who had spent the longest time in the industry, were more likely to have worked in the widest range of jobs

Few had trained specifically, the majority learning their craft ‘on the job’

All had experienced strong and positive influences to enter and remain in the industry, from parents, family, and/or colleagues

The majority had strong and positive feelings about their Māori identity, and their belief that working in the Māori screen industry was both important and rewarding

A series of questions related to their self‐belief (Chen et al, 2001), the self‐rated strength of their Māori identity and their entrepreneurial intent (based on company, employer and GST tax status). When the data was cross‐tabulated it was found that there was a statistically significant correlation between the strength of Māori and entrepreneurial variables. Thus, those who were more likely to know about their language and culture were also more likely to manifest entrepreneurial and employer characteristics. The second phase of the study involved a series of in‐depth interviews with Māori who owned production companies that have produced a significant body of Māori‐centric work, over an extended period of time. This group, though small, were and remain very influential in producing film and television for, with and by Māori. In 2010, there were twenty companies owned by Māori that met these criteria, and ten of these consented to be interviewed. These interviews were conducted and filmed by the author over a twelve month period. They were an equal mix of male and female, ranging in age from 32 to 60 years, with a variety of educational backgrounds, marital status, sexual orientation and knowledge of Māori language and culture. They came from different tribal backgrounds, but all their companies were based in Auckland. The interviews highlighted these

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Ella Henry differences, but the similarities were equally pronounced and informed the propositions that underpinned the theory of creative spirit in Māori screen production. Despite their differences, each of the participants experienced the following, outlined here as both propositions and principles:

People who shaped, informed, empowered and encouraged their life choices, career pathways and entrepreneurial endeavours (glossed as Mana Tangata);

Places that nourished and sheltered them; be they birth‐places, schools, communities, work‐places, and other sites that enhanced their achievements in their chosen fields (glossed as Mana Whenua);

People and places that infused them with a passion for story‐telling, creative careers and entrepreneurial endeavour (glossed as Mana Atua);

People and places that made them believe that self‐determination for Māori is an important aspiration, that taking control of Māori story‐telling was important, as was the drive to create organisations in which they could enact authentic identities and inwardly‐derived Māori values (glossed as Mana Motuhake);

Wairua Auaha is the expression of emancipatory Māori entrepreneurship. Story‐telling is a visible sign of emancipatory Māori entrepreneurship, which is reflected in the creation of production companies that are underpinned by the desire to take control of the story‐telling process, to participate in the revitalisation of Māori language and culture, and the achievement of tino rangatiratanga (self‐determination) through creative enterprise. The notion of creative spirit, Wairua Auaha describes the essence of the invincible Māori‐ness of a whānau/community of extraordinary talent that drives their entrepreneurial endeavour. This PhD was presented as a thesis‐exegesis, a written work and documentary. The documentary drew on the narratives from Māori producers. It provided a research outcome that enables these individuals to tell their stories in their own ways to as wide an audience as possible.

5. Application of theory The author is a lecturer in the Faculty of Māori Development, Te Ara Poutama, within Auckland University of Technology (AUT). It offers a Bachelor of Māori Development, with a Māori Media major. This research has informed the author’s professional practice, and underpinned her aspirations for further development of the Māori Media programme. The theory‐model of emancipatory Māori entrepreneurship in screen production has provided a framework for courses in creative writing, screen production and business, in ways that reinforce Māori identity, self‐efficacy and entrepreneurship. The challenge for those involved in Māori media education is to concurrently deliver Kaupapa Māori, philosophical foundations alongside technical skills, whilst nurturing self‐belief and creativity. However, universities, by their nature, are often large, formal organisations and Auckland University of Technology is no exception. In 2011, there were over 26,000 students enrolled at AUT, in five Faculties (Culture and Society; Business and Law; Design and Creative Technologies; Health and Environmental Science; and Māori Development). Te Ara Poutama is the smallest Faculty. Whilst 1,500 Māori study at AUT, only one third of those are enrolled in Te Ara Poutama. The Faculty provides multi‐disciplinary courses at graduate and post‐graduate level, with Māori‐language being the cornerstone of all programmes. It is also the host of the Marae (community centre), Ngā Wai o Horotiu. This Marae is pan‐tribal, and is the cultural hub of the University, where visitors and new staff and students are formally welcomed, in a traditional Pōwhiri (welcome ritual), where memorial services are held for those who have passed away, where Māori‐language courses are taught, and for Hui (formal meetings), Noho Marae (total immersion courses), and Wānanga (intensive programmes lasting more than one day). There are two ‘majors’ available to Te Ara Poutama undergraduate students: the Bachelor of Arts (Māori Development), with a focus of history, social science, business and political studies and the Bachelor of Māori Development (Māori Media). The latter is taught in conjunction with the School of Communications, where radio and television production are taught. Within Te Ara Poutama students focus on Māori language, culture, history and philosophy, this is complemented with ‘digital technologies’ and ‘new media’ courses.

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Ella Henry Given the small size of the Faculty, and the limited resources, the challenge has been to provide students with opportunities to meet, interact with, and learn from people and places that can infuse their Wairua Auaha. In recent years this has been achieved through a variety of endeavours that are shaped by the Wairua Auaha principles, to introduce students to people and create spaces, which nurture the passion for story‐telling and self‐determination. Strategic relationships fostered between AUT and the Māori production community: Ngā Aho Whakaari, the association of Māori in screen production. This relationship has resulted in the hosting of their National Hui at the Marae in 2008, 2010, 2012 and 2013. At these events students are able to interact with a wide range of Māori screen practitioners and representatives of government, broadcasting and funding agencies. Wairoa Māori & Indigenous Film Festival The Wairoa Māori & Indigenous Film Festival has been held for the last seven years in the Wairoa community, bringing renowned indigenous film‐makers to New Zealand to screen their works alongside Māori film‐makers. Te Ara Poutama has provided scholarships for Māori Media to attend the Wairoa Māori & Indigenous Film Festival. In 2012 students who attended met the award‐winning Taiwanese producer of the film ‘Voices in the Clouds’, and an ensuing invitation for the students to participate in a cultural exchange to Taiwan in 2013. Matariki Festival Trust Matariki marks the start of the Māori New Year, which occurs in June‐July each year when the Matariki/Pleiades Constellation reappears in the night sky, which coincides with the beginning of the mid‐ winter planting season for traditional Māori. The Matariki Festival Trust is funded by the Auckland Council to organise events that celebrate this event, and Te Ara Poutama will host a screen symposium in 2013, in collaboration with the Trust. Programme Development that reinforces academic, creative and technical skills: Within the Māori Media major, Māori language, history and culture papers are complemented by applied technology and creativity courses. Four of these have a specific focus on media skills underpinned by Māori philosophy. These are:

Year 1: Kaupapa Māori Screen Production, an introduction to Māori philosophy and values, as they apply to story‐telling and screen production

Year 2: Tuhituhinga Māori: Creative Writing

Year 2: Māori Media Project, in which students write and product a Māori‐themed production

Year 3: Cooperative Education, students engage in an internship in a Māori organisation and develop a strategy or media outcome for that organisation

Māori Media Major graduates have been extremely successful, finding work in Māori production companies and Māori broadcasters. Some have already set up their own businesses in screen and digital production. These programmes and courses, supplemented by strategic relationships, are still in their infancy, but they hold great promise for education of Māori screen practitioners and production that is underpinned by Māori philosophy and values, and which contributes to self‐determination for Māori. The Wairua Auaha Model provides a theoretical construct against which ideas can be tested, including how and when the ‘creative spirit’ of Māori entrepreneurship can be enhanced, and how we can support future generations so their Wairua Auaha is both ignited and strengthened. This Model provides an innovation in entrepreneurship education for Māori, which may be applied to other indigenous and minority communities.

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Chiefs of industry: Māori tribal enterprise in early colonial New Zealand. Auckland: Auckland University Press. Royal, C. (2003). The Woven Universe: selected writings of Reverend Māori Marsden. Masterton: Published by Estate of Reverend Māori Marsden. Scott, D (1975). Ask That Mountain: The Story of Parihaka. Wellington: Heinemann. ISBN 0‐14‐301086‐7 Statistics New Zealand. (2007). Screen Industry Survey. Retrieved from: http://www.stats.govt.nz/browse_for_stats/industry_sectors/film_and_television/screen‐industry‐2007.aspx Shirres, M. (1997) Te Tangata: The human person. Auckland: Accent Publications Smith, L. T. (1999). Decolonising methodologies, research and indigenous peoples. Dunedin, New Zealand: University of Otago Press. Wadeson, N. (2006). Cognitive aspects of entrepreneurship: Decision‐making and attitudes to risk. In M. Casson, B.Yeung, A.Basu, & N.Wadeson, (Eds),The Oxford Handbook of Entrepreneurship, Oxford: Oxford University Press. Waitangi Tribunal. (1994). Māori Broadcasting Claim Report Summary. Waitangi Tribunal: Wellington, New Zealand. Waitangi Tribunal. (1986). Te Reo Māori Claim Report. Waitangi Tribunal, Wellington, New Zealand. Walker, R. (1990) Ka Whawhai tonu matou: Struggle without end. Auckland: Penguin Books. Wicks, D. A., Rowland, D. (2009). Qualitative Research in the New Century: Map points in insider research. Proceedings rd from the Canadian Association for Information Science Conference, Ontario. Retrieved on May 3 2010 from: http://www.cais‐acsi.ca/proceedings/2009/Wicks_Roland_2009.pdf Wilson, C. (2012). New Zealand History. Ministry for Culture and Heritage. Retrieved from: http://www.nzhistory.net.nz/media/photo/charles‐wilson, updated 20‐Dec‐2011

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Research on the Trust Governance in the Venture Capital Syndication Heyin Hou1 and Weixing Qu2 1 School of Economics and Management, Southeast University, Nanjing, China 2 Kaifeng Subbranch, China Construction Bank, Kaifeng, China heyinhou@hotmail.com qwx0109@163.com Abstract: Venture capital is a risky and long‐term equity investment activity, and venture capitalists widely use the syndication, a jointly investment model, to finance entrepreneurial start‐ups. And, the syndication’s successful operation is inseparable from trust between participants. Our paper focuses on trust governance between the leader and the follower, players in the syndication, through constructing an evolutionary game model. In the model, both players adopt Replicator‐ Dynamics‐based learning rules and their strategy space is {Trust, No‐Trust}. The trust governance mechanism contains two aspects: punishment and reward, both of whose intensity are categorized into three levels, low, middle, and high level. After comprehensively computing and comparing players’ evolutionary stable strategy (ESS), we find relationships between the trust governance mechanism and players’ ESS. If both of the intensities of reward and punishment are at low level, then both the leader and the follower choose “No‐Trust”. If both of the intensities of reward and punishment are at high level, then both the leader and the follower choose “Trust”. If the intensity of punishment is at low or middle level, and the intensity of reward is at middle level, then the leader chooses “Trust” and the follower does not. In the intensity of punishment is at middle level, and the intensity of reward is at low or middle level, then the leader chooses “Trust” and the follower does not. If the intensity of punishment is at low level and the intensity of reward is at high level, or if the intensity of punishment is at high level and the intensity of reward is at low level, player’s ESS combination shows a rather varied changes. Keywords: venture capital syndication, trust governance, replicator dynamics, evolutionary stable strategy (ESS)

1. Introduction Venture capital has become a major funding source for many start‐ups in the US and other developed countries (Han 2008). However, imported into early stage start‐ups with perceived long‐term and high‐speed growth potential, venture capital typically entails high risk for investors. So, venture capitalist, who provides venture capital to promising start‐ups, should take some mechanisms to lessen or avoid diversified risks. Syndication, when a group of venture capitalists work together to provide funds for promising start‐ups, is a widely taken risk‐aversion mechanism by venture capitalists (Lerner 1994; Wright and Lochett 2003). As a jointly investment process, the syndication promotes specialization and cooperation among venture capitalists in different regions and even in different countries. Such that, the syndication greatly extends venture capitalists’ investment opportunity and scope, and rapidly improves the venture capital industry’s operating efficiency. The syndication process is a double‐edged sword, bringing new issues, such as adverse selection and moral hazard, to syndicated venture capitalists. The syndication contract in venture capital industry is a document not defining participants’ actions but defining their rights (Wright and Lochett 2003). In view of these negative issues, scholars have begun to study governance mechanisms of syndication and test their effectiveness in practice. For example, trust between participants play key roles in the venture capital syndication. With information asymmetry, the trust mechanism can suppress opportunistic behaviours, and, to some extent, improve confidence between participants (Beamish and Banks 1987). The trust mechanism is an effective complement for the control mechanism, and the trust mechanism and the control mechanism work together to improve participants’ confidence in the syndication process (Das and Teng 1998). Using hand‐collected data on European venture capital, Bottazzi, et al (2012) show that, in a micro‐economic environment where trust is exogenous, the Eurobarometer measure of trust among nations significantly affects financial investment decisions.

303

Heyin Hou and Weixing Qu Venture capital syndication network is based on trust between network ties; inviting other venture capitalists to join syndication is aimed at being invited to join a profitable project in the future (Zheng 2004). When investing a high‐risky entrepreneurial project, participants prefer to invite more reliable partners to join the syndication (Sorenson 2008). Trust, which is based on emotional exchange or other relationships, between venture capitalists, changes with their position in the network (Smith and Lohrke 2008). Through the hostage exchanges, information asymmetry could be resolved to some extent; this could improve trust between venture capitalists. When the follower believes that leader’s emphasis on future deal flows can constraint her opportunistic behaviour, the follower is willing to “trust” the leader and join the leader’s syndication (Kuan 200). Although trust between participants play key roles in the venture capital syndication, the trust governance mechanism, which is indispensable and implicit, has not yet attracted enough attention and research, both in theory and in practice. Our paper contributes to a normative research on the trust governance in the venture capital syndication, through constructing an evolutionary game model. In the model, both players, the leader and the follower, adopt Replicator‐Dynamics‐based learning rules and their strategy space is {Trust, No‐Trust}. The trust governance mechanism contains two aspects: punishment and reward, both of whose intensity are categorized into three levels, low, middle, and high levels. After comprehensively computing and comparing players’ evolutionary stable strategy (ESS), finally, we find relationships between the trust governance mechanism and players’ ESS.

2. Modelling In the venture capital industry, all venture capitalists are divided into two groups, the leader group and the follower group, where the leader invites the follower to join syndication, simultaneously or sequentially investing an entrepreneurial project together. We suppose that the syndication in our paper adopts the “sequential investment” pattern. That is, into the same entrepreneurial project, the leader invested capital before the follower. However, investment timing into the entrepreneurial project is rather critical. So, the sequential investment pattern must exacerbate information asymmetry between players. And, this would encourage players to take opportunistic behaviours, such as conspiracy or free‐riding, grabbing abnormal returns for self and damaging other side’s interests.

2.1 Basic game model In the syndication, the leader tends to invite more than one follower. However, we assume that there is only one leader and one follower joining the syndication. That is, we will just focus on trust between a leader and a follower in syndication. 2.1.1 Players’ strategy space We assume that players’ strategy space is S ≡ {Trust,No-Trust} . If a player chooses “Trust”, then she would consider other player’s benefit and believe that the other side also would consider his benefit. That is, she would not take opportunistic behaviours. If a player chooses “No‐Trust”, then she only pursues her own benefit optimization without considering the other player’s benefit. That is, she would take opportunistic behaviours. If one player chooses “Trust” and the other player chooses “No‐Trust” at the same time, then the former player would bear a loss, R S , and the latter would seize the corresponding gain, R S . 2.1.2 Entrepreneurial project’s net income For the entrepreneurial project, jointly financed by the lead venture capitalist and the follow venture capitalist, its net income is determined by both sides’ effort.

304

Heyin Hou and Weixing Qu If both players trust each other at the same time, then the project would produce the biggest net income, denoted by R H ; If one player chooses “Trust” and other player does not, then the project would produce a medium net income, denoted by R M ; If both players do not trust each other at the same time, then the project would produce the smallest net income, denoted by R L . Overall, we assume that: R H > R M > R L (1) Before devoting their efforts, the leader and the follower sign an ordinary equity distributing the entrepreneurial project’s net income. That is, the leader’s ratio is α and the follower’s ratio is 1 − α . Due to that leader usually displays more crucial roles and demands a higher residual claim, we assume that: α ∈ (1 2,1] . Basic Game Model without the Trust Governance Mechanism After assuming the project’s net benefit and its distribution contract, we get a game model (see Figure 1). In the basic game, we furthermore assume that: ⎧α R M + R S > α R H ⎪α ⎪ RL > αRM − RS (2) ⎨ 1− α ) R M + R S > (1 − α ) R H ⎪( ⎪(1 − α )R L > (1 − α ) R M − R S ⎩ Then, we define that: R C1 ≡ R H − R M and R C 2 ≡ R M − R L . And, because that α ∈ (1 2,1] , Eq. (2) is equivalent to: ⎧R S > α R C1 (3) ⎨ ⎩R S > α R C 2 Under assumptions (1) and (3), the basic game is a typical “Prisoner’s Dilemma Game”. And, it’s Nash Equilibrium (NE) is that both players choose “No‐Trust” and realize the worst payoff profile (α R L,(1 − α )R L ) . Leader

Follower Trust

No‐Trust

Trust

α R H ， (1 − α ) R H

α R M − R S ， (1 − α ) R M + R S

No‐Trust

α R M + R S ， (1 − α ) R M − R S

α R L ， (1 − α )R L

Figure 1: Basic game model without the trust governance mechanism 2.1.3 Basic game model with the trust governance mechanism How to overcome the Prisoner’s Dilemma, depicted in Figure 1? We introduce the trust governance mechanism. The trust governance mechanism contains two aspects: punishment for choosing “No‐Trust” and reward for choosing “Trust”. Here, reward may include performance compensation, reputation accumulation, future cash flow increase, etc. and, punishment may include non‐performance penalty, reputation loss, future cash flow loss, etc. We assume that: if one player chooses “Trust” and the other chooses “No‐Trust” at the same time, then the former player would gain a reward, denoted by E , and the latter player would bear a punishment, denoted by C . And, if both of players choose “Trust” or “No‐Trust” at the same time, there is no punishment or reward for them. In reality, players’ strategy‐choosing is not completely transparent and observable. That is, the trust governance mechanism does not run well all the time. So, we assume that the probability that a player’s strategy‐choosing is observed is θ .

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Heyin Hou and Weixing Qu With the trust governance mechanism, the basic game depicted in Figure 1 would be changed to be the game shown in Figure 2.

Leader

Follower Trust

No‐Trust

Trust

α R H ， (1 − α ) R H

α R M − R S + θ E ， (1 − α ) R M + R S − θ C

No‐Trust

α R M + R S − θ C ， (1 − α ) R M − R S + θ E

α R L ， (1 − α )R L

Figure 2: Basic game model with the trust governance mechanism For categorizing the intensities of punishment and reward, we define following parameters: R S − α R C1 * (4) C1 ≡

C2 ≡ *

R S − (1 − α ) R C1

θ R S − α RC2 * (6) E1 ≡ θ R S − (1 − α ) R C 2 * E2 ≡ θ

(5)

(7)

Obviously, C 1* < C 2* , E 1* < E *2 , just because that α ∈ (1 2,1] . So, both the intensities of punishment and reward can be categorized into three levels. If C < C 1* , then the intensity of punishment is called at low level; if C 1* < C < C *2 , then the intensity of punishment is called at middle level; and, if C > C *2 , then the intensity of punishment is called at high level. If E < E 1* , then the intensity of reward is called at low level; if E 1* < E < E *2 , then the intensity of reward is called at middle level; and, if E > E *2 , then the intensity of reward is called at high level.

2.2 Learning rules based on the replicator dynamics The venture capital industry is a complex social‐economic system, and the syndication is a complex investment process. So, it is reasonable to assume that all venture capitalists, whether leaders or followers, are boundedly rational. Evolutionary game theory is an extension of the classical paradigm towards bounded rationality. And, an evolutionary game model is made complete by postulating the game dynamics, i.e., the learning rules that describe the update of strategies in the population (Szabó and Fáth 2007). On the macroscopic level, by far the most studied learning rule is the replicator dynamics, which was introduced originally by Taylor and Jonker (1978). The replicator dynamics has exceptional status in the models of economic evolution. We also use the replicator dynamics to describe learning rules of players, the leader and the follower. We assume that, in the leader group, the ratio of players who choose “trust” is p ( t ) , and the ratio of players who choose “no‐trust” is 1 − p ( t ) . And, we assume that, in the follower group, the ratio of players who choose “trust” is q ( t ) , and the ratio of players who choose “no‐trust” is 1 − q ( t ) . With the trust governance mechanism, let π L1 to denote the leader’s expected payoff when she chooses “Trust”, let π L 2 to denote the leader’s expected payoff when she chooses “No‐Trust”, and let π L to denote the leader’s overall expected payoff.

306

Heyin Hou and Weixing Qu

π L1 = q ( t ) α R H + (1 − q ( t ) ) (α R M − R S + θ E )

(8)

π L 2 = q ( t )(α R M + R S − θ C ) + (1 − q ( t ) ) α R L

(9)

π L = p ( t ) π L1 + (1 − p ( t ) ) π L 2

(10)

Then, the leader’s learning rule based on the replicator dynamics is: dp ( t ) = p ( t )(π L1 − π L ) dt

{

}

= p ( t ) (1 − p ( t ) ) ⎡⎣(α R C1 + θ C ) − (α R C 2 + θ E ) ⎤⎦ q ( t ) − ( R S − α R C 2 − θ E )

(11)

With the trust governance mechanism, let π F 1 to denote the follower’s expected payoff when she chooses “Trust”, let π F 2 to denote the follower’s expected payoff when she chooses “No‐Trust”, and let π F to denote the follower’s overall expected payoff. π F 1 = p ( t )(1 − α ) R H + (1 − p ( t ) ) ⎡⎣(1 − α ) R M − R S + θ E ⎤⎦ (12)

π F 2 = p ( t ) ⎣⎡(1 − α ) R M + R S − θ C ⎦⎤ + (1 − p ( t ) ) (1 − α )R L

π F = q ( t ) π F 1 + (1 − q ( t ) ) π F 2

(13)

(14)

Then, the follower’s learning rule based on the replicator dynamics is: dq ( t ) = q ( t )(π L1 − π L ) dt

{{

}

= q ( t ) (1 − q ( t ) ) ⎡⎣(1 − α ) R C1 + θ C ⎤⎦ − ⎡⎣(1 − α ) R C 2 + θ E ⎤⎦ p ( t ) − ⎡⎣R S − (1 − α ) R C 2 − θ E ⎤⎦

(15) Dynamics (11) defines the leader’s learning rule and dynamics (15) defines the follower’s learning rule. Based on these two dynamics, we would comprehensively analyze the leader’s and the follower’s evolutionary stable strategy (ESS).

3. Players’ evolutionary stable strategy 3.1 Analysis about the Leader’s ESS Let L ( p ) ≡

dp ( t ) dt

, and, define the following equation:

F ( q ) ≡ ⎡⎣(α R C1 + θ C ) − (α R C 2 + θ E ) ⎤⎦ q ( t ) − ( R S − α R C 2 − θ E )

(16)

Then, Eq. (11) would be transformed as: L ( p ) = p (1 − p ) F ( q ) (17)

According to the dynamics (17), if F ( q ) = 0 , then L ( p ) ≡ dp ( t ) dt always be 0, which means that all p ∈ [0,1] are stable states; if F ( q ) ≠ 0 , then p = 0 and p = 1 are stable states. More precisely, if F ( q ) > 0 ,

then p = 0 is the evolutionary stable strategy; if F ( q ) < 0 , then p = 1 is the evolutionary stable strategy.

307

Heyin Hou and Weixing Qu Table 1: Value ranges of F ( q ) E C

E < E 1*

C < C 1*

F (q ) < 0 If q > q , then F ( q ) > 0 . If q < q , then F ( q ) < 0 . *

C >C

If q > q , then F ( q ) < 0 .

If q < q , then F ( q ) > 0 .

F (q ) > 0

If q > q , then F ( q ) > 0 .

* 2

E > E *2

* C < C < C2 * 1

* * E1 < E < E 2

If q < q , then F ( q ) < 0 . *

For obtaining the leader’s ESS, F ( q ) should be clarified. All possible value ranges of F ( q ) are determined by the combination of punishment and reward intensities, see Table 1. For example, when C < C 1* and E < E 1* , then F ( q ) < 0 . When C > C *2 and E < E 1* , if q > q * , then F ( q ) > 0 , and if q < q * , then F ( q ) < 0 .

Table 2: The leader’s ESS E C

E < E 1*

C < C 1*

p = 0

* * E1 < E < E 2

E > E *2

If q > q , then p = 0 .

If q < q , then p = 1.

p = 1

If q > q , then p = 1.

* * C1 < C < C 2

If q < q , then p = 0 . *

If q > q , then p = 1. *

C > C *2

If q < q , then p = 0 . *

Based on values of F ( q ) , depicted by Table 1, we get all possible ESSs of the leader according to different combination of punishment and reward intensities, see Table 2. For example, when C < C 1* and E < E 1* , the leader’s ESS is p = 0 . When C > C *2 and E < E 1* , if q > q * , then the leader’s ESS is p = 1, and if q < q * , then the leader’s ESS is p = 0 .

Table 3: Value Ranges of q * . E C

E < E 1*

* * E1 < E < E 2

E > E *2

C < C 1*

* q ∉ ( 0,1)

* q ∈ ( 0,1)

* * C1 < C < C 2

q ∈ ( 0,1)

q ∉ ( 0,1)

C > C *2

* q ∈ ( 0,1)

* q ∉ ( 0,1)

In Table 1 and Table 2, there is an important parameter q * , which is defined as follows:

* q ≡

R S − α RC2 − θ E (18) α ( R C 1 + θ C ) − (α R C 2 + θ E )

308

Heyin Hou and Weixing Qu The value of q is determined by the combination of punishment and reward intensities. In Table 3, all *

possible values of q * are listed. For example, if C < C 1* and E < E 1* , then q * ∉ ( 0,1) . If C > C *2 and E < E 1* , then q * ∈ ( 0,1) .

3.2 Analysis about the follower’s ESS Let F ( q ) ≡

dq ( t ) dt

, and, define the following equation:

{

}

L ( p ) ≡ ⎡⎣(1 − α ) R C1 + θ C ⎤⎦ − ⎡⎣(1 − α ) R C 2 + θ E ⎤⎦ p ( t ) − ⎡⎣R S − (1 − α ) R C 2 − θ E ⎤⎦

(19)

Then, Eq. (15) would be transformed as follows: F ( q ) = q (1 − q ) L ( p ) (20) Based on the dynamics (20), if L ( p ) = 0 , then F ( p ) ≡ dq ( t ) dt always equals to 0, which means that all q ∈ [0,1] are stable states; if L ( p ) ≠ 0 , then q = 0 and q = 1 are stable states. More precisely, if L ( p ) > 0 , then only q = 0 is the follower’s ESS; if L ( p ) < 0 , then only q = 1 is the follower’s ESS. Table 4: Value ranges of L ( p ) E C

E < E 1*

* * E1 < E < E 2

C < C 1*

L ( p) < 0

* C < C < C2

L ( p) < 0

If p > p , then L ( p ) > 0 .

If p < p , then L ( p ) < 0 .

* 1

C > C *2

E > E *2 If p > p , then L ( p ) < 0 . *

If p 0 . *

If p > p , then L ( p ) < 0 . *

If p 0 . *

L ( p) > 0

For obtaining the follower’s ESS, L ( p ) should be clarified. All possible value ranges of L ( p ) are determined by the combination of punishment and reward intensities, see Table 4. For example, when C < C 1* and E < E 1* , L ( p ) < 0 . When C > C *2 and E < E 1* , if p > p * , then L ( p ) > 0 , and if p < p * , then L ( p ) < 0 .

Based on Table 4, we list all possible ESSs of the follower, see Table 5. For example, when C < C 1* and E < E 1* , the follower’s ESS is q = 0 . When C > C *2 and E < E 1* , if p > p * , then the follower’s ESS is q = 1 , and if p < p * , then the follower’s ESS is q = 0 .

Table 5: The Follower’s ESS E C

E < E 1*

* * E1 < E < E 2

E > E *2 If p > p , then q = 0 . *

C <C

q =0

* C < C < C2

q =0

If p > p , then q = 1 .

* 1

If p < p , then q = 1 . *

If p > p , then q = 0 . *

* 1

C >C * 2

If p < p , then q = 1 . *

If p < p , then q = 0 . If p < p , then q = 0 . *

309

q = 1

Heyin Hou and Weixing Qu In Table 4 and Table 5, there is an important parameter p * , which is defined as follows:

* p ≡

R S − (1 − α ) R C 2 − θ E ⎡⎣(1 − α ) R C1 + θ C ⎤⎦ − ⎡⎣(1 − α ) R C 2 + θ E ⎤⎦

(21)

The value of p * affects the follower’s ESS and is determined by the combination of punishment and reward intensities. In Table 6, all possible values of p * are listed. For example, if C < C 1* and E < E 1* , then * * p ∉ ( 0,1) . If C > C *2 and E < E 1* , then p ∈ ( 0,1) .

Table 6: Value ranges of p * . E C

E < E 1*

* * E1 < E < E 2

E > E *2

C < C 1*

* p ∉ ( 0,1)

* p ∈ ( 0,1)

* * C1 < C < C 2

* p ∉ ( 0,1)

* p ∈ ( 0,1)

C > C *2

* p ∈ ( 0,1)

* p ∉ ( 0,1)

3.3 Comprehensive analysis about two players’ ESSs Comparing the leader’s ESS (see Table 2) with the follower’s ESS (see Table 5), we get Table 7. And, We formulate all results in Table 7 as formal propositions. ⎧C < C 1* ⎧C 1* < C < C *2 ⎧C < C *2 p = 0 q = 0 , then and . So, if , then p = 0 and q = 0 .That is, both the or If ⎨ ⎨ ⎨ * * * ⎩E < E 1 ⎩E < E 1 ⎩E < E 1 leader and the follower choose “No‐Trust”, and realize the worst social payoff R L . Proposition 1: If the intensity of punishment is at low or middle level, and the intensity of reward is at low level, then both the leader and the follower would not trust each other. ⎧C < C 1* ⎧C 1* < C < C *2 ⎧C < C *2 ⎧C 1* < C < C *2 p = 1 q = 0 If ⎨ * . Therefore, if and , or , then ⎨ ⎨ * ⎨ * * * * * ⎩ E 1 < E < E 2 ⎩E 1 < E < E 2 ⎩E > E 2 ⎩E 1 < E < E 2 ⎧C * < C < C *2 , then p = 1 and q = 0 . That is, the leader choose “Trust” and the follower choose “No‐Trust”, or ⎨ 1 * ⎩E > E 1

And realize the second best social payoff R M + θ ( E − C ) . Proposition 2: If the intensity of punishment is at low or middle level, and the intensity of reward is at middle level, then the leader would trust the follower, but the follower would not trust the leader. Proposition 3: If the intensity of punishment is at middle level, and the intensity of reward is at middle or high level, then the leader would trust the follower, but the follower would not trust the leader. ⎧C > C *2 ⎧C > C *2 ⎧C > C *2 p = 1 q = 1 or , then . Therefore, if , then p = 1 and q = 1 . That is, and If ⎨ * ⎨ ⎨ * * * ⎩E > E 1 ⎩E > E 2 ⎩E 1 < E < E 2 both the leader and the follower choose “Trust”, and realize the best social payoff R H .

Proposition 4: If the intensity of punishment is at high level, and the intensity of reward is at middle or high level, then both the leader and the follower would trust each other. When C < C 1* and E > E *2 , there are two possible ESS combinations. If p q * , then p = 0 and q = 1 . That is, the leader chooses “No‐Trust” and the follower chooses “Trust”, and realize the second best social payoff R M + θ ( E − C ) . If p > p * and q < q * , then p = 1 and q = 0 . That is the leader choose “Trust” and the follower choose “No‐Trust”, and realize the second best social payoff R M + θ ( E − C ) too.

310

Heyin Hou and Weixing Qu Proposition 5: If the intensity of punishment is at low level, and the intensity of reward at high level, then the leader’s strategy is contrary to the follower’s strategy. When C > C *2 and E < E 1* , there are two possible ESS combinations. If p p * and q > q * , then p = 1 and q = 1 . That is, both the leader and the follower choose “Trust”, and realize the best social payoff R H .

Proposition 6: If the intensity of punishment is at high level, and the intensity of reward at low level, then both the leader and the follower would choose identical strategy, i.e. they would trust or would not trust each other at the same time. Table 7: Comprehensive Analysis about Two Players’ ESS E C

E < E 1*

E > E *2

* * E1 < E < E 2

If p q , then p = 0 *

p = 0,q = 0

C < C 1*

p = 1, q = 0

and q = 1 . If p > p and q < q , then p = 1 *

and q = 0 .

p = 0,q = 0

C <C <C * 1

* 2

p = 1, q = 0

p = 1, q = 1

If p < p and q < q , then p = 0 *

C > C *2

and q = 0 . If p > p and q > q , then p = 1， q = 1 . *

4. Conclusion In venture capital industry, venture capitalists usually jointly invest entrepreneurial projects, forming diverse and appropriate syndication process, which needs trust between participants. However, the trust governance mechanism in venture capital syndication has not yet attracted enough attention and research. Suitably designed trust governance mechanism can improve venture capital syndication’s performance. In our paper, the trust governance mechanism composes of two components, the punishment and the reward. Through constructing an evolutionary game model, where players adopts the replicator dynamics as their learning rules, we get all possible evolutionary stable strategy (ESS) combinations under all possible punishment and reward combinations. Especially, if both the intensities of punishment and reward are high, then both the leader and the follower would trust each other and realize the best social payoff; if both the intensities of punishment and reward are low, then both the leader and the follower would not trust each other and realize the worst social payoff. Through the evolutionary game modelling, we get some significant propositions and do not test those using empirical data. Normative research needs the support of empirical research. So, corresponding empirical study about the trust governance mechanism would enter into research scope for academicians.

Acknowledgements Financial support from Jiangsu Provincial Education Department [Grant No. 09SJD630001] and Nanjing Planning Office of Philosophy and Social Science [Grant No. 12Y07] is gratefully acknowledged.

References Beamish, P.W. and Banks, J.C. (1987) “Equity Joint Ventures and the Theory of the Multinational Enterprise”, Journal of International Business Studies, Vol 18, No. 2, pp 1–16. Bottazzi, L., Da Rin, M. and Hellmann, T. (2012) “The Importance of Trust for Investment: Evidence from Venture Capital”, [online], University of British Columbia and NBER, http://strategy.sauder.ubc.ca/hellmann/pdfs/working_papers/Bottazzi‐DaRin‐Hellmann‐Trust‐Jul12.pdf.

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Heyin Hou and Weixing Qu Das, T.K. and Teng, B.‐S. (1998) “Between Trust and Control: Developing Confidence in Partner Cooperation in Alliances”, The Academy of Management Review, Vol 23, No. 3, pp491‐512. Han, S.E. (2008) “Venture Capital Syndicate Network:A Game‐theoretic Model”, [online], Indiana University, http://www.iub.edu/~econdept/conference/JRC_2008/Han_Eunseok_3rd‐year%20Paper‐Final.pdf. Kuan, J. (2004) “Hostage Exchange in Venture Capital Syndicates”, [online], Stanford University, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.203.1177&rep=rep1&type=pdf. Lerner, J. (1994) “The Syndication of Venture Capital Investments”, Financial Management, Vol 23, No. 3, pp 16‐27. Smith, D.A. and Lohrke, F.T. (2008) “Entrepreneurial Network Development: Trusting in the Process”, Journal of Business Research, Vol 61, No. 4, pp315‐322. Sorenson, O. and Toby, E.S. (2008) “Bringing the Context Back In: Settings and the Search for Syndicate Partners in Venture Capital Investment Networks”, Administrative Science Quarterly, Vol 53, No. 2, pp266‐94. Szabó, G. and Fáth, G. (2007) “Evolutionary Games on Graphs”, Physics Reports, Vol 446, No. 4‐6, pp 97‐216. Taylor, P. and Jonker, L. (1978) “Evolutionary Stable Strategies and Game Dynamics”, Mathematical Biosciences, Vol 40, No. 1‐2, pp145‐156. Wright, M and Lochett, A. (2003) “The Structure and Management of Alliances: Syndication in the Venture Capital Industry”, Journal of Management Studies, Vol 40 No. 8, pp 2073‐2102. Zheng J. K. (2004) “A Social Network Analysis of Corporate Venture Capital Syndication”, [online], University of Waterloo, http://etd.uwaterloo.ca/etd/jkzheng2004.pdf.

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Employee‐Driven Innovation (EDI): Toward an Extended Concept of Innovation Steen Høyrup Aarhus University, Denmark shp@dpu.dk Abstract: The aim with this article is to present new knowledge in an emergent field of international and interdisciplinary research called Employee‐Driven Innovation (EDI) ‐ a research that extend our knowledge of how to explore, exploit and further cultivate new innovative potentials among employees and firms, especially in the field ‘workplace innovation’. The purpose of the article is twofold: To present and discuss major trends in new and current conceptualisations of innovation, and to present a new concept and field of research i.e. Employee‐Driven Innovation. The article places EDI in a wider literature on innovation and shows how the concept of innovation still include the basic criteria of ‘newness’ and ‘value’. Furthermore it is shown how the concept is applied in new ways that include an extension of the basic criteria, adding new criteria for innovation. The broadening of the concept reflects new theoretical approaches and new fields of theoretical and empirical research. Especially research about the relation between innovation and learning in workplaces, seems to develop fast and to be very fruitful, bringing new insight about the basic dynamics of innovation processes. The article discusses EDI in relation to “social innovation” and ‘workplace innovation’. In this perspective employees have a potential to become the central drivers of innovation. Keywords: employee‐driven innovation (EDI), social innovation, workplace innovation, innovation, workplace learning

1. Introduction For more than half a century, innovation has been addressed by dedicated researchers, politicians and practitioners trying to unveil and apply the secrets and potential of innovation. Thus, the phenomenon of innovation is not in itself new, but today we find a large number of new conceptualizations of the notion. Today much confusion exists about the proper definition of innovation. Thus, the concept of innovation is currently defined in very different ways. Despite the huge diversity in meanings, we find a shared core of meaning referring to the early work of Schumpeter (1934). The very term ‘innovation’ was coined by Schumpeter in the 1930s and defined as a novelty that creates economic value. (Schumpeter, 1934) It is obvious that innovation implies change, and according to Schumpeter, change has to meet two criteria to constitute an innovation: newness and value. In Schumpeter’s theories, innovation was about economic development. Consequently the criteria ‘value’ was equal to ‘economic value’. Further, innovation was primarily about things and technology. Still ‘newness’ and ‘value’ are the two basic criteria applied today as basic core elements in different conceptualizations of Innovation. Contemporary researchers seem to use these classic criteria as the point of departure for their conceptualizations, but at the same time newer conceptualizations often transgress these basic criteria. An analysis of the development in the conceptualization of innovation is interesting, because it reflects important developments in theoretical disciplines and approaches and new fields of interest in innovation research and thinking today. EDI is a new and important concept and a new field of research in this context. On this background the purpose of the article is to discuss major trends in new conceptualisations of innovation, especially different kinds of innovations often neglected by approaches that emphasizes a technological point of view, ‐ and to present a new concept and field of research i.e. Employee‐Driven Innovation.

2. Social innovation: Changing the criteria of value ‘Value’ for Schumpeter equated economic value. Today many researchers find it necessary and fruitful to think of value in a broader sense, e.g. in terms of human, social sustainability and global perspectives. This seems to be one of the most important extensions of the concept we find today. We find this extension of the meaning of the criteria in the field called social innovation in particular. The concept “social innovation” is a relatively new one, but social innovation itself is not new. Today, an important development in the field of innovation is

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Steen Høyrup going on in the area of social innovation, both in terms of research and policy. However, the same degree of confusion exists about the proper definition of social innovation. We find an early outline of the concept of social innovation in the writing of Peter Drucker. He uses the term, but does not give an explicit definition of social innovation. In 1985, Drucker writes that one of the most interesting examples of social innovation and its importance can be seen in modern Japan. (Drucker, 1985). He underlines what he calls a prevailing belief – which he does not share – that innovation (exclusively, Ed.) has to do with things and is based on science or technology. Japan's success is based on social innovation. Referring to the Japanese development since 1867, Drucker states: This meant that social innovation was far more critical than steam locomotives or the telegraph, and social innovation, in terms of the development of such institutions as schools and universities, a civil service, banks and labour relations, was far more difficult to achieve than building locomotives and telegraphs. (Drucker, 1985: 29). Obviously Drucker’s thinking represents a break with Schumpeter’s approach. It seems that Drucker’s conceptualization of social innovation is characterized by the product of innovation that manifests itself at the society level and concerns new or improved social institutions. It may be concluded that, in Drucker’s thinking, social innovation concerns change in the social institutions of society and may include social, technological as well as economical processes. Relating Druckers thinking to our criteria of success, ‘value’ implicitly seems to be economic value, and ‘newness’ implies some kind of fundamental renewal in society mediated by institutions. The European Commission takes a slightly different position: Social innovation is about new ideas that work to address pressing unmet needs. We simply describe it as innovations that are both social in their ends and in their means. Social innovations are new ideas (products, services and models) that simultaneously meet social needs (more effective than alternatives) and create new social relationships or collaborations. (European Commission, 2013) Relating this conceptualization to our criteria – newness and value – we see that the value of social innovation is meeting social needs more effectively (than alternatives) and that the new is new social relationships or collaborations. Compared to Drucker’s thinking, ‘the new’ is conceptualized to a much higher degree on the micro level (social relationships and collaborations compared to new social institutions). SIE (Social Innovation Europe) adds an interesting distinctive feature to the notion of social innovation: Social innovation, by its iterative and adaptive nature, means that we do not know what the outcome of a given social innovation initiative will be – this means that any effort to create and deliver an innovative solution is incredibly challenging and often quite lonely work. (SIE, Jan. 2011‐Dec. 2012). This conceptualization implies that a new dimension is added to the criteria of newness: It can be difficult to state precisely what the newness is about. This paves the way for an understanding of the nature of the innovative process as being very explorative, and an open search for solutions to meet the social needs at hand. The thinking presented here includes the actors and qualities in the innovation process. This is in accordance with the thinking of P. Rasmussen, which conceptualizes social innovation (Rasmussen, 2012). In the article “Education and Social Innovation” he states: Social innovation is about developing original responses to societal needs that are not sufficiently met by existing types of private and public service. Innovative responses are often developed by non‐commercial organizations and actors through creative processes with a strong element of initiative “from below”. (Rasmussen, 2012: 92) Rasmussen underlines the connection between non‐commercial organizations and social innovation. The driver of innovation is not the market or profit. Social innovation is a response to societal needs and problems. Furthermore it is important to notice that Rasmussen involves the actors of the organization in terms of a “strong element of initiatives from below”. Further, a quality of the innovation process is emphasized in terms

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Steen Høyrup of creativity. By the presented conceptualization, Rasmussen definitely takes steps towards the concept of EDI. In sum, it is concluded that in the conceptualization of social innovation, the new is change at the societal level in terms of new or renewed social institutions. The value created is in terms of meeting societal needs. The process is often characterized by having non‐commercial organizations as targets and a strong element of actor initiatives and involvement in terms of initiatives from below. Furthermore the process may be characterized in terms of creativity and open‐ended processes such as exploration, and an open search for solutions.

3. ‘Workplace innovation’ and ‘innovations in work organization’ ‘Workplace Innovation’, ‘Innovations in work organization’ and ‘organizational innovation’ are notions with only slightly different meanings, and they are often used interchangeably, e.g. by Cox, A. (Cox, A. et al 2012). A reasonable distinction could be that workplace innovation is a broader concept that might include small, informal and emergent change processes that do not necessarily influence the very organization of the workplace, but they may also include changes in the organization of the workplace. Cox, A. et al claim that innovation in work organization has tended to be overlooked by the dominant innovation literature based on technology studies (Cox, A. et al 2012: 9). The authors clarify the notion of Innovations in work organisation’. (Cox, A. et al 2012: 9). They state that ‘social innovation’ is the broader concept that includes ‘Innovations in work organisation’. Yet the two notions have slightly different meanings: Workplace innovations are more specifically focused on innovations within organisations rather than in wider society. (Cox, A. et al 2012: 9). Innovations in work organisation have the potential to optimise production processes in companies and to improve the employee’s overall experience of work. (Cox, A. et al 2012: 1). Innovations in work organisation can thus contribute to meeting the goal of the Europe 2020 strategy of attaining “smart” growth through the development of higher‐quality jobs in higher value‐added industries and ’inclusive’ growth in which all citizens have access to high‐quality employment opportunities. Innovation in work organisation may also lead to wider innovation in products and services which could result in employment growth. These points of view underline the importance of workplace innovation in society. The newness criteria in workplace innovation/innovation in work organization may include a very broad range of improvements, e.g. improvement of production and service processes and development of higher‐quality jobs. The value criteria may include issues relating to both the psychological, work environment and societal values: work satisfaction, the employee’s overall experience of work, work‐life balance. On the societal level, employment growth, more and better jobs and increased efficiency and performance of the organization. In line with, this Cox,A., et al – referring to Ramstad and Pot ‐ underline the importance of workplace innovation in society today: They (workplace innovations) are often a prerequisite for technological developments because they encompass the process changes required ‘to change the beliefs, attitudes, values, and structure of organizations so that they can better adapt to new technologies, markets, and challenges (Ramstad, 2008: 29). Therefore workplace innovations can be vital to advancements in overall productivity and competitiveness through enabling optimal utilization of the potential workforce (Pot, 2011). Thus the criteria of ‘newness’ for workplace innovation is about changes in terms of new forms of organization and more or less radical changes in the organization of work. Addressing the work organization as part of the innovation process creates a new problem: how do we conceptualize the notion of ‘work organization’ ‐ the target of the innovation processes in this approach. Ramstad conceptualizes innovation related to work organisation as:

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Steen Høyrup Renewals in the structures, processes or boundaries of a work organization that achieve savings in the use of labour or capital resources, or an improved ability to respond to customer needs. Examples of reforms can be selfmanaging teams, flatter hierarchies, outsourcing, diversified personnel skills and management systems (Cox, A. et al 2012:10, Ramstad, 2009: 2) The characteristic feature of this approach to workplace innovation is that it addresses rather complex units, areas and reforms of the organisation. The value criteria appear primarily to be organizational benefits. The management‐employee relations are underlined in the work of Pot (Pot,2011:1, Pot et al 2012: 175). Pot has accomplished comprehensive research in the field of workplace innovation. Pot claims that “there is currently no uniform definition of workplace innovation”. (Pot et al 2012: 175). In the present publication (Pot et al 2012: 175) workplace innovation is defined as: Workplace innovations are strategy induced and participatory adopted changes in an organisation’s practice of managing, organizing and deploying human and non‐human resources that lead to simultaneously improved organizational performance and improved quality of working life (Eeckelaart et al., 2012) And further (Pot et al 2012: 175) Workplace innovation includes aspects of management and leadership, flexible organisation, working smarter, continuous development of skills and competencies, networking between organisations and the moderation of labour relations and human resource management. It is obvious that a management perspective is prevailing in this conceptualization, but the employee perspective is also included in terms of employee participation. With regard to the newness criteria, it is very broad: innovation processes can transgress the borders of the organization (networking between organisations) and include social relations and education. According to the value criteria focus is on “improving the quality of working life and productivity, especially as an effect of change projects that involve employee participation” (Pot et al 2012: 175) According to Pot, workplace innovation might indirectly (but not directly) have an effect on (value for) issues such as illness, injuries, absenteeism and accidents at the workplace. In terms of value, improvement of the quality of working life and productivity is the most important value. Pot underlines that research indicates that, through workplace innovation, a simultaneous improvement in quality of working life and productivity is possible, in particular in projects with strong employee participation (Pot et al 2012: 175, Ramstad, 209; Pot 2011). The European commission conceptualizes workplace innovation: Workplace innovation is a generic term to cover – notably but not only – innovations in the way enterprises are structured, the way they manage their human resources, the way internal decision‐making and innovation processes are devised, the way relationships with clients or suppliers are organised or the way the work environment and the internal support systems are designed. Workplace innovation is a reflexive process, grounded in continuing reflection, learning and improvements, and involving employees and managers at all levels. (European Commission 16.11.12) From this conceptualization it appears that this form of innovation addresses the criteria of “newness” in terms of improvement of a broad range of structures and processes that constitute the workplace. The conceptualization also addresses the quality of the innovation process itself, addressing reflection and learning as important issues. Moreover, the conceptualisation focuses on the individuals involved in the process, that is, employees and managers at all levels. A new and important trend is, that learning is included in the apprehension of innovation. It should be concluded that workplace innovation manifests itself as powerful processes with a potential to create newness in terms of improvement of basic areas of the organization, and that the created value covers a broad range of issues including the productivity of the firm as well as improvement of the quality of working life. The management perspective is dominant, but employees have the potential to obtain an important position in the innovation process via employee participation.

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4. Employee‐driven Innovation: the employee's active role and learning becomes significant Introduction The nature of innovation in Schumpeter’s thinking and later in the area of social innovation and workplace innovation can be apprehended as antecedents of “Employee‐Driven Innovation”. Yet in EDI an important new perspective is added: The very source of innovations. Here, focus is on the Employees. It is a basic view that ordinary employees of the organization constitute a strong, but often overlooked, resource of innovation. The recognition of ordinary employees as being important and continuous producers of new knowledge, new ideas and solutions, and who are continuously remaking their jobs, comprises a new and fruitful perspective on innovation in organizations. (Høyrup, 2012). The changes/innovations may occur as subtle changes that influence the way in which the workplace evolves over time by initiating changes to the work practice. It is possible that these innovations may never be part of the conscious and explicit agenda of the organisation or be something that managers have a strong role in initiating. However, their effects can be cumulative and substantial. (Price et al, 2012: 77) Based on this preliminary outline of the concept of EDI it should be recognized that the concept is quite similar to – and share important elements with – related and earlier concepts, e.g. ‘idea management’. (Ekvall, G. 1991). Ekvall explained idea‐management or idea‐handling as: …new values, ambitions and attitudes at work, which results in demands from employees to participate in problem‐solving and decision‐making. Companies need the and support of all their employees in the implementation of the new. Idea‐management then becomes a necessary activity. (Ekvall, G. 1991:73) Ekvall states that idea‐management is about finding and taking care of ideas for change in the organization’s operations, concerning both products and processes. And further: Idea management has two sides: One concerns general features of the organization which stimulate or hamper innovation, the other includes special formal systems and procedures for idea‐finding and use. (Ekvall, G. 1991:73) The basic approach of EDI and idea‐management is the same: the value of the employees’ contributions to the implementation of the new. Some differences include:

Idea‐management favor the management perspective on handling new ideas.

The point of departure in conceptualizing newness is new ideas. The unit of analysis is handling of ideas. In EDI, the focus is on new practice. Unit of analysis is social interaction in an organizational context.

The focus of idea‐management is the organizational conditions for creativity and innovation. This is also an important focus in EDI, but EDI adds further perspectives, e.g. micro‐processes in employee‐ organizational interaction, and learning of employees that contribute to innovation.

Formal systems and procedures for idea‐finding and use can be applied in EDI, but EDI also consider informal and emerging processes as important conveyors of innovation processes.

Idea‐management does not focus on the social collectivity in producing innovations, which is outstanding in EDI.

Thus, EDI and idea‐management are two overlapping concepts and approaches to innovation in the workplace. In a sense, EDI can be apprehended as part of social innovation and workplace innovation, as the concept shares many characteristics with these phenomena. Thus, EDI is basically characterized by the extended meaning of the classical criteria of newness and value outstanding in social‐ and workplace innovation. Furthermore, some of the phenomena touched on – in terms of an open exploration process, learning and participation – have a slightly different quality in EDI. At the same time, these modified qualities constitute outstanding characteristics inherent in the concept of EDI. The following new and outstanding qualities are manifested in EDI:

The role of the employees involved in the innovation.

Top‐down and bottom‐up processes in innovation

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Workplace learning by employees as the raw material for innovation

The spontaneous emerging nature of the innovation

The collective aspects of EDI

These qualities are described in detail below. The Nature of EDI Employee‐driven innovation is an umbrella concept that covers a broad range of innovation processes and issues. Price et al address the essential point of departure for the EDI approach: We take the view here that innovation arises from the everyday cultural practices of workers – the ways workers enact their jobs, interact with each other and seek to become fuller members of their organizations. It occurs through workers finding ways of meeting their own interests and desires as well as those of their employers. This approach underlines the organization–individual interaction, and here innovation arises from the everyday cultural behaviour of employees. (Price et al, 2012:77). This approach differ from the management perspective on innovation claimed by Pot in which workplace innovations are strategy‐induced and participatory adopted changes in an organisation’s practice. EDI may fall outside the management’s official strategy of innovation. The role of employees can be participatory, but it may also manifest itself in different ways. On this basis EDI may be defined: EDI refers to the generation and implementation of new and valuable ideas, products, and processes – including the everyday remaking of jobs and organizational practices – originating from interaction of employees, who are not assigned to this task. The processes are unfolded in an organization and may be integrated in cooperative and managerial efforts of the organization. Employees are active and may initiate, support or even drive/lead the processes. (Høyrup, 2012: 8) In this conceptualization, EDI indicates a bottom‐up process in the organization. Employee‐driven innovation begins at the job and at worker level. EDI may begin at the job level, but turns out to be an interaction between several actors that may include employees and managers as well. Therefore it may be difficult to isolate EDI as a pure bottom‐up process, and the processes may not be isolated from management, but related to management. In some conceptualizations of EDI, the management perspective seems to be dominant, and management plays a role in EDI in several ways. Shortcomings of this definition is that it is not made explicit who the actors are that benefit from the innovation, e.g. owners of the firm, employees or shareholders, and how formalized or informal the EDI‐ processes are. It may be possible for the employees in units of the organization without interference from management to continuously develop and remake their daily work practice and to conduct other kinds of innovations. But if the organization is overflowing with uncoordinated ideas and solutions from employees, this may threaten to tear apart the very order of the system, and the process of change may therefore appear anarchic and unpredictable. Consequently, managers may be involved in EDI on two levels. First, they may join the process of EDI to coordinate the processes initiated by the employees, to use the resources of the employees and make these processes constructive to the organization. Cooperation between management and employees is thus essential. EDI in this case is a mixture of bottom‐up and top‐down processes in the organization. Second, managers may take the initiative in innovation by inviting employees to participate in innovative processes, and the involvement of employees in the innovation process may be formally organized. It may be questioned whether this form of top‐down innovation should be included in the concept of EDI. We prefer to conceptualize EDI both in a narrow sense – referring to bottom‐up processes and the mixture of bottom‐up and top‐down processes – and in a broader sense that includes the top‐down process as well.

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Steen Høyrup Thus, it appears fruitful to distinguish between: First order EDI: These are bottom‐up processes. Innovation arises from the everyday cultural practice of workers – the ways workers enact their jobs, interact with each other and seek to become fuller members of their organizations. It is a reconstruction of work practices that is not initiated with a goal of innovation in mind, but which results in innovation as a central outcome. Second order EDI: a mixture of bottom‐up and top‐down processes in which management strives to systematize and formalize significant innovation processes initiated by employees, for example those mentioned above. Third order EDI: a top‐down process in which managers invite employees, and involve employees in participating in innovative processes, e.g. in terms of involvement in developmental projects. Thus EDI covers a broad range of complex processes that can be related to both a formal–informal dimension and a bottom‐up/top‐down point of view. Different roles of employees in EDI The distinction between top‐down processes and bottom‐up processes as a framework for innovation seems to be too simple. The interplay between management and employees is far more complex than grasped in these terms, and the notions do not allow for different roles that management and employees can play in the innovation process. (Kristensen, C.J., 2011). Kristensen coins the term “bottom‐linked innovation”: By bottom‐linked Innovation I understand innovations created in more or less explicit interaction (dialogue and negotiations) between management and employees. Bottom‐linked innovations can be based on ideas posed and developed by managers or employees, or in collaboration between the two groups. …(Kristensen, 2011). The notions of participation or involvement are prominent ways of conceptualising the active role of employees in innovation. (Pot (2011); Bessant (2003)). Meanwhile, these notions seem to have shortcomings in relation to EDI. Kristensen presents three sub‐concepts: employee initiated innovations, are innovations that employees have taken the initiative or coined the idea to. This innovation can be self‐initiated or part of a planned idea phase. Employee involving innovations are innovations where employees participate in the development and refinement of ideas created by e.g. managers or colleagues. Employee steered innovation are steered by and significantly influenced by employees (Kristensen, 2011). These concepts are the cornerstones of the concept of EDI and clearly transcend the traditional notions of participation and involvement, giving the employees a much more active and multi‐faceted role and influence on innovation in the workplace. De Spiegelaere et al also contribute to the conceptualization of the employee’s role in innovation. (De Spiegelaere et al, 2012), referring to Høyrup’s notion of third order EDI that covers the innovations which are developed by employees on the invitation of the management. The authors propose to distinguish between three types of third order EDI called ‘delegation’, ‘ideation’ and ‘execution’, depending on the level of employee involvement.

Delegation: Here, the employees are invited by the management to generate, develop and introduce innovations in the workplace. The management therefore gives a certain degree of autonomy to the employees over the whole innovation process.

Ideation: In ideation, the role of the employees is limited to proposing ideas and giving advice about workplace innovations. The management keeps control over the selection of the ideas and the actual implementation.

Execution: In execution, the role of the employee is limited to the introduction of innovations on the work floor. Employees do not have any influence on the selection or development of the innovation but need to change existing work practices in order to integrate the new innovation on the workplace.

Kristensen’s and De Spiegelaere’s concepts contribute to underlining the distinctive character of EDI: the multi‐ faceted role and actions of the employees. This conceptualization also underlines the fact that EDI is not an

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Steen Høyrup individual performance, nor the product of innovation heroes. This point of view is emphasized by Aasen & Amundsen (2011) in their book: Innovation as collective performance, and Aasen et al, (2013). We have paved the way for a new an extended concept of innovation ‐ EDI ‐ by expanding on the original conceptualization by Schumpeter (1994). Both ‘value’ and ‘newness’ have a broader meaning, and the focus is on the practice of employees and employee‐management – interaction in convening innovation processes in the workplace. The active role and learning of employees is the core of the concept, emphasizing delegation, ideation and execution. The concept of EDI still has to be developed in these terms. EDI and learning Learning can produce EDI. Fenwick states: “All learning in work is to some extent innovative in that it introduces change” (Fenwick, 2003:124). Ellström claim that the concept of learning is the key concept in the research on innovation, and that empirical research supports the central role of learning as a fruitful approach to the research on innovation (Ellström, 2010). According to Ellström (2010:27) and Høyrup (2012:22), “The learning product is not only mental changes or social processes, but also tangible results such as new ideas, new knowledge and new solutions to problems.” In this conceptualisation, the relation between learning and innovation is quite clear: workplace learning is a fundamental mechanism behind EDI. “Learning – in terms of tangible results – produces innovation”. Learning theories in this field cover a broad range including individual learning and organisational learning. As an example of a conceptualisation that links learning and EDI, Billet’s thinking should be mentioned: Innovation at work is conceptualized as comprised by two kinds of change processes that occur interdependently of each other: 1) the individuals learning and 2) the transformation of workplace practices. The changes occur in relation to each other. In this view everyday process of thinking and acting at work are constructive acts through which work tasks and process are reconfigured in response to new requirements arising at a particular moment in time and in response to specific situational requests or problems, e.g. work tasks. This everyday process of work related thinking and acting leads to the remaking of occupational practice and comprises employee‐led innovations. When confronting and responding to significant changes (innovations) of practice, both new learning for those enacting these tasks and the transformation of practice co‐occur. In this way learning is both a response to innovative processes and a spur for innovative processes of the firm. (Billett, 2012; Høyrup, 2012: 16)

5. Conclusion Changes in the meaning of the basic criteria of innovation are analysed and it is obvious that the “value‐ criteria” still include “economic value”; e.g. improved effectiveness and productivity of the firm, more and better jobs in society, etc. Yet, other forms of value are added: better quality of life, improved quality of education and care, higher job satisfaction and creativity of employees at the job. Increased value is related to both society, organisations, work‐teams and the individual employee. The described broad values apply to especially EDI. The value and newness criteria are closely interconnected. Newness may be located at individual, organisational and societal levels, not least in EDI. In both Workplace Innovation and EDI ‘the new’ may manifest itself as new products, new processes, new knowledge and new solutions to problems. When placing EDI in the literature of social and workplace innovation/organizational innovation it becomes evident that the three forms of innovation share many qualities in terms of value and newness. Meanwhile, the nature of employee‐driven innovation stands part from these forms of innovations. The most distinctive characteristics are: (1) The role of employees in the innovation process. Several roles and patterns of interaction are described. (2) The collective nature of EDI. (3) Learning at the workplace may create EDI. These issues are analysed in more details to show the distinctive characteristics of EDI.

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Steen Høyrup On this basis, a definition of Employee‐Driven Innovation is proposed, a definition that distinguishes between first, second and third order of Employee‐Driven Innovation. In the chosen conceptualization of EDI, workplaces have the potential for becoming the new nucleus of the future innovative economy in Europe, and employees at all levels have the potential for becoming central drivers of innovation.

References Bessant, J. (2003) High‐Involvement Innovation. Wiley. West Sussex, England Billett, S. (2012) Explaining Innovation at work: A socio‐Personal Account. In: Høyup et al (2012) Cox, A., Rickard, C. and Tamin, P. (2012) Work organization and innovation. European Foundation for the Improvement of Living and Working Conditions. http://www.eurofound.europa.eu/pubdocs/2012/72/en/1/EF1272EN.pdf (10.04.2013) De Spiegelaere,S., Gyes,G.V., Hootegem, G.V. (2012) Mainstreaming innovation in Europe‐ Findings on employee innovation and workplace learning from Belgium. LLinE, Issue 4/2012. Drucker, P. (1985) Innovation and Entrepreneurship. Elsevier Butterworth Heinemann. Oxford. Eeckelaert, L.; Dhondt, S.; Oeij, P.; Pot, F.;Nicolescu, G.I.; Webster, J. and Elsler, D. (2012) Review of workplace innovation and its relation with occupational safety and health. Bilbao: European Agency for Safety and Health at Work. Ekvall, G. (1991) The organizational culture of idea‐management: a creative climate for the management of ideas. In: Henry, J. & Walker, D. (1991) Managing Innovation. Chap. 7, p. 73‐79. Sage publications, London. Ellström, P.‐E. (2010) Practice‐based innovation: a learning perspective. Journal of Workplace Learning 22 (1/2), pp 27‐40. European Commission. Industrial innovation, social Innovation. 01.03.13. http://ec.europa.eu/enterprise/policies/innovation/policy/social‐innovation/ (3) European Commission. Enterprise and Industry. Industrial Innovation. Workplace Innovation. Last update: 16.11.12. http://ec.europa.eu/enterprise/policies/innovation/policy/workplace‐innovation/index_en.htm Fenwick, T. (2003) Innovation: Examining workplace learning in new enterprises. Journal of workplace learning. 15 (3), pp 123‐132 Høyrup, S. et al (2012) Employee‐Driven Innovation. A new Approach. Palgrave Macmillan, N.Y. Kristensen, C.J. (2011) Employee‐driven innovation in social work. Paper for employee‐driven innovation and workplace learning. International research meeting, Bologna, Oct. 2011. Pot.F, Steven Dhondt, Elisabeth de Korte, Peter Oeij, Fietje Vaas (2012). Workplace innovation in the Netherlands. Chapter 8 In: I. Houtman (ed), Work Life in the Netherlands (pp. 173‐190). Hoofddorp: TNO. Innovation for Life. Pot, F. D. (2011) Workplace innovation for better jobs and performance. International Journal of Productivity and Performance management, Vol. 60, No.4, pp 404‐415. Prise, O. et al. (2012) Creating Work: Employee‐Driven Innovation through Work Practice Reconstruction. I: Høyrup, S. et al (2012) Employee‐Driven Innovation. A new Approach. Palgrave Macmillan, N.Y. Ramstad, E. (2009) Promoting performance and the quality of working life simultaneously. International Journal of Productivity and Performance Management Vol. 58, No 5, pp 423‐436. Rasmussen, 2012. Uddannelse og social innovation. Dansk Sociologi, nr. 4, december 2012, pp. 75‐90, 92‐93. (Danish Sociology, Education and Social Innovation nr. 4, December 2012). Schumpeter, J.A. (1934). The theory of economic development. Cambridge, MA: Harvard University Press. SIE, Social Innovation Europe, Jan.2011‐ Dec.2012. http://ec.europa.eu/enterprise/policies/innovation/files/social‐ innovation/sie‐final‐report_en.pdf Aasen, T.M., & Amundsen, O. (2011) Innovasjon som kollektiv prestasjon (Innovation conceived as collective performance). Gyldendal akademisk, Oslo. Aasen, T.M., Møller, K. & Eriksson, A.F. (2013) Nordiske strategier for MDI – 2013. MedarbejderDrevet Innovasjon (Nordic strategies for EDI – 2013, Employee Driven Innovation. The Nordic Council of Ministers.

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Innovative Approach in Managing the Process of Manufacturing Removable Partial Dentures Danut Iorga, Alexandru Ghiban and Cezar Scarlat Doctoral School of Entrepreneurship, Business Engineering and Management, University Politehnica of Bucharest, Romania danut.iorga@yahoo.com ghiban.alexandru@gmail.com cezarscarlat@yahoo.com Abstract: The consumers are even more fastidious than ever in this changing economic environment. And particularly, the health industry is very sensitive because of the “very corporal” implication of the customer. In the last two decades many hospitals in the USA have found the utility of using Total Quality Management and Lean Six Sigma, also prestigious companies as General Electric are using process management concepts and Lean Six Sigma methodology to design sophisticated medical devices to scan the entire human body. However, the literature referring to the managerial side of the manufacturing process of the medical devices and products is rather limited. This paper is focused on the process of manufacturing removable partial dentures (RPDs) aiming to increase their durability. The main factors that influence the RPD durability are presented as well as the ways to increase it by better manufacturing process management. A removable partial denture is produced through two main stages: clinic stage and laboratory stage, which also imply intermediary steps. Both clinic and laboratory steps are identified. Taking into consideration the significant gaps which occur during the production process and the high rate of failures due to the strong interdependence between clinical and laboratory areas, a process oriented approach could be the answer to these challenges. The innovation proposed as process management is the industrialization of the activities. That means to create circumstances to make the process repeatable and predictable. In order to obtain the stable process using the Lean Six Sigma methodology, the paper is analyzing the impact of Process Management philosophy over the current RPD manufacturing technology. As a result, a maturity process evolution matrix will be defined based on the quality of the results and customer satisfaction. The evolution matrix will be a helpful tool for the organization involved in the “process oriented” transformation. The major limitation is the shortage of information with respect to the product’s lifetime expectancy (ten years in case of RPDs). Paper relevance: Innovation in health processes and products is something not very usual in Romania. From this perspective based on our current information our paper is a premier, because it combines the dental manufacturing techniques with Lean Six Sigma and Process Management Philosophy. Keywords: removable partial dentures (RPD), clinic and laboratory stages, process management, process repeatability and predictability, industrialization of activities

1. Basic concepts in process management Process management appeared in the late 90’s in IT Industry. Since then, the concept has been extended to describe the effort needed in managing the entire company, with all the integrated processes. A simple definition of Process Management is: “a management practice that provides for governance of a business’s process environment toward the goal of improving agility and operational performance. BPM (Business Process Management) is a structured approach employing methods, policies, metrics, management practices and software tools to manage and continuously optimize an organization’s activities and processes”. (Hayler and Nichols, 2006) A basic element of Process Management is the layout of the organization. The structure of the companies should be radically changed in order to adjust to a process oriented strategy. Many companies that took over these methods (Genpact, Accenture etc.), especially from outsourcing for financial areas, human resources, and acquisitions, demonstrated that this kind of approach generates costs reduction and positive effects in quality services. The major issue in traditional companies (from a functional point of view) is the “silo effect” over the information flow and over the production processes. A negative element is the oversight of the real objectives, when different functional areas face particular events. In general, the challenges generated by the “silos” inputs and outputs are seen as elements that must be “passed on” to the following department as soon as possible.

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Danut Iorga, Alexandru Ghiban and Cezar Scarlat Lately, more and more managers have understood the importance of the holistic approach in processes; therefore the systemic approach becomes more popular in the business environment. As Pourshahid said “Business processes and their management have always represented challenges for organizations. These difficulties are now amplified by processes that are often cross‐functional in the organization or that are crossing the organization’s boundaries.” (Pourshahid et al., 2009) Business Process Management supporters consider that discipline in action and thinking helps to create a stable, predictable and comfortable environment, favorable for stimulating employees’ creative thinking. Nowadays, top companies include innovation at systemic level, seeking rational means for stimulating collective or individual creativity (projects and improvement initiatives). Created in these circumstances, the circuit for generating ideas is maintained by the relationship systemic thinking ‐ sustained innovation, based on projects managed by people who know best the business processes, as being their users. The history of this approach started with implementing the Deming Cycle Plan – Do – Check – Act (Figure 1) in traditional business, which brought remarkable results in Japan’s industry, immediately after the World War II.

Figure 1 : The PDCA cycle The PDCA Cycle is the one of the first tries to implement continuous improvement in the manufacturing areas, especially in automotive industry. As the figure above shows the entire philosophy consists in rolling the four steps of the principle (plan – the people identify the problem, analyze cause, formulate solutions, do – develop plan to implement solutions, communicate plan, execute plan, check – monitor results, modify plan if necessary, monitor progress of implementation plan, act – evaluate results and standardize solutions) (Juran et all, 1999). Right from the beginning, one of the obstacles that continuous improvement encountered in the classical (functional) approach is the “formal” allocation initiative to specialists, without taking into consideration the importance of management, in order to obtain successful results. Often, the breakdown of the improvement initiatives are caused by a lack of will or a deficiency in the management understanding, regarding the importance of improvements projects results, that must be implemented in current activity. The collapse appears when management doesn’t get involved in order to establish the improvement targets, when it isn’t interested in constant tracking of the activity evolution, and furthermore, is perceived as being absent when identifying improvement solutions or passive in implementing the results of the investigations conducted by the project teams. In the last decades, the former specified obstacles have been outrun using philosophies like Six Sigma. In these cases, management becomes an active part in finding improvement solutions or in business process development. “Process governance” becomes the managers’ main concern in the systemic approach of the business. Thereby, new positions appear in the company’s organization structure. For example, the process owner and the process specialist, who are involved in business process architecture projection and at the same time, in creating premises for coherent functioning of the company from cross functional perspective. Companies like GE, Accenture, and IBM decided to introduce instruments specific to Operational Excellence concepts, in order to stimulate the entire company to participate in creating architecture, capable of

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Danut Iorga, Alexandru Ghiban and Cezar Scarlat generating remarkable results for the clients, as being part of projecting business systems. The beneficiary of this approach becomes the main leader of this entire strategy and of the entire company. The customer needs and requirements are closely analyzed and most of the decisions and innovating or development initiatives of the company are strategically aligned according to these expectations.

2. Business process The process is defined as a set of activities that transform different tangible or intangible resources in necessary results that are expected by a beneficiary. In order to execute the activities resources are needed and used. Processes can be identified in every performed action. Some of them are generated for an actual purpose, and others are documented, planned, monitored and maintained for longer periods of time (weeks, months or years). In a business environment, performing processes represent an important element in order to obtain profit. Therefore, lately, many companies decided to pay attention to a systemic approach of enterprise organization, allocating time for developing resources, capable of using all the benefits resulted from process based management. Improvement systems for product quality or for creating new products that start with quality management like Kaizen, TQM and Lean Six Sigma or Design for Six Sigma represent powerful approaches in the entire business structure and in process based activity. Companies such as General Electric, Honeywell, Toyota, etc., have discovered that most of the problems appear in the modulation points of the processes, precisely at the limit of functional areas. They all understood that managers must get ready for a process based approach, where the final result is the most important and knowing the entire process (“end to end”) by all involved employees is critical in order to perform. Some specialists define organization as: “people, processes, control, and structure mechanisms” (Madison, 2005). In an organization, the „people” dimension can be defined through role, responsibilities, skills, learning, motivation, capability, and work adjustment. The „processes” dimension is characterized by two major flows: work and information. At the informational level, it is important to mention the influence the control of the informatics system has over the business processes and, also, over the design and redesign methods of the processes. Moyano‐Fuentes analyzes the relationship between informational level and implementation of Lean manufacturing philosophy, disclosing possible bottlenecks caused by rigid informatics systems. (Moyano‐ Fuentes, 2012). In conclusion, a balance should be maintained between the company’s informatization and the „flexibility” level regarding the gradual development of business processes. „Control mechanism” dimension refers to the business processes and these are, generally, electrical, mechanical or statistical. Usually, in services, the control mechanism is realized by the employees or the supervisors, who work in the process. Modern management is eager to exclude feedback control systems, and to introduce capable control systems, able to prevent and generate self‐adjust processes. In order to do this, companies use continuous improvement concepts, along with improvement projects, try to find solutions able to permanently adapt to the environment challenges. One of the most accepted business process models is the one presented by Rowland Hayler and Michael D. Nichols in the book Six Sigma for Financial Services (Figure 2). The concept is easily understood at an intellectual level. Actually, the people fail to follow the rules mostly due to the key persons who are not ready to accept the need for continuous change generated by the new philosophy of process management. For this reason, the organization in question was structured based on the outsourcing companies’ model (as Genpact, Accenture) with key roll people in the process management (process owners, process management specialists, operational excellence specialists). The organization management defines roles and responsibilities. Process specialists identify and propose lean Six Sigma projects, ensure process governance, survey and monitories process performance, manage the project portfolio. “Operational excellence specialists develop end to end process management plans to ensure that robust dashboard data are available for decision making, support benchmarking initiatives” (Hayler and Nichols, 2007).

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Figure 2: The strategy and logic of a process oriented organization The general concept of the processes is defined by input, set of activities, output, feed‐back and “noise”. Therefore, Y’s vs. X’s should be strongly correlated through activities. The General Model for the Transfer Function, shown in Figure 3 is Y[y1, y2, …, yn]=F(X[x1, x2, …, xn])

Y= F(X)

Figure 3: The general model for the transfer function Taking into consideration the general theory, the business management decided to identify the particular Transfer Function Matrix for current business (Iorga, 2012). In order to be aligned to the critical customer requirements, each factor should have established clearly defined specification limits (Figure 4). Y X1 X2 y1 x11 x12 y2 x21 x22

X11

LSL1

Y1 LSL

USL1

USL2

Figure 4: Specification limits for input and output For example, if it is needed to keep Y1 variance range within LSL2 – USL2, than must be found a distinct mathematical model in which X11 variance should be maintained within LSL1 – USL1 range. That means the operators have to focus on X’s to keep their values within specification limits in order to obtain the quality of the output at the desired level (Iorga, 2012). As a consequence, TFM is used by management permanently to prevent the failure of the process output. Although, due to the continuous change of the environment even the characteristics of the Transfer Function should be surveyed. The Important Stages of the Process Evolution are: Stage Zero (Idea Stage) → Unstructured activities → Stable Process → Mature and Stable Process

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3. Continuous improvement – using root cause technics in healthcare industry Most of the methods mentioned in this paper like PDCA, TQM, and Lean Six Sigma are developed to continuously improve the business results (increase the customer satisfaction therefore make more money). The common tool for all these methods is the root cause analysis. RCA is the hardcore of all initiatives in creating stable activities and reaching the final results with the highest level of quality. Due to the fact that Romania is far behind the developed western countries in healthcare reform, the researchers decided to use benchmarking based on USA healthcare continuous improvement initiatives. Based on the paper “Root Cause Analysis and Improvement in the Healthcare Sector, a Step by Step Guide”, Bjorn Andersen, Tom Fagerhaug, and Marti Beltz could be citated that: “Borrowing from its successful use in manufacturing, root cause analysis became the tool of choice in the endeavor to increase healthcare quality….” As it could be seen even in the USA Healthcare Industry, the continuous improvement initiatives and quality approach is almost new. That delay could be explained on the common perception that quality and improvement of activities are something common only with product creation. Taking into consideration that most of the continuous improvement initiatives come from manufacturing area, the research team decided to use a more “industrial approach” in rating the clinical and laboratory stages of RPD. Therefore, RCA was considered the critical element in changing the perception of the people involved in healthcare environment from anecdotic decision to fact based initiatives and creative endeavor based on data.

4. The process of developing removable partial dentures A removable partial denture, RPD, (Bortun and Sandu, 2007; Min and Yih, 2009; Susz et all, 2010) is part of the secondary type of prosthetic restorations, which can be inserted and removed voluntarily by the patient, in and out of the mouth. It is a body or physical system, which replaces: missing teeth and their associated structures (periodontal, alveolar bone), tissue lost after extraction and it is characterized by precision and smoothness of the operation. The prosthetic pieces used as support: the remaining teeth, hard component (reliefs osteoperiostale underlying structures) and soft component (fibro‐mucosal) edentulous prosthetic field. Any partial removable denture has a metal component and an acrylic component (Bratu et all, 2008; McGivney and Carr 2000). Images of removable partial dentures images are given in Figure 5.

Figure 5: Removable partial dentures (Ghiban and Bortun, 2009): a – maxillary RPD; b – mandibular RPD The necessary and logic sequence of steps for realization of RPD are given in High Level Map. Any mistake, either during clinical stages or during laboratory stages can induce the causes of damage or premature rupture of the prosthesis. Accidents that may cause the damage to RPD are: fractured arm or spur active occlusal clasp; fractured secondary connector and/or opponent of clasp arm, distorted or broken main connector, terminal saddle distortion or breakage, damage to the normal component acrylic the partial denture. Numerous researchers (Bortun et all, 2010, 2011; Bratu et all, 2008; Ghiban et all, 2010; Ghiban and Bortun, 2009; Ghiban and Ghiban, 2009; Min and Yih, 2009) identified the main causes of fracture. Naik (Naik, 2009) wanted to determine the causes for the fracture of complete dentures and divided them into material factors and clinical/technical factors. In his opinion, there is need for denture care instructions after denture’s delivery; he also concluded that it is important to use resins that have increased fracture toughness. Phases interdependencies implied in RPD making are presented in Figure 6.

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Figure 6: Interdependencies between manufacturing phases The RPD manufacturing process is designed in two stages – clinical and laboratory; there is continuous interdependence between them throughout the process. Following the recommended sequence of the clinic and laboratory steps during the process of RPD realization, by proper process management, might lead to an increased durability of these prostheses, and over 10 years guaranteed durability. By well‐defined methods of optimization and re‐optimization, the increased RPD durability will positively influence the patients’ life quality. The clinic‐technique steps in the manufacture of a RPD are given in a logic sequence in the High Level Map. One may remark the alternative sequence of the steps between these two stages; a very good interdependency being noticed during the whole process of RPD realization. The developing and manufacturing steps are presented in the High Level Process Map (Figure 7).

5. A lean six sigma approach in designing a capable RPD manufacturing process in Romanian healthcare Currently in Romania the RPD manufacturing process is still designed based on a reactive way of solving the defects and failures. Therefore, the main objective is to solve the problems after they occurred and not to design form the start a defective free device. Hence, the specialists have categorised the way of solving the problems in optimization (minor intervention) and reoptimization (major intervention) RPD optimizations are referred to whole improvement of new prosthesis after their insertion. As a rule, only optimization regarding to keeping the stability of the prosthesis, which may be realized by modern methods in every clinic (such as: adhesive using, adapting elements made by the doctor at the movement elements, support and stabilization, facing, restorations). RPD reoptimizations are addressed to integrity and functionalizing optimum recovery of the prosthesis pieces after passing the adapting period and utilization in the mouth cavity. This is necessary due to different accidents which may influence both acrylic and metallic component of the prosthesis. In this category there can be integrated the following: cracks repairing, recovery of acrylic component, fractures, pores inside the metallic components. Welding of the metallic alloys have recently entered in this category, which is influenced by the existence of new performance equipment and adjacent knowledge in the field of metallurgy and welding science. In special equipped laboratory (which may have welding devices) all steps of RPD optimization may be done. The re‐optimizations regarding the plastic forming of the metallic component of RPD, or dropping and crushing could not be done.

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Figure 7: High level process map (crossing the two areas clinic and laboratory)

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Danut Iorga, Alexandru Ghiban and Cezar Scarlat A new possible perspective From a business perspective there is room for improvement of the RPD activities set. To solve the transformation of the design and manufacturing process from unstructured activities to a profitable structured process, the paper propose a Lean Six Sigma for Process Management approach. Thus DMAIC methodology was decided to be used (Iorga, 2012). The first step is Define – Problem statement – Based on questionnaires completed by patients, resulted in a success rate upon insertion of the prostheses in the mouth that is low and always an optimization intervention done by doctor in clinical area is needed. Metrics – % success design and insertion of the prostheses for the first time trial, % success insertion of the prostheses in the mouth after optimization Goal – Increase the success rate after optimization Scope – Clinical and Laboratory areas Critical Customer Requirements and Critical to Quality elements were identified: Critical Customer Requirements:

Minimal time for treatment

Easy to use and fit properly in the mouth cavity

Comfort during mastication and other specific anatomic movements

Durability

Affordable cost

Critical to Quality

Appropriate treatment

Mounting defection free

Prevention of damage or premature rupture of the prosthesis

Inappropriate use of the prosthesis – possible damage

Appropriate post‐treatment

Adequate advisement of the prostheses use

Robustness of the prostheses to different efforts

Based on CTQ formulation it is possible to design the complete process map and identify the relevant factors which influence the output. Measuring the process – Information were collected based on clinical examination and informal questionnaires to determine the cause of reoptimization request. The current data of the paper were informally provided by doctors and technicians:

Number of patients with removable partial dentures optimization – 87%

Number of patients with reoptimizations – 23%

Number of patients with no optimization and reoptimization – 9%

Number of patients who have not returned to dental practice – 4%

Process Analysis RPD are subject to a series of forces deployed (gingival‐occlusal vertical) such as: traction forces exerted by sticky foods, forces exerted by muscles displaced peri‐prosthetic acting on too long edges of the prostheses and deploys the various reflex acts (cough, nausea, vomiting, sneezing). Also other vertical forces (oclusal‐gum)

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Danut Iorga, Alexandru Ghiban and Cezar Scarlat tend to clog prosthesis and prosthetic field structures can damage these (chewing forces, forces arising in para‐functions‐bruxism). This kind of forces cannot be completely balanced, only a very good design doing this. RPD may be moved in – or out of the transversal and sagittal plan due to special anatomical configurations or a deficitary construction, the defective mounting of the artificial teeth (too large/small increases alveolar). When building such prosthesis, it must be met some goal maturities of patients aesthetic, mechanical resistance and the stability in regard to optimal use by patients. So, the following features are very important: accurate working steps, knowing the newest and the most precise modalities of improving the prosthesis durability. RPD may have non‐detectable defects during casting, which may determine a rapid breakage. These defects may be observed by naked eye after dissembling or rapid processing of the prosthesis. Also, these defects could be put in evidence by defectoscopic methods, such as radiographies, holograms, ultra‐wave tests. The prosthetic piece may suffer different modifications of the acrylic components, due to acrylic base of the prosthesis or, artificial teeth. All these modifications are due to the miss of patients’ abilities or to different accidents (cracks, fractures) After the root cause analysis done based on informal answers given by doctor’s results that the percentage distribution of causes that determine the need of removable partial dentures reoptimization had the following distribution:

The clasp tip placed in area with insufficient retention 25%

The fall of the dentures during the hygiene action or clasp’s fracture 25%

Extraction of abutment teeth 18%

Too large size of claps or high rigidity 17%

Casting defects 15%

From Quality perspective the capability of the activity results of the two correlated areas is very poor. Taking into consideration the actual level of rework and failure rate it could be stated that the expected results from customer perception are not satisfactory, based on the data it is almost “impossible” to reach good prostheses from the first trial. As a matter of fact the process itself is designed to cope with failure; this process is not designed to be capable from the beginning. The process steps show a lot of back and forth motion between the two areas. In conclusion from process management perspective it is a gold mine, due to the great opportunity to use the full concept of combination of Design for Six Sigma and Lean Six Sigma with Process Management approach. In the next paragraph the paper will present a possible Transformation Process Maturity Matrix in order to enhance the capability of the results and much more to design from scratch a new process and approach. Transformation Process Maturity Matrix The researchers proposed a matrix in three “rolling” steps to set a management able to create a valuable business from customer perspective. To reach the next stages the management and specialist involved in RPD manufacturing should learn the rules of continuous improvement and to better understand the importance of compliance with customer expectations. Currently the clinics and laboratories from Romania are working as individual entities and are not sharing the same vision to cope with customer requirements, and as a result almost all are behaving as entities in stage 1 (Implement clear rules – unstructured activities). Objectives

Implement clear rules

Methods

Stage – Unstructured activities (current status) Kaizen, PDCA methodology

Results

Procedures Created, both processes are fully understood by the laboratory technicians and doctors

Implement Process Management Concepts Stage – Stable Process TQM, Six Sigma, Lean Production Clinical Process and Laboratory Process are perceived as one process and whole people involved

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Implement Continuous Improvement Concepts Stage – Mature and Stable Process Process Management integrated with Lean Six Sigma and Design for Six Sigma Clinical and Laboratory Processes are fully integrated, doctors, technicians and all the people involved

Danut Iorga, Alexandru Ghiban and Cezar Scarlat understand the importance of cooperation between the two stages (laboratory & clinical) to achieve customer satisfaction

understand the “end to end” process, knows the customer requirements and participate proactive to continuous improvements initiatives. The communication flow is continuous and all the barriers are removed by mutual consensus.

6. Final conclusions and further steps Researchers are in a process of starting a common Design for Six Sigma project with a few clinics and laboratories from Romania. Based on discussions with doctors and technicians it can be concluded that there is a lot of interest in having a methodology to improve the quality of the RPD processes. The matrix was well received by the specialists interviewed at an informal level. Most of technicians expressed their accord regarding necessity of an evaluation method and a work system creation in handling the interrelation process between the two areas involved in RPD design and manufacturing. The matrix seems to respond to their need of communication within processes borders and also was perceived as an objective tool to set plans for common projects (laboratories and clinics) to improve their businesses. Due to the advantage that one of the researchers is Master Black Belt in Lean Six Sigma there is a great opportunity to start a wide program with these entities and schedule trainings with specialist in continuous improvement technics. The originality of this research is the premiere usage of the tools and the methodology in Romanian health industry.

References Bortun, C., Sandu, L. (2007) Ghid practic de tehnologie a protezelor parțiale mobilizabile scheletate, Editura Eurobit, Timişoara. Bortun, C.M., Cernescu, A., Ghiban, N., Faur, N., Ghiban B., Gombos, O., Podariu, A.C. (2010) Durability Evaluation of Complete Dentures realized with Eclipse Prosthetic Resin System, Materiale Plastice,Vol. 47, Issue 2, pp. 240‐243. Bortun CM., Ghiban B., Ghiban A., Cernescu A., Ghiban N., Semenescu A., (2011) Comparative studies of tensile and Bending Behaviour for Some CoCrMo Alloys, Metalurgia International, Vol. 16, Issue 7, pp. 5‐13. Bratu, D., Bratu, E., Antonie, S., Bara, N.A., Baldea, B., Benghia, V., Bortun, C., Chisevescu, M.B., Erimia, R., Fabricky, M., Goguta, L., Jivanescu, A., Marcauteanu, C., Negrutiu, M., Pop, D.A., Sallai, A.M., Sandu, L., Scurtu, R., Topala, F., Borsan, I.A., Maciu, N. (2008) Restaurarea edentațiilor parțiale prin proteze mobilizabile, Editura Medicală Bucureşti, Imprimeria de Vest, Oradea. Cardoso, E.C.S., Guizzardi, R.S.S., Almeida, J.P.A. (2011) Aligning goal analysis and business process modelling: a case study in healthcare. Int.l J. of Business Pro.s In.t and Man. Vol. 5, No. 2, pp. 144‐158. Ghiban, A., Scarlat, C., Iorga, D. (2012) Managing the process of developing removable partial dentures for their increased durability. CD Proceedings of the “4‐th International Conference on Materials Science and Technologies" – ROMAT 2012, October 17th – 19th, 2012, Bucharest, Romania. Book of Abstracts; p.67. ISSN 2285‐7133. Ghiban, B., Ghiban, N., Ghiban, A., Bortun, C.M., Faur, N., Cernescu, A. (2010) ‐ Fracture behaviour of some heat curing dental resins, BIODENTAL ENG., pp. 35‐40. Ghiban, B., Bortun, C.M. (2009) Aliaje dentare de cobalt. Structură, procesare, optimizare, Editura Printech. Ghiban, B., Ghiban, N. (2009) Cobaltul şi aliajele de cobalt, chapter 17, Tratat de Ştiința şi Ingineria Materialelor Metalice, Academia de Ştiințe Tehnice din România, Editura Agir, vol. 3, pp. 960‐970. Jia, J., Du, R., Hu, Q. (2010) Consumer’s optimal policies for purchasing durable goods. International Journal of Services Technology and Management, Vol. 14, No. 1, pp. 41‐57. Hayler, R. and Nichols, M. (2006) Six Sigma for Financial Services, McGrawHill, New York Iorga, D., Scarlat, C. (2012) The Transfer Function, a valuable tool towards the ‘Process‐Focused Organization’. Presented at the International Conference on Technology Innovation and Industrial Management 2012, Building Competences, Synergy and Competitiveness for the Future, May 22 – 25th, 2012, Lublin, Poland, E‐Book of the Conference; p.16 – 31. Juran, M.J., Godfrey, A.B., Hoogstoel, R.E., and Schilling, E.G. (1999) Juran’s Quality Handbook, Fifth Edition, McGraw‐Hill, New York Madison, D. (2005) Process Mapping, Process Improvement, and Process Management, A Practical Guide for Enhancing Work and Information Flow, Paton Professional, Chico California Masoud, A.S.S.A. and Qasim, M. (2005) Increasing spur gear durability: two‐material spur gear. International Journal of Computer Applications in Technology, Vol. 24, No. 3, pp. 171‐179. McGivney G.P., Carr A.B.(2000) McCracken's Removable Partial Prosthodontics, Tenth Ed., Mosby, 2000. Min, D., Yih, Y. (2009) A simulation study of registration queue disciplines in an outpatient clinic: a two‐stage patient flow model. European Journal of Industrial Engineering, Vol. 3, No. 2, pp. 127‐145.

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Danut Iorga, Alexandru Ghiban and Cezar Scarlat Mont, O. (2008) Innovative approaches to optimising design and use of durable consumer goods. International Journal of Product Development, Vol. 6, No. 3/4, pp. 227‐250. Moyano‐Fuentes, J., Martínez‐Jurado, P.J., Maqueira‐Marín, J.M. and Bruque‐Cámara, S. (2012) ’Impact of use of information technology on lean production adoption: evidence from the automotive industry’, International Journal of Technology Management, Vol.57, No.1/2/3, pp.132 ‐ 148 Naik, A.V., (2009) Complete denture fractures: A clinical study, Journal Indian Prosthodont, 9, pp. 148 Phoenix, R.D., Cagna, D.R., Defreest, C.F. (2003): Stewart's Clinical Removable Partial Prosthodontics, Quintessence Publishing Co, Inc, Chicago. Pourshahid, A., Amyot, D., Peyton, L., Ghanavati, S., Chen, P., Weiss, M. and Forster, A.J. (2009) ’Business process management with the user requirements notation’, Electron Commer Res, Vol. 9, pp. 269‐316 Susz, C., Reclaru, L., Ardelean, L., Ghiban, B., Rusu, L. (2010) Aliaje dentare, Editura „Victor Babeş” Timisoara. Wagner, B. and Kern, M. (2000) Clinical evaluation of removable partial dentures 10 years after insertion: success rates, hygienic problems, and technical failures. Clinical Oral Investigations, Vol. 4, No. 2, pp. 74‐80. Waldmeier, M.D., Grasso, J.E., Norberg, G.J., Nowak, M.D. (1996) Bend testing of wrought wire removable partial denture alloys. Journal of Prosthetic Dentistry, Vol. 76, Issue 5, November 1996, pp. 559‐565.

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Entrepreneurial Behavior and Interactivity of Sri Lankan Farmer Groups Chandana Jayawardena1, 2 and Madushi Abeyrathne2 1 Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic 2 Department of Agric Extension, University of Peradeniya, Sri Lanka chandanacj@gmail.com Abstract: Farming is increasingly been seen to be less attractive in commercial viability in the Sri Lankan farming community. Among the many factors influencing the entrepreneurial behavior of farmers, group interactions are of high importance. Understanding these interactions could be useful to foster entrepreneurial activities. Study was conducted among the farmers in Matale district, which is among the top 4 districts producing high amount of vegetables in Sri Lanka. Two successful farmer organizations, one farming throughout the year (in Yala and Maha seasons) and the other farming only in Yala season, were selected for the study. Overall objective of the study was to examine the entrepreneurial behavior of vegetable farmers. Stratified random sampling was used to select a sample of 60 vegetable farmers, 30 each from the two farmer organizations. Descriptive and inferential analyses were conducted. Overall group interaction and entrepreneurial behavior of the sample was at a moderate level. Study revealed effective entrepreneurial behavior involving high planning ability, and decision making ability. Majority of the farmers possessed a moderate level of innovativeness, risk orientation, coordinating ability, opportunity seeking behavior, self‐confidence, and achievement motivation. Group interactions were low at land preparation, pest and disease controlling, harvesting, irrigation water distribution, participating in training programmes, and selling of harvest. Entrepreneurial behavior of farmers have enhanced with group interactions. The group characteristics of the two farmer groups had resulted significant differences in their group interactions and entrepreneurial behavior. Entrepreneurial behavior of the farmers was not prominent in vegetable cultivation. Risk orientation of farmers’ was reportedly low. Low group interactions in the marketing of produce seemed to have an impact on the commercial viability of their operations Entrepreneurial behavior of farmers enhanced with socio‐economic status and social participation. Keywords: entrepreneurial behavior, farmers, interactions

1. Introduction Amidst the diversity of approaches to study entrepreneurship, one can find different definitions for entrepreneurship. Webster’s Dictionary defines entrepreneurship as “creation of a new, innovative, profit oriented, visionary economic organization that exists in uncertain environments carrying some risk”. In other words, an entrepreneur can recognize a great opportunity and add value, using the necessary resources. In developing countries entrepreneur is identified as a person who is self‐employed, earns his living, establishes his business and has a status in society (Farook, 1992). There is a long history of economic research on entrepreneurship. Empirical evidences suggest entrepreneurial behavior as a function of the characteristics of the person and the environment (Chell et al., 1991). As per Solanki and Soni (2004) an entrepreneur may be differentiated not only in terms of the kind of activities he pursues but in the context of his life style, attitudes, values and behavior which together go to make the entrepreneurial personality. Entrepreneurs have been instrumental in initiating socio‐economic development. Entrepreneurs discover new sources of supply of materials and markets and they establish new and more effective forms of organizations and perceive new opportunities with super‐normal will power and energy, essential to overcome resistance that social environment offers (Solanki and Soni, 2004).

1.1 Entrepreneurship among farmers Empirical findings suggest that entrepreneurship is conceived as a personal quality which enables certain individuals to make decisions with far reaching consequences by acting differently from other people and achieving success in doing so. These examples often cause other people to change their mind too. Many contextual factors may exert an influence on entrepreneurial behavior and success (Woo et al., 1988). Agricultural development facilitates a better living standard for farmers by producing more and selling more. Farming success tends to increase farmers’ self confidence. Their increasing contacts with merchants and government agencies would draw them into a closer acquaintance with the world beyond them.(Kruijssen et al. 2006) Compared with other enterprises, agriculture has some unique problems, as it heavily depends on a biological relationship which is affected by factors like climate, diseases, pests, storage, and fluctuation of price. An entrepreneur has little or no control over many of these factors. Under the existing dynamic and

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Chandana Jayawardena and Madushi Abeyrathne competitive economic environment, individual farmer can do very little. Collective effort of farmers empowers them with greater control. (Kruijssen et al. 2006). Entrepreneurial behavior of farmers has an impact on their profit making. Entrepreneurial behavior depends on a number of factors like risk taking, feedback usage, persistence, hope of success, confidence, knowledge, manageability, achievement motivation, persuability, and innovativeness (Murali and Jamtani, 2003). Chaudhari et al. (2007) have indicated that, entrepreneurial behavior was based on nine characteristics, viz. innovativeness, achievement motivation, decision making, risk orientation, co‐coordinating ability, planning, information seeking behavior, cosmopoliteness and self confidence. Furthermore, Chaudhari et al. (2007) developed an index to measure entrepreneurial behavior of dairy farmers. Individual’s entry into entrepreneurship that relies on theories of social norms and individual attitudes typically posits that intentions precede entry and attitudes precede intentions (Krueger et al., 2000).

1.2 Network linkages Johannison (1987) identified a high degree of network linkages and ties in two rural regions in Sweden, indicating that in some circumstances the network may lead to direct support in raising finance, inter trading and cooperative efforts. Wijekoon, and Jayawardena (2010) found positive significant relationships ‘between the use of information sources and personal factors, viz. age, social participation, degree of exposure to mass media, innovativeness, and risk orientation’. They also identified fellow farmers to be the mostly available information source. Johannisson (1987) pointed out that the entrepreneur is a networking person and that the personal network is the vehicle by which the established entrepreneur exchanges information while he acquires resources from the environment. In the conduct of a collaborative task, there are varying levels of interaction among group members. It has been found that main characteristics of informational influence such as information sharing, factual and task messages, rational decision model, etc., are reflected in task activities of asking for and giving information, suggestions, and directions (Bales, 1950). Social interactions refer to particular forms of externalities, in which the actions of a reference group affect an individual’s preferences. The reference group depends on the context and is typically an individual’s family, neighbors, friends or peers (Steiner, 1972).

1.3 Groups and interactions The main characteristics of normative influence, such as group relationships, morality of care, seeking subjective virtue, group norms, preferences, maintaining harmony, etc., are essentially centered on relationships between group members or needs/ preferences of members (Bales, 1950). Interpersonal relations are the important aspects of social life and it is easily achieved at group situations (Festinger, 1953). Group is a stage where members meet and negotiate personal interests and some members try to obtain power and status through groups and organizations (Pretty and Word, 2001). ‘Behavior of a person is governed by interactions, and interrelations with other people’ (Padmaja and Batilan, 2005). Pretty and Word (2001) reported that factors such as age, education, gender, group size, heterogeneity of members, resourcefulness of members, and previous experience on collective actions influence collective actions. However, Kruijssen et al. (2006) reported that collective activities were always not possible in the resource‐less farmer groups. Accordingly, lack of capital makes difficult in maintaining groups among poor farmers. Farmer groups reduce transaction cost, improve marketing facilities, reduce cost of cultivation, and facilitate other services (Choupkova and Bjornskov, 2002). Other benefits of farmer groups are; initiating and establishing culture of cooperation and coordination for their own benefits (Putnam, 1995), conducting collective actions to overcome common problems (Bebbington, 1996), improving resource management strategies resulting in growth of local market and rural economy (Bebbington, 1996), developing networks among members and facilitate members to share ideas and find ways for mutual supports. Farmers’ groups help extension agents to improve member farmers’ knowledge and practical skills of agricultural technologies (Putnam, 1995). Entrepreneurial action is embedded in social interactions with other individuals (Sarason et. al. 2006). Autio and Wennberg (2010) revealed strong group‐level effects on entrepreneurial behaviors. They found nearly 50% of the total variance in entrepreneurial behaviours resides between social groups, and that it is not attributable to individual level characteristics. Further, the influence of group‐level attitudes and social norms on individual level entrepreneurial behaviours was up to three times as strong as the influence of individual‐ level attitudes and norms. These findings show that individual‐level entrepreneurship is, to a grater degree, a reflection of group‐level dispositions, suggesting that the dominant, individual‐centric and dispositional explanations of entrepreneurship are therefore, at best, incomplete.

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1.4 Scope of the study Among the many factors influencing the entrepreneurial behavior of farmers, group interactions are given a high importance. Especially, in Sri Lankan context group interactions help to manage labour cost in farming. This study examines ‘whether there is an impact from group interactions to improve entrepreneurial behavior of farmers?, and, what the resulting effects?.’ General objective of the study was to examine the entrepreneurial behavior of vegetable farmers. The specific objectives of the study were to identify the major entrepreneurial behavioural characteristics of farmers, to distinguish, and assess the varying entrepreneurial behaviours of farmers and to examine the relationship between the interactions and entrepreneurial behaviour of farmer groups.

2. Methodology 2.1 Operationalization of research Farmer organizations of Matale district in Sri Lanka was selected for the study. Matale has been among the top 4 districts producing high amount of vegetables in Sri Lanka. It has over 220 farmer Organizations. An exploratory research to identify the farmer groups, and activities was conducted with the participation of community leaders and government Agricultural Instructors (AIs’). Naula, and Dambulla Divisional Secretariat (DS) areas were selected from Matale district. Naula DS area consists of farming organisations growing vegetables throughout the year, namely during the seasons of Yala and Maha. However, majority of farmers in Dambulla DS area cultivates vegetables only during the Yala season. Sinha farmer Organization from Naula DS area and Mahasen farmer Organization from Dambulla DS area were selected for the study. Among the 75 farmer organizations in Naula DS area, Sinha farmer organization was the most active farmer organization, as per the reports of AIs’. Similarly, among the 90 farmer organizations in Dambulla DS area, Mahasen farmer organization was the most successful.

2.2 Research instruments and data analysis Stratified random sampling was used to select a sample of 60 vegetable farmers, 30 each from these two farmer organizations. Farming experience, Age, and continuity in farming were identified as the major criteria. Primary data were collected through a questionnaire survey, which was followed by informal discussions and key informant discussions. The entrepreneurial behavior scale developed by Chaudhari et al. (2007), was incorporated into the questionnaire to assess the farmers of entrepreneurial behaviour. Assessment of group interactions was based on the five statements (covering the differing aspects) used for assessing group interactions introduced by Kaplan and Miller for research on Group decision making (1987). It had a likert scale for answers in the range of 1 to 5 for each statement. Data were analyzed using the Statistical Package for Social Sciences. Descriptive data were presented using tabular analysis and relationships were tested through correlation tests, and using 2‐independent sample t‐tests (Mann Whitney Test) for non‐parametric data.

3. Results and discussion All the respondents (farmers) were males and they varied from 25 years to 60 years in age.

3.1 Group interactions among farmers Group interactions of farmers were assessed by measuring their involvement in group activities of selected eight practices in vegetable cultivation. Group interactions of each practice were measured using five statements and responses are depicted in table 1. Table 1: Scoring pattern of group interactions Answer Very high High Low Very low Not at all

Score 5 4 3 2 1

Source: Authors’ classification

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Maximum score 25 20 15 10 05

Chandana Jayawardena and Madushi Abeyrathne Group interactions of the farmers were measured in eight identified activities namely; seasonal planning, crop selection, land preparation and field planting, irrigation water distribution, controlling of pests and diseases, participating in training programmes, harvesting, and selling. Table 2 depicts the categorization of group interactions of practices as low, moderate, and high. Table 2: Categorization of group interactions by their scores Group interactions category Low Moderate High

Score ≤15 16‐20 ≥21

Source: Authors’ classification

High 3

Low 30

Moderate 67

Figure 1: Percentage distribution of respondents by group interactions As shown in Figure 1 above, 67% of the farmers perceived their group interactions in vegetable cultivation as moderate.

3.2 Task interactions and social interactions Task interactions among farmers were at a moderate level. Seventy two percent of the farmers responded that, sharing of information, suggestions, directions, and rational decision making of the group were at a moderate level. Social task interactions of the respondents were at a moderate level. Fifty five percent of the farmers responded that, conformity to norms, consideration about preferences of group members, and morality of care of the group were at moderate levels.

3.3 Entrepreneurial behaviour characteristics of respondents Farmers were assessed of their following seven characteristics of entrepreneurial behaviour. i.) Planning ability of the respondents Planning ability of the respondents was measured by using five statements, each of them were allocated scores from 1 to 4. Total scores below 10 were categorized as low; 10‐15 scores as moderate, and scores over 15 was categorized as high. Among 60 respondents, 70% of farmers had well planned their cultivation activities. In Mahasen farmer group planning ability of the respondents was higher than observed at Sinha farmer group. Farmers in the Mahasen farmer group had to adopt the seasonal plan, and those who could not follow that would have to pay a fine. ii.)Information seeking behaviour of the respondents Information seeking behavior of the farmers was measured by using 14 information sources and their frequency of usage by farmers. Frequencies were given scores from 1 to 3. Total scores below 18, were categorized as low, 18 and 28 as moderate and scores over 28 was categorized as high information seeking behavior. About 85% of respondents had a moderate information seeking behavior. Majority of the farmers did not use television, radio, newspapers, telephone, and NGO officers to get information frequently. Most of them had used family members, friends, relatives, AI’s, agriculture research and production assistants (ARPA’s) frequently to get information. iii.) Innovativeness of the respondents Innovativeness of the respondents was measured by using five practices which were introduced recently for vegetable cultivation and were allocated scores from 0 to 3, based on the number of years they had used

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Chandana Jayawardena and Madushi Abeyrathne them. Total scores below 5 were categorized as low, 6 and 10 were categorized as moderate, and scores over 10 were categorized as high. Seventy five percent of the respondents had a moderate level of innovativeness. Most of them never searched for new markets. However, they used plastic trays to transport their products. Mahasen farmer group had 30% of framers with a high level of innovativeness. iv.) Risk orientation of the respondents Risk orientation of the respondents was measured by using five statements, assigning scores from 1 to 3. Total scores of below 8 were categorized as low, 8 and 12 as moderate, and over 12 were categorized as high. There was not much difference in the risk orientation between the two farmer groups. Sixty three percent of respondents had a moderate level of risk orientation. Majority considered vegetable cultivation as risky and they opted to try new practices only after seeing successful results of other farmers. v.) Decision making ability of the respondents Decision making ability of the respondents was measured using eight practices and allocating scores (1 to 3) based on approach to taking decisions. Total scores below 13 were categorized as low, 13 to 19 as moderate, and over 19 were categorized as high. Ninety percent of the farmers had high level of decision making ability. Most of the farmers decided on their cultivations through their own experiences. Majority of farmers were not mindful/ thoughtful of practicing sprinkler or drip irrigation, and crop insurance. vi.) Achievement motivation of the respondents Achievement motivation of the respondents was measured by using ten statements awarding scores of 1 to 2. Total scores below 7 were categorized as low, 7 and 8 were categorized as moderate, and scores over 8 were categorized as high. About 52% of total respondents had a high achievement motivation. Motivation levels to earn higher profits, to be a well known farmer, and to accomplish tasks better than others were at moderate levels. Sixty percent of the farmers in Mahasen group had a high level of achievement motivation. They were highly profit oriented, and ambitious in farming. vii.) Self confidence of the respondents Self‐confidence of the respondents was measured by using five statements, allocating scores of 1 to 2. Total scores below 8 were categorized as low, 8 and 10 were categorized as moderate, and scores over 10 were categorized as high. About 47% of the respondents had a moderate level of self confidence. Most of the farmers lacked confidence in profit making through vegetable cultivation, and most of them relied on others in carrying out farming activities. They did not take the initiative in selecting a crop/s for the season, deciding time for land preparation, planting, harvesting and selling etc. Farmers perceived that adapting to new situations, concentrating on a task, and saying the right opinion at right time to be at a moderate level among them.

3.4 Entrepreneurial behaviour of the respondents Based on the values obtained from the entrepreneurial behavior (Index) three categories were identified. Index value below 65 was categorized as low, 65 and 75 as moderate, and over 75 was categorized as high. The overall entrepreneurial behavior of the respondents was at a moderate level (mean value 71.186, standard deviation = 0.17). Among the ten entrepreneurial characteristics planning ability and decision making ability were at a high level (mean values were 2.7 and 2.9 respectively). Other characteristics were at a moderate level. As shown in Figure 2, Twenty three percent of the respondents had a high level of entrepreneurial behaviour. High 23

Low 24

Moderate 53

Figure 2: Percentage distribution of respondents’ entrepreneurial behaviour

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3.5 Significant associations

% Respondents

Relationship between group interactions and entrepreneurial behaviour There was a positive significant relationship between the group interactions of farmers and their entrepreneurial behavior (r=0.507, p=0.001, significant at 0.01 level). Figure 3 indicates that all the respondents indicating high group interactions reported high entrepreneurial behavior (EB). Among the farmers reporting low group interactions, 50% of them had low entrepreneurial behavior.

100 90 80 70 60 50 40 30 20 10 0

EB Low EB Medium EB High

Low

Medium

High

Level of Group Interactions Figure 3: Percentage distribution of respondents’ group interactions and entrepreneurial behaviour Entrepreneurial behavior of the two farmer groups As per the 2‐independent sample t‐test (Mann Whitney Test) there was a significant difference in entrepreneurial behavior (p=0.007, significant at 0.01 level) of two farmer groups. Eighty six percent of the respondents who had high entrepreneurial behavior belonged to Mahasen farmer group, whilst the corresponding figure was 14% in Sinha farmer group. In Mahasen farmer group planning ability, coordination ability, and innovativeness of farmers were at a higher level than Sinha farmer group.

4. Conclusions 4.1 Conclusions There was a significant relationship between the group interaction level, and entrepreneurial behavior of farmers. Entrepreneurial behavior of farmers varied with farmer groups. Group interactions of farmers were found to be moderate. Entrepreneurial behavior of the farmers was not prominent in vegetable cultivation. Majority of the farmers possessed a moderate level of innovativeness, risk orientation, coordinating ability, opportunity seeking behavior, self‐confidence, and achievement motivation. Decision making ability and planning ability of farmers were at a high level. Risk orientation of farmers’ was reportedly low. Entrepreneurial behavior of farmers enhanced with socio‐economic status and social participation. Group interactions of the farmers were high at seasonal planning, and selecting of crops. Very low group interactions in marketing the produce seemed to have an impact on the commercial viability of farming operations.

4.2 Limitations and further research The static nature of data is a serious weakness of contemporary management research. This study also falls into this category as the data collection (interviewing and surveying) was carried out at a particular point in time during the year 2011. Also, the farmers behaviours were assessed only based on their perceptions. A longitudinal research incorporating more objective data (i.e. profits, and profitability of farmers, times spent

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Chandana Jayawardena and Madushi Abeyrathne for farming, alongwith feedback of key stakeholders in addition to farmers) is bound to provide more insightful facts.

Acknowledgements Authors are thankful to the Internal Grant Agency of FaME TBU No. IGA/FaME/2012/038 (Emotional Intelligence, academic performances and managerial effectiveness) SPP No: 50905 / 2110 / SV50134001020‐ 2110‐UN, for providing financial support to this research.

References Autio, E. Wennberg, K. (2010), Social Attitudes and the Transition to Entrepreneurship, Summer Conference 2010, Imperial College, London Business School. Bales, R. F. (1950), Interaction process analysis: A method for the study of small groups, Cambridge, MA: Addison – Wesley. Bebbington, A. (1996), Organizations and Intensifications: Campesino Federations, Rural livelihoods and agricultural technology in the Ands and Amazon: World Development. Chaudhari, R. R., Hirevenkanagoudar, L. V., Hanchinal, S. N., Mokashi, A. N., Katharki, P. A. and Banakar, B. (2007), A Scale for Measurement of Entrepreneurial Behavior of Dairy Farmers. Karnataka Journal of Agricultural Science. Vol.20, No. 4 Chell, E., Haworth, J. and Brearly, S. (1991), The entrepreneurial personality: Concepts, cases and categories. Routledge, London. Choupkova, J. and Bjornskov, C. (2002), “Counting on social capital when easing agricultural credit constraints”, Journal of Microfinance. Farook, M. R. M. (1992), Traditional and New Entrepreneurs in Sri Lanka, PIM conference of Management Studies, University of Sri Jayewardanapura. Festinger, L. (1953), “Group Attraction and Membership”, in Cartwright, D. and Zander, A.,(eds). Group Dynamics. Research and Theory, Evaston , Row, Peterson and Company. Fershtman, C. Murphy, K. M. and Weiss, Y. (1996). Social Status, Education and Growth, Journal of Political Economy, Vol.104, No.1, pp. 32 ‐ 108. Granovetter, M. (2005). The Impact of Social Structure on Economic Outcomes, Journal of Economic Perspectives, 19(1): pp. 33–50. DOI: 10.1257/0895330053147958 Johannisson, B. (1987), “Beyond Process and Structure”: Social Exchange Networks, International Studies of Management and Organizations, Vol. XVII, No. 4. Kaplan, M. F. and Miller, C. (1987), Group decision making and normative versus informational influence: Effects of type of issue and assigned decision rule. Journal of Personality and Social Psychology, Vol. 53, No.2. Krueger, N. F., Reilly, M. D. Carsrud, A. L. (2000), Competing models of entrepreneurial intentions, Journal of Business Venturing, Vol. 15, pp.5‐6. Kruijesen, F., Keizer, M. and Giuliani, A. (2006), Collective actions for small produces of agricultural biodiversity products. Research Workshop on Collective action and market for smallholders, Oct.2‐5, 2006, Cali, Colombia. Murali, K. and Jamtani, A. (2003), Entrepreneurial Characteristics of Floricultural Farmers. Indian Journal of Extension Education. Vol. 34, pp.1, 2. Pretty, T. and Word, H. (2001), Social Capital and Environment. World Development, Vol. 29, No. 2. Putnam, R. (1995). Bowling Alone: America’s Declining Social Capital. Journal of Democracy. Vol. 6. Sarason, Y., Dean, T., and Dillard, J. F. (2006), Entrepreneurship as the nexus of individual and opportunity: A structuration view, Journal of Business Venturing, Vol. 21, No. 3 Solanki, K. D. and Soni, M. C. (2004), Entrepreneurial Behavior of Potato growers, Indian Journal of Extension Education. Vol. 40, pp. 3‐4 Steiner, I. D. (1972), Group process and productivity. New York, Academic Press. Webster’s Seventh New Collegiate Dictionary. (1975), Springfield, MA: G. C. Merriam. Wijekoon, W M N D., and Jayawardena, L N A C., (2010), Utilization of Sources of Information for decision making of Farmers – A Case Study, Peradeniya University Annual Research Sessions‐2010, University of Peradeniya, Sri Lanka. Woo, C. Y., Dunkelberg, W. C. and Cooper, A. C. (1988), Entrepreneurial typologies: definitions and implications. International Journal of Selection and Assessment,Vol. 1, No. 2.

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Business Modeling for Sustainability: Identifying Five Modeling Principles and Demonstrating Their Role and Function in an Explorative Case Study Jan Jonker1 and Nikolay Dentchev2 1 Nijmegen School of Management (NSM),Radboud University Nijmegen (RU), Holland 2 University of Brussels (VUB) and HUBrussel, Belgium j.jonker@fm.ru.nl nikolay.dentchev@vub.ac.be Abstract: The mainstream literature describes business as tools for earning money (e.g. Osterwalder, 2004, Magretta, 2002). Although profit generation is an important business outcome, it tends to overlook the business opportunity of embracing issues of sustainability. Conventional business models theories do not capture the value of social and environmental assets, nor do they stimulate the development of business models focused on the solution of sustainability issues (i.e. not on earning money). We approach this void in the literature from the literature on on sustainability and corporate social responsibility. This literature was used a top‐down theorizing approach (Shepherd and Sutcliffe, 2011) that allowed us to propose 5 additional principles of business modeling next to the principle of profitability: (1) multiple value creation; (2) basic logic; (3) strategic choice; (4) value network and (5) cooperative organizing. We have provided further corroborative evidence of these principles from an explorative case study of Close the Gap. This paper contributes to extend the profit generation focus in the literature of business planning toward principles of sustainability. Attention to social and environmental issues makes a perfect sense to business, and can lead to new opportunities. Keywords: sustainable business models, sustainable development, corporate social responsibility, profit generation, case study, theory building

1. Introduction Conventional business models are predominantly oriented towards shaping the process of making money. Osterwalder argues that, “A business model is a conceptual tool that contains a set of elements and their relationships and allows expressing a company's logic of earning money.”(Osterwalder, 2004) p. 15, emphasis added). Using Magretta (2002), business models can be described as narrative and exactable stories, in which human behaviour and stakeholder motivations are combined in such a way that this leads to sensemaking. This may initially appear as a different approach to business modeling, however, she then subsequently also stresses that business models answer one of “the fundamental questions every manager must ask: How do we make money in this business?” (Magretta, 2002), p. 87).A perspective towards business models significantly resembles mainstream neo‐classical economic thinking. A famous proponent of this theory, Milton Friedman, once asserted that the only social responsibility of business organizations is profit generation (Friedman, 1970). Although earning money and profit generation are important business derivatives, this paper intends to question the centrality of this thinking by exploring how sustainability can be embedded into business models. Traditionally, business models are not (always) oriented towards the values and principles of sustainable development, perhaps due to the fact that these are not expressed in monetary terms. Excluding these values and principles from business models is a clear shortcoming in view of the challenges that our planet is facing. Even businessmen, exposed to the pressure of profit generation, acknowledge that business models are about more than earning money. Herman Wijffels (former CEO of the Dutch Rabobank), for example, asserts that “What companies do isn’t just important to shareholders and employees, but also to society and the earth as the source of life as well” (Wijffels, 1999, p. 113). We readily acknowledge that many businessmen, even amongst the most hardnosed profit‐driven ones, are convinced about the need for sustainability. Their attention is caught by the “Inconvenient Truth”, as Al Gore would say. Or stated otherwise, the attention of businessmen is caught once the risks of global warming, resource depletion, and social instability for their businesses become evident. Without doubt, some business leaders pay genuinely personal attention to sustainability; however, their numbers must be rather insignificant as evidenced by Ban Ki‐moon, the secretary‐general of the United Nations, stating rather recently that our current model of economic development and growth is ‘suicidal’ (Source: digital press‐release website World Economic Forum, Davos, 2011).

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Jan Jonker and Nikolay Dentchev Since conventional business models pay insufficient attention to sustainability, this void will be addressed here. This paper first elaborates on the values and principles of sustainability and subsequently, illustrates them in an exploratory case study. This pattern allows this paper to contribute to strengthening theory building of sustainable business models. An empirical example of a successful sustainable business model is also provided in support of our theory that there are powerful alternatives to resolve the sustainability issues of our planet. We conclude this contribution with a discussion on the implications of our ideas on sustainability management and on future research.

2. Sustainability principles The literature on sustainable development has a long tradition of opposition towards emphasising only profit generation. The contemporary idea of sustainable development is concerned with addressing social capital and protecting the natural environment in addition to creating welfare (Aguirre, 2002). This central idea refers to the so‐called triple bottom line principle advanced by Elkington (1997). According to this principle, companies should organise in such a way that they pay simultaneous attention to people, planet and profit. Waddock goes one step further and is even a proponent of multiple‐bottom lines (Waddock, 2000). Extending the profit bottom line, as argued by the World Commission for Sustainable Development, needs to take place “in harmony and enhance both current and future potential to meet human needs and aspirations” (Brundtland, 1987), p. 46). In other words, our attention to multiple bottom lines needs to also be sustained over time with attention paid to future generations. Related perspectives to sustainable development (e.g., corporate social responsibility, social return on investment, and circular economy) are critical towards the neo‐classical dogma of ‘pure’ profit generation(Windsor, 2001, Wood, 2000, Margolis and Walsh, 2003, Dentchev, 2009). Carroll adds to the economic principle of profit generation three principles of corporate social responsibility: legal, ethical and discretionary (Carroll, 1979, Carroll, 1991). Business organizations are expected, in the CSR tradition, to prevent negative social impacts and to promote social prosperity (Fitch, 1976, Jones et al., 2000, Wells, 1998). Overall, corporate social responsibility advances normatively correct principles of business (Swanson, 1995, Wartick and Cochran, 1985, Wood, 1991). CSR scholars have even attempted to demonstrate the superiority of their theory over the neo‐classical economic theory by demonstrating that CSR leads to superior financial performance (Orlitzky et al., 2003). However, such a demonstration proves quite challenging due to the high level of aggregation and the complexity of the phenomena under study (Jawahar and McLaughlin, 2001, Griffin and Mahon, 1997, Arlow and Gannon, 1982, Margolis and Walsh, 2001). As these studies revealed positive, neutral, and negative relationships between CSR and financial performance, certain scholars have argued in favor of more corroborative approaches to CSR strategies (Dentchev, 2004, Perrini et al., 2011). Taking into account the inability of many organisations to address organizing multiple values competence development in this respect is urgently needed. Evidently this will take time. Addressing these may not be the quickest path to wealth, however, it is a very appropriate way to solve pressing social and environmental issues involving our planet. In addition to the idea of multiple bottom lines, sustainable development scholars argue in favor of inclusive and connected development(Gladwin et al., 1995). This implies attention and involvement of stakeholders including the less privileged ones(Sen et al., 2002). It also implies that businesses engage not only the most powerful stakeholders (in terms of the capability of being heard and exercising influence) (Clarkson, 1995) but also the fringe ones (Hart and Sharma, 2004). The engagement of these stakeholders results, ultimately, in positive business outcomes since these groups are powerful sources of innovation and an important source for future businesses. Translated in regards to business models, the above principles of sustainability imply simultaneous attention to the business case, the natural case, and the social case (Birkin et al., 2009). Otherwise stated, sustainable business models possess the ability to generate multiple values. Engagement with a wide range of fringe stakeholders, as Hart and Sharma (2004) demonstrate, is based on clear business logic. They contribute to sustaining the operating business while opening up new horizons and innovative opportunities for the organization. In addition, Prahalad (2010) clearly indicates that attention to the “bottom of the pyramid” is a sound strategic choice rather than an idealistic decision. The same strategic logic is argued for companies with proactive attention to environmental issues (Buysse and Verbeke, 2003, Aragón‐Correa and Sharma, 2003).

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Jan Jonker and Nikolay Dentchev Integrating sustainability in business models requires a systemic and holistic approach (Senge et al., 2008, Dentchev et al., 2011). From this perspective, multiple value creation is realized as a joint effort between the organization and its stakeholders. It is the culmination of stakeholder engagement and cooperation in an environment that enables such a type of cooperation (Simanis and Hart, 2009). Sustainable business models are based on the conception that value networks of stakeholders create value in cooperation. These networks share a basic logic – a set of values – and have made a strategic choice regarding the issues they will address in their collective organizational efforts. Based on the above, a number of principles enabling the creation of sustainable business models can be identified: (1) multiple value creation; (2) basic logic; (3) strategic choice; (4) value network and (5) cooperative organizing.

3. An explorative case study We would like to illustrate the above principles of sustainable business models in a corroborative case study. The development of this case study follows an inductive top‐down theorizing approach (Shepherd and Sutcliffe, 2011). According to Shepherd and Sutcliffe: “Inductive top‐down theorizing begins with data contained in the Literature from which problems (tensions, conflicts, and/or contradictions) and potential solutions (literature, theories, constructs, relationships) emerge to offer a description and then a coherent resolution of a research problem, ultimately constituting a new theory of organization.” (p. 366) In fact, the preceding sections of this paper were based on literature where we have identified the tension between the conventional business models theory (advancing profit generation) and sustainability (advancing attention to multiple values and multiple stakeholders). As a result, we proposed five fundamentals of sustainable business models (multiple value creation, basic logic, strategic choice, value network, cooperative organizing) and would like to corroborate them with an exploratory case study. We have studied the case of Close the Gap, a non‐profit organization active in IT systems for low budget projects in primarily developing countries, and headquartered in Brussels, Belgium. This case was selected due to its fit with the phenomenon of our study, sustainable business models, and on the following criteria: (i) profit generation is not central here (non‐profit); (ii) attention to social issue (IT access in developing countries); (iii) attention to environmental issues (recycling of IT systems); and (iv) the success of the initiative (UN recognition). The second author conducted a systematic search in a Belgian newspaper database, Mediargus (on 13.03.2013) and gathered 57 pages (A4, Times New Roman font, single spacing) of articles about Close the Gap. Article publication dates range from 3.4.2003 through 3.10.2012. Our search resulted in 115 articles. After eliminating irrelevant articles and the same article being published in different journals, we gathered information from 48 articles. Articles are in Dutch and quotes further in the text are a free translation. In addition, this information was triangulated with the organization’s website (http://www.close‐the‐gap.org), annual reports, film describing the organization (duration 12:12 min), and testimony of the founder, Olivier vanden Eynde, during the class time of the second author on 27.11.2012 (duration 1h30min).

4. ‘Close the Gap International’ and its sustainable business model 4.1 Background Olivier vanden Eynde (°1979) founded Close the Gap International vzw (hereafter, Close the Gap) in 2003 during his studies at the University of Brussels (VUB), Belgium. The initiative began as a student enterprise of a group of six students during his studies in commercial engineering. Olivier’s idea was a natural occurrence resulting from his father’s decision to renew the computers at his company. Olivier, the oldest in a family of 6 children, recycled the old computers into an IT network for his siblings. This led to the epiphany, “If an SME like my father’s replaces PC’s like that every few years, what about multinationals?” Olivier realized that an old PC can easily function for many years after being replaced and could be more beneficial in developing countries, where resources for IT are a luxury. Hence, this straight‐forward logic gave birth to Close the Gap, i.e., closing the digital gap in developing countries. Following his studies, Olivier dedicated himself full time to developing this noble venture and even rejected two proposals for a career within the big 4 consultant firms. Ten years later, Close the Gap has been recognized as a UN – NGO with 250.000 donated PCs realised in projects in 40 countries.

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4.2 Basic logic Close the Gap approaches the social issue of digital exclusion with a basic, simple logic. Quoted in an article in Het Nieuwsblad dd 26.11.2013, Olivier vanden Eynde explains this logic as follows: “Companies change their computers every 3 to 4 years while there is, basically, nothing wrong with these computers. Removing them safely costs easily 50 EUR per computer, so we offer an alternative: we collect the computers and take care of all necessary treatments and logistics”. Hence, old computers function perfectly in such a second life and could be beneficial in budget sensitive communities. Close the Gap guarantees certified elimination of the information from the computers. Subsequently, they repair and clean the computers, install new software, and ship them to developing countries. The same basic and simple logic was applied when Close the Gap derived a spin‐off activity known as WorldLoop. The service performed by WorldLoop is oriented to recycling outdated PCs in developing countries. Close the Gap realized that, by solving one sustainability issue (closing the digital gap in budget limited environments), another is fueled, i.e., IT waste in developing countries. Hence, WorldLoop organizes the recycling of IT waste in developing countries. For complex recycling matters, whereby it is not possible to rectify the situation locally, the organization discovered a solution in the Umicore n.v. plant near Antwerp, becoming one of the few organizations authorized to import industrial garbage into Belgium.

4.3 Value network During the 10 year journey of Close the Gap, it depended on a profound and valuable network. Advise and active support was granted by Nobel Prize Winner Desmond Tutu; King Philippe and Queen Mathilde of Belgium; IOC chairman Jacques Rogge; (former) European Commissioners Neelie Kroes ‐ Étienne Davignon ‐ Karel Van Miert;(former) ministers Frank Vandenbroucke – Xavier de Donnea – Louis Michel – Patricia Ceysens; many professors; businessmen; and friends. Such an extended network adds value to the project and induces commitment, contacts, and further opportunities for growth. A good example of active support is initiatives that have attracted media attention and sponsoring. For example, Professor Wim Blonk (VUB), former director of the European Commission, supported Close the Gap with a remarkable initiative. He completed a cycling tour in May 2003 of 4.000 kilometers in France and generated some publicity and sponsoring. This type of publicity and sponsoring effort was repeated in 2007 by two proponents in their mid‐20s, Luk De Brauwer and Alex Gay, who accepted the challenge of a 9.200 km touring in Africa with a Citroen 2 PK.In June 2012, another initiative called “Bike to Close the Gap”, gathered more than 200 cyclists, 55.000 EUR sponsoring, and the needed media attention. Overall, such initiatives further fuel the value network and attract the attention of potentially valuable stakeholders.

4.4 Cooperative organizing Close the Gap began, in its infancy, with limited forces and without profit. Even currently (i.e. December 2011, last available financial figures) the organization counted 3,8 FTEs despite the extended activity and positive financials, cf. 4,7 million EUR cash on balance (or ca. 84 % of the total balance sheet). The ability to obtain 250.000 donated computers and to realize projects in 40 countries with such a limited force is only possible in a model of cooperative organizing. The following “cooperative” partners seem crucial for Close the Gap:

Donation: There are dozens of well‐known companies ready to donate. Close the Gap works with business partners (not private) to realize economies of scale. Additionally, the donating companies are also occasionally involved in the advertisement and the realisation of the projects.

Refurbishment: Flection Group (http://www.flection.com) removes data from old computers, repairs them, and installs new software. The Windows software license is almost free with the guarantee that computers are employed in noncommercial projects.

Project selection: Local authorities, local NGO’s, and the UN provide a solid base for selecting promising projects. Close the Gap works predominantly with social projects, universities, hospitals, and NGO’s and avoids individual and commercial projects.

Installation, training and maintenance: Projects are accomplished by local social entrepreneurs who realize the installation, the training (partially), and maintenance.

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Transport: KLM Cargo transports for free, shows Close the Gap films to passengers, and motivates them to exchange miles in support of the project. One of the first transportations of PCs was shipped to Congo with the airplane of the foreign minister at that time, Louis Michel.

Recycling: Recupel and Umicor are partners in the recycling. Both are experts in this field.

4.5 Strategic choice On many occasions, the above‐mentioned partners, utilizing cooperative organizing, have made strategic choices for their involvement in Close the Gap. For example, the companies donating computers do so for philanthropic reasons that enhance their reputation (Dentchev, 2004, Fombrun et al., 2000, Fombrun, 2001). Concurrently, these donors are concerned with cost efficiency and the safe removal of information from their computers. In a newspaper article in De Tijd, Jozef Schildemans and Johan Zwiekhorst (dd 17.11.2004) explain that simple formatting of PC disks (and other digital devices) does not sufficiently, nor safely, remove all information. According to this article, it is more advantageous for companies to outsource this activity to specialized service providers for economic reasons as the safe removal of information appears rather time consuming. Close the Gap guarantees a certified removal of information. This task is outsourced to Flection in Kontich, Belgium, an ISO 9002 certified company, who then, subsequently, prepare the computers for their second life. Close the Gap provides, in fact, a professional solution to their donors by allowing a savings of approximately 50 EUR with the removal of old computers and the corporate information contained in them. Safe removal of corporate information is not only of economic value. We believe, it is a key element in the success of the sustainable business model of Close the Gap as donating companies are sensitive to possible leaks of (sometimes) secret corporate information. Cumulatively, all partners in the cooperative network have a strategic reason for joining forces with Close the Gap. Yet, Close the Gap has also made sound strategic choices. It remains headquartered at the University of Brussels (VUB) campus with a legal status of a not‐for‐profit organization. A student with a sound character of idealism and enthusiasm can count on the support of many, as mentioned above. However, we suspect that this project would not have been so successful in a for‐profit oriented initiative, or as a hobby of an established manager. The idealism and attention to quality attracts the support of many, and the manner in which this sustainable business model is structured signals genuine quality.

4.6 Multiple value creation Close the Gap does not freely give away the computers but instead sells them for ca. 50 EUR to cover all expenses and logistic organization. Selling them instead of giving them away also guarantees the involvement of local parties. Additionally, these local NGO’s and institutions are carefully selected with the advice of Bishop Desmond Tutu. Close the Gap is searching for partners that possess the capabilities to bring the projects to a success and, of course, they would support and coach them through the entire project. In this event, not only are the computers valuable, but they provide also the ability afforded to local schools, hospitals, NGO’s, governments to work with these computers, which gives access to plenty of digital information. It is also advantageous to receive local repair services if and when necessary and to teach local users (young and old, with or without disability) how to work with computers and with the Internet. In this aspect, computers are the necessary condition while the entire ecosystem that closes the digital gap in developing countries is most valuable in this business model. It is important to mention here that “value” is most probably perceived differently by each stakeholder. Donors value certified information removal and their contribution to a good cause. Commercial flight carriers value their contribution to local communities, which could be a strategic asset in a regulated business with a growing market potential. Local organizations value the overall end‐to‐end support required for the successful completion of projects. Ultimately, the value created by Close the Gap is social (combating digital exclusion, enhancing human capital), environmental (trough recycling initiatives), and economic (efficiency and effectiveness of local communities).

5. Conclusions This paper advanced five principles of sustainable business models, specifically, multiple value creation, basic logic, strategic choice, value network and cooperative organizing. These principles were introduced to extend the conventional business model logic, based on pure financial profit generation. We employed an inductive

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Jan Jonker and Nikolay Dentchev approach to advance these five principles of sustainable business models. An explorative case study of ‘Close the Gap’ was introduced to corroborate our ideas. This complex case illustrates that sustainable business models can be perfectly grounded in not‐for‐profit organizations that provide valuable solutions to the multitude of social and environmental issues concerning our planet. Our arguments open up the discussion in business model theorizing at least on four different levels:

Sustainability principles in business models: The case of Close the Gap shows how an NGO can be managed according to a mixture of sound business and sustainability principles. However, these principles need further validation. Besides, further research is needed to explore how for profit business organizations put profitability on the background and focus primarily on the principles of sustainability.

Business models without profit focus: In this paper, we have challenged the idea that business models are tools for earning money (Osterwalder, 2004, Magretta, 2002). Close the Gap’s focus is to close the digital gap in developing countries. Facebook’s focus was on building a social network. Google’s focus was to organize the world’s information. Profit generation is only the result of a business activity, and it would be surprising if all great entrepreneurs were ex ante focusing on the monetary success they have eventually realized. Besides, there are many who focused on the same business opportunities like Zuckerberg, Peage and Brin, but yet did not have the same success (Ries, 2011). Hence, it is even the question if only one principle is under the focus of entrepreneurs who realize successful ventures.

Various measures of success: The above discussion poses the question if business models can be evaluated upon various measures of success. Could a loss making business model be called successful, and under what conditions?

Additional variety of legal structures: Close the Gap suggests that an non‐profit organization can be extremely liquid (cf. 4,7 mio EUR on balance), i.e. it was profitable. Yet, its legal structure does not provide the opportunity of IPO, selling shares, or merging with other organizations, all of which may have an industrial logic to better address the digital gap of developing countries. Inversely, for‐profit organizations that address social and environmental issues may not benefit from a wide support of politicians or opinion makers, who may fear that the ultimate goal behind such noble intentions are profit generation. Hence, it seems plausible to have hybrid legal structures, or allow a group of legal structures to have a mixture of profit and non‐for‐profit organizations.

Further research is required in order to address the aspects advanced in the above discussion. In any case, more studies are necessary to understand how cohesive the identified principles are, what the transferability of these principles is to other sectors, and, ultimately, how this is translated into a new generation of business models.

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Innovation Process Planning: Aim, Scope and Constraints Magdalena Jurczyk – Bunkowska Opole University of Technology, Opole, Poland m.jurczyk@po.opole.pl Abstract: The article concentrates on the issue of innovation process planning which appears to be a rarely discussed topic in literature. The problem of innovation process management lies in its non‐linear character and the lack of precisely for‐ mulated aim. There is also no current innovation process model that could be the basis for research on developing the methods and tools in operational management. Literature rather refers to significant diversification of processes. Never‐ theless the following article presents some regularities which can be indicated. Even though the process has non‐linear course, it is realized in phases happening one after another in a strictly set order: front‐end, development, commercializa‐ tion. While the process is progressing, the uncertainty reduces due to creation and gathering of knowledge. The concept for elaborating the proposed model of innovation process planning led to observations of applied practices in enterprises. Over 100 examples of managing different innovation processes were analyzed and the research led to highlighting several rules. This was the basis for elaborating the innovation process planning model. The model describes gradual decision‐ making during the realization of the process. Detailing the plans is made in three layers. The first layer sets the limits, the second plans the phases and the third constructs detailed action plans. Thus created plans need to be accepted due to constraints which describe the requirements related to the aim and possibilities of the entrepreneur. Basing on the con‐ ducted observations the plan scope was indicated in every layer. The elaborated approach integrates particular process fragments and makes it goal‐oriented, i.e. gradually specified. Environment has significant impact on innovation processes. The situation, therefore requirements and possibilities, can abruptly change. That is why the option of verifying the con‐ straints during innovation process was applied. The article concentrates as well on the characteristic of those decisive problems that accompany planning decisions. It enables to choose adequate approach to decisive process realization. The difficulty level and meaning of planning decisions are different, therefore identical involvement in every case would be irrational. The differences between decisive problems relate to innovation process category and the layer in planning model. Three categories of innovation processes were proposed and singled out due to their novelty degree and influence scope on the system in an enterprise. In order to group those decisions of similar difficulty, a map was used where problem characteristic corresponds to innovation process category and layer in planning model. The article ends with conclusions showing the expected effects of applying the model. Keywords: innovation management, innovation process, planning, decision problem, decision‐making, constraints

1. Introduction Modern management requires constant use of innovation processes regardless the organization’s maturity phase. The effect of innovation on firm’s performance has been widely discussed (Prajogo, 2006). All the tur‐ bulence surrounding the organization influence on developing possibilities, however they also increase the uncertainty of actions. Organizations become more and more flexible, ready for innovative changes and they often make use of open, adaptable strategies (Badawy, 2011). Problematic aspects discussed in the article are related to innovation management on the operational level; this area is seldom discussed in literature. The most well‐known solutions in the operational innovation management scope are Stage‐Gate (Cooper, 1998), Innovation Funnel (Wheelwright, 1992) and Innovation RoadMap (Eversheim, 2009). The latter one is com‐ monly linked and used with models of technology planning basing on concretely presented stages and deci‐ sions leading to goal achievement (Caetano, 2011), (Oliveira, 2010). Nevertheless in order to be applied, they require certain level of innovative culture and proper system organi‐ zation. Moreover they primarily concentrate on managing numerous ideas. The use of the above‐mentioned methods is limited with certain groups of organizations. The majority of enterprises is characterized by innova‐ tiveness, therefore a question arises: Is it possible to characterize the approach towards innovation process planning in a model? What are the aim, scope and constraints for innovation process planning? Can the model of approach be applied together with other methods like Stage‐Gate? Innovation is never a one‐time phenomenon, but a long and cumulative process of a great number of organiza‐ tional decision‐making process, ranging from the phase of generation of a new idea to its implementation phase. New idea refers to the perception of a new customer need or a new way to produce. It is generated in the cumulative process of information‐gathering, coupled with an ever‐challenging entrepreneurial vision. Through the implementation process the new idea is developed and commercialized into a new marketable product or a new process with attendant cost reduction and increased productivity (Urabe, 1988). There is

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Magdalena Jurczyk – Bunkowska some empirical evidence that innovation and its processes are contingent, differing from company to company owing to the vagaries of their activities and business/industry environment. The difficulty in their management is multiplied by the fact that they do not have linear character, do not happen step by step. Schroder et al (1986) is rejecting the sequential, consecutive progress presented by conceptual innovation process models, explains that they lack empirical correctness or validity in proposing such regimented sequences. Cheng and Van de Ven (1996) also corroborate with these views. However, they propose that portions of the journey may be methodical, whilst others chaotic, providing a dynamic platform for further development by a firm. The innovation processes are likely to follow tortuous tracks, sometimes failing to connect to crucial actors and resources, while (sometimes) succeeding to connect to actors and resources other than the ones anticipated (Hoholm, 2011). The following article assumes that innovation processes are non‐linear, however they are related to particular stage: front‐end, development or commercialization. Thus the whole innovation process consists of realization of those stages. The article presents an original approach towards innovation process planning. It is described in a form of a model whose basis is the research of practices applied in Polish enterprises. The use of models for planning is particularly important for SMEs. The lack of resources (temporal, financial, and human re‐ sources) makes the planning stage critical for these firms. Planning would prevent SMEs from making technical decisions based on contingencies (Scozzi, 2005).The research, its project and data gathering manner is dis‐ cussed in Chapter 2. Chapter 3 focuses on conclusions from research which became the basis for the presented model. The essence of the model is presented in Chapter 4, it indicates that the need is the basis for created plans, it discusses the scope of planning decisions. Furthermore the chapter includes the relation scheme be‐ tween decisions in innovation process planning model and the characteristic of particular decisive problems. The article ends with conclusions highlighting the meaning of the elaborated approach in the context of needs of the operational innovation management.

2. Research methodology The aim of the research was to determine how innovation processes are planned, how managers realize this task considering the uncertainty of the aim and essential actions and resources. In order to find regularities one has to consider innovation process management as an integrity. This will require the analysis of planning examples, their evaluation, generalization of observations and formulation of rules. Therefore the method of direct interview was chosen as the most adequate.

2.1 Research project Proper research was conducted using preliminary analysis. It was done basing on literature as well as on case study type analysis of different innovative projects in a medium sized IT company. Several projects of various meaning and novelty degree were analyzed. During preliminary research all the observations enabled to hy‐ pothesize and formulate the direct interview questionnaire. The choice of the research attempt was imposed by the will of finding proper planning mechanisms. Thus it was decided to conduct the research in those com‐ panies which realize innovation processes and achieve satisfying effects. The companies were selected from Polish innovation ranking leaders. So as to formulate general rules, observations were made in companies of different sizes and branches. Medium‐sized companies, which employed ca. 100 people, constituted the big‐ gest percentage among those which agreed to take part in the research (ca. 50%). Every enterprise was in‐ formed about the research aim, firstly with a letter and secondly with a detailed presentation which preceded the interview. Each time the information gathered during the interview was summarized in a form of a note. The note was elaborated within several days and later sent to interviewers to be verified.

2.2 Data gathering Every interview referred to several examples of innovations conducted in the space of 2‐3 years. Its aim was to compare the approach towards innovation planning regarding the character of the process. One of the pre‐ liminary hypothesis concerned differences in approach towards innovation process planning due to their cate‐ gory. It somehow determined the data gathering manner. Three categories of innovation processes were dis‐ tinguished related to short, medium and long‐term management. The analyzed examples of innovation proc‐ esses were therefore characterized by various novelty degree, scope of changes and meaning for the enter‐ prise. They concerned innovations of different types however the majority related to product innovations (ca. 60%). The research was successfully conducted in 28 companies, about 100 examples of innovation processes

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Magdalena Jurczyk – Bunkowska were analyzed. The examples were selected basing on the evaluation of managers who were asked to discuss those processes which, in their opinion, ended successfully. The interviewers concentrated on gaining informa‐ tion, nevertheless also referred to other managerial functions. The interviews lasted on average 1,5 hours and were conducted with people directly managing the processes and also with board members of the enterprise. Some part of the gathered information was noted on diagrams during the interviews. Despite preliminary assumption, not many companies possessed documentation related to innovation process planning, neverthe‐ less even those companies decided not to provide information in this form.

3. Research conclusions Conducted research led to a number of conclusions which were the basis for formulating the assumptions of innovation process planning model. The most important conclusion was the fact that plans are created gradu‐ ally, it enables managers to use the gradually collected knowledge. That is why the plan of the whole process is not created at its beginning. Only its realization frames are set and within those frames further decisions are made concerning logic fragments of the process such as stages and actions. These decisions are made directly before commencing a particular fragment. It is compliant with Du Preez's (2008) statement that in order to improve the innovation management process, it is wise to break the whole process into smaller stages of activ‐ ity. This helps to guide and focus on activities, especially the information generation and collection activities. A staged approach therefore simplifies the management of the innovation process by providing clear manage‐ ment decision points. This ensures better control of the process in terms of time and quality. The research also confirmed the non‐linear character of innovation process, especially at its beginning, similarly to Fuzzy Front End model assumptions (Koen 2001). Even though next phases are more linear, one cannot assume deter‐ mined set of actions within process phases. Recurrences happen frequently and actions are experimental. Therefore while starting particular phase, it is impossible to indicate actions for forerunner and follower. Gradual aim identification is an important issue. Entrepreneur thinks about achieving future effects while de‐ ciding about starting an innovation process, however these effects are formulated very generally. It enables flexibility and use of knowledge appearing during an innovation process. Progressing task realization leads to specification of given aims, it can be therefore stated that planning is dynamic. All decisions are made referring to current knowledge and forecast. It should also be noted that realization of innovation process depends on company's resources. Competences are the most important among the resources. The use of external re‐ sources is frequent while executing particular process fragments and it is also determined by the company's possibilities. Thus managers, while making planning decisions, on the one hand consider the requirements describing the expectations towards process effects. On the other hand they take into account the possibilities describing expenses for achieving those effects. To sum up, a manager who creates plans can only gradually analyze the situation with the process progress, that is with the creation of new knowledge. The lack of knowl‐ edge constraints planning, as it is shown on figure 1.

goal

time

A Figure1: Option of formulating planning problems

While passing between symbolic points, one makes further decisions and clearly sees the aim. Point A, the beginning of an innovation process, is a place where decisions are made about the limits. In point B the man‐ ager refers to the first phase of the innovation process. It is in point C that detailed decisions are made con‐ cerning actions. In the presented example it can be idea generation or opportunity identification, depending on the impulse which provoked the innovation process. Hence passing from point to point unknown number of times in an unknown sequence, particular actions of front‐end phase are planned. Only after achieving the assumed aim, which is being in point D, one has the accurate knowledge to elaborate plans for development phase. This phase is more structured, however recurrences and repetitions of certain actions cannot be ex‐ cluded.

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4. Innovation process planning model Observations of innovation process examples confirmed significant differences between them, especially in their structures and conduct. The processes are non‐linear in their initial fragments which mostly determines their planning possibility. While searching for innovation process planning rules, it was necessary to refer to their most elemental parts‐ planning decisions. The first from those decisions relates to activating the innova‐ tion process whereas the last to its evaluation. The elaborated model distinguishes three layers of planning decisions, figure 2, where first layer decisions determine these made in the second layer and those are the basis for third layer decisions. environmental scanning

Verifying the possibility of amending the constraints in the current situation (environment + knowledge)

identification of the need

constraints

requirements

planning of the innovation process frames constraints

requirements

planning of the innovation process phases

requirements

constraints planning of the activities

N Y

Verification of the requirements in the context of the current situation (environment + knowledge)

Is it possible to develop acceptable plan of activity?

realisation of the activity

Figure 2: The outline of innovation process planning The innovation process planning model refers as well to constraints of particular decisions. The proposed scheme of actions includes the necessity to verify the constraints during the realization of the innovation proc‐ ess. Its goal is to include environmental and new knowledge changes which can alter the manager's view on the process. Moreover, in order to enable the choice of proper approach to decision‐making, the characteristic of decisive problems was taken into account. It results not only from the model layer but also from innovation specificity which is created during the process.

4.1 The need as the basis for innovation process planning Progress is the reason for entrepreneur's engagement in innovation processes. Progress should allow easy adjustment to the future environmental state and obtainment of desired competitive position. The innovation strategy is the basis of successful innovation management (van der Panne, 2003). To specify a future‐oriented innovation strategy it must be determined in which areas of business and with which innovative products (and underlying technologies) the enterprise wants to address the market. Market and technology orientation as well as their suitable integration are the three substantial criteria for strategy development (Chesbrough, 2003). Therefore the first task of planning is to set its goal. The goal is very general at the beginning, it be‐ comes more specific together with gained knowledge and later can transform into a product or a process. Realization of innovation processes results from particular needs of the company. They can be considered in the context of a horizon: short, mid and long‐term. It is determined by the formulating manner of innovation process aim, but mostly by the complexity of decisive problems which a manager will have to face. For in‐ stance, the need in short‐term innovation process management can be precisely formulated unlike in mid and long‐term management horizon. Innovation processes related to long‐term management horizon usually have higher novelty degree and require elaboration and implementation of wider knowledge. It results from the fact that changes occurring from implementing such innovations concern the whole system of the company or the majority of its functions. Management horizon related to the need also determines the manner and scope of environmental analysis, which means creation of forecasts. Figure 2 presents a scheme which describes the connection between need and environment, in which horizon it is identified and how it affects the scope of necessary environmental analyses.

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4.2 Decision scope in the layers of planning model Despite the differences between innovation processes, the substantial scope of decisions made in distin‐ guished model layers is similar. Every layer was given a set of key decisions basing on the observations in re‐ searched companies. First layer, which sets the process limits and refers to all further decisions, includes:

identification of the need which is the outline for the innovation process aim,

initial estimation of the budget,

setting the process priority towards other current processes in the company,

setting the time horizon convenient for fulfilling the need,

indication of the leader responsible for the whole process,

possibilities of cooperation with external units during the realization of the process.

Particular phases of the innovation process are planned in the second layer. They differ from one another in terms of aim and characteristic, however their planning requires similar decisions. The most important are:

determining the final expected effect of the phase,

setting the key actions,

estimation of time needed for phase realization,

setting the phase budget,

formulation of a team,

setting the access to resources and means,

indication of external resources use scope,

identification of risk factors,

setting the scope and frequency of environmental monitoring.

Third layer concerns preparation of detailed plans about actions as a set of logically related tasks. All settings in this layer have the most detailed character and they include:

task realization effect,

setting the time for achieving given effect,

ensuring the means for achieving given effect,

choice of tasks executors,

setting the moment for beginning the task,

scope of using external resources.

Every layer, despite the above‐mentioned decisions, also determines the form and manner of signalling termi‐ nation of the stage and evaluation manner of its effects. As it was shown, settings from further layers directly depend on decisions made in the previous layer, are becoming more detailed. Decisions from the previous layer constitute the constraints for further decisions in the next layer.

4.3 Entrepreneur's requirements and possibilities as the basis for planning decisions A plan must precede current actions, must be goal‐oriented and possible to realize. Every layer of the model confronts requirements with possibilities which refer to planning the innovation process fragment. Require‐ ments represent the expected effects of realizing a particular process fragment. Possibilities describe entre‐ preneur's expenses to spend in order to obtain the effect. These decisions are the constraints for created plans. Before planning development phase, for instance, its budget and time are being set. Manager has to take these constraints into account while deciding about realization manner of a phase. An identified need allows to indicate requirements for the process. A company which can increase its chance for a bigger market share due to its competitor's problems, can be taken as an example. Unfortunately the company does not possess proper infrastructure to offer the same services to bigger amount of clients. The firm also does not possess sufficient financial resources to increase potential in a traditional way. The need

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Magdalena Jurczyk – Bunkowska was identified as a change in procedure of the service so as to decrease contribution of tasks done in the com‐ pany's headquarter. The imposed requirements included retaining the quality of the service guaranteeing keeping current and overtaking new clients. Possibilities were represented by time and budget needed for elaborating and implementing the solution. During the first phase the firm used assistance from a consulting company which prepared several alternative concepts acceptable in terms of requirements and possibilities. One of the alternatives referred to changing the process of service realization, other referred to using coopera‐ tion and another to modifying the service itself. First alternative was chosen and it allowed to elaborate devel‐ opment phase plan. Each from the proposed alternatives required different type of actions leading to the con‐ cept development. The development phase plan assumed redirecting some part of actions in this scope to an external company due to time limits. Only after preparing and testing the procedures, the solution implemen‐ tation manner was planned and clients were informed and prepared for changes. The example shows sequen‐ tial planning, formulating and referring to constraints. While setting the budget entrepreneur did not head for minimization of solution costs, he was heading for a fast service offer to a greater number of clients. Therefore he indicated how much he is willing to spend in order to achieve the expected effect. While formulating the time constraint, he used the forecasts related to his competition and its possible speed of overtaking the cli‐ ents of the bankrupt company. If that happened, even better and cheaper solution would not make any sense. The priority also represents the possibilities of a given process. It shows the entrepreneur's importance of the process in terms of others simultaneously conducted. The process from the described example was character‐ ized by a high priority.

4.4 Innovation process categories and the characteristic of decisive problems As it was mentioned in section 4.1 innovation processes differ in terms of managing horizon where the need is identified. A classification of processes was proposed, it refers to novelty degree and scope of changes which elaborated innovation should provide. It was the basis for distinguishing three categories of innovation proc‐ esses. First of them relates to short‐term company needs therefore it was called innovation of current needs. These processes are characterized by low novelty degree and limited range in terms of company system. They do not require connections between units involved in their creation. The result of this category includes singu‐ lar task or a group of logically related tasks, determined as action. Processes within this category are financed from the current budget and their duration time does not exceed several months. Information needed for realization of these processes are very often in the possession of the company or in close entourage. Managing this category does not require complicated decisions due to low uncertainty degree. The second innovation category is related to mid‐term management. Needs result from the constantly appearing possibilities to strengthen the competitive position thus they were called innovation processes of developing potential. Their novelty degree is higher than in the previous category, this is the branch or national novelty. Their range cov‐ ers at least one business process thus it requires cooperation of several departments within the company. This category realization time varies from a couple of months to one year, therefore more advanced methods are used to forecast environmental states. The budget of these processes is also higher than in the previous cate‐ gory. Information is gained from a wider scope and managers are often dissatisfied with the acceptable solu‐ tion of a particular problem. Planning decisions related to these processes are more complex and demand bigger involvement. Innovation processes related to long‐term managing horizon respond to the needs of company's strategy. They are connected with the creation of new products or elaboration of new production technologies. They were called innovation processes of new business creation due to the significant changes they make in a company. Processes belonging to this category have very high novelty degree and often result in radical innovations. Their duration time exceeds a year and budget constitutes an important part of the company's finances. Significant involvement in gaining information and environmental analysis are essential to obtain proper results, quality forecasting methods are applied. Managing this category is the hardest. Deci‐ sions may require many connections and relate to different scenarios of possible events. In case of planning decisions the manager frequently searches for most beneficial solution options due to many evaluation criteria. Decisions in this innovation process category are often made collectively and are supported by experts. Decisions in setting goals and limitations of innovation process can be very complicated however there are also such decisions whose difficulty degree is low. Despite their uniqueness, some decisions are similar. It usually concerns decisions from the third layer of planning. Due to decision costs such as expenses for information gathering, it is advisable to consider proper choice of approach towards particular decisive problem. It can be done better and faster in case there is a previously elaborated map. Figure 3 shows the construction of such device. The proposed map allows to read the difficulty degree, decision‐making level, and spread and depth of

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Layer of planning

necessary analysis. The division basing on the innovation process category and on the planning layer. Such division of decisive problems can also be the guideline for delegating the authorities. It eliminates the problem of who should make particular decision. process

phase

activity

Middle management level; analysis of the current and expected situation of near external environment. Low level of management; knowledge obtained from the internal environment. Low level of management; based on knowledge available at the moment.

innovation processes of current needs

High level of management; advanced analysis of current and future state of the far external environment Middle management level; analysis of the current and expected situation of near external environment Low level of management; knowledge obtained from the internal environment.

innovation processes of developing potential

Top management, trends and directions of macro environment. High level of management; advanced analysis of current and future state of the far external environment Middle management level; analysis of the current and expected situation of near external environment

innovation processes of new business creation

Figure 3: The example of the map indicating the approach to decision‐making in the context of the category of the innovation process and the layer of planning

5. Conclusions The realization of an innovation process has a creative character therefore the actions are usually experimen‐ tal and result in determining further actions. Nevertheless making an effort in management including process planning enables achieving better results than focusing only on managing the process; this is based on manag‐ ers' experience and literature indications (Tidd, 2005). Realization of all the intentions being the genesis for an innovation process is the key to planning. Entrepreneur always pursues to implement innovations in order to obtain the assumed benefit in particular time frame. He evaluates the possible means engagement in the per‐ spective of his expectations. Therefore plans mainly aim at consistent pursue to fulfill particular entrepreneur's needs. The areas, in which innovation implementation will impact the development of the enterprise, result from the chosen strategy. It is usually determined by the environment of the company. While achieving effects different than those assumed and compliant with the strategy, one cannot talk about innovation process suc‐ cess. That is why the issue of process realization aim has a key meaning and is the basis for all the remaining planning decisions. Plans are created gradually and successively due to the fact that further process actions have their source in knowledge gathered during the realization of the process. The proposed model distin‐ guishes three levels of planning. The first one begins at the starting of the process and has general guidelines. Second planning level, whose issue is to formulate aims and conditions for realization of particular phases, takes place before starting the phase it directly concerns. Third level plans precisely relate to actions taken within the phases and are formulated straight before their beginning. Thanks to this model the manager can be fully directed by the knowledge gained from the previously conducted work while making detailed decisions. All the constraints resulting from the possibility of process realization need to be taken into account while elaborating plans on every level. It often requires cooperation with an outside organization. However such actions usually demand higher organizational skills. Innovation process planning is the way to concentrate on achieving the assumed goals. Unfortunately they are not set unambiguously enough to decide in advance about all the planning issues. The manager can most often set the general area of the innovation process where changes would be beneficial and he is able to formulate the vision of their effects. Thus the use of traditional forms of planning does not bring the satisfying results. Innovation process plans need to be divided into fragments which describe the manner of achieving the partial aims that constitute the aim of the whole process. The proposed model answers the question of how to divide innovation processes into fragments so as the elaborated plans could be sufficient to manage them in a way guaranteeing the pursue of the assumed aim. The planning decision scopes were set in which the manager possesses the knowledge enabling the decision‐making process. While using the model one can choose analy‐ sis tools adequate to the decisive problem. The model can also be helpful in making support systems for deci‐ sion‐making process and in creating tools supporting other managing functions of innovation processes. The offered solution may be the supplementation to such solutions as Stage‐Gate or Innovation Funnel. However it was created basing on the examples of companies which did not apply those concepts of managing innovation processes.

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Acknowledgements The project funded by the National Science Center in the scope of the research project No. 4025/B/H03/2011/40 Fri: "Developing a model of planning and estimating the cost of innovation"

References Badawy, M. K. (2011) Is Open Innovation a Field Of Study or a Communication Barrier to Theory Development? A Perspec‐ tive, Technovation, Vol. 31 (1), pp. 65‐ 67. Caetano, M. and Amaral, D. C. (2011), Roadmapping for Technology Push and Partnership: A Contribution for Open Innova‐ tion Environments, Technovation, Vol. 31 (7), pp. 320‐335. Cheng, Y., & Van de Ven, A. (1996) Learning the Innovation Journey: Order out of Chaos? Organization Science, Vol. 7(6), pp. 593‐614. Chesbrough, H. (2003) A Better Way to Innovate. Harvard Business Review, Vol. 81(7), pp. 12–13. Cooper, J. R. (1998) A multidimensional approach to the adoption of innovation. Management Decision, 36( 8), pp. 493‐502. Du Preez, N.D. & Louw, L. (2008) A framework for managing the innovation process. Cape Town: PICMET. Eversheim W. (2009) Innovation Management for Technical Products: Systematic and Integrated Product Development and Production Planning, RWTHedition, Springer‐Verlag Berlin Heilderberg. Hoholm, T & Araujo, L. (2011), Studying innovation processes in real‐time: The promises and challenges of ethnography, Industrial Marketing Management, vol 40 (6), pp. 933‐939. Koen P. and Ajamian G. et al. (2001) Providing clarity and a common language to the 'fuzzy front end', Research Technology Management, Vol. 44, pp. 46‐55. Oliveira M. G. and Rozenfeld H. (2010), Integrating Technology Roadmapping and Portfolio Management at The Front‐ End of New Product Development, Technological Fore‐ casting & Social Change, Vol. 77 (8), pp. 1339‐ 1354. Prajogo, D. I. (2006), The Relationship between Innovation and Business Performance ‐ A Comparative Study between Manufacturing and Service Firms. Knowledge and Process Management Vol.13(3), pp. 218‐225. Schroeder, R., Van de Ven, A., Scudder, G. & Polley, D. (1986) Managing Innovation and Change Processes: Findings from the Minnesota Innovation Research Program. Agribusiness, Vol. 2(4), pp. 501‐523. Scozzi, B., Garavelli, C., Crowston, K. (2005) Methods for modeling and supporting innovation processes in SMEs, European Journal of Innovation Management, Vol. 8 (1), pp. 120 ‐ 137. Tidd, J. and Bessant, J. and Pavitt, K. (2005) Managing Innovation Integrating Technological Market and Organizational Change, 3ed, John Wiley and Sons Ltd. Urabe, K. (1988) Innovation and the Japanese management system. In Urabe K., Child J., & Kagono T. (Eds.), Innovation and management international comparisons. Berlin: Walter de Gruyter. Van de Ven, A. (1986) Central Problems in the Management of Innovation. Management Science, Vol.32 (5), p. 590‐607. van der Panne, G., Beers, C. & Kleinknecht, A. (2003) Success and Failure of Innovation: A Literature Review, International Journal of Innovation Management, 7(3), pp. 309–338. Wheelwright, S.C., & Clark, K.B. (1992) Revolutionizing Product Development. New York City, New York: Free Press.

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Higher‐Order Learning in Entrepreneurship: A key‐Issue for Lifelong Learning and Career Counselling? Alexandros Kakouris1, 2, Niki Perdikaki2 and Panagiotis Georgiadis2 1 Career Office, National and Kapodistrian University of Athens, Athens, Greece 2 Faculty of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece akakour@phys.uoa.gr Abstract: Considering real‐life entrepreneurship as a learning process, corresponding study and teaching requires inclusion of higher‐order learning beyond the customary experiential one. Higher‐order learning involves meta‐cognitive capacities and its essential role has been highlighted in both individualistic and organisational level. Effective teaching of entrepreneurship, aiming to achieve impact and to induce entrepreneurial initiatives, supposes fostering of entrepreneurial mindsets through lifelong learning and also connection of entrepreneurship with career counselling and vocational training. Nonetheless, there is poor evidence that the previous connections have been already established. Especially confrontation with underlying beliefs and attitudes, which characterise adult learning and trigger higher‐order learning, does not appear as a key‐issue in literature. In the present article, we first develop a conceptual framework about the occurrence and the role of higher‐order learning in business venturing and then we provide bibliometric data which examine the frequency and the impact of relevant studies. We also examine through data the connection of entrepreneurship with lifelong learning and vocational training. Keywords: entrepreneurship, entrepreneurial learning, experiential learning, higher‐order learning, lifelong learning, career counselling

1. Introduction How learning becomes an entrepreneurship component? Unequivocally, it underlies everyday activity of entrepreneurs and it also drives entrepreneurship education. Jason Cope (2005) discussed entrepreneurship as a learning process concluding that “further research may reveal entirely new dimensions of learning in entrepreneurial contexts and more interdisciplinary, in‐depth empirical work is a vital part of this [i.e. entrepreneurship] theory‐building process”. Following Cope’s perspective, entrepreneurial learning can be thought as a fundamental pole for innovative entrepreneurship (Kakouris and Ketikidis 2012). In parallel, the wide provision of entrepreneurship education, emerging from relevant educational policies, fares a more “mature” phase after the initial “fostering entrepreneurial mindsets” period (e.g. Katz 2003, Kuratko 2005, Oslo Agenda 2006). Currently, the impact of educational programmes and the entrepreneurial learning, i.e. the outcome of entrepreneurial courses, have become pivotal issues and are being investigated (e.g. Kakouris 2011). For example, a longitudinal survey about the impact of entrepreneurial courses worldwide is underway through the Entrepreneurship Education Project of Illinois State University (http://entrepeduc.org/). Similar surveys appear in the European Education Area as well (e.g. European Commission 2012). Entrepreneurship education, i.e. the systematic provision of entrepreneurship courses from educational organisations, has been associated with educational polices, guidelines and surveys in Europe (relevant documents can be found at “Enterprise and Industry” directorate of European Commission). These documents refer to the provision of entrepreneurial courses in different educational levels and target groups. Notably, entrepreneurship has been included amongst the eight key‐competencies to be fostered through lifelong learning across Europe (European Commission 2007). Thus, there are schedules to promote entrepreneurship in secondary schools, in university faculties – different than business schools, in vocational training and in lifelong learning. A wide provision of entrepreneurial courses requires a full consideration of the intrinsic learners’ needs, the perceived “targets” and goals of governing agencies, the promoted theoretical background of the relevant courses and other aspects in order to attain impact. It has been well documented that entrepreneurship education is not irrelevant to governmental policies and expectations. Entrepreneurship is thought as a means for employability, a motor for economic development, a crucial feature of developed, knowledge‐driven economies. Therefore, a common goal of worldwide educational agencies is to inspire, through entrepreneurship education, entrepreneurial intention or orientation to graduates. It is straightforward that the increase of entrepreneurship courses is expected to lead to an increase in the number of start‐ups. Since the age at which people decide to become entrepreneurs

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Alexandros Kakouris, Niki Perdikaki and Panagiotis Georgiadis significantly varies, entrepreneurship education is not restricted to Economics and Business faculties. It is now connected to vocational training, to career counselling and to adult education obtaining an inclusive character. Conclusively, different teaching methods and different types of learning intrude the entrepreneurial curricula. Traditionally, entrepreneurial learning is considered a cognitive process (e.g. Baron 2004, Mitchell et al. 2007). Much of the literature addresses cognition as a central process for entrepreneurial knowledge transfer. There are also alternative contemporary streams which consider entrepreneurialism: (a) learnt from experience (e.g. Minniti and Bygrave 2001, Politis 2005), (b) a cognitive developmental process (Krueger 2007), (c) a higher‐ order learning process (Cope 2003, 2005, Kyrö 2008. Rae and Carswell 2000). The alternatives focus on reflection and other meta‐cognitive capacities taking into account the societal environment, critical events and personal beliefs of ‘wannabe’ entrepreneurs. Reflection is also the key‐process for double‐loop organisational learning (Argyris and Schön 1978). Such considerations are close to effective career counselling practices and vocational training that aim to induce subsequent praxis of the clients/trainees. As we do not aim to discuss further the differences of each individual stream, we will refer to processes (a) to (c) as higher‐order learning in the sequel. Higher‐order learning involves meta‐cognitive processes in order to cope with personal assumptions and modifications of a person’s epistemology. In the previous framework, the research question that arises is “in which extent higher‐order learning is studied and connected with vocational training, career counselling and lifelong learning in entrepreneurship literature?” Provided that this type of learning is under‐researched, higher‐order learning may offer a promising framework to develop and enhance further entrepreneurial vocational training and career counselling. The method we follow to answer the previous question is based on bibliometric data (cf. Bhuparitaju et al. 2012, Landrstöm et al. 2012).

2. Methodology In order to study the keywords and key–phrases of entrepreneurship literature, we retrieved 7726 abstracts (in total) from the SCOPUS bibliographic database (http://www.scopus.com/) under the search keyword “entrepreneurship”. The abstracts span from 1980 to 2012 and correspond to articles, reviews or editorials. The evolution of the number of papers per year is shown in Figure 1. It is clearly illustrated that the number of papers has grown exponentially over time. Concerning the subset of abstracts which include the keyword “innovation”, it is shown through the asterisks in Figure 1. Similarly, abstracts including “education” are shown by the squares and those including “learning” are shown by the diamonds. All these subsets exhibit similar exponential growth; nonetheless, their systematic appearance begins after the millennium and more specifically after the year 2005. We further analyse the keywords which classify the previous abstracts in bibliography. These keywords have been set either by authors or in accordance with journals’ bibliographic lists. Different word clouds for different sets of keywords are compared. We further divide the recurrent words, appearing in abstracts, as shown in Figure 2. Three separate keyword classes are considered for the present study. First, we examine learning class and related phrases as: experiential learning, organisational learning and higher‐order learning. Relevant learning processes refer to cognition, reflection, meta‐cognition or critical thinking. The lifelong learning class involves training, formal or informal, self‐directed learning or other adult learning processes. The vocational training class can be considered different than lifelong learning aiming to connect education and learning with the career options of the trainees. In this class, (self)employment is essential, along with entrepreneurial orientation or intention of trainees which also refer to nascent entrepreneurship. The classification shown in Figure 2 is not strict. There can be various overlaps amongst the domains and with certain keywords (e.g. innovation, SMEs, social entrepreneurship, etc.) of the complementary domain denoted as “other” in the figure. However, the classification of Figure 1 illustrates the methodological approach we pursue in the present bibliometric study.

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Figure 1: Evolution of the sample’s number of papers per year (since 1980). Circles correspond to the overall sample, asterisks to “innovation”, squares to “education” and diamonds to “learning” keywords

Figure 2: Classification of key‐words and phrases for the present study

3. Findings Bibliometric analysis of the 7726 SCOPUS sample of papers which appear under the search keyword “entrepreneurship” concerns (a) author and index keywords and (b) abstract’s content and citation analysis. In the first “word‐clouding” representation, section 3.1, we observe differences between the author’s classification and the journal lists’ classification. In section 3.2, citation analysis is indicative for the impact which papers within certain classes attain.

3.1 Author and index keywords First we analyse keywords which classify each paper bibliographically. As “entrepreneurship” was the search keyword it has been excluded from the sample along with the repetitive keyword “entrepreneurialism”. In Figures 3 and 4, the word clouds for the 50 more often keywords are shown. The used font size per keyword is proportional to the frequency it appears. Entrepreneurship literature spans in a wide set of journals as the research field is new and interdisciplinary, lacking its own well‐established journals. For this reason, we analyse keywords set arbitrarily by authors (Figure 3) separately than the ones provided by journals’ keyword lists (Figure 4). In Figure 3, the more frequent keywords pertain to “innovation” and “entrepreneurs”, with “education” following them. These keywords are expected since entrepreneurship has been studied for a long time

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Alexandros Kakouris, Niki Perdikaki and Panagiotis Georgiadis referring to entrepreneurs as individuals and entrepreneurship has also been connected to innovation due to the Schumpeterian view. Expected keywords as “social capital”, “corporate entrepreneurship”, “gender”, “international entrepreneurship”, “self‐employment”, “economic development”, “venture capital” and “networks” do also appear large in the figure. For the classification of Figure 2, we note that the keyword “learning” appears small (next to “education”) with no other keywords from its domain. The domain of lifelong learning is also absent. For the domain of vocational training and career counseling there are implicit keywords in the list. For example, “entrepreneurial intention” and “entrepreneurial orientation” refer to the tendency of individuals, or other entities, to behave entrepreneurially. The literature includes a variety of surveys, mostly quantitative, which measure the inclination of people to become entrepreneurs along with studies of nascent entrepreneurship. However, this is not necessarily an outcome of vocational training or entrepreneurship education. Similarly, most of employment due to entrepreneurship refers as “self‐employment”. Self‐ employment has been an equivocal form of entrepreneurship as the latter refers to start‐ups and new firms with more than one employee. Especially in innovative entrepreneurship studies, self‐employment is usually excluded. In sum, we note that domains of Figure 2 receive poor bibliographic evidence or implicit attention despite the significant volume of education articles in the sample. The relevant picture from journal list keywords is dramatically different (Figure 4). The keyword “entrepreneur” dominates validating that entrepreneurship has been traditionally connected with the entrepreneur and his/her traits. There is also important regional classification with “United States”, “Eurasia”, “Europe” and “United Kingdom” the more frequent keywords. This result is understood due to the economics journals included in the list which focus on regional economies and economic development. The keywords “education” and “self‐employment” also appear. Self‐employment differs than “employment” which appears separately. We also note that the keywords “organisational” or “organisation” are frequent due to the strong management component in the sample of articles. Keywords of Figure 2 are absent. Comparing Figures 3 and 4, the discrepancy between author and journal keywords is apparent. Entrepreneurship scholars introduce keywords different than the ones found in lists. The former are more close to the recent conception of entrepreneurship as it appears after 2000. Especially literature relevant to the keywords of Figure 2 has been produced after 2000 as shown in Figure 1.

Figure 3: Author keywords word cloud

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Figure 4: Index keywords word cloud

3.2 Abstracts’ search and citation indices The total sample of papers (7726) includes the word entrepreneurship in the abstract. As “entrepreneurialism” is contained in the majority of them, the word has been excluded from the analysis. In Table 1, the number of citations that papers receive is summarised. For example, 483 papers contain both words “entrepreneurship” and “innovation” in the abstract. These papers have been cited 5631 times and the relative “citations per paper” index is 12.43. The latter is indicative for the impact the papers attain in literature. Table 1: Number of papers and citation indices per keyword Keyword Entrepreneurship Innovation Learning Education

# papers # citations (total) # citations per paper 7726 483 150 345

92765 5631 1534 2216

12.00 12.43 10.22 6.42

327 2466 94

23.36 16.78 11.75

3931 3222 45 475 246 6

17.40 10.33 7.50 6.69 3.62 2.00

Organisational learning Cognition / ive Experiential learning

14 147 8

Orientation / Intention Employment Vocational training Career Training Lifelong learning

226 312 6 71 68 3

The overall “citations per paper” index (hereafter cpp) of the sample is 12. It is shown in Table 1 that “innovation”, “education”, “orientation/intention” and “employment” abstracts are the most populated subsets. Subsets which contain the keywords “learning” or “cognition/cognitive” follow. Notably, the subset of “education” exhibits the lowest impact (cpp=6.42). The subset of “learning” shows cpp=10.22 which could be expected since learning also includes surveys for educational purposes but also for the study of real life entrepreneurial venturing. Concerning different types of learning, the “organisational” one receives the highest impact (cpp=23.36), the “cognitive” one follows (cpp=16.78) with the “experiential” one third in the list

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Alexandros Kakouris, Niki Perdikaki and Panagiotis Georgiadis (cpp=11.75). Notably, “organisational learning” receives a double cpp factor than the overall sample. The result can be understood due to the large number of articles which study entrepreneurship focusing on the firm as the entity of analysis. Moreover, there is strong tradition in cognitive methods of learning while experiential learning is a relatively “new” stream which focuses to the entrepreneur and his/her performance as an individual. The “experiential” stream also includes studies for in‐class entrepreneurship education based on learning‐by‐doing. Table 2: Number of articles, number of citations (in parentheses) and number of citations per article (italics) Innovation Education Learning Cognition Orientation / Intention Employment

Innovation Education Learning Cognition Orientation / Intention 9 (32) 3.56 15 (207) 13.80 5 (5) 1.00 10 (229) 22.90 9 (117) 13.00

28 (95) 3.39 4 (55) 13.75 17 (97) 5.71 14 (71) 5.07

5 (99) 19.80 7 (153) 21.86 1 (2) 2.00

7 (29) 4.14 4 (11) 3.75

4 (2) 0.50

The lower part of Table 1 refers to the connection of entrepreneurship with career planning. In this domain (see Figure 2), the “orientation/intention” surveys receive the largest attention (cpp=17.40). The “employment” subset follows with cpp=10.33. At this point, we cannot distinguish between general employment studies (i.e. from the economics perspective) and self‐employment which is an implicit form of entrepreneurship. A relevant remark could only refer to the non‐for‐granted connection of entrepreneurial intentions with the outcomes of entrepreneurial education. Vocational training encompasses only 6 articles with cpp=7.5, while the “training” subset attains just a ccp=3.62 and “lifelong learning” encompasses 3 papers with a “poor” cpp=2. Evidently, we conclude that higher‐order learning is poorly discussed in the examined entrepreneurship literature. Furthermore, in Table 2, subsets of abstracts which encompass two more keywords beyond entrepreneurship are summarised. Notably, articles which compound “orientation/intention” with either “innovation” (cpp=22.9) or “learning” (cpp=21.86) attain the highest impact. “Intention/orientation” combined with “education” attains much less cpp=5.71. Hence, more research is needed in this direction. Entrepreneurial “education” illustrates 4 articles with higher impact (cpp=13.75) when combined with “cognition”. On the other hand, “cognition” illustrates little impact (cpp=1) when combined to “innovation”. In addition, “education” along with “learning” shows a low cpp=3.39 while “learning” combined to “cognition” receives high cpp=19.80. The conclusion from Table 2 is that entrepreneurial learning is thought predominately cognitive, however; learning has been under‐researched towards its contribution in educational programmes especially when such programmes aim to focus on innovative entrepreneurship. Research towards entrepreneurship education/learning processes and career planning/employment has also been poor. Given the bibliometric results of Tables 1 and 2, research which refers to higher‐order learning, as introduced by Cope (2003, 2005), is rare in entrepreneurship literature. Scholars may find reflective learning processes only in the context of organisational learning (Argyris and Schön 1978) which has been introduced and studied for a long period in management research. Keywords as “critical thinking” and “meta‐cognition” gave no results within the sample. We propose that the incorporation of reflective, meta‐cognitive or higher‐order learning processes in research may link to fostering entrepreneurship through lifelong learning (or vocational training) or to effective incorporation of entrepreneurship in traditional career counselling.

4. Limitations of the research A certain limitation of the present survey is the omission of books and edited volume chapters in the analysed sample. Since entrepreneurship is a new field of research, books are important as they present various influential perspectives (Landrstöm et al. 2012). The use of a single bibliographic database (SCOPUS) is also a weakness for the generalisation of the results.

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Alexandros Kakouris, Niki Perdikaki and Panagiotis Georgiadis Another limitation is the lack of a bibliometric algorithm to justify the evolution of citation number over time. Hence, older articles receive more citation than newer ones. However, the conceptions about entrepreneurship research have been significantly modified during the last decades. In addition, the present analysis lacks a clustering method in order to link and identify cross‐citations (Landrstöm et al. 2012). Therefore, present results can be considered indicative but primitive; i.e. a first step for further analysis.

5. Conclusions According to educational policies, entrepreneurship education undergoes a further expansion phase in order to include wider populations of trainees. At the same time, its impact and its contribution to nascent entrepreneurship and start‐ups is under investigation. Hence, entrepreneurial learning induced in various learning groups becomes central in relevant surveys. Beyond education and training, entrepreneurial learning is important for real entrepreneurs’ trajectories and performance. If so, learning is an inherent component for entrepreneurship theory building. Thus, higher‐order learning is expected to be considered in the entrepreneurial practice and research beyond the traditional cognitive approaches. In the present article, we examined the bibliometric evidence for learning and education studies in connection with other entrepreneurship aspects. Bibliometric results from the SCOPUS database show that there is poor evidence for advanced learning processes in entrepreneurship research. An increasing number of articles deal with education; however, the relevant impact is still low. Especially in the context of innovative entrepreneurship there is little research referring to learning processes. This result may due to the confrontation with creativity and its complex nature. There is also little research towards the connection of the entrepreneurial intention/orientation with relevant education taken by the potential entrepreneurs. Besides, entrepreneurship has not been extensively studied in connection with career counselling and employment. Present results indicate that future research is needed as to reveal a more concise picture of the “fostering entrepreneurial mindsets” process. Towards this direction, learning is a crucial component which involves meta‐cognitive processes beyond the cognitive ones. We finally maintain that considering learning as a higher‐order process, entrepreneurship will be facilitated in the contexts of lifelong learning, vocational training and career counselling. Since the relevant existing literature lacks an adequate academic debate in these subjects, we expect the entrepreneurship community to actively incorporate higher‐order learning processes in the academic discussion and practice.

Acknowledgements This work was financially supported by the Greek Ministry of Education and Religious Affairs, Sport and Culture through the “Education and Lifelong Learning” programme. All authors are grateful to the National and Kapodistrian University for financial support.

References Argyris, C. and Schön, D. (1978) Organisational Learning: A Theory of Action Perspective, Addison Wesley, Reading. Baron, R. (2004) “The cognitive perspective: A valuable tool for answering entrepreneurship’s basic “why” questions”, Journal of Business Venturing, Vol, 19, No.2, pp. 221–239.

Bhuparitaju, S, Nomaler, Ö, Triulzi, G. and Verspagen, B. (2012) “Knowledge flows – Analyzing the core literature of innovation, entrepreneurship and science and technology studies”, Research Policy, Vol. 41, No. 7, pp. 1205– 1218. Cope, J. (2003) “Entrepreneurial learning and critical reflection: Discontinuous events as triggers for higher level learning”, Management Learning, Vol. 34, No. 4, pp 429–450. Cope, J. (2005) “Toward a dynamic learning perspective of entrepreneurship”, Entrepreneurship Theory and Practice, Vol. 29, pp. 373–398. Entrepreneurship Education Project. [online], Illinois State University, http://entrepeduc.org/ European Commission. Enterprise and Industry directorate, [online], http://ec.europa.eu/enterprise/policies/sme/documents/education‐training‐entrepreneurship/ European Commission (2007) “Κey competences for lifelong learning”, European Reference Framework, [online], European Commission, http://ec.europa.eu/dgs/education_culture/publ/pdf/ll‐learning/keycomp_en.pdf European Commission (2012) “Effects and impact of entrepreneurship programmes in higher education”, [online], European Commission, http://ec.europa.eu/enterprise/policies/sme/promoting‐ entrepreneurship/files/education/effects_impact_high_edu_final_report_en.pdf Katz, J.A. (2003) “The chronology and intellectual trajectory of American entrepreneurship education 1876–1999”, Journal of Business Venturing, Vol. 18, No. 2, pp 283–300.

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Krueger, N. (2007) “What lies beneath? The experiential essence of entrepreneurial thinking”. Entrepreneurship Theory and Practice, Vol. 31, No. 1, pp. 123–138. Kuratko, D.F. (2005) “The Emergence of Entrepreneurship Education: Development, Trends, and Challenges”. Entrepreneurship Theory and Practice, Vol. 29, No. 5, pp 577–598.

Kyrö, P. (2008) “A theoretical framework for teaching and learning entrepreneurship”, International Journal of Business and Globalization, Vol. 2,No. 1, pp. 39–55. Landström, H., Harirchi, G. and Εström, F. (2012) “Entrepreneurship – exploring the knowledge base”, Research Policy, Vol. 41, No. 7, pp. 1154–1181. Minniti, M. and Bygrave, W. (2001) “A dynamic model of entrepreneurial learning”, Entrepreneurship Theory and Practice, Vol. 25, No. 3, pp 5–16.

Mitchell RK, Busenitz L, Bird B, Gaglio CM, McMullen J, Morse E and Smith B. (2007) “The central question in entrepreneurial cognition research”, Entrepreneurship Theory and Practice, Vol. 31, No. 1, pp. 1–27. Oslo agenda (2006) “Oslo Agenda for Entrepreneurship Education in Europe”, [online], European Commission, http://ec.europa.eu/enterprise/entrepreneurship/support_measures/training_education/doc/oslo_agenda_final.pdf Politis, D. (2005) “The Process of entrepreneurial learning: a conceptual framework”, Entrepreneurship Theory and Practice, Vol. 29, No. 4, pp 399–424.

Rae, D. and Carswell, M. (2000) “Using a life‐story approach in researching entrepreneurial learning: The development of a conceptual model and its implications in the design of learning experiences”, Education and Training, Vol. 42, No. 4/5, pp. 220–227. SCOPUS bibliographic database, [online], http://www.scopus.com/

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Innovation Capital as a Driver of Eco‐Innovations: A Case of European Enterprises Tomasz Kijek Department of Economics and Management, University of Life Sciences in Lublin, Poland tomasz.kijek@up.lublin.pl Abstract: Within the field of environmental economics and management, determinants of eco‐innovations have received much attention. There are an increasing number of empirical papers that deal mainly with demand side and regulation determinants of eco‐innovations. While, there is a gap in identifying the role of knowledge assets in eco‐innovations activities. According to the knowledge‐based view, the ability of a company to exploit and upgrade its knowledge base determines innovative success. The dynamic nature of the process of knowledge base development requires keeping balance between knowledge flows and knowledge stocks. The aim of this paper is both a theoretical analysis of the influence of innovation‐related intangibles on the decisions of enterprises regarding the implementation of eco‐ innovations and an empirical verification of the discussed relationships. The theoretical framework focuses on peculiarities of eco‐innovations and explains the links between innovation capital and eco‐innovative performance. The research questions derived from the literature review pertain to the relationship between organizational and technological eco‐ innovations, as well as the role of knowledge and cooperation mechanism for environmentally‐friendly innovations. The empirical analysis uses data gathered in a survey conducted at the request of the European Commission in 2011. The sample consists of 5222 managers of small and medium–sized enterprises from the 27 EU countries, who were interviewed about their activity in the field of the implementation of eco‐innovations. In order to find answers to the research questions, a logistic regression model was used, where analysis subjects were groups of enterprises from the 27 EU countries. The results of research show that stock of knowledge capital (technological capabilities) and qualified personnel trigger eco‐innovations, while the effects of external knowledge flows and cooperation mechanism are equivocal. Keywords: eco‐innovation, innovation capital, knowledge stock, knowledge flow, cooperation mechanism

1. Introduction The key role of eco‐innovations in today’s economy, i.e. a knowledge‐based economy, results from the fact that environmentally‐friendly innovations are a factor in the sustainable development of enterprises and economies which allows substitution of tangible inputs by knowledge capital, without the need for natural capital depletion (Kijek 2013a). In the European economy, environmentally friendly innovations pretend to the term of coupling agent within both a strategy of sustainable development, which was set up to integrate and balance all areas of human activity (Cao and Piecuch 2012), and a strategy of intelligent development, i.e. those based on knowledge and innovations (Kijek and Kasztelan 2013). Enterprise inclination towards eco‐innovations is conditioned on the one hand by the occurrence of factors (premises) of an external character, e.g. market pressure and environmental regulations; while on the other hand it is determined by tangible and intangible assets providing services required in the process of the design and implementation of new solutions favoring the environment (Rehfeld et al. 2007, Johnstone et al. 2010). While there exists a broad literature on the external determinants of eco‐innovations (for a comprehensive review, for example, see del Rio (2009)), the literature on the internal drivers of eco‐innovations is less extensive. This dearth of knowledge on endogenous factors such as innovation capital which affects the propensity of enterprises to innovate in environmental dimension becomes quite problematic, since knowledge assets regarded as the elements of innovation capital are seen as key contributors to a firm’s success in eco‐innovations activities (Horbach 2008). This paper attempts to address this gap in the literature by providing both a theoretical insight into the nature of eco‐innovation and an empirical analysis of its knowledge‐based drivers. The analysis is based on country‐ data obtained from the results of the investigation into the activity of European enterprises in the field of the implementation of eco‐innovations conducted in 2011 by Gallup Hungary at the request of the European Commission. The method used in the research is a logistic regression. Providing estimation results of the logistic regression allows for a deeper understanding of the relationship between knowledge assets and the propensity to innovate in the environmental dimensions.

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Tomasz Kijek The remainder of this paper is organized as follows: section 2 provides a literature review on the nature of eco‐ innovation and its driver in the form of innovation capital. Sections 3 present and discuss the methodology and the results of research. Section 4 concludes.

2. Literature review and research questions This paper addresses two subject areas. Firstly, the paper attempts to find the nature and key features of eco‐ innovations. Secondly, the paper tries to establish the link between innovation capital and eco‐innovations. In the following, this section will give a concise review of the literature dealing with these two issues.

2.1 Concept and types of eco‐innovation The eco‐innovation concept appeared in the 1990s and was for the first time introduced to environmental economics nomenclature by Fussler and James (1996) in their book Driving Eco‐Innovation: A Breakthrough Discipline for Innovation and Sustainability. The authors defined eco‐innovations using alternatively the terms sustainable innovations, as new products and processes creating value for enterprises and clients, and reducing (negative) environmental effects. A similar stance on defining eco‐innovation has been adapted by many authors and institutions (table 1). Table 1: Definitions of eco‐innovations Authors (Kemp and Pearson 2008)

(Hemmelskamp (1997) (Beise and Rennings 2003) (OECD 2011)

Definition Eco‐innovation is the production, assimilation or exploitation of a product, production process, service or management or business methods that is novel to the organization (developing or adopting it) and which results, throughout its life cycle, in a reduction of environmental risk, pollution and other negative impacts of resources use compared to relevant alternatives Environmental innovation is an innovation which serves to prevent or reduce burdens on the environment, clean up damage already caused, or diagnose and monitor environmental problems. Environmental innovations consist of new or modified processes, techniques, practices, systems and products to avoid or reduce environmental harms. Eco‐innovation is a new or substantially improved product (manufacture or service), process, organization or marketing method, which reduces negative influences on an environment and/or optimize the use of resources [3].

The above definitions show a key feature of motivated eco‐innovations, i.e. their real effects on a firm's environmental impact. The environmental benefits are interpreted in terms of the reduction of environmental risk, pollution and harms. It is quite obvious that the beneficial environmental impact of eco‐innovations is socially desirable, but the double externality problem reduces the private incentives for firms to invest in environmental R&D. Apart from this characteristic of eco‐innovation, Rennings (2000) identifies two more peculiarities, i.e.: the regulatory push/pull effect and the increasing importance of social and institutional innovation. Given the presented approaches for the definition of innovations beneficial for an environment, three dimensions of the analysis of the eco‐innovation activities may be distinguished (OECD 2009):

Target ‐ selection of subject range of eco‐innovations, i.e. product, process, marketing or organizational method, institution.

Mechanism ‐ way the aims are realized, i.e. 1) modifications in the form of small adjustments in the product or process, 2) re‐design involving considerable changes in existing products, processes, organizational methods, 3) introduction of substitutes for previously offered products or services, 4) design and implementation of entirely new products, processes or organizational and marketing methods.

Impact ‐ effect of eco‐innovation on an environment, where the range of influence spreads from incremental environmental improvement to total elimination of harmfulness for an environment.

According to the target dimension of the analysis of the eco‐innovation activity, eco‐innovations include new or modified products/services providing environmental benefits (e.g. phosphate‐free detergents, solid waste management, etc.) and environmental technologies (process eco‐innovations) which may be divided into integrated technologies (preventive) and additive technologies (end‐of‐pipe) (Rennings 2000). Technologies preventing the formation of pollutants constitute either the entirety or a part of the production process and

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Tomasz Kijek are designed to decrease both the amount and the quality of pollution created during the production process (e.g. membrane technology in chlor‐alkali production). In turn, end‐of‐pipe technologies reduce or eliminate pollution after its production (e.g. wastewater treatment plants). Illustrative examples for these types of eco‐ innovations can be found in papers by Kowalczyk et al. (2010) and Piecuch et al. (2011) among others. Except for solutions of a product and process character, eco‐innovations also include new organizational and marketing methods (e.g. environmental management systems – EMS and eco‐labeling, respectively) directed towards the solution of environmental problems. It is worth noting that environmental organizational innovations are seen as a trigger for process and product eco‐innovations by helping to overcome the problems of incomplete information and managerial coordination (Horbach et al. 2012). However, most of the empirical studies prove a positive impact of EMS on process innovation but no effect on product innovation (Pereira and Vence 2012).

2.2 Innovation capital and eco‐innovations In the intellectual capital theory of a firm (Edvinson and Malone 1997, Castro et al. 2010), innovation capital is a bundle of the firm’s intangible assets that renders services in the process of new knowledge (innovation) creation and commercialization. A portfolio of innovation capital consists of technological knowledge in the form of intellectual property rights and R&D stock as well as non‐technological knowledge embodied in the organizational routines and thinking of employees (Kijek 2012). The stocks of innovation capital elements can be increased by knowledge flow from inside or/and outside of the firm. For technological assets, Dierickx and Cool (1989) made the distinction between the stock of technological know‐how and R&D expenditure, treated as the knowledge flow, using “bathtub” metaphor. The ability to upgrade knowledge base, i.e. absorptive capacity, determines the firm’s innovation success (Spender and Grant 1996). According to the evolutionary approach to industry competition (Nelson and Winter 1982), the increase in the firm’s knowledge base creates opportunity for innovation. The literature on determinants of eco‐innovations categorizes the elements of innovation capital, i.e. R&D stock, organizational capabilities and employees qualifications, as supply side factors for the introduction of environmentally‐friendly innovations (Pereira and Vence 2012). According to the general innovation theory (Rosenberg 1974), knowledge capital (technological capabilities) seems to be a main determinant of efficiency and effectiveness of environmental innovation activities. Among few empirical studies dealing with this issue, Horbach (2008) finds that the introduction of cleaner technologies and products is supported by R&D investment specifically related to environmental matters. Similarly, Mazzanti and Zoboli (2006) prove that R&D is one of the major inputs driving the adoption of eco‐innovative output. The authors also highlight the role of other sources of knowledge, i.e. other firms and research institutes, in creating a firm’s knowledge base (Matras‐Bolibok 2012a). This conclusion is consistent with innovation network theory which emphasizes cooperation as an important factor increasing innovation capabilities (Baptista and Swann 1998, Matras‐ Bolibok 2012b). Apart from other empirical studies which confirm the positive impact of knowledge capital on a firm’s propensity to innovate in environmental dimensions (Rehfeld et al. 2007), there are also studies showing opposite results. For instance, Kammerer (2009) finds that a firm’s innovation capital proxied by the share of employees in R&D has no impact on environmental product innovation. According to the author this result may stem from two reasons. Firstly, the operationalization of innovation capabilities in this study differs from a commonly used proxy, i.e. R&D expenditures or stocks (Acs and Audretsch 1988). Secondly, the author suggests that the impact of R&D capabilities on environmental product innovation is sensitive to sector characteristics. Besides technological know‐how, another important elements of innovation capital is employees’ knowledge regarded as a driver of absorptive capacity that manifests itself in the firm’s ability to acquire, assimilate and utilize new knowledge (Kijek 2012; Baumol 2002). Enterprises attempt to increase the knowledge stock necessary for innovations by investments in hiring highly qualified employees or training for innovative activities (Al‐Laham et al. 2011). According to Bruno et al. (2008), the lack of adequately trained employees is an important issue for eco‐innovation. Despite this fact very few empirical studies deal with the role of employees’ knowledge/qualification in eco‐innovation activities (Horbach 2008). The lack of empirical studies in this field results from difficulties in counting of employees’ knowledge stock. However, given the nature of

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Tomasz Kijek these assets, Johnson (1999) argues that the use of sociological measurements may be most appropriate in this case. Based on the considerations in this section with regard to the knowledge‐based determinants of eco‐ innovations, three important research questions can be asked:

How is the relationship between organizational and technological eco‐innovations?.

What is the role of innovation capital for eco‐innovations?.

How does cooperation mechanism matter in eco‐innovation activities?.

3. Methodology and results of research The data used to carry out this research was obtained from the results of the investigation into the activity of European enterprises in the field of the implementation of eco‐innovations conducted in 2011 by Gallup Hungary at the request of the European Commission. The survey was conducted on a randomly selected sample composed of 5222 managers of small and medium–sized enterprises from the 27 EU countries (European Commission 2011). In order to find answers to the research questions, a logistic regression model was used, where analysis subjects were groups of enterprises from the 27 EU countries. The applied logistic regression model is presented by the equation: (1) where: P – percentage of enterprises which introduced eco‐innovative processes in the years 2009‐2010, X1 – technological capabilities (knowledge capital) and qualified personnel, X2 – access to external information and knowledge, X3 – collaboration with research institutes and universities, X4 – percentage of enterprises which introduced eco‐innovative organizational methods in the years 2009‐2010. In case of the first explanatory variable, which was used as a proxy of innovation capital, it was measured at the level of an enterprise on an ordinal scale from 1 to 4, where 1 meant very serious lack of technological capital and qualified personnel and 4 meant not at all serious lack of technological capabilities and qualified personnel. For the given objects of my analysis, i.e. the 27 groups of enterprises from EU countries, the values of the variable were calculated as weighted means, where the weights were fractions of inquired respondents assessing the lack of technological capabilities and qualified employees as very serious, somewhat serious, not serious or not at all serious. In case of the second explanatory variable, it was measured on the ordinal scale from 1 to 4 as well, where 1 meant very serious limited access to external information and knowledge and 4 meant not at all serious limited access to external information and knowledge. For the third explanatory variable, which was also measured on the ordinal scale from 1 to 4, the indications related to the intensity of the lack of collaboration with research institutes and universities. The procedure of weighted means calculation for these two variables was the same as for the first one. Table 2 presents estimation results of the logistic regression model of the form specified in the equation 1. The parameters of the model were estimated using the ordinary least squares – OLS method. In order to identify a set of explanatory variables which have considerable predictive capability, backward elimination was employed. Table 2: Determinants of eco‐innovations variable coefficient standard error t‐Student p value constant ‐2,366 0,332 ‐7,109 p<0,01 X1 0,300 0,127 2,359 p<0,05 X2 X ‐ ‐ ‐ X3 X ‐ ‐ ‐ X4 0,034 0,005 6,535 p<0,01 R2=0,642, F=21,505 (p=0,00), χ2=2,408 (p=0,299)

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Tomasz Kijek Note. x‐eliminated variable, χ2‐chi‐square statistics in Doornik‐Hansen test for normality of random disturbance, F‐test for model utility. The econometric results in table 2 show that technological capabilities and qualified personnel, interpretable as the indicator of innovation capital, determine process eco‐innovations. The coefficient for this variable is highly and positively significant. This outcome is in accordance with the literature on determinants of eco‐ innovations. Although in this study the influence of innovation capital is not possible to be split into two separate effects pertaining to technological capabilities and qualified personnel, it may be assumed that these elements of innovation capital are complementary and reinforce each other. On the one hand, only employees have ability to create new knowledge and consequently build up its stock. On the other hand, the lack of well qualified employees may cause inefficient exploitation of technological know‐how. Such constrain becomes specifically relevant for eco‐innovations, since firms are still inexperienced in dealing creatively with environmental issues (Porter and van der Linde 1995). As theoretically outlined, organizational eco‐innovations trigger process eco‐innovations, A plausible explanation for this finding is that organizational eco‐innovations in the form of EMS and other managerial tools allow firms to develop certain routines with respect to their behavior. In turn, these new routines help to resolve problems with organization and coordination of other eco‐innovation activities within a firm. As far as the access to external information and knowledge is concerned, the influence of external knowledge on eco‐innovations is not significant. This outcome is unexpected on the assumption that the flow of external knowledge has a direct effect on innovation performance, but could be partially explained by the fact that knowledge stock stimulates the relationship (Al‐Laham et al. 2011). This viewpoint draws on the observation that the only effect of knowledge flows would be on the level of knowledge stocks which directly affect eco‐ innovation performance. The same explanation may be applied to the relationship between firms’ collaborations with research institutes/universities and eco‐innovations.

4. Conclusions This paper produces a few important contributions for the theory on the internal determinants of eco‐ innovations. Theoretical and empirical implications of this work concern two subject areas: the literature on knowledge‐based drivers of environmental innovations and the literature on the role of cooperation mechanism in eco‐innovation activities. In the first case, the paper provides the insight into the relationship between innovation capital and eco‐ innovation in dynamic context. Moreover, the results of research show that technological capabilities and qualified personnel trigger eco‐innovations. On the other hand, the findings offer little support for the view that access to external knowledge and information affect eco‐innovation performance directly. The explanation for this outcome may be that the effect of knowledge flows on eco‐innovation performance is indirect and it is moderated via knowledge stocks. In the second case, collaboration with research institutes and universities exhibits an insignificant influence on eco‐innovations. One reason for this finding is that the effects of collaboration are time‐lagged and indirect. Finally, it turns out that organizational eco‐innovations influence the decision to introduce process eco‐innovations, suggesting a complementary relationship between them. The paper is not exempt from some limitations. The main drawback pertains to a narrow set of the innovation capital elements included in the empirical analysis. A consequent extension of this study is to include a broader set of innovation capital indicators, e.g. patents, so as to reflect the firm’s innovation capabilities more accurately. Another shortcoming of the paper concerns the data used in the analysis. The data has been aggregated at the country level, so there is the possibility that micro‐relations may be obscured by aggregation biases. In order to overcome these limitations future research should investigate the relationship between knowledge‐based factors and eco‐innovations using longitudinal micro data.

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Tomasz Kijek Al‐Laham, A., Tzabbar, D. and Amburgey, T.L (2011) “The dynamics of knowledge stocks and knowledge flows: innovation consequences of recruitment and collaboration in biotech”, Industrial and Corporate Change, Vol. 20, No. 2, pp 555– 583. Ballot, G., Fakhfakh, F. and Taymaz, E. (2001) “Firms’ Human Capital, R&D and Performance: A Study on French and Swedish Firms”, Labour Economics, Vol. 8, No. 64, pp 443–462. Baptista, R. and Swann, P. (1998) “Do firms in cluster innovate more?”, Research Policy, Vol. 27, pp 525‐540. Baumol, W.J. (2002) The Free‐Market Innovation Machine—analyzing the Growth Miracle of Capitalism, Princeton University Press, New Jersey. Beise, M.K. Rennings, K. (2003) “Lead Markets of Environmental Innovations: A Framework for Innovation and Environmental Economics”, [online], Mannheim, ftp://ftp.zew.de/pub/zew‐docs/dp/dp0301.pdf. Bruno, N., Miedzinski, M., Reid, A. and Yaniz, M.R. 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(2012)b „Efektywność współpracy przedsiębiorstw w zakresie działalności innowacyjnej”, Research Papers of Wrocław University of Economics, No. 262, pp 232‐240. Mazzanti, M. and Zoboli, R. (2006) “Examining the factors influencing environmental innovations”, [online], http://dx.doi.org/10.2139/ssrn.879721 Nelson, R. and Winter, S. (1982) An Evolutionary Theory of Economic Change, Harvard University Press, Cambridge. OECD (2009) Eco‐Innovation in Industry. Enabling Green Growth, OECD Publishing, Paris. OECD (2011) Better Policies to Support Eco‐innovation, OECD Publishing, Paris. Pereira, A. and Vence, X. (2012) “Key business factors for eco‐innovation: an overview of recent firm‐level empirical studies”, Cuadernos de Gestión, Vol. 12, pp 73‐103.

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Employee Driven Innovation: Bridging Open and Close Innovation Management Practices Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg Novancia Business School Paris, France elaviolette@novancia.fr rrediencollot@novancia.fr ateglborg@novancia.fr Abstract: This article explores the role of Employee Drive Innovation (EDI) as bridges between close and open innovation management practices in a large chemical company. Traditionally Employee driven innovation is an « internal » approach to innovation by encouraging creativity by employees within the organization. However, if EDI’s focus is « inside », it encourages connections and porosity « outside » at different levels of the organization. To explore these porosities, we built on a case study of a large chemical company with a long established tradition in EDI and a more recent Open Innovation Policy. We show how EDI can be articulated to open innovation programs and serve as technical bridges between the inside and the outside but also social bridges between technology and market. Furthermore, the role of various actors (ideators, supporters, facilitators and managers) at different level of the organization (top/down; inside/out) are illustrated. Keywords: employee driven innovation, open innovation

1. Introduction The traditional approach to innovation is a vertically integrated sequence starting from technological research to market development. (Chesbrough, 2003a ; 2003b ; Christensen et al., 2005 ; Chesbrough et al., 2006 ; Chesbrough et Schwartz, 2007 ; Elmquist et al., 2009). Open innovation proposes to break this sequence by knitting more closely market and technology through outside‐in and inside‐out connections. If such proposal is stimulating for the expansion and diffusion of innovation, it raises questions on the organizational design to support innovation at the interface between the inside and the outside. This article aims at exploring the organizational design of such inside‐outside articulations by focusing on Employee Drive Innovation (EDI) and their role as bridges between close and open innovation practices. Traditionally Employee driven innovation is an internal approach to innovation by encouraging creativity by employees within the organization. However, if EDI’s focus is inside, it encourages connections and porosity outside at different levels in the organization. Our objective is to explore these porosities are potential bridges with other innovation management practices. We will discuss how employee‐driven innovation is one of the bridges between the R&D‐based management of innovation and approaches to innovation management based on Market‐based innovation. Taking into account the innovative character of these hybrid approaches to managing innovation, we have chosen to examine a case study of the Solvay Group. In effect, our initial observations prompted us to postulate that, within the firm, new practices are emerging that articulate open innovation, R&D, and employee‐driven innovation, and that these practices have not aroused much interest within the academic community. An analysis of their most significant aspects has enabled us to induce plausible hypotheses about the originality of these forms of management from a theoretical perspective (David and Hatchuel, 2007). New configurations in terms of the design and management of innovation revealed by this case prompted us to examine the innovation model at work at Solvay. Is it an Open Innovation model of the kind described by Chesbrough, or is it, taking into account the new overlapping practices encouraged by employee‐driven innovation, a new model of innovation management? To attempt to reply to this question, we will start by describing the innovation paradigm shift described by Chesbrough from a closed to an open innovation model, before moving on to highlight the questions posed by that kind of shift in terms of innovation management. We will then analyse the Solvay case in the light of the innovation model described by Chesbrough in order to describe its limits and underline the innovative role played by employee‐driven innovation as bridge between Internal R&D and Open Innovation practices.

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg

2. Innovation management: A shift from closed to open models? Acccording to Chesbrough (2003a), the open innovation model originally emerged at the end of the 20th century as an alternative to what he refers to as the closed model of innovation. In this model of innovation, firms generate, develop and market their own ideas exclusively. In order to do so, they apply vertical integration strategies and closely monitor the development of innovations (Chesbrough, 2003a). In the open innovation model, firms market ideas developed both within and outside of their R&D units and apply various approaches to promoting ideas developed internally to their traditional markets, as well as investing in start‐ups and licences (Chesbrough, 2003b). Thus, the frontiers between the firm and its environment become increasingly porous, making it possible for innovators operate on both sides of the divide contemporaneously (Chesbrough, 2003b). This porosity encourages firms to be less defensive in terms of intellectual property rights and to focus on using patents to exploit opportunities in the wide world by means of licences and joint‐ventures. In the open innovation model, firms analyse all the ways in which they can potentially exploit innovative ideas both in terms of their existing clients and of the market in general. Another alternative is for firms to sell their patents to competitors. In effect, there is no inherent value in a given technology; a technology is only of value to the degree that it is coherent with the business model of the firm that develops it (Chesbrough, 2006a). Indeed, many ideas are not used because innovation processes applied by firms are highly decentralised (Chesbrough, 2006a). Selling unused ideas not only generates additional financial resources, but also new knowledge about technology and the market (Chesbrough, 2006a). Chesbrough (2003b) summarize the shift from a close model to an open model in the following table. Table 1: Adapted from Chesbrough (2003b) Close innovation principles The most talented people works for us

Open innovation principles Not all talented people work for us. We rely on an external pool of talents. Outsourced R&D can create substantial value. Internal R&D contributes to capturing this value We don’t have to reinvent the wheel. We can also exploits what has not been invented here Developing an effective business model is preferable to systematically assuming the posture of a first‐time entrant. Exploiting the best ideas give us a leap ahead competitors Selling and Buying IP from stakeholders is key

For profit generation, the firm must discover, develop and market innovations If the firm discover first, it will commercialize first Being the first mover for commercialisation of innovation is the major competitive advantage Generating the best ideas give us a leap ahead competitors Protecting our IP from competitors is key

According to Chesbrough (2006a), there are two main advantages to open innovation: firstly, it helps reducing costs associated with the development costs of technological innovation by insourcing external technologies, thereby saving time and financial resources. Secondly, the new model also makes it possible to increase revenue by providing more outlets for innovations (Chesbrough, 2006a). If Chesbrough and his colleagues have received widespread attention among professionals and companies making “open innovation” a popular business concept, the open innovation model raises empirical and theoretical issues from an academic standpoint.

3. Empirical and theoretical issues First of all, open Innovation has not been extensively validated empirically, even if the model is examplified in Chesbrough works. Furthermore, one of the main criticism is that open innovation is unsufficiently anchored in the literature on innovation management (Elmquist et al., 2009 ; Huang et Rice, 2009 ; Lichtenthaler et Lichtenthaler, 2009 ; Van de Vrande et al., 2010 ; Remon ; 2010). It does not bring a discussion about the existing models on R&D and Innovation management where knowledge has become the key asset (Rogers, 1996). For instance, Wang and Kleiner (2005) have shown the evolution of R&D Management models in six types : 1) “technical push” in the fifities/sixties; 2) “market pull” in the seventies ; 3) “coupling model” in the eighties ; 4) “integration and parallel development” in the nineties ; 5) “coordination and systemic integration” in 2000 ; 6) “a refocus on research and Multi‐Technology” Research Networks. The openness of innovation management practices is a long established process in companies since the second world war. Openness means that companies are permeable to knowledge flows, multiple collaborations with suppliers, customers, competitors

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg and other stakeholders. Given this historical perspective, Remon (2010) shows that Open Innovation cannot be considered as a new paradigm for it corresponds to the 4th and 5th Model of Wang and Kleiner (2005), which are centred on integration and interaction. Furthermore, Open innovation raises different issues concerning organizational design

4. Organisational issues to open innovation The main postulate in Open Innovation is that External R&D Innovation Management is becoming equally important as Internal R&D. There is a need to a systemic approach of R&D Management that is balanced in terms of openness and closeness. However, such perspective is not new either. Introducing the concept of absorptive capacity, Cohen & Levinthal (1990) have shown that to be able to absorb external knowledge bases, firms need to have minimal knowledge bases inside. Building on that concept, Teece and his co‐authors (Teece, Pisano and Shuen, 1997; Teece, 2007) have developed the proposal of a dynamic capabilities enabling both exploration and exploitation of internal and external knowledge and resources for competitiveness. The interesting aspect in Chesbrough’s Open Innovation Model (West, Vanhaverbeke et Chesbrough , 2006) reside in the focus on two specific processes (Leadbeater, 2010 cited by Remon, 2010) related to dynamic capacity building for innovation. First of all, Outside‐In processes consisting in exploring and integrating external knowledge bases by collaborating with multiple stakeholders, who might resolve potentially innovation problems. If such processes reduces the size of internal R&D, it increases the management of these multiple interfaces. A key issue is the appropriation of the diversity of ideas so that companies do not face the NIH (“Not Invented Here”) syndrome (Chesbrough, 2006a). In effect, the actors of the firm are often decidedly reticent about “foreign” innovations. This translates into a systematic rejection of external ideas that can inhibit the firm’s capacity to seek out knowledge and innovations developed externally that are of potential benefit to the firm’s business model (Chesbrough, 2006a). The NIH syndrome is linked to an essential problematic in the management of open innovation, namely how to encourage the monitoring and integration of external innovations. Secondly, Inside‐Out processes consisting in exploiting and outsourcing internal knowledge bases by selling intellectual property to different actors such as public and private researchers through divestiture and spin‐ offs. One of the main obstacle to this process us the corollary of NIH, which is “NSH” (“Not Sold Here”), meaning that: “If we don’t sell it, no one should sell it.” In effect, as with those who “reject” external ideas, individuals working on innovation within the firm sometimes opt to ignore new ideas rather than develop them (Chesbrough, 2006a). This syndrome prevents technologies that do not fit the parameters of the firm’s business model being exploited in the wider world. Unused ideas are a waste of company resources. Furthermore, the fact that such ideas are left to languish on the shelf has a demotivating effect on their inventors and renders the firm’s innovation system less effective. NSH syndrome signals another problematic characteristic of the field of innovation management, namely how to encourage the diffusion and promotion of internal innovations. Furthermore, it is not always easy to convince R&D teams to accept innovations. Those teams often shoulder the blame when insourced technologies prove disappointing. Conversely, the success of insourced technologies sometimes encourages top management to make cuts in R&D personnel (Chesbrough, 2006a). Managers are thus encouraged to reappraise the role of R&D within the company. While Chesbrough is aware of these issues, he does not provide recommendations about how they should be addressed. The linkages between traditional more internally centred innovation management practices and new more externally centred innovation practices need a more thorough analysis. Identifying links between organisational innovation and open innovation is still limited, though several recent work discusses the issue. In our analysis of the Solvay case, we will suggest a number of approaches that could potentially be used to overcome these organisational obstacles.

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg Methodology Focusing on the case of Solvay, we examine the emergence of two forms of innovation that have characterised the firm’s evolution at its main production site, located in Tavaux in the Jura. From a methodological point of view, it should be underlined that, as analyses of contemporary phenomena have shown (Yin, 2003: 13), case studies enable us to explore the emergence of decisive organisational factors, evidenced in this instance by the hybridisation of two different types of innovation. According to Eisenhardt and Graebner (2007), the choice of a single case study is justified in the longitudinal examination of extreme cases both in terms of resources applied and results achieved. In the case study, we will therefore highlight the scope and evolutive character of these innovations. From an epistemological point of view, the objective of our research is either to add to the value of the open innovation model in regard to the Solvay case or to develop a theoretical apparatus based on the Solvay case if the practices observed have not been subject to any theoretical elaboration (David and Hatchuel, 2007). To reduce the degree of rationalisation in the content of the interviews conducted within the framework of this research project, we have triangulated the data with two other sources, namely internal (institutional) documents describing the process of open innovation and employee‐driven innovation and the way in which they potentially overlap, and documents produced by employees to present their innovative ideas (Yin, 1984).

5. Solvay: Innovation at the heart of the firm Based on the values of innovation, scientific progress and human development, Solvay has accrued a substantial amount of experience in the field of managing innovation since its foundation in 1861. However, in the early 2000s, Solvay’s management became aware that the company, founded on a major discovery in the chemicals sector, was no longer innovating. Thus, Solvay started to focus on new areas of business development, including renewable energies, nanotechnologies, printable organics (inks), and sustainable (or green) chemicals. These objectives are part of a strategy of open and structured innovation designed to promote sustainable and profitable growth, the two pillars of which are innovation and competitiveness.In that perspective, the open innovation policy was introduced by Solvay in 2003‐2004. However, the Group initially began to focus on innovation in the late 1990s, launching a major employee‐ driven innovation programme called “Innovation for growth” that was part of a trend that questioned the central role of R&D in innovation. This program encouraged employees to take a fresh look at their own day‐ to‐day activities, at those of the Group, and at those of firms close to them with a view to suggesting different kinds of ideas in fields as diverse as improving safety, production processes, client service, and identifying new market opportunities for chemicals and plastics. It also served as an opportunity to align the innovative ideas of the most creative employees with the Group’s overall strategy. According to T. Collard, “[w]hen we initially attempted to organise this process of creativity in the 1990s within the framework of product‐market groups including representatives of different departments at Solvay, the purpose of which was to develop ‘inter‐ business’ products. However, these working groups often lacked strategic support and resources,” explains T. Collard. “Innovation for Growth” made it possible to integrate the innovative ideas developed by the most audacious employees – those who had a transversal and open view of their sector and activity – into all the company’s sites and units. For instance, in Tavaux, one of the major production site, ideas suggested by employees entered a circuit of validation and accompaniment. In 1999‐2000, with a view to encouraging employees to develop a broad range of ideas, a suggestions system was set up on the Innoplace platform. When an employee suggested an idea, it was displayed immediately and could be viewed not only by Solvay employees, but also by partners of the firm and by experts involved in related projects. The “Innoplace” Ideas Box system is equipped with a “Véritis” search engine. A questionnaire is provided to employees to help them formulate their ideas. Not only are employees able to view their own ideas on the system, but experts are able to access any ideas that need to be examined. It is thus possible to consult local Ideas Boxes in reference to categories such as “area”, idea to be replicated, most often consulted idea, and ideas with the highest investment/profit ratio. Lastly, firms that are not partners of Solvay can subscribe to the system in function of their activities and future projects.

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Figure 1: Mapping of EDI’s Social Interactions “Innoplace” provides the Tavaux site with an efficient and practical system for collecting and processing ideas. A network of functions that stimulate this process underpins the system. The role of the Department Head is to develop a climate favourable to the emergence of innovative ideas within his or her unit. Managers are provided with objectives: 60% of their personnel must take part in innovation, and an “Innovation” section has been added to the annual interview form. The employee‐driven innovation process can be characterised as follows: an employee is invited by facilitators to enter an idea in the “Innoplace” system; the idea is processed by an expert designated by the facilitator within a period ranging from 15‐30 days; it is then either accepted or rejected, in which case the author of the idea is provided with an explanation. If the idea is accepted, it is examined by a commission which decides whether or not it should be applied and have resources allocated to it. In this case, the author will see his or her idea implemented. But the progress of ideas through the system is not always straightforward. They are often blocked by experts or, indeed, by the commission. However, once an idea has been implemented, the potential profits associated with it are evaluated and the author of the idea is rewarded. Innovators are regularly honoured at trophy ceremonies and events organised by the factory to support the approach (forums, challenges). As the figures outlined below demonstrate, more and more employees are taking part every year: Table 2: Innovation performance at Solvay (2006‐2009)

2006

2007

2008

Number of innovative ideas submitted

1,578

1,908

2,185

First semester 2009 1,081

Number of innovative ideas implemented

456

629

633

306

Acceptance rate (number of ideas implemented/ideas submitted)

28.9%

33%

29%

28.3%

Number of employees having suggested at least one idea

705

815

811

568

Participation rate (number of employees having suggested at least one innovative idea: idea/total number of personnel)

47.5%

54.7%

55.4%

38.9%

Estimation of overall profits generated by the approach and/or in terms of profit per employee

€4,891 / pers.

€3,373 / pers.

€2,200 / pers.

€811 / pers.

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg At Tavaux, Innoplace managers administer Ideas Boxes – where employees deposit their innovative ideas electronically – while five “Innovacteurs” manage the process, steering the Ideas Boxes in their sector, providing reports to management, discussing good practices in the field of innovation with other “Innovacteurs” in the Solvay Group, and ensuring that ideas are replicated in the global Champions of Innovation network. There is also the “Innovation Sponsor”, who defines objectives and indicators, and monitors results. He or she runs two operational networks: a national Champions of Innovation network, and a sector‐based Champions of Innovation innovation network. As T. Collard puts it, the Innovation Sponsor ensures that “all employees are aware of the issues associated with innovation and encourages employees working in R&D to produce and promote radical innovations.” Examples of such innovations are PVC tiles, a new membrane used to transform water into an electric current, etc. There are also incremental innovations, particularly those coming from the maintenance department: a mobile shower so that employees can clean their protective clothing on site; and a “handle/pliers” device invented by sub‐contractors to prevent potential injury when handling severed pipes. This last application is now used by all the sub‐contractor’s teams. While the employee‐driven innovation approach was gradually developed by articulating the national and sector‐based Champions of Innovation networks, R&D at Solvay was reorganised in function of two relatively large fields of activity, namely Future Business and Advanced Technologies. Future Business focuses on radical innovations in the sustainable energy sector (fuel cells; organic solar cells), while Advanced Technologies concentrated more on vegetal chemistry and nanotechnologies. From 2003, an increasing number of research teams struck partnerships with external entities, in the form of joint research projects or venture capital projects. Solvay‐Tavaux initiated a certain number of joint research partnerships with local academic institutions (universities and University Technological Institutes), as well as with SMEs/SMIs. As we have seen above, particularly insofar as sub‐contractors are concerned, these SMEs/SMIs had worked with Solvay‐Tavaux in a previous phase within the framework of employee‐driven innovation, before joining Innoplace and going on to strike official partnerships with Solvay‐Tavaux to launch ambitious research projects such as development of the new hydro membrane. Nevertheless, in some other projects emanating from the innovation process involving R&D teams and external partners, for example the use of recuperated ashes, progress has been difficult to achieve. On the other hand, the management at Tavaux has not yet set up venturing partnerships involving investments or share capital. Innovative companies in the plastics and chemicals sectors are monitored, but nothing has come of this so far. It should be noted, however, that, within the framework of employee‐driven innovation, links between various departments have become stronger and ideas are being transferred between units and adapted to different contexts.

6. EDI as social and technical bridges From 2003/2004, Solvay has accorded equivalent importance to knowledge generated both internally and externally and fully recognises the fact that some of the knowledge useful to the firm is dispersed in the environment. This implies that Solvay uses the open innovation model (Chesbrough, 2006b). However, far from being neglected, internal R&D is reinforced both at the corporate level and at the level of the Group’s various business units. The objective of corporate R&D is to develop radical innovations useful to the Group as a whole. The approach is articulated around Future Business, the objective of which is to develop the products of tomorrow (in the field of sustainable energy, for example), and Advanced Technologies focusing on technological innovations like green chemicals and nanotechnology. Meanwhile, the objective of R&D in business units (PVC, carbonates) is to develop incremental innovations linked to those units. While reinforcing its internal capacity to generate knowledge useful in the field of innovation, the firm is branching out into its environment by developing both local and corporate partnerships. Numerous joint‐research projects with research centres (including the CEA and the CNRS), SMEs/SMIs, and other chemicals companies have been launched in emerging fields. Shares have been purchased in Belgian, German and British start‐ups (focusing on fuel cells and organic solar cells) following joint‐research programmes that have led to the setting up of new companies. In France, Solvay essentially develops venturing projects by working with investment companies specialising in emerging sectors such as sustainable energy. The objective is to invest in companies capable of generating complementary knowledge. The table below summarises the various internal R&D and open innovation approaches applied, giving examples.

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg Table 3: Types of innovation management practices at Solvay Innovation Practices

Objectives

Type

Corporate Level Future businesses Advanced technologies

Radical innovation Tomorrow’s products Future technologies and procedures Incremental innovations

Technology‐Centred ; Internal R&D or Close Innovation

Business Unit Level Joint‐research projects Venturing

New knowledge in emerging fields Identifying firms with complementary expertise

Market‐Centred ; External R&D or Open Innovation

These different approaches to innovation demonstrate the importance granted to the development of knowledge generated both internally and externally. Solvay’s focus on innovation displays one of the characteristics of Chesbrough’s innovation model (2003a). The corollary is the increase in the number of approaches to promoting innovation developed internally externally, notably by exploiting patents in the form of licences. For the time being, Solvay does not seem to be developing this approach. Consequently, we believe that the firm is developing an open innovation model based on the exploitation of externally generated knowledge, while at the same time intensifying its internal R&D, but that it does not exploit, externally in the form of licences, innovations developed internally.

Figure 2: From employee driven innovation to open innovation In terms of an analysis of Solvay’s model of innovation, Chesbrough’s approach is incomplete. Solvay defines innovation as “the process by which a firm converts the creativity of its employees and partners into added value more rapidly and effectively than its competitors” (Solvay’s Innovation Policy Handbook). According to this definition, employees and external partners are sources of innovation on which emphasis should be placed. However, in Chesbrough’s model, internal innovation is focused on R&D. In the revisited model, internal innovation is open to all employees as well as to R&D. At the local level, the Tavaux factory applies an open innovation approach vis‐à‐vis its sub‐contractors of a kind that is not described in Chesbrough’s model. Of course, he underlines that users outside the firm in question can be sources of innovation based on the practices that they develop in their day‐to‐day routines, but he does not speak explicitly about employees (Chesbrough, Vanhaverbeke, & West, 2006b) and about the role that employees can play in establishing the kind of innovation communities that he believes are essential for the management of internal and external innovations (Chesbrough, 2006: 134). In this sense, Chesbrough’s model “outsources” innovation to such a degree that the role of the firm’s internal actors tends to be forgotten. However, the way in which external innovations should be appropriated and

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Eric Michael Laviolette, Renaud Redien‐Collot and Ann‐Charlotte Teglborg internal innovations exploited is a central problematic in the open innovation model. Currently, the model introduces an “overly explicit” form of competition between internal and external innovation, but in reality it is a matter of encouraging cooperation between employees and partners, and monitoring the evolutions in the environment with a view to increasing the potential for innovation. Moreover, in spite of the fact that human resources are a key factor in the competitiveness of knowledge‐based companies, Chesbrough does not emphasise the human potential of the firm. Instead, he merely underlines the importance of “de‐partitioning innovation” in regard to development costs, and of outsourcing certain innovations and exploiting assets created by the innovation process. In this perspective, although open innovation is in fact designed to extend innovation to all levels (internal and external), it runs the risk of being perceived as a strategy designed to reduce innovation activity. This is how conservative reactions like NIH and NSH have emerged. To reduce such risks and encourage an open‐minded attitude, it is vitally important to stimulate innovation internally through an “internalised” but open approach to innovation management.

7. Conclusion Employee‐driven innovation is an approach that makes a substantial contribution to decentralising and democratising innovation in firms in which R&D plays a key role. Innovation at Solvay is now everyone’s concern and the firm has implemented tools that everyone can use to innovate at their own level. Furthermore, this approach is gradually being extended to partners of the firm, EDI thus becomes a means of encouraging the circulation of ideas from the base to the summit, between various business units and, beyond, with key partners. It serves as a bridge between the inside and the outside but it is also the missing social bridge between technology and market.

References Chesbrough, H. 2003a. Open Innovation. The New imperative for creating and profiting from technology. Boston : Harvard Business School Press. Chesbrough, H. 2003b. “The era of open innovation”. Sloan Management review, 44(3): 35‐41 Chesbrough, H. 2004. “Managing open innovation.” Research technology management, 47(1): 25‐36. Chesbrough, H. 2006a. Open business model, how to thrive in the new innovation landscape ? Boston: Havard Business School Press. Chesbrough, H. 2006b. “Open innovation: a new paradigm for understanding industrial innovation”. In H. Chesbrough & W. Vanhaverbeke & J. West (Eds.), Open innovation Researching a new paradigm. Oxford: Oxford university press. Chesbrough, H., Vanhaverbeke, W., & West, J. 2006b. “Open innovation: a research agenda.” In H. Chesbrough & W. Vanhaverbeke & J. West (Eds.), Open innovation Researching a new paradigm. Oxford: Oxford university press. Cohen, W.M et Levinthal, D.A (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1): 128‐152. David, A. & Hatchuel, A. 2007. “Management innovation at discovery stages: a challenge for management research,” EURAM. Jouy‐en‐Josas HEC‐Paris. Durieux, F. (Ed.). 2000. Management de l'innovation. Paris: Vuibert Elmquist, M., Fredberg T. and Ollila, S. (2009). Exploring the field of open innovation, European Journal of Innovation Management, 12(3): 326‐345. Eisenhardt, K.M and Graebner, M.E. (2007). Theory building from cases : opportunities and challenges, Academy of Management Journal, 50(1) : 25‐32. Huang, F. et Rice, J. (2009). The role of absorptive capacity in facilitating “open innovation” outcomes : a study of Australian SMEs in the manufacturing sector. International Journal of Innovation Management, 13(2) : 201‐220. Innovation ouverte en contexte de PME : role des capacités et de l’innovation organisationnelless, thèse de doctorat. Trois‐ Rivières: Université du Québec à Trois‐Rivières. Leadbeater, C. (2010). Two faces of open innovation, cited by Remon (2010) Lichtenthaler, U. and Lichenthaler, E. (2009). A capacity‐based framework for open innovation complementing absorptive capacity. Journal of Management Studies, 46(8), 1315‐1338. Remon (2010). Innovation ouverte en contexte de PME : role des capacités et de l’innovation organisationnelless, thèse de doctorat. Trois‐Rivières: Université du Québec à Trois‐Rivières. Teece, D.J ; Pisano, G. et Shuen, A/ (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509‐533. Teece, D.J (1982). Towards an economic theory of the multiproduct firm. Journal of Economic Behaviour and Organization. 3(1). 39‐63. Van de Vrande, V., Vanhaverbeke, W. and Gassman, O. (2010). Broadening the scope of open innovation : past research, current state and future directions. Technology Management, 52 (3/4), 221‐235. Wang, J. and Kleiner, B.H. (2005). The evolution of R&D Management. Management Research News, 28(11/12), 88‐95. Yin, R.K. (1984), Case Study Research, Thousand Oaks, CA: Sage.

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Social Capital, Knowledge Strategy, and new Venture Performance: Evidence From Graduate Entrepreneurial Ventures in China Jun Li1 and Weihe Gao2 1 Essex Business School, University of Essex, Elmer Approach, Southend on Sea, UK 2 School of International Business Administration, Shanghai University of Finance & Economics, Shanghai, P. R. China junli@essex.ac.uk goodweah@yahoo.com.cn Abstract: Employing a sample of 156 graduate enterprises based in China, we examine the relationship between knowledge strategy (exploration or exploitation) and new graduate venture performance, and the effects of social capital (structural, relational, and cognitive dimensions) on trade‐offs of knowledge strategy. Results indicate that relational social capital is positively related to both exploration and exploitation, while cognitive social capital is negatively related to exploration. Additionally, we find that exploration and new venture performance is a U‐shape nonlinear relationship, while exploitation and new venture performance is an inverted U‐shaped relationship, indicating that there is a point at which focusing on either exploration or exploitation leads to reversed performance. Keywords: social capital, exploration, exploitation, new venture performance, graduate entrepreneurial ventures, China

1. Introduction To achieve high performance, new ventures must hold heterogeneous knowledge that is rare, valuable and difficult to imitate (Barney, 1991) and must also be capable of learning from knowledge sources beyond the boundaries of the firm. Marsh (1991) proposed exploration and exploitation as two distinct knowledge strategies that guide knowledge creation and renewal in firms. Exploration involves searching and experimenting with new knowledge or entrepreneurial opportunities through non‐routinized learning, while exploitation is characterized as routinized learning and tends to refine and extend existing competencies without changing the nature of a firm’s competences and capabilities (March, 1991). In making knowledge strategic options that involve trade‐offs, a new venture is usually hamstrung by its severe resource constraint. This raises a serious question as to how new firms’ knowledge strategies can affect venture performance. In this research, we focus on the effect of alternative knowledge strategies on organisational performance in new ventures. Additionally, a new venture positions its knowledge strategies in alignment with the availability of network resources in its inter‐organisational relationships as entrepreneurship is embedded in social networks. The acquisition of knowledge and learning are also predominantly social process, and new ventures may develop social capital as a strategy to aid in acquiring new knowledge (Yli‐Renko, Autio and Sapienza 2001). Nahapiet and Ghoshal (1998) identify social capital to include three dimensions, i.e., structural, relational, and cognitive dimensions. In this study, we examine the different effects of social capital on explorative and exploitative learning in the context of new venture creation. Furthermore, due to their short labour market experience, graduate entrepreneurs are the cohort of entrepreneurs who faces the most severe resource constraint and hence depends in large part on how well they can leverage the external sources of knowledge to achieve high venture performance. This study aims to fill a gap in our understanding of graduate enterprises by specifically investigating the effect of knowledge strategies on graduate enterprise performance and the antecedents of their knowledge strategies. We define graduate entrepreneurial venture as businesses being started by graduates within the first five years of leaving higher education. Thus, in this study, we addressed two research questions: what is the effect of knowledge strategies on new venture performance? how do different social interaction characteristics relate to explorative or exploitative learning of knowledge? We develop an original empirical setting based on survey data to test our hypotheses.

2. Hypothesis development and framework 2.1 Social capital and knowledge strategies Social interactions underpinned by social capital act as a conduit of knowledge exchange between network members. Social capital has been identified to include three dimensions, i.e., structural, relational, and

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Jun Li and Weihe Gao cognitive dimensions (Nahapiet and Ghoshal 1998). Structural social capital refers to the impersonal pattern of relationships between actors in a social network (Nahapiet and Ghoshal 1998). It is characterized by the range of network (i.e. presence or absence of ties) rather than the intensity of social interactions (strength of ties)(Simsek, Lubatkin & Floyd, 2003). Due to its lack of intensity in all properties that exemplify the strength of a tie, structural social capital represents what Granovetter (1973) calls weak ties. Network ties of this kind have a much narrower bandwidth and a longer reach; they are thinner and less durable; they are full of brokerage opportunities that allow network entrepreneurs to obtain non‐redundant information in the forms of access, timing and referrals (Burt, 1992). They thus provide better access to new and explicit knowledge which is spelled out in writing, verbalised, or coded in drawings, or other products (Afuah, 2003). Broader network ties increase the variety and quantity of explicit knowledge a network actor can access and the richness of non‐redundant information is in favour of knowledge exploration strategy. In contrast, tact knowledge is often embedded in the routines of organisations or in an individual’s actions and is difficult to articulate and transfer, unless those who possess it are willing to demonstrate it to others (Nonaka and Takeuchi, 1995). Therefore the exchange of tacit knowledge requires much more intensive and sustained personal interactions that are not the characteristic of structural social capital. Hence, the greater amount of new ideas associated with high discreet information loading may actually distract the graduate entrepreneur’s attention to integrate new knowledge for competence enhancing, thereby affecting negatively the performance of a new business venture. Thus: Hypothesis 1: Structural social capital is positively related to knowledge exploration and is negatively related to knowledge exploitation in new venture creation. Relational social capital refers to the interpersonal relationship that is derived from sustained social interactions or strong ties (Nahapiet and Ghoshal 1998). Strong ties are based on common interests, consequently most information that is passed reinforces existing views; strong ties are more cohesive, and often prove to more effective at the exchange of complex information; strong ties between two parties may restrict information gathering in terms of the breadth of search, but the information that is exchanged is “thick”, or detailed and rich (Granovetter 1973). Underpinning relational social capital is the existence of mutual trust among individuals and a pool of goodwill residing in a social network. Trust increases interactions and closeness among network members in a relationship, creates cooperation that stimulate learning and exchange of tacit knowledge (Tsai and Ghoshal 1998), and facilitate free flow of knowledge since any opportunistic behaviour is readily observed and punished (Coleman, 1988). In an ethnographic account of the networking activities of fourteen respondents, Jack (2005) finds that strong ties are instrumental for business development due to the strength of a tie leading to trust in information and resources available in social contacts, and that strong ties also provide the mechanism to invoke 'weak' ties that facilitates the acquisition and sharing of new information. Thus, relational social capital creates an environment in which people feel psychologically safe to make mistakes and offer and receive criticisms, thereby fostering knowledge exploration (Atuahene‐Gima and Murray 2007). Thus: Hypothesis 2: Relational social capital is positively related to exploration and exploitation in new venture creation. Finally, cognitive social capital is related to shared vision that provides shared representations, interpretations, and systems of meaning among parties (Nahapiet and Ghoshal 1998). Cognitive social capital can facilitate exploitation as a result of cognitive similarity, solidarity, strategic consensus and collective sanctions (Simsek, Lubatkin & Floyd, 2003). Cognitive similarities can positively influence knowledge exploitation by increasing efficiency of inter‐organizational communication and allowing entrepreneurs across the network to quickly acquire a common definition of the situation. Solidarity places emphasis on the benefits of mutual goal attainment among network members and thus advances a more constructive approach to information sharing. Strategic consensus ensures a common level of understanding and predictability of network members’ actions and behaviors. Collective sanctions define and reinforce the parameters of acceptable behaviour (Jones et al., 1997). This reduction in uncertainty and ambiguity about network members’ behaviors increases the effectiveness in the exchange of complex knowledge. Therefore, cognitive similarity, solidarity, strategic consensus and collective sanctions ensure a tendency for better and deeper understanding of existing technologies and markets, thus enhancing exploitation. Cognitive social capital may inhibit exploration, however. Too tightly knit networks may discourage network members from challenging one another’s positions in knowledge exploration and turn the networks inward‐looking. Furthermore, ties without cognitive diversity may limit network members’ capacity to

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Jun Li and Weihe Gao recognise preferable alternatives and lock members into “group think”. This cognitive lock‐in eventually led to the decline of steelmaking in Germany. Thus: Hypothesis 3. Cognitive social capital is negatively related to exploration in new venture development and is positively related to exploitation in new venture development.

2.2 Knowledge strategies and new venture performance Knowledge exploration can contribute to new venture performance because it provides the firm the foresight, through the acquisition of novel knowledge, to act in anticipation of future demand and shape the environment and it equips the firm an opportunity to reap the benefits that come from developing knowledge breakthrough, which is more likely to lead to a sustainable competitive advantage. Exploration in search of novel opportunities and radical new product development, however, is inherently costly and has a higher probability of failure, so, after a certain point, overdependence on exploration results in lower new venture performance. An exploitation strategy offers benefits to graduate entrepreneurs. Firstly, exploitation is a means of fully using their limited resources in existing technology and product‐market domains. Secondly, firms learn efficiently from local and proximate sources because prior related knowledge facilitates the identification, interpretation, and assimilation of related knowledge (Cohen & Levinthal, 1990), because new knowledge is often created through the combination of existing knowledge items and related new knowledge is less likely to conflict with the established dominant logic and the established mental models within the firm. However, overdependence on exploitation may impede the entrepreneur’s exploration of opportunities arising from paradigm shift. Thus, exploitation may enhance new venture performance and, after a certain point, results in lower new venture performance. March (1991) argues that firms need to balance between activities that contribute to exploration of new knowledge, and capabilities and activities that contribute to exploitation of the existing knowledge or capability base of the firm. Yet, this balancing act may well be beyond the means available to new ventures, so we argue that higher performing new ventures could be those who execute a knowledge strategy with clarity and focus. Hypothesis 4: There is an inverted U‐shaped relationship between exploration and performance; as exploration increases, performance increases up to a point of optimization, after which performance decreases as exploration increases. Hypothesis 5: There is an inverted U‐shaped relationship between exploitation and performance; as exploitation increases, performance increases up to point of optimization, after which performance decreases as exploitation increases. Hypothesis 6: Firms that simultaneously pursue exploration and exploitation will have lower levels of performance than those that focus primarily on one or the other of these strategies.

3. Data and methods Sample We obtained data from a survey conducted in two Shanghai incubators. From the list of student entrepreneurs, we identified the founding entrepreneurs of graduate enterprises as the key informant because only he/she possess well‐rounded knowledge about the topic that we would examine. After conducting face‐to‐face interviews with all confirmed respondents, we obtained a total of 156 completed surveys, representing a response rate of 91.8%. Measures Performance. Performance in terms of market share, revenue growth rate and pre‐tax profit growth rate was measured as the relative change in preceding three years. Therefore, respondents were asked to rate their business growth performance relative to competitors on five‐point scales from very good to very bad (1 =“very good,” 5 = “very bad”)(Cronbach alpha = 0.86). Social capital. Based on Nahapiet & Ghoshal’s (1998) scale, we used three items to measure cognitive dimension of social capital (Cronbach alpha = 0.76), five items to measure trustworthiness, integrity, and benevolent attitudes (Cronbach alpha = 0.73), and three items to measure interpersonal interactions, interpersonal information, and long‐term, stable linkages (Cronbach alpha

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Jun Li and Weihe Gao = 0.75). Knowledge strategies. In line with previous studies on explorative and exploitative learning (Katila & Ahuja 2002), we adopted four items to measure exploration (Cronbach alpha = 0.82) and four items to measure exploitation (Cronbach alpha = 0.76). Control variables. In this study we controlled for potential differences that might exist in gender, age, human capital, family business background, year gap between graduation and start‐up, and industry sector. Hierarchical regression analysis was utilized as the main statistical procedure to test our hypotheses for social capital, knowledge strategies and new venture performance.

4. Results Our results are reported in Tables 1 and 2. Models 1 and 3 in Table 1 test the control variables on knowledge exploration and knowledge exploitation respectively. Models 2 and 4 examine the effects of three dimensions of social capital on exploration and exploitation respectively. Model 2 is significant and contributes 8.6% above variance explained by the control variables in Model 1. Model 4 is also significant and contributes 12.5% above variance explained by the control variables in Model 3. The results in Models 2 and 4 show that the relationships between structural social capital and exploration and between structural social capital and exploitation are insignificant (β=‐.012, p>.05; β=.026, p>.05). Thus, H1 is not supported. In Models 2 and 4, relational social capital was found consistently to be a significant influence on exploration and exploitation respectively (β=.610, p<.001; β=.586, p<.001). Thus, H2 is supported. Moreover, cognitive dimension of social capital was significant in Model 2 (β=‐.652, p<.001) and was not significant in Model 4 (β=‐.313, p>.05). Thus, H3 that proposed that cognitive social capital is negatively related to exploration and is positively related to exploitation is partially supported. Table 1: Results of the hierarchical regression analysis for learning in graduate enterprises Control variables Gender Age Education Entrepreneurship training Prior entrepreneurship experience Family business Year gap between graduation and start‐up Industrial sector Independent variable Cognitive social capital Relational social capital Structural social capital Observations R2 R Square Change F Significance

Explorative learning Model 1

Model 2

Exploitative learning Model 3 Model 4

‐.098 (‐1.259) .431*** (4.511) ‐.326*** (‐3.813) ‐.021 (‐.259) ‐.211* (‐2.579)

‐.051 (‐.676) .344*** (3.657) ‐.247** (‐2.960) .053 (.669) ‐.170* (‐2.165)

‐.071 (‐.857) .099 (.970) .006 (.063) ‐.266** (‐3.095) ‐.052 (‐.600)

‐.049 (‐.623) .014 (.142) .054 (.620) ‐.222** (‐2.687) ‐.041 (‐.500)

‐.043 (‐.561) ‐.120 (‐1.464)

‐.010 (‐.134) ‐.105 (‐1.322)

‐.103 (‐1.263) .021 (.234)

‐.091 (‐1.189) .033 (.391)

‐.116 (‐1.421)

‐.088 (‐1.109)

.034 (.391)

‐.008 (‐.096)

‐.652*** (‐4.106) .610*** (3.847) ‐.012 (‐.126) 140 .321 .086 5.977 .000

‐.313 (‐1.877) .586** (3.525) .026 (.265) 140 .253 .125 4.277 .000

140 .235 .235 5.452 .000

Significant level: *= p<.05; ** = p<.01; *** = p<.001

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140 .128 .128 2.604 .011

Jun Li and Weihe Gao Table 2: Results of the hierarchical regression analysis for new venture performance

New venture performance Model 1 Model 3 Control variables Gender .141 .124 Age .172 .283* Education ‐.038 ‐.157 Entrepreneurship training .084 .188* Prior entrepreneurship experience ‐.017 ‐.064 Family business .098 .122 Year gap between graduation and start‐up .010 ‐.011 Industrial sector .087 .008 Independent variables Explorative learning ‐.304** Exploitative learning .336** Explorative learning squared .219** Exploitative learning squared ‐.258** Explorative x exploitative learning Observations 140 140 R2 .043 .236 R Square Change .043 .029 F .774 3.481 Significance .626 .000

Model 4 .121 .281* ‐.153 .235* ‐.077 .087 .002 .016 ‐.277** .362** .355* ‐.020 ‐.353 140 .251 .014 3.450 .000

Significant level: *= p<.05; ** = p<.01; *** = p<.001 Model 1 in Table 2 is the base model that examines the effects of all control variables on new venture performance. The model is not significant, indicating that none of the control variables has significant effect on new venture performance. In model 2, the coefficient of exploration is negative and significant (β=‐.304, p<.001), and the coefficient for the squared term of exploration is positive and significant (β=.219, p<.01), indicating a U‐shape nonlinear relationship between exploration and new venture performance. Thus, as exploration increases, performance decreases up to a point, after which performance increases as exploration increases. This finding contradicts our hypothesis and thus does not support hypothesis 4. Model 2 also shows that the coefficient of exploitation is positive and significant (β=.336, p<.001), and the coefficient for the squared term of exploitation is negative and significant (β=‐.285, p<.01), indicating an inverted U‐shaped relationship between exploitation and performance that supports hypothesis 5. Thus, as exploitation increases, performance increases up to point, after which performance decreases as exploitation increases. The interaction term of exploration and exploitation is negatively related to new venture performance but is not significant (β=‐.353, p>.05), thus hypothesis 6 is not supported.

5. Conclusion The results of this study advance graduate entrepreneurship literature in several ways. First, we find that relational social capital increases exploitation and exploration. Thus, when there was trust among network members, they were more willing to engage in the exchange of information, which in turn enhanced the opportunity for exploitation as well as exploration. Our results also show that cognitive social capital has negative relationship to knowledge exploration, suggesting that too in‐grained frame of sense‐making between network members could lead to lock‐in and ‘group think’ that inhibits exploration. Second, our finding shows that the relationship between exploration and new venture performance is a U‐shaped (instead of an inverted U‐shaped) curve. This suggests that explorative activities are inherently risky and hugely uncertain and that they are less likely to contribute to shorter‐term performance when knowledge explorative activities are lack of focus and fairly a hit and miss affair. However, as disparate explicit knowledge is gradually assimilated and is converted into the new venture’s capabilities, the disadvantage of exploration could reverse. Third, we find that exploitation has a curvilinear (inverted U‐shaped) relationship for new venture performance, suggesting an increase in the disadvantages of exploitation after a certain point.

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References Afuah, A. 2003. Innovation Management: Strategies, Implementation, and Profits. 2nd Edition. New York and Oxford, Oxford University Press. Atuahene‐Gima, K. and Murray, J.Y. (2007). Exploratory and Exploitative Learning in New Product Development: A Social Capital Perspective on New Technology Ventures in China. Journal of International Marketing: Vol. 15, No. 2, pp. 1‐29. Barney JB. 1991. Firm resources and sustained competitive advantage. Journal of Management 17(1): 99–120. Cohen, W.M. and Levinthal, D.A. (1990) ‘Absorptive capacity: a new perspective on learning and innovation’, Administrative Science Quarterly, 35, pp.128‐152. Granovetter, M. (1973) ‘The Strength of Weak Ties’, American Journal of Sociology 78: 1360–80. Jack, S. 2005. The role, use and activation of strong and weak ties: a qualitative analysis. Journal of Management Studies, vol 42, no. 6, pp. 1233‐1260. March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Nahapiet, Janine and Sumantra Ghoshal (1998), “Social Capital, Intellectual Capital, and the Organizational Advantage,” Academy of Management Review, 23 (2), 242–66. Yli‐Renko, H., Autio, E. and Sapienza, H.J. 2001. Social capital, knowledge acquisition, and knowledge exploitation in young technology‐based firms. Strategic Management Journal 22: 587‐613.

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For Strategic Environmental Sustainability not to be Lost in Translation(s) Anymore Sophie Liénart and Annick Castiaux University of Namur, Namur, Belgium sophie.lienart@unamur.be annick.castiaux@unamur.be Abstract: The increasing scale of environmental externalities related to technological firms’ activities shows the limits of today’s economic system and development path. It forces these firms to integrate environmental sustainability concerns not only in their operations but also strategically in their business processes, to ensure legitimacy and the protection of their competitive advantage. However, a strategic implementation of environmentally‐oriented initiatives remains difficult given the poor understanding of human and non‐human actors’ interactions taking place during that process. Environmental sustainability strategy development and implementation can be seen as an organisational process of change. In this paper, we propose a conceptual model that combines some key elements of Callon and Latour’s actor‐ network theory and Lewin’s model of change. On the one hand, actor‐network theory proposes a sociology of science in which technology is not to be seen as an autonomous artefact. Therefore, the strategic integration of environmental sustainability issues in technological business processes is understood as a co‐constitution and transformation of artefacts, actors and practices within the firm. It focuses on how socio‐technical actor‐networks are created in the organisation through a process of translation(s) ‐ i.e. interpretation(s) that every actor makes of other actors present in the network. On the other hand, Lewin’s three‐step model of change highlights some useful stages (unfreeze‐move‐refreeze) that can be followed by practitioners to successfully plan, design and implement change in a structured way, as well as keep track of the achievements attained. We show that their complementary aspects of emergent and planned approaches to environmental sustainability change ensure a better understanding of actors’ interactions taking place in the technological organisation. While actor‐network theory reinforces Lewin’s model in a dynamic and iterative way, Lewin’s model brings some structure to the numerous translation processes taking place in the organisation and hence, eases the transmission of actor‐network theory perspectives to the practitioners.

Keywords: environmental sustainability, technological innovation process, organisational change process, actor‐network theory, Lewin’s three‐step model of change

1. Introduction For two decades, technological firms have been facing increased pressure from consumers, regulators and business partners to demonstrate more responsible behaviours. The growing scale of environmental externalities caused by the firm’s activities shows the limits of today’s economic system and development path (Freeman 1996). It forces firms to integrate environmental sustainability (ES) concerns strategically in their business processes. More specifically, the development of environmentally sustainable innovations ‐ i.e. the integration of ES issues in the innovation process of technological products ‐ has recently received a growing deal of attention from the business and the academic worlds. This has emerged as both a key challenge and opportunity for firms as it may enhance the protection of their competitive advantage, confer legitimacy and show environmental responsibility in an environment of regulatory and consumer sensitisation (Porter and Kramer 2006). However, if a change towards a more environmental‐friendly behaviour is acknowledged, strategic implementation remains difficult. This is partly due to the poor understanding of interactions between human and non‐human actors, taking place during that process. In this paper, we propose a conceptual model that combines Callon and Latour’s actor‐network theory (ANT) and Lewin’s model of change. We show that their complementary aspects ensure a better understanding of actors’ interactions taking place in the technological organisation, when such a transformational process towards the adoption of ES practices is required. This article is organised as follows. First, we present ES strategy as an organisational change process. Then, we show that both ANT and Lewin’s change model serve as useful analytical frameworks to explain this change process. Next, we present a conceptual model that maps the key elements of both models. Finally, we discuss the complementary aspects of these theories as well as the limitations and future improvements considered for our model.

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2. Environmental sustainability strategy as organisational change process After having defined ES, we show how ES strategy development and implementation can be seen as an organisational change process.

2.1 Defining environmental sustainability According to Tukker (2008) sustainability is a large and multi‐interpretable notion. Originating in the 1980’s, the term ‘sustainable development’ was introduced as a new paradigm with the publication of ‘Our common future’, the final report of the Bruntland Commission, where it is defined as a development that meets the needs of the present without compromising the ability of future generations to meet their own needs (Brundtland Commission 1987, p.54). Numerous models of sustainability have been developed and conceptualised in academic literature. The famous triple bottom line model (Elkington 1994) highlights the need for balance between sustainable environmental practices and social equity for the stakeholders whilst ensuring economic imperatives. For the purpose of this paper, we will focus on the environmental aspect of sustainable development. Morelli defines it as a condition of balance, resilience and interconnectedness that allows human society to satisfy its needs while neither exceeding the capacity of its supporting ecosystems to continue to regenerate the services necessary to meet those needs nor by our actions diminishing biological diversity (2011, p.24). ES is a stakeholder‐oriented concept extending beyond the boundaries of the organisation. It is driven by the firm’s acknowledgement that its business activities have a non‐negligible impact on the environment. This impact needs to be taken into account by truly integrating ES concerns into the organisation’s products and strategy (Maon et al. 2009).

2.2 Organisational change process ES strategy development and implementation can be considered as an organisational change process (Verhulst and Boks 2012). Two main approaches have been highlighted in the literature: the planned and the emergent approach to change. The planned approach to change foresees the difference between the current and the desired state as well as the means to reach that desired state, going from strategy formulation, to strategy implementation and then strategy outcome. There isn’t any significant disruption coming from factors internal or external to the organisation. Several models of planned change can be helpful as reference points for thinking about how to carry out change (e.g. Lewin 1947, Kotter 1996, Cameron and Green 2012). But this planned approach to change shows some limits. First, it ignores the complex and dynamic nature of environmental and organisational processes. Second, it doesn’t address the continuous need for structural adaptations, necessary to keep realigning in a rapidly changing environment. Third, it ignores organisational conflicts and politics among the parties involved in the change process. The emergent approach to change stresses the developing and unpredictable nature of change. It views change as a process that unfolds through the interplay of multiple variables and participants within the organisation (Blomme 2012). Change is seen as an ongoing process characterised by unforeseen events, disruptions and opportunities that emerge within that period and allow for alignment and adjustments to a turbulent environment (Burnes 2004a). Change management is a complex process consisting of analyzing the internal and external environment, formulating a change plan and implementing it. But the complexity of the issues coupled with the diversity of individuals involved pose a serious problem to the change management attempts. In this paper, we show that the planned approach to change serves as a framework that both structure and influence the emergent approach(es) to the corporate ES shift. The need for change is mainly linked to the changes happening in the external environment, which clearly impact the organisation. Those pressures determine the emergent actions taken by various agents in the organisational system. Managers initiate change when they assess a gap between what the external

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Sophie Liénart and Annick Castiaux environment requires to be competitive and what the organisation can offer (Longo 2011a).The firm shows its intent to move from a current to a new state where its business concerns are better aligned with its environmental concerns. It therefore shows its ability to identify and manage agents’ environmental expectations. ES also involves learning skills over time. To ensure that the change is beneficial and supported by appropriate mechanisms, the organisation needs to understand the specific industrial context in which it operates and make sure that it encounters agents’ expectations (Burnes 2004a). As pointed by Mitleton‐Kelly (2003), in order to react most appropriately, managers must understand and show awareness of both the context and expectations as well as recognise that any change they implement will in turn have an impact and shape the environment. Therefore, the development of environmentally‐oriented practices, can entail evolutionary and recursive activity that acts on and reacts to and with the business environment (Maon et al. 2009, p.72).

3. Relevant analytical frameworks for environmental sustainable change In this section, we present two theoretical frameworks: the actor‐network theory and Lewin’s three‐step change model. We then show the relevance of those models in a context of change and explain how they view the development and implementation of an ES strategy in a technological organisation.

3.1 Actor‐network theory 3.1.1 What is actor‐network theory? Actor‐network theory is part of the sociology of technology approach developed in the sixties, stating that science can be studied from a sociological point of view. ANT was pioneered in the 1980s by the French scholars Michel Callon and Bruno Latour (Callon and Latour 1981, Callon 1986). Three main principles characterise ANT. First of all, ANT shows that the role of objects shouldn’t be underestimated as they shape the people and other objects around them. This means that there is no distinction between society (i.e. actors), nature (i.e. environment) and technology. An ‘actor’ is defined in its performance as a ‘figurehead’ or a more or less ‘opaque’ black‐box which stands for, conceals, defines, holds in place, mobilizes and draws on, a set of juxtaposed bits and pieces (Law 1994, p.101). Actors are people, organisations and objects. Second, ANT argues that technology is not to be seen as a mere autonomous artefact. There is a social shaping of technology ‐ i.e. a situated process of co‐evolution (Callon 1986) and co‐production (Latour 1991) of human and non‐human actors. Therefore, the integration of ES issues in the technological innovation process is understood as a dynamic co‐constitution and transformation of artefacts, actors and practices within the firm. Finally, people and objects interact with each other and create actor‐networks. Callon (1987, p.93) defines an actor‐network as follows: An actor‐network is simultaneously an actor whose activity is networking heterogeneous elements and a network that is able to redefine and transform what it is made of. ANT focuses on how socio‐technical networks are created, structured and maintained. It is the interplay between different actors’ forces that will define the configuration of actors in an actor‐network (Cordella and Shaikh 2006). While interplaying with the actor‐network, actors negotiate their forces in a process of translation(s) – i.e. interpretation(s) that every actor makes of other actors present in the network. As reported by Callon and Latour (1981, p.279), by translation we understand all the negotiations, intrigues, calculations, acts of persuasion and violence thanks to which an actor or force takes, or causes, to be conferred to itself, authority to speak or act on behalf of another actor or force. Four translation steps are necessary to understand the constitution and functioning of an actor‐network (Callon 1986): ‘problematisation’, ‘interessement’, ‘enrolment’ and ‘mobilisation’. We detail them in the next section in the light of the specific ES context. 3.1.2 ANT translation process in the environmental sustainability context ANT appears as a useful instrument for analyzing the integration of ES requirements within a technological corporation. An organisation can be seen as a giant network of actors in which a particular translation process takes place when the firm needs to strategically integrate ES concerns (Blomme 2012). This actor‐network

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Sophie Liénart and Annick Castiaux needs to find a new ‘sustainability’ stability. As pointed by Benn and Baker (2009, p.388) sustainability draws on the interrelatedness of technological, social, political, and ecological systems and sub‐system (…) the relationship between human and ecological systems should be reconceptualised in terms of a dynamic co‐ evolution towards sustainability. Hereunder, we analyse the four steps of the process of translation in this ES context. The first step, ‘problematisation’, consists in becoming indispensable. A focal actor raises an issue, and dealing with this issue requires the involvement of several other actors, whose roles and relationships configure an initial problem‐solving network (Tatnall and Burgess 2002). The organisation develops an opinion as to whether the focal actor ‐ ES concerns ‐ is actually of importance to the other actors and should be accepted, or rejected. The problem is re‐defined in terms of solutions offered by the adoption of an ES strategy which then attempts to establish itself as an ‘obligatory passage point’ (OPP) (Callon 1986). It can be thought of as the narrow end of a funnel that channels all interests in one direction (Blomme 2012). It thereby becomes a necessary element for the constitution of a network as it mediates all the interactions between the actors in this network. If accepted, this OPP will create a ‘black box’ where the translation process will run automatically and isn’t renegotiated anymore (e.g. the ISO 14001 norm can be considered as a black‐boxed actor network (Bengtsson and gerfalk 2011)). The second step, ‘interessement’, refers to the art of getting actors interested. The aim is to convince other actors in the corporate network to accept the definition of ES strategy, whose identity has been consolidated. According to Akrich et al. (2002a), the environmentally‐oriented technological product innovation would spread out thanks to its intrinsic environmental and technological properties. Nevertheless its destiny also depends on the active participation of those who want to advance it. Therefore ‘interessement’ allows for understanding how a ‘sustainable’ innovation is adopted and how it spreads to become a success. The socio‐ technical analysis underlines that this adoption is the result of an adaptation, which itself, generally is the result of a collective development and thus of an interessement process, getting bigger and bigger in the company (Akrich et al. 2002b). The third step, ‘enrolment’, represents a successful interessement. Roles are specified among actors, and alliances between them are established. The focal actor (i.e. the need for ES) has enrolled others to believe and support it (Latour 1987). Actors that are less prescribed get more easily translated into the interest of others that are more firmly inscribed and prescribed. In this way, ANT allows studying power relationships through examining how human and non‐human actors interact and negotiate. ‘Mobilisation’ is the last step. Allies are mobilised to represent the group effectively. Some actors are used as (new) initiators and become delegates or spokespersons for the focal actor (Tatnall 2010). Rice (2011, p.35) explains: CO2 initially acted as a spokesperson for sustainability, like a union representative on behalf of its members. Mobilisation has gone further; CO2 not only speaks for others, it causes others to act on its behalf. In our case, the content and probability of success of the environmentally‐oriented sustainable technological product innovation are to be found in the choice of the spokesmen (i.e. key actors and management) who will negotiate to transform and shape the sustainable technological product innovation to make it successful ‐ i.e. make it match with business operations and strategy. Through those steps, we get to a network of links between actors, known as the actor‐network (Callon et al. 1985). Strategic ES initiatives are successful if they stabilise in an acceptable compromise between actors. Several negotiations and iterations in the implementation of the ES strategy may be needed to get to that point. Indeed, the beliefs but also the identities of the actors involved in the actor‐network may fluctuate if there is a controversy ‐ i.e. if the representativeness and legitimacy of the spokesmen is challenged (Callon 1986). Actors may defend different perspectives and constitute other ‘competing’ networks that are intertwined and contribute to the development of a controversy (Daroit and Nascimento 2009). As reported by Stubbs (2000) this fits well with the ES pressures the organisation suffer from internal and external stakeholders and hence, the need to identify important actors.

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3.2 Lewin’s change model Kurt Lewin is the intellectual father of the planned approach to change that was developed in the late 1940s. Through his work on field theory, group dynamics, action research and the three‐step model, this German psychologist and social scientist contributed to our understanding of individual and group behaviour and the role they play in organisations and society (Burnes 2004b). Lewin’s cornerstone contribution to organisational change is the three‐step model (unfreeze‐move‐refreeze) he developed in 1947. This model is still considered as extremely relevant by numerous scholars and practitioners as it enables businesses to successfully plan, design and implement change in a structured way. Moreover, it helps managers keep track of the achievements attained. Hereafter, we present these three steps and show how they help to structure the development and implementation of an ES strategy. The ‘unfreeze’ step consists in creating the motivation for change. The organisation must understand that the existing way of operating cannot continue and that there is a need for change. Therefore, the existing corporate status quo, which is supported by a complex field of driving and restraining forces, needs to be broken down. Old behaviours, values and beliefs need to be unlearnt to allow for building a new way of operating (Burnes 2004b). In our case, unlearning ‘gray’ behaviour in favour of a more ‘green’ responsible behaviour is critical to allow for the development of an ES orientation. This may provoke strong resistance to change among those that believe ‐ i.e. that ES may threaten the stability of the company that will lose sight of its core values (Maon et al. 2009). Managers must understand those doubts and concerns. The ‘move’ step consists in developing and implementing change towards the adoption of ES practices. The organisation is guided towards a new set of assumptions. When people understand how these changes may benefit them, they are encouraged to act in ways that support the new direction and integrate ES concerns in the innovation process of technological products. This may take some time but effective communication is central to move successfully through the change process. The last ‘refreezing’ step consists in institutionalizing ES change in the organisation in a stabilised way. In our case, it corresponds to the actions taken at a strategic level to ensure the alignment of ES considerations with the business strategy. This is an important step to ensure that the adoption of ES practices won’t be short‐ lived. Moreover, it creates organisational confidence, necessary to tackle the next ES initiative effectively.

4. Conceptual model of organisational change In this section, we propose a conceptual model of change that maps the key elements of the two models presented above: ANT translation processes and Lewin’s three‐step change model (cfr. figure 1). Maon et al. (2009) include a fourth ‘sensitize’ step to Lewin’s model. It represents the ES awareness that needs to take place in the organisation before the actual change process can take place. We argue that our model brings light onto the organisational change that constitutes the development and implementation of an ES strategy.

Figure 1: Proposed conceptual model of organisational change ANT‐ Lewin

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Sophie Liénart and Annick Castiaux The technological organisation ‐ represented by the dotted rectangle ‐ can be seen as a giant network of actors composed of several smaller actor‐networks, consisting of non‐human and human actors (internal to the organisation here, and represented by the decision and implementation levels). Different translation processes take place in those actor‐networks as the firm evolves through the different stages of change required by the strategic integration of ES considerations. By mapping both models, we thus show that the planned approach to change proposed by Lewin serves as a framework that structures and influences the emergent approaches to change developed in each actor‐network. The arrows represent the main internal and external information and communication flows as they should occur ideally in the organisation. The organisation is represented by a dotted rectangle as it interacts with the outside world and adjusts to external pressures by implementing change processes. Arrowed circles represent translation nodes taking place in the actor‐networks at different corporate levels. Note that little a’s and b’s refer to the temporal dependence and succession of translation processes. 1a.Translation of external pressures and expectations in a preliminary view of sustainability by the managers; 1b.Translation of this preliminary view in a perspective related to work; 2a.Translation of the preliminary view in an ES vision and objectives at the corporate level; 2b.Translation of objectives into an operational view of ES; 3a.Translation of the operational view of ES into concrete actions taken at the different steps of the technological innovation process. Environmentally‐oriented pilot projects are developed; 3b.Translation of environmental sustainable initiatives with corporate objectives. At this point, major controversies may appear, requesting a re‐appraisal of the way ES initiatives should be integrated in the technological products; 4a.Translation of environmental sustainable practices into sustainable standards; 4b.Translation of tangible environmental sustainable results into an environmental sustainable internal and external communication policy.

5. Discussion Interesting insights can be drawn from the interlinkage of well‐established organisational theories coming from different scientific disciplines and having complementary visions of the way to approach change (Sorge and van Witteloostuijn 2004). Despite critiques to Lewin’s planned model of change, Burnes (2004b) explains that these are based on a narrow interpretation of his work that often disregards the field theory, group dynamics and action research parts. Lewin was very much conscious that change was a complex, often slow and iterative process, depending on the conditions and intricate driving and resisting forces at stake in the current corporate situation. What is more, Lewin argued that change could only take place if a need for change was acknowledged by all those concerned. Change could thus be initiated from the top management level but needs the active participation of all. This model is still widely used by practitioners and by organisational development consultants. To ‘unfreeze’ an organisational system, the agents need to disconfirm current attitudes or behaviours. Afterwards, barriers to change and threats caused by past failures need to be reduced in order to create a climate of psychological safety, favourable to change. Several initiatives can then be taken by the practitioners to lead the ‘change’ step. According to Harwood (2008) after having established a sense of urgency, the agents need to form a powerful leading coalition, communicate a vision and then empower others to act on this vision. New approaches are then institutionalised by planning for and creating short‐term wins. Finally, a variety of strategies may be adopted to ‘refreeze’ and reinforce the organisational change process, such as creating new rules and developing new reward and regulations schemes in order to maximize the desired behaviour of both the staff and the employees. In our view, ANT and Lewin’s change model are complementary. On the one hand, ANT reinforces Lewin’s model in a dynamic and iterative way. It highlights the interactions taking place between actors at different corporate levels and at different moments in time as well as the interpretations each actor make of the others present in its actor‐network. On the other hand, Lewin’s model, together with the additional ‘sensitize’ step presented in this paper, can be seen as a prism that helps managers structure the ‐sometimes obscure‐

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Sophie Liénart and Annick Castiaux translation processes taking place in the organisation. Therefore, this model can ease the transmission of ANT perspectives to the practitioners. The current limitations of our conceptual model are twofold. First, it doesn’t make any reference to the particular context of change in which the organisation evolves. Second, it does not refer to any key actors to be targeted in the company to ensure the successful adoption of environmentally sustainable practices. According to Longo (2011b), business leaders should strive to identify the target groups the most directly concerned by the change implementation process although getting the full support of the organisation’s staff is of paramount importance to successfully achieve change. However, Crane (2000) suggests that greening an organisation doesn’t require a commitment from all the employees. Through his interdependency network perspective, Newton (2002) argues that it may be more profitable to research the minimal configuration of interdependent networks that support greening processes. An empirical study should be conducted to refine and validate the model in these regards.

6. Conclusion In this paper, we have developed a conceptual model that can be used as a framework to study changes due to the integration of ES requirements in an organisation. This model combines two views. On the one hand, we have mobilized the three‐step change model proposed by Lewin and updated by Maon et al. (2009); on the other hand, we have used ANT to take into account the dynamics such changes require from stakeholders. Our model put into evidence “networks” of interactions between different actors, occurring at different corporate levels and different steps of the organisational change process. Those networks contribute to a progressive change of the whole organisation, where all concerned stakeholders understand their possible contribution, thanks to a relevant “translation” of the organisation’s new vision at the stakeholders’ level. Future research should focus on an operationalisation of the model. Empirical research could check if the various processes described in the model happen; if yes, how they happen, and how they contribute to an integration of ES in an organisation.

Acknowledgements The authors would like to thank the reviewers, as well as Dr. Julie Hermans (University of Namur) and Pr. Dr. Valérie Swaen (Catholic University of Louvain) for their valuable feedback on earlier versions of this paper.

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Social Responsibility Like aim of Innovation Activity in Information and Communication Industry: The Spanish Case María Jesús Luengo1, Teresa Areitio2 and María Obeso3 1 Department of Management Evaluation and Business Innovation, School of Business Studies, University of the Basque Country, Bilbao, SPAIN 2 Department of Industrial Economy, School of Business Studies, University of Basque Country, Bilbao, SPAIN 3 Department of Business Administration, Faculty of Business and Economics, University of Cantabria, Santander, SPAIN mariajesus.luengo@ehu.es teresa.areitio@ehu.es maria.obeso@unican.es Abstract: In the new knowledge economy, innovation and social responsibility, environmental and health care in organizations are fundamental tools in order to obtain competitive advantages and sustainability. In this scenario, we present an interesting study about how Spanish enterprises in information and communication industry linked innovative activity and social responsibility although innovation investment is not reflected in the turnover. This study has been realized using data obtained by Spanish National Institute of Statistics (INE). First, we present a short bibliographic review about environmental and health highlighting their importance. In this way, we want to identify how the generation of innovation strategies related to environment and healthy are important in Spanish information and communication industry although they don´t be reflected in turnover. In the next section, we describe methodology, database and variables. In the research, we present an empirical study using confirmatory factor analysis technique (Structural Equations Model). We use data extracted by Spanish National Institute of Statistics in the annual questionnaire about innovation in enterprises in the year 2010. This questionnaire is sent to the Spanish organizations with R+D+ i activities. Then we select different types of variables (investment, result and aims), all of them related to the topic. After that the results are exposed with a short discussion about factors identification, exogenous variables and the relationship established between them. From this relationship we conclude that innovation aims and social responsibility is not influenced by turnover or investment needs. Finally we expose the principal findings and the implications of the research, and we propose future relevant studies. Although our work is in progress yet, we hope that it will be useful to some agents: first, academy area, because we present a unique research with objective data of enterprises; and second, this research will be useful to the private enterprises because it shows the principal factors in strategies related to environment and health. Keywords: innovation, environment, health of people, Spanish firms, information and communication industry, SEM

1. Introduction We live in a society based on knowledge, where creation and cooperation between agents are the center of its social and economic activity (Ayestaran & Gomez, 2010). In this way, we are in an innovative economy where organizations develop values in order to promote ideas and challenges (aims of innovation) (Ortiz, 2012) that influence in the competitiveness and sustainability of them. Whereas some years ago countries interested in achieve an environment related to an economy of excellence need physical infrastructure, industry and efficient services, now in the welfare society is needed add learning infrastructure with the aim of manage knowledge (Luengo, 2011). In this scenario, we present a study where we analyze high technology enterprises in information and communication industry, characterized by knowledge and innovation intensive, and they focus their aims of innovation in social responsibility (improve environment and people healthy) because they know that benefits from this social responsibility have intangible character and influence in their continuity and competitiveness. With the aim of identify the aims linked with social responsibility regardless their repercussion in the turnover, we present a confirmatory factor analysis applying structural’s equations, analyzing results and conclusions. In short, the highlight aim is to demonstrate that enterprises in information and communication industry in Spain establish their aims of innovation related to improve environmental and health of people, without study their consequences in the turnover.

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The paper is structured as follows: first, we realize a bibliographic review where we explain the highlight of this study and build the theoretical framework. Also in this section, we present the hypothesis of this study and amplify the aim of the study. In the next section, we expose the methodology used in the analysis and describe the sample. In the fourth section we present the proposed model, its verification and the results obtained explaining them. And finally, we expose conclusions, the principal contributions in the scholar area and industry, the study highlights, limitations and future research possibilities derived by this analysis.

2. Theoretical background 2.1 Innovation Entrepreneurial competitiveness should be compatible with welfare social, environmental sustainability and reduction of territorial imbalance (Caravaca et al., 2005), and that implies changes in investments and technological transformations like a consequence of innovation need linked with the principal factors of national society system (Trigo et al., 1991). In addition, one of the most highlight font in order to obtain competitive and sustainable territorial (that is to say, sustainability competitive advantage) is knowledge; and more concretely, economic effects derived by the intelligent use of knowledge (Mulet, 2005) because through this use countries achieve more wealth and competitiveness producing better and cheaper. This concept is each and every day more frequently and following Mendez (2002), an effort in innovation is necessary like a key element in order to improve competitiveness in organizations and stimulate territorial development. As a result, knowledge is essential in order to promote sustainable development in regions because it motivates competitiveness without influence in the turnover. For example, knowledge could be stimulate reduce costs using better resources. We focus our analysis on innovation and more concretely, on social innovation because all innovations are novelties in economic and social sphere (Formichella, 2005). In this way, following Schumpeter (1934: 84) “if, instead of quantities of factors, we vary the form of the function, we have an innovation (…) Therefore, we will simply define innovation as the setting up of a new production function”, thus until society recognize and accept the innovation, it is not valid. Schumpeter´s definition has been amplified to organization and management area because it is defined as “production or adoption, assimilation and exploitation of value‐ added novelty in economic and social spheres; renewal and enlargement of products, services and markets; development of new methods of production, and establishment of new management systems” (Crossan & Apaydin, 2009: 1155). People are very important in innovation activity because society (composed by people) must to accept the new changes and challenges, therefore the process requires engagement people working in teams and dedicating efforts to the activity (Acemoglu and Pishke, 1999). Following Un et al. (2010) collaborations with suppliers, competitors, universities and clients linked with R&D influence on product innovative activity in organizations.

2.2 Social responsibility Corporate social responsibility is an interesting part of organizations. Some years ago, Nobel Prize of Economics in 1976 Milton Friedman highlighted in one of his papers published in the New York Times that the social responsibility is more linked with people than organizations (Friedman, 1970). This viewpoint is based in the concept narcissistic enterprise proposed by Kliksberg in 2004 hence social responsibility in organizations could be transform in a guarantee responsibility with respect to their environment because they are defined like a group of people and communities adapted to the environmental changes (following authors like for example Senge or Nonaka and Takeuchi). As consequently, like organizations are composed by people, people should decide what part of the benefit will be dedicated to activities related to territorial sustainability. That is to say, they decide the level of social responsibility. In this way, corporate social responsibility is defined like a volunteer integration of people, social and environmental concerns in commercial operations and the relationship between people and organizations (COM, 2001). There are more definitions, but all of them have in common their dynamic characteristics:

Integral, because it is composed by different dimensions of the organizations

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Gradual, because it is the way of the excellence

Proportional, because the power and the influence in the environment are related to the size of organization.

Besides this, social, economic, legal and institutional environment influence enterprises activity and, in consequence, their social responsibility. Then organizations interested in social responsibility activity should be analyze some environmental characteristics like globalization, demands derived by social, economic and environmental problems, new ways of work, the increase of the enterprises influence, the creation of value and the technological innovation (Reyno, 2006). Social responsibility renews the enterprise concept where in order to obtain benefits for their stakeholders they include economic, social and environmental sustainability. Then economic increasing and competitiveness are increasing integrating economic objectives with social and environmental worries. Then we can talk about the responsible enterprises, because social responsibility is effected when firms satisfying the expectations of stakeholders (Grupo de Trabajo nº 21, 2002). Organizations that reach economic benefits through products and services improving life quality of clients, workers, suppliers, local communities and other stakeholders, work in order to achieve more value for the society. In fact, experience acquired investing in technologies and in friendly practices could be improve enterprises competitiveness (Alfaya and Blasco, 2002).

2.3 Aims and hypothesis In order to realize our study, we choose information and communication industry that it is considered like high technology and with innovative character. It presents a sustainable growth and in general this sector is composed by micro, small and medium enterprises (Sieber & Valor, 2010). In addition, these enterprises are considered like organizations knowledge intensive (Aguer, 2002). We choose the case of Spain because this country is experiencing a difficult economic situation (Suarez, 2010), and innovation could be help its government in order to improve its results. Then enterprises in this sector are characterized by network operate in hypercompetitive environments and intangibles are essential resources (Ordoñez de Pablos, 2002). At the same time, they include aims of innovation for their continuity and contribute to different areas related to sustainable territorial in the communities that they are located. In order to define constructs Aims of innovation in order to improve environment and health and Expenditure in innovation in order to improve environment and health, we use indicators used in the questionnaire about innovation in Spain in 2010 (INE, 2012). Analyzing this questionnaire, the following hypotheses are enunciated: Hypothesis 1 (H.1): Indicators linked to the opportunity of determine aims of innovations in order to use less resources or energy by unit, reduce their environmental impact, improve health and security of people and achieve formal environmental, health and security requirements are reflected in the construct Aims of innovation in order to improve environment and health. Hypothesis 2 (H.2): Indicators related to expenses designated to innovation dedicated to control and care environmental and health determine the construct Expenditure in innovation in order to improve environment and health. The construct Aims of innovation in order to improve environment and health should not compromise organization´s profitability (Alfaro, 2007), therefore the following hypothesis is defined: Hypothesis 3 (H.3): Aims of innovation dedicated to environmental and health of people are not moderating variables of expenditures realized by the organizations. Finally, we propose the relationship between aims of innovative activity linked to environmental and health of people, and the tangible results in enterprises measured using the turnover (Alfaya and Blasco, 2002). Therefore the following hypothesis has been presented: Hypothesis 4 (H.4): The aims of innovation linked with environment and health of people are not moderating variables of turnover obtained by the organization.

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3. Research methodology 3.1 Data base and sample Database is composed by results of the annual questionnaire about innovation in enterprises in the years 2008 and 2010 realized by the Spanish National Statistics Institute (INE). More concretely, our sample includes enterprises in the sector Information and Communication Industry. This questionnaire is included in European Union statistics and it is realized following the methodological lines defined in Oslo Manual in 2002. The directory of enterprises is composed by firms with innovative potential and they have been selected by random by DIRCE (central directory of enterprises). Sample is composed by 1317 Spanish enterprises in the followings codes of National Classification of Economic Activities (CNAE): code 60, Programming and broadcasting activities, code 61 Telecommunications, code 62 Computer programming, consultancy and related activities and code 63, Information service activities. This sample, for a confidence interval about 95 per cent, the margin of error is 2,65 per cent, therefore the model REM (structural equations) is feasible (Ruiz et al., 2010).

3.2 Description of variables From the information of constructs defined in the questionnaire and their explained variables, we have defined three constructs ad hoc for our analysis:

Aims of innovation in order to improve environmental and health of people. This construct explains the opportunity of propose this types of objectives in the decision making process.

Innovation expenditure in order to improve environmental and health. This construct includes expenditures destined to these activities.

Turnover. This construct measured the results. 1

Indicators about expenditures and turnover measure expenses and incomes and they are formative variables , while indicators about aims of innovation are instrumented using a Likert scale between 1 and 4 and they have reflective character 2 . Therefore all of endogenous variables are quantitative, so we can apply SEM model based on correlations and covariance between variables in each equation and latent explained variables. This approach follows the procedure suggested by Williams et al. (1989) in order to reduce implicit effects realized by interviewees and the problem of common variance. Codes, constructs and variables are described on Table 1. Table 1: Summary about the relationships and the codes Construct

Explanatory variable

Code

Description

Code

Description

OBRS

Aims of innovation in order to improve environmental and heatlh

E6O9

Reduce inputs by unit

E6O10

Reduce energy by unit

E6O14

Reduce environmental impact

E6O15

Improve heatlh and safety

E6O16

Satisfy requirements about environmental, health and safety rules

GI6

Control and care environment

GI8

Protect and improve human health

GI10

Education

A7110

Turnover in 2010

GINRS

Innovation expenditure in order to improve environmental and health

CNEM

Turnover

Formative variables are causal variables linked with the theoretical latent construct (Mackenzie et al., 2005). Effect variables are linked with the non‐observed construct that explaining that we observe. (Fornell, 1982; Bollen & Lennox, 1991; Chin, 1998)

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3.3 Research method We propose an empirical analysis about sustainable of indicators in order to explain the constructs, and also we want to demonstrate the inexistent causal independence relationship between the construct about the aims and the constructs about incomes and expenses using Structural Equation Modeling (SEM). In this sense, they estimate structural parameters and also they provide complete information which means that it represents a theoretical relationship cause‐effect (Page, 1990) specified in the subjacent theory function. Accordingly to Bizquerra (1989) the principal advantage is that a verbal theory is converted to a mathematical model. For this point, this model is also called confirmatory analysis, because its highlight is to confirm the relationships using the sample analysis Jöreskog, 1979).Accordingly, we use AMOS statistical pack, version 20 applying SLS method (scale‐free leas squares), because the model does not present multivariate normality and there is a lack of correlation between formative variables linked with the construct Expenditures and we cannot use ML (maximum likelihood) like ADF (asymptotically distribution free).

4. Results and interpretation 4.1 Specifying and identifying the model, and estimating parameters The model has 31 degrees of freedom (df) and it is recursive. Besides this and following Batista and Coenders (2000), the model is identified. Related to the estimation of parameters, reflective variables have an intensive correlation and they present high levels of internal consistency and fiability, because all of them are the reflection of a same subjacent construct. In the case of our analysis, the variables linked with the construct Aims of innovation in order to improve environment and health have a Cronbach alpha around 0,8, that is to say, more than the level of fiability 0,7 (Nunnally, 1978). Also there is a high level of correlation between them with a signification around 0,01, therefore we can conclude that the estimation of parameters is adequate (see Table 3). Table 2: Correlations between varibles in reflective construct Correlations Variable

E6O9

E6O10

E6O14

E6O15

E6O16

E6O9

‐

E6O10

0,791**

‐

E6O14

0,473**

0,565**

‐

E6O15

0,457**

0,507**

0,704**

‐

E6O16

0,444**

0,494**

0,703**

0,799**

** The correlation is significant to level 0,01 (bilateral)

4.2 Model evaluation Confirmatory factor analysis explains the correlation between constructs ant the association between each of them and their observed variables through the factor loadings. In our analysis, all of the observed variables are between 0,5 and 1 and their errors are not significant (Schumacker and Lomax, 2004). As a result, the path diagram proposed is accepted (see Table 4). On the other hand, there is not causal relationship between the constructs proposed (see Figure 2). Table 3: Standardized regression weights E6O9 E6O10 E6O14 E6O15 E6O16 GINRS GINRS GINRS CNEM

<‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐ <‐‐‐

OBRS OBRS OBRS OBRS OBRS GI6 GI8 GI10 A7110

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Estimate 0,67 0,74 0,81 0,82 0,81 0,54 0,61 0,58 1

María Jesús Luengo, Teresa Areitio and María Obeso

Figure 1: Measurements of adjustment in global model and path‐diagram About the model adjustment, global adjustment is perfect if there is a perfect correspondence between the matrix reproduced by the model and matrix of observations. In this way, we differentiate three types of measurements in the global adjustment:

Absolute measurements of adjustment. They establish the measurement of model predict initial matrix of data. Generally, measurements accepted after apply SLS method are X2 and P value therefore the adjustment of the model has quality. At the same time, measurements introduced by Jöreskorg and Sörbom (2001) are less sensible to the sample size, like RMR index (root mean square residual) and a GFI index (goodness of fit index). Besides this, the adjustment has a high quality of absolute measurements.

Measurements increasing adjustment or comparative. They are based on the comparison between the proposed model and the null model, because in this last there is not relationship between variables (Hu and Bentler, 1999). For these measurements we use AGFI (adjusted goodness of fit index), NFI (Bentler‐ Bonnet nor med fit index) and RFI (relative fit index). Consequently the values should be around 1, like is the case of our analysis.

Measurements of parsimony adjustment. They show the adjustment quality through the number of estimated coefficients in order to achieve the adequate level (Akaike, 1987). In this way, the adjustment has more confident when it had been realized using less variables because there is not a over fitting. A good parsimony adjustment maintain results if we analyze another sample. Their index are PNFI (parsimony normed fit index) I (James et al., 1982; Mulaik et al., 1989), PGFI (parsimony goodness of fit index) and PRATIO (Hu and Bentler, 1999). In our case all of them are around 0,9, so the adjustment is acceptable.

4.3 Discussion Variables about the construct Aims of innovation in order to improve environment and health are more than consistency and reliability tests because they have high highlight correlations to 0,01 level and their Cronbach alpha is more than 0,7 so they satisfy the reflective variables requirements. At the same time, the loading factors are more than 0,5 and less than 1, as a result the model is available. Besides this hypothesis 1 is confirmed because indicators are validated to this construct and the model quality explained is high. Values of variables E6O14, E6O15 and E6O16 show that enterprises focus their efforts in improve environment, health and safety of people and they realize fewer investments with the aim of reduce inputs or energy in their production process. If we analyze variables linked with innovation expenditure, related to the construct Innovation expenditure in order to improve environment and health, results show that they also present loading factors more than 0,5, so

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the construct quality is good and hypothesis 2 is accepted. In addition results show that the high loading factors correspond with variables linked with improve health and safety of people and education, while the variable linked with improve environment is on the last position. In this sense, we can appreciate coherence between objective variables and expenditure variables. From this information we perceive an absence of direct or indirect relationship between Aims of innovation in order to improve environmental and health and Investment in innovation in order to improve environmental and health, thus we verify hypothesis 3. In other words, organizations prioritizing their profitability and they determine investments there from. With respect to the relationship between Aims of innovation in order to improve environmental and health and turnover, the regression coefficient is near zero, thus these organizations do not prioritizing these objectives according their influence on the turnover, that is to say, they are independent variables and hypothesis 4 is confirmed. Results about goodness adjustments demonstrate that model is defined and identified correctly and it is very close to reality. In addition, parsimony adjustments are acceptable; therefore probably model will be the same analyzing other samples.

5. Conclusions At present time in Spain, in a economy characterized by knowledge highlight and a severe economic crisis, innovations with the aim of improve environment and people´s life are an essential intangible for enterprises. However these innovations do not influence in the turnover, they represents an intangible benefit related to the organizations social projection, and they improve their sustainability and maintain the competitiveness. In this way, we can talk about continuity and we present an original study about how high technology enterprises in information and communication industry in Spain manage their innovations analyzing their influence in the turnover, the expenditures and the aims linked with social responsibility. The principal aim is to contribute to literature identifying subjacent constructs in this process with the purpose of managers efforts in this topic. We conclude that when managers determine their aims they don´t take into account they influence in the turnover either the expenditures. Besides this we can affirm that Spanish managers in this industry are aware of innovation highlights. On the other hand, managers prioritizing aims related to health and safety of people and education. That is to say that they know that people are the most highlight resource in organizations and improve their welfare proportionate to them motivation and implication in the entrepreneurial project. As a result, the continuity is more probable. With this analysis, we assist enterprises interested in improve their innovation activity and also the sustainability, because it supposes a first step in order managers know some interesting variables linked with aims of innovation. Consequently enterprises know the innovation highlight although it is not reflected in the turnover. Finally we identify an implication to government and public administrations interested in the topic, highlighting the collaboration between enterprises and other agents related to innovative activity about social responsibility in enterprises. Nevertheless, we recognize the limitations in this research. First, we have used a questionnaire created and conducted by an external entity in order to analyze innovation activity in enterprises. In this sense, other important variables for our study could not be included in the research. In addition, we identify all of the limitations derived by the selected sample and data obtained by the INE. And finally, as the analysis is only done with data from 2010, it provides only a static vision. The last limitation recognizes also future possibilities, in which data from different years is compared. In this sense, maybe it could be interesting to compare the situation before the economic crisis and the situation

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afterwards. Another interesting future investigation could be to compare the situation between different sectors: Do enterprises in different sectors manage their aims of innovation linked with social responsibility differently or are there similarities between sectors? Finally, we think that an interesting future study could be to compare the situation in the same sector in different countries: Do Spanish firms in the information and communication industry manage their aims of innovation related to social responsibility like other enterprises in the same sector in another country?

Acknowledgements The authors thank to the Department of Management Evaluation and Business Innovation in the University of Basque Country for partial support this work.

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State Parenting Entrepreneurship ‐ the Process of Seizing Opportunities – a Case of a Chinese Entrepreneur Sabrina Luthfa Karim and Hanjun Huang Halmstad University, Halmstad, Sweden sabrina.luthfa@hh.se chanyuejingxin@hotmail.com Abstract: The purpose of the paper is to explore how an entrepreneur seizes opportunities in different contexts over the course of time through the developmental phases of an enterprise. The investigation is about a Chinese entrepreneur who founded a feather processing firm in 1978 after the start of the economic reform in the country. A qualitative research approach was selected to guide the exploratory nature of the study. Relevant data have been collected from news reports, articles and books written about the entrepreneur and the case company. During the early phase of the firm’s development, the entrepreneur depended heavily on political connections to search for and seize opportunities. Institutional actors, such as the local government and the central government, played the role of mediators by introducing the entrepreneur to the most important actors in the market and providing resources such as loans, land, labour, etc. The foundation of the company was not the result of the foresightedness of the entrepreneur but of the Chinese central government. Thus, we refer to this entrepreneurship as state‐promoted entrepreneurship. The entrepreneur’s relationship with the institutional actors was represented by patronage, privilege and protection. As time progressed, experience grew and institutional policies changed towards favouring foreign trade, the entrepreneur sought opportunities independently, occasionally bypassing the important institutional actors. We refer to such a phenomenon as “State‐parenting entrepreneurship”, which is similar to how parents raise their children in a protective environment during the early years and subsequently allow them, over time, to move on independently. Keywords: Chinese entrepreneur, seizing opportunities, State‐parenting entrepreneurship

1. Introduction In response to Schumpeter’s call (1947) for understanding entrepreneurship ‐ how it shapes long term outcomes for the economy and how it varies from context to context and over the course of time ‐ several American historians, sociologists, psychologists and economists worked for years in an attempt to explain the role of entrepreneurs and the level and characteristics of entrepreneurship (Jones and Wadhwani, 2006). Despite numbers of studies for more than half a century, it is argued that the definition of the field of entrepreneurship is inadequate (Gartner, 1988, Venkataraman, 1997). Shane and Venkataraman (2000) have argued that hitherto, scholars have shown interest in why, when and how entrepreneurial opportunities exist, sources and process of opportunity discovery, evaluation and exploitation, where the central focus is “opportunities”. They have attempted to define entrepreneurship as “how, by whom, and with what effects opportunities are discovered, evaluated and exploited”. Entrepreneurs do not discover, evaluate and exploit opportunities in a void, but rather in a context. Context means interrelated conditions in which something occurs, for example, environment (Merriam Webster Dictionary). Bygrave and Hofer (1991) have claimed that the entrepreneurial process is contextual since its evolution is influenced by a system of interacting variables. Thus, how an entrepreneur seizes opportunities in a certain context (interacting conditions) at a certain time may differ in other contexts at another time. O’Donnell, Gilmore, Cummins and Carson (2001) suggested that entrepreneurial researchers should acknowledge the environment within which firms function, and accordingly, should take into account the environmental factors to explain entrepreneurship. Hitherto, several studies have been done to explain the entrepreneurial process in the environmental context but most of these studies have investigated the process in a specific context and at a specific time. Some studies have investigated new venture creation in high tech industry, and some have investigated the roles, abilities, and experiences of the entrepreneurs in transitional economies (Zahra and Gravis, 2000, Smallbone and Welter, 2006; Tanas and Audretsch, 2011). Some of these aimed to find the differentiating factors in the entrepreneurial process in two different market contexts; either among two transitional countries or between a transitional and a developed country. However, Schumpeter’s plea for understanding “how entrepreneurship varies from context to context and in course of time”, has not yet been studied. In this paper, we aim to explore how an entrepreneur seizes opportunities (discovery, evaluation and exploitation) in

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Sabrina Luthfa Karim and Hanjun Huang different contexts over the course of time. To convey a comprehensive picture of the entrepreneurial process we intend to follow the developmental phases of an enterprise over a period of time. The paper is structured as follows. The next section describes a review of literature, followed by a theoretical framework. Thereafter, the methodological section discusses the process of data collection and analysis which is followed by a case study, an analysis and a conclusion.

2. Literature review While Schumpeter (1947) recognized an entrepreneur as a person who creates opportunities by exploiting something new, Kirzner (1973) recognized the same as an alert person who discovers opportunities from the environment. Sarasvathy’s (2001) entrepreneur who uses “effectuation” reasoning is also a creative person who imagines possible opportunities with no specific goals in mind with a given set of means and allows the goals to emerge contingently. On the contrary, Sarasvathy’s entrepreneur who uses “causal” reasoning, discovers and exploits opportunities in the most efficient way to meet the predetermined goals with a given set of means. Despite the debate of an entrepreneur being creative vs. alert, there is a general acceptance that an entrepreneur is a person who discovers, evaluates and exploits opportunities (Shane and Venkataraman, 2000) through initiating, developing and maintaining a profit oriented business (Cole, 1965). Opportunity is the central concept of the field of entrepreneurship (Shane and Venkataraman, 2001). Companys and McMullen (2007) have defined opportunity as a situation that promises potential for profit. Casson (1982) defined opportunities as certain situations in which new products, services, raw material etc. are introduced in the market and sold at greater than their cost of production. Thus, an opportunity occurs at a certain time and offers certain conditions for making profit. Stevensson and Jarillo (1990) defined it as a “future situation which is deemed desirable and feasible”. Having asserted that, the authors proclaimed the fact that (1) opportunities are those situations which are both desirable and capable for one to pursue; accordingly (2) recognition of those opportunities is subject to the entrepreneur’s desirability and capability; and (3) in pursuit of the opportunity entrepreneurs must consider organizational capabilities and resources. According to Weick (1995), such situations do not simply exist in an environment and entrepreneur must interpret such situations as opportunities which we believe depend on “feasibility”. Then again, according to Stevensson and Jarillo (1990) in new venture creation entrepreneurs pursue opportunities regardless of the resources under control. Weick (1995) argues that entrepreneurial opportunities exist once they are defined and enacted by individuals, thus actualization of the goal determines the existence of opportunities. Behind the process of seizing opportunity, several researchers have recognized the contribution of the network partners (Ardichvili, Cardozob and Ray, 2003; Hills, Hoskisson and Kim, 1997; Kirzner, 1973; Burt, 1992; Koning, 1999, Granovetter, 1973, Baron, 2006). According to them, network partners give access to differential information and resources and enable connecting opportunities. Burt’s (1982) structural holes concept provides the possible “mantra” of how opportunities can be seized in a network. Originally, the concept explains how individuals connect resources from unconnected sources in a social network. According to the concept, complementary resources remain poorly connected or unconnected and an individual connects these resources from the two ends by developing relationships. However, in reality as social beings our choices can be constrained by the social institutional context which encompasses unwritten rules, norms, and practices, thus we may not be able to connect resources from wherever we desire. In this regard, Burt’s (1982) structural holes concept can be seen as limited to some extent. In a similar manner, an entrepreneur’s choice of business partners and consequently his ability to connect important resources can be constrained by the institutional environment of the market. For example, export quotas imposed by the government constrain a firm’s ability to develop a business relationship with a potential foreign customer. North (1990) defined an institutional environment as a condition encompassed by “the rules of the game in a society” that structures incentives in human exchange. Jansson (2008) argues that a firm’s network is conditioned by the market environment/s within which the firm and its network partners function and is affected by the institutional frameworks of the respective markets. Several researchers have suggested that individuals tend to develop relationships with non‐market actors like governmental organizations in a difficult institutional context (Jansson, 2008, Yang, 2004, Hellman, Jones and Kaufmann, 2000; Hoskisson, Eden, Lau, and Wright, 2000), for example, institutional ambiguities resulting from incompletely defined rules (Yang, 2004). Hellman et al (2000) have shown that when laws supporting property

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Sabrina Luthfa Karim and Hanjun Huang, rights are absent, entrepreneurs maintain their relationships with political actors. A survey study based on firms from 22 transitional countries shows that large firms inherited from previous communist systems tend to maintain formal and informal ties with the state and try to influence the formation of rules of the games through private payment to public officials (Hellman et al 2000, p. 2). The study has also shown that private firms which lack secured property rights tend to shape the institutional framework through illicit and non‐ transparent actions. Interestingly, entrepreneurs of these firms maintain relationships with those who decree the rules, possibly to bypass the rules. An interesting variation of Burt’s concept can be observed in the emerging economies where it is not the entrepreneurs but the institutional actors who tend to maintain relationships with the entrepreneurs and connect resources and opportunities for them. For example, Oi (1995) discussed government officials of China having career incentives to help improve the local economy by encouraging entrepreneurial firms. In many cases, the community governments transferred advanced technologies, dispatched managers, engineers and other highly skilled workers from the SOEs to township companies to promote their growth (Xu and Zhang, 2009) as well as bearing the risks on behalf of the entrepreneurs (Oi, 1995). In a way, the entrepreneurs in these cases were not pursuing their own opportunities; rather someone else was providing the opportunities for them. The aforementioned findings challenge the existing definition of an entrepreneur and the explanation of how entrepreneurs seize opportunities. To what extent do the institutional actors sponsor entrepreneurs to seize opportunities? Hitherto, how many studies in the field of entrepreneurship have looked into this phenomenon? There are several studies done in the field of developmental economies which have investigated the role of the state behind industrialization at the macro level (Grabowski, 1994; Wade, 1990; Goetzmann and Köll, 2000). According to Wade (1990) almost all the industrial nations of Europe used “government‐inspired” and th “government‐administered” infant industry policies to launch successful industrial transformation in the 19 century. In a similar fashion, the East Asian economic success is indebted to state controlled import substitution and export promotion policies. Sponsoring companies had been an old practice of the Chinese government for centuries (Goetzmann and Köll, 2000). In the 60s, in some developmental states such as South Korea, Japan, Taiwan, and Brazil, the state coordinated and steered market agents, and created “search networks” or coordination forums with sustained “public‐private” interactions (Grabowski, 1994). It is evident that, in underdeveloped economies, institutional actors tend to ensure promotion and protection to entrepreneurial firms in order to promote overall economic growth as long as the market is not stable and industry is not mature. Wade suggested that “once the protected industries have matured and are able to compete, the protection would be withdrawn and competition in the international market would occur”. That is, with gradual development of the market conditions, such “parenting style” of the state in promoting entrepreneurial firms is expected to be reduced over time. Despite these findings and observations, the entrepreneurial researchers have not yet looked into this phenomenon. We argue therefore, that there is a need for research in this aspect.

3. Theoretical framework An entrepreneur initiates, develops and maintains a profit oriented business through discovering, evaluating and exploiting opportunities (Shane and Venkataraman, 2000; Cole, 1965); however, we have noticed that entrepreneurs can be sponsored by institutional actors (Oi, 1995; Xu and Zhang, 2009). Discovery of opportunity can be directed by the predetermined goals and to some extent can occur with sudden realization of a situation as resourceful (Sarasvathy, 2001). Accordingly, the process of opportunity discovery can be both conscious and unpredictable. Evaluation of opportunities depends on the availability and attainability of resources and capabilities that support the exploitation of the discovered opportunities later on. Entrepreneurs exploit opportunities through developing and maintaining relationships with their partners who offer important resources to them (Burt, 1982); however, their choices can be affected by the institutional arrangements. As Jansson (2008) mentioned, institutional changes leading to changes from the premarket context (homogeneous, limited actors, low competition) to mature market (heterogeneous, competition from unlimited actors), create a great deal of shift in market demand, consumption behaviour, rivalry and service demand (Jansson, 2008) and eventually offers possibilities to reconsider business partners. An entrepreneur who intends to seize opportunities must take into account the interconnectedness (key affecters) that encompasses a firm’s business environment. Then again, network relationships with the institutional actors enable bypassing the complexities involved in the institutional arrangements and managing important

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Sabrina Luthfa Karim and Hanjun Huang resources. They are the key connectors of opportunities. In markets where institutional ambiguity is high, both the entrepreneurs and the institutional actors have incentives to maintain a relationship with each other (Yang, 2004; Jansson, 2008; Oi, 1995; Xu and Zhang, 2009). Institutional actors tend to patron, protect and promote entrepreneurs’ interests and to some extent administer entrepreneurial activities (Hoskinsson et al. 2000; Hellman et al. 2000; Wade, 1990; Grabowski, 1994), until the market matures (Wade, 1990; Jansson, 2008). Based on the previous discussion we have formulated a theoretical model that explains how an entrepreneur seizes opportunities in any context and what the key connectors and key affecters in this process are. Figure 1 narrates the process of seizing opportunities. The arrow in the middle is the depiction of the three stages of seizing opportunities: discovery, evaluation and exploitation. The network partners (key connectors) provide important resources and thus enable the process of seizing opportunities. However, the process of seizing opportunity is embedded in an environment which is composed of various interconnected conditions (key affecters) that affect network development (network structure reorganizes). By applying this model to different phases of development of a firm’s life cycle we expect to explain the variations and similarities in different contexts in different time frames and thus expect to convey a comprehensive picture of entrepreneurship.

Affecter: factors in network context, institutional context, market context and social context which affect network development and seizing of opportunity

Entrepreneurial process of seizing opportunities Discovery –evaluation - exploitation

Actualization of goal determines seizing of opportunities

Entrepreneur

Opportunity Connector: Network partners

Figure 1: Conceptual model of the entrepreneurial process of seizing opportunities

4. Methodology The paper has been based on previous work done in a MSc. project, in the University of Halmstad, by one of the authors of this paper, Huang Hanjun. The name of the original work was “The business model of Chinese manufacturing born global companies”. The aim of the project was to investigate the business model of a Chinese manufacturing company. Only a fraction of the original data, which discussed the entrepreneur and his activities, has been used in this paper. Complementary data have been collected by the co‐author Huang Hanjun. The research question of our study recognizes various interrelated factors affecting seizing of an opportunity. Qualitative study best suits in this regard, as qualitative study helps to explain a complex process involving many variables (Yin, 1994). According to Yin (1994) a qualitative study is suitable for exploratory, descriptive and explanatory studies which address what, how and why questions respectively. A case study method has been used. A case study allows in‐depth insight into an empirical phenomenon and its contexts (Yin, 1994), thus offering a unique means of developing theory. A single case study however may not always be the right choice since the results cannot validate the theories (Bryman and Bell, 2007). The case company is one of the leading manufacturing companies in China, which was established at the advent of the reform and thereby went through various phases of adaptation. In China economic transformation had taken place in a number of phases over three decades (Tisdell, 2009). Each reform decision

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Sabrina Luthfa Karim and Hanjun Huang, created new institutional and market conditions for firms. By studying this leading company we could follow the entrepreneurial journey of seizing opportunities under different phases of institutional reforms over a long period. For the entrepreneurial stories we relied mainly on the secondary sources, one of which is the company website, where the interview of the entrepreneur has been sited. There are also books written about this company and the entrepreneur and information about the Chinese political and economic environment from the 70s to 80s which have been referred in this paper. Huang Hanjun collected the data that are written in Chinese. The data have been categorised under various phases of development of the company based on its decision to change the product category and business expansion. The entrepreneurial process of seizing opportunities has been analysed under various contexts based on the institutional changes and the response of the market to the institutional change.

5. Empirical findings The company was set by the local government officials as a township and village enterprise (TVE) in Gunagdong province in 1978 by an order from the central government of China. TVEs were partially owned by the local government until the ownership conversion completed in 2000 (Xu and Zhang, 2007). The man behind this enterprise is Li. Seven officials accompanied Li and established Gamma; however, they were unwilling initially since they were insecure of the fate of the reform. Li had responsibility to devise an income generating idea for the people who had been mainly engaged in agriculture and poultry production for many years. They lacked higher education and know‐how of using technology. Resources that were available to start the business were “duck feathers”. Li knew that feather coats were popular in the western world during that time and some Chinese SOEs were exporting feathers abroad. Li planned to start a feather processing workshop which would not require huge financial resources and highly educated workforce. He planned to supply feather dusters to SOEs. In 1978 only the SOEs had export rights. During the early years there was only one bank in China which could lend money (Chow, 2004) but TVEs had no access to state bank loans. Under the guarantee of the local government, Li managed to secure some loans from the state bank; 300 thousand RMB came directly from the local government and the rest from the founders’ personal networks. In Gamma, feather dusters were washed manually by the workers then supplied to an SOE. The local government introduced Li with the SOE. Being a TVE, Gamma had to deliver most of the profit to the central government and could only keep a small percentage of it. However, Gamma was also privileged. The central government dispatched some machine parts at low cost from its SOEs to Gamma to lessen the manual work load of its labours. Soon Li realized that the feather duster business was not profitable so he planned to expand the product category to feather rags. He aimed to export directly as well. By that time, the government started to encourage foreign investments from Hong Kong and Taiwan, and approved import and export. To produce feather rags Gamma needed to purchase an advanced production line. However, his workers lacked knowledge of handling advanced machineries. So, he sent some workers to SOEs to learn the use of advanced machineries and some workers to universities to study professional management and English. Gamma then took out its profit and imported the advanced production line from Japan. Japanese engineers assembled the machines and trained the work force. Shunde Trading introduced Gamma to a Hong Kong textile company for whom Gamma would produce feather rags. With the new experience Li signed joint venture agreements with two firms in Hong Kong and Taiwan which had direct export rights. Thus Gamma bypassed the regulations in the mainland China. At the end of the 80s, the international market for down products became saturated and prices dropped. Li realized that Gamma needed diversification to survive. In 1989 Chairman Jiang Zemin confirmed the new direction of China’s development policies towards scientific and technology based production including

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Sabrina Luthfa Karim and Hanjun Huang extension of the market system and greater economic openness (Tisdell, 2009). Accordingly, from 1992‐1996 the central government encouraged the development of the infrastructure to support technology based production in some preferred provinces where Guangdong would be the household appliance industrial zone. In 1992 Li went to Japan for a business trip where he noticed a microwave oven in a shop. He saw the potential for microwave business in the local Chinese market since by this time people’s income and living standards had improved a great deal from previous years. However, his engineers were not convinced to start producing microwaves since they lacked the technical knowledge (Deng, Zi and Wang, 2006). During that time, there were only four Chinese companies which were assembling microwaves for some foreign companies. The total yield was very low and none were selling to the domestic market. Li convinced his team members to diversify into the microwave business targeting the domestic market. Once again, Gamma lacked skilled labourers and machinery for microwave production. Li convinced one engineer from a SOE to join Gamma who could exploit the core technology of the microwaves (Deng, Zi and Wang, 2006). By using several years of profit from the textile business, Li bought the assembly line from Toshiba. Toshiba’s engineers trained the workers and installed the assembly line. However, available resources were not enough to support the production and promotion of microwaves. So, Gamma withdrew from the textile industry and concentrated fully on the new business. According to Li “sometimes one should burn his boat to cut off his route of retreat”. Increasingly, adopted privatization and the presence of foreign companies were creating competition in the market thus challenging Gamma’s existence once again. In the mid 90’s many TVEs disappeared and many converted to private companies (Xu and Zhang, 2009; Perotti, Sun and Zou, 1998). Li and his colleagues were sceptical about conversion since the privatization policy was not complete. Moreover, they were afraid of coping with the changes at company level. In 1997 the Shunde local government finally decided to sell all its companies to respective management teams (The Economist, 2011). Li bought 70% of the shares on behalf of the management team and the local government kept 30% of the shares until the change stabilized in 2000. However, many economic journalists argue that Chinese private firms are still somewhat under the influence of the state and there is lack of transparent lines between the state and the private entities (The Economist, 2011, BBC news, 2013). Already in 1997 with the new freedom, Li decided to buy a production line for making components for Gamma’s own brands of microwaves. He went to Europe to purchase a component called “transformer”. Due to the lack of financial capability, Li offered to produce transformers for a European manufacturer at a low rate and in exchange Gamma would use their production line. Gamma got the deal. In 1997, Gamma established a research institution in the USA where its own components would be produced and recruited international experts to work for it. Gradually, Gamma entered into many other foreign markets (Russia, South Korea, USA) as OEM producers of various white goods and learned their technologies. Today it produces a wide range of white goods and is present in 100 countries (Gamma group’s website).

6. Analysis This section discusses how Li seized opportunities over the years along the different developmental phases of Gamma. Each phase went through different conditions which had resulted from changes in the institutional arrangements in China and consequently changes in the market environment. The foundation of Gamma had been arranged by the central government in a context which was characterised by a lack of infrastructure and financial facilities, a limited number of market actors, an underdeveloped domestic market and laws restraining exports and imports (except for the SOEs). Initially, Li was an appointed officer and his responsibility was to find ways to attain the goal set by the government. Li seized opportunities by maintaining relationships with the institutional actors as argued in the literature (Jansson, 2008; Yang, 2004; Hoskinsson, et. al, 2000; Hellman, et. al., 2000). However, we have observed that it was the institutional actors which had a greater interest in maintaining a relationship with Li and helping Li to manage important resources, like land, labour, bank loans, etc. It could be the Chinese government policies as Grabowski (1994) described, or Gamma’s ownership structure (partial ownership of the local government), or it could also be a th phenomenon that Wade (1990) and Grabowski (1994) observed in the late 19 century in Europe. However, Li’s activities have not been administered as in some European countries. We observed furthermore, when the reform relaxed from the initial phase, Li made decisions to import new advanced lines without the permission of the local government. Li knew where the opportunity existed and

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Sabrina Luthfa Karim and Hanjun Huang, who could complement his resources. He made a conscious choice as a causal entrepreneur of Sarasvathay (2001). Fortunately, the new reform mediated the process of exploiting the opportunity where the different government bodies patronized Li’s activities by training his work force or introducing it to foreign customers. State patronage and promotion were evident. Gamma’s network structure started to change soon after he made his own decisions. The network was no longer limited to the institutional actors. Later on with greater openness in the domestic market and barriers in the international market, Li discovered opportunities like Kirzner’s (1973) alert entrepreneur. He was transformed from an appointed entrepreneur to someone whom the existing literatures recognize, someone who initiated and developed business through discovering, evaluating and exploiting business opportunities (Cole, 1965; Shane and Venkataraman, 2000). However, he maintained Gamma’s dependency on the institutional actors until the institutional reform stabilized with privatization policy and ownership conversion. In our case, discovery of opportunity sometimes was guided by the predetermined goals, and sometimes occurred from sudden realization of a situation as resourceful. Opportunities had been evaluated by availability and attainability of resources, sometimes in terms of factors of production and sometimes in terms of explicit and implicit state patronage. Initially, opportunities had been exploited with the patronage, promotion and protection of the institutional actors. Thus, Gamma enjoyed a privileged environment created by its institutional partners and could thus seize opportunities effortlessly. Later on opportunities had been seized independently by Li through an extended network including foreign actors. This was possible due to the shift in the institutional context and consequent shifts in the market environment as claimed by Jansson (2008). We have observed a gradual pattern of moving away from the state patronage over time due to stabilization of the institutional framework from the premarket condition.

7. Conclusion Entrepreneurs can be appointed to attain a predetermined goal. We refer to such entrepreneurship as state promoted entrepreneurship. Entrepreneurs can also be evolved over time through entrepreneurial activities. Opportunities can be pursued or seized differently by the same entrepreneur depending on the changes in market context resulted from changed institutional framework. In our case as time progressed, experience grew, state policy relaxed, market context changed towards more mature market economy, state patronage, promotion and protection were withdrawn from the entrepreneurial firm. We refer to this type of entrepreneurship as state parenting entrepreneurship, which is similar to how parents raise their children in a protective environment during the early years and subsequently allow them, over time, to move on independently. This unique phenomenon perhaps can be found in many other firms’ early phases of business. We welcome more studies in this regard.

Acknowledgements We would like to pay our gratitude to Prof. Gabriel Baffour Awuah for his suggestions and comments on our work. We would also like to thank Prof. Mike Danilovic, Dr. Fawzi Halila, Dr. Maya Hoveskog, Prof. Svante Andersson, Prof. Bernd Hofmaier, Carmen Li, Jasmine Lihua Liu and Robert Wentrup for their comments on the paper.

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The Impact of the Economic Downturn on Innovative Performance in Poland Anna Matras‐Bolibok Department of Economics and Management, University of Life Sciences in Lublin, Poland anna.matras@up.lublin.pl Abstract: Contemporarily, innovations play a crucial role in strengthening competitive advantage of emerging economies. Effective innovation activity provides opportunities for diminishing the innovative gap between these economies and innovation leaders. In case of Poland a relatively less severe economic downturn in comparison to other European Union countries may prove a significant accelerator of this process. On the other hand the increase of risk aversion caused by the global economic crisis of recent years leads to constraining innovative projects, especially by private investors, and this could in turn affect adversely the long‐run competitive position of Polish enterprises. The paper aims at investigating the impact of the global economic downturn on the innovative performance in Poland. The analysis was conducted for the period 2006‐2011, on the base of statistical data provided by Central Statistical Office of Poland and Eurostat. The impact of economic downturn on general macroeconomic characteristics and on the demand‐ and supply‐side determinants of innovativeness in Polish economy were examined. In order to achieve the aim of the paper the analysis of the share of innovative enterprises, level of innovation expenditures and the effects of innovation activity measured by the share of revenues from sales of new or significantly improved products was conducted. Additionally, the impact of the size of enterprises on their resistance to unfavourable economic conditions during the latest global crisis was examined. The results of the analysis indicate that the uncertainty caused by the global economic crisis affected adversely the overall innovative performance of Polish enterprises. The analysis revealed simultaneous increase of R&D expenditures intensity and patent activity. As R&D expenditures in Poland are financed mainly by public funds these results imply that the innovative activity during the economic downturn may be focused increasingly on basic instead of applied research. This indicates the potential weakening of connection between the sectors of science and business. Moreover, the analysis revealed, that the larger enterprises proved relatively more resistant to economic turbulences. Furthermore, economic crisis turned out to be a factor that contributed to increase of the level of divergence between large and small or medium enterprises. The results imply therefore the necessity of creating favourable conditions for development of networks of collaboration on innovation activity. In this light the innovation policy aiming at strengthening the collaboration between science and business sectors as well as between enterprises, during the current economic downturn becomes of crucial importance. Keywords: innovation, innovative performance, economic downturn, emerging economy

1. Introduction Contemporarily, innovations play a crucial role in strengthening competitive advantage of economies. Effective innovation activity provides opportunities particularly for diminishing the innovative gap between emerging economies and innovation leaders. International evidence indicate that encouraging endogenous, ie. based on the internal development factors, innovation processes is the most efficient way of catching up with the highly developed economies (Fagerberg and Godinho 2006). This involves therefore the necessity of establishing the favourable conditions in these economies not only for absorption of innovative solutions from abroad, but first of all, for creation of innovation on their own. The relationship between innovation and economic development is not unidirectional, as there are strong feedbacks between these variables. Therefore, the innovativeness of the economy is strongly correlated with the level of its economic development (Matras‐Bolibok 2008). The macroeconomic conditions influence undoubtedly the proneness to innovate. As the innovation process is immanently connected with high costs and risk, the uncertainty caused by the global economic crisis of recent years leads inevitably to constraining innovative projects, that could affect adversely the long‐run competitive position of economies. The paper aims at investigating the impact of the global economic downturn on the innovative performance in Poland, one of the least developed countries in the European Union. The paper is structured into two sections. The first portrays the relationship between economic performance and innovativeness of economies, basing on the results of theoretical and empirical evidences. The second presents the results of the analysis of the impact of the last economic downturn on the innovativeness of Polish economy.

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2. Innovation and economic disturbances Innovation is regarded as an evolutionary, non‐linear, and interactive process between firms as well as between the firm and its environment (Rothwell 1994; Kline and Rosenberg 1986). The ability of a company to create and commercialize innovations, considered as innovation capital, is regarded as a bundle of assets and, more generally, resources (Kijek 2012). The complexity of innovation process implies that it is stimulated and influenced by many factors. These factors could be divided into two groups: internal factors, i.e. firm’s general characteristics, strategies or structure and contextual factors connected with firm’s environment, in which macroeconomic conditions are the key determinant. The economic crisis of last years revealed that these macroeconomic conditions to large extent influence the innovative performance of the economies around the world. Due to its global impact, it became the most severe economic downturn after World War II, as large number of crises that have occurred in recent decades remained national or regional events (Economic crisis… 2009, Staszczak 2011). A large body of literature has already demonstrated the fundamental role played by innovation in fostering long‐run growth performance (Verspagen 2006, Grossman and Helpman 2001). But the relationship between innovation and economic performance is not just unidirectional as feedbacks occurs between them. Innovativeness of the economy depends largely on the level of income and economic development of the given area. Economic growth provides an effective innovation process as it allows for increased investment in new technologies, infrastructure and education, which in turn contributes to further creation of innovations, and they, in turn, generate economic growth in the economy. Innovation is a market process, hence its impulses may be found among both supply‐side, connected with R&D performance (Jaffe 1989, Mansfield 1991, Acs et al. 1992, Matras‐Bolibok 2007) and demand‐side factors. The economic downturn inevitably contributes to decrease of incentives to innovate on both sides of the market. The uncertainty caused by the economic disturbances has severely reduced the proneness of companies to invest in innovation (OECD 2012, Paunov 2012). Innovation is a process immanently connected with risk and high costs, that firms would avoid undertaking, during the periods of economic disturbances. Moreover, financing risky and costly projects requires acquiring adequate sources of capital, and as such disturbances increase risk aversion, capital becomes more expensive (Bolibok 2007). However, as Joseph Schumpeter stated the process of creative destruction fosters innovation and technological progress by replacing the old with the new (Schumpeter 1942). From this perspective, the economic downturn may be a source of opportunities for innovators. As the results of conducted studies revealed this group of innovators consists of fast growing, new and often small firms that were not necessarily involved in innovation before the crisis. (Archibugi et al. 2013). Simultaneously, the resistance to economic disturbances proved to be the greater in case of large high‐technology innovating firms for which markets will continue to be strong (OECD 2012). These are the most dynamic firms, that innovate continuously, irrespectively of the business cycle. The effects of the economic downturn differ substantially across countries, sectors, enterprises and types of innovation (OECD 2012). The economic crisis has negative impact on innovative performance in almost all EU countries, however the catch‐up countries are the most affected (Archibugi and Filipetti 2011). The growing disparities in innovative capabilities may result in strengthening the divergence also in economic development. Given the above mentioned circumstances, an assessment of the impact of the economic downturn on innovative performance in Poland, as well as the comparison of the resistance of different size classes of enterprises to this downturn, becomes an interesting research problem.

3. The analysis of the impact of economic downturn on innovative performance in Poland 3.1 Data and methods In order to present the impact of economic downturn on the Polish economy the general macroeconomic characteristics were examined. The analysis of the value of gross domestic product (GDP) and domestic

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Anna Matras‐Bolibok demand in purchasing power standard (PPS) per inhabitant and their growth in Poland in the 2006‐2011 period against the EU 27 average was conducted, basing on the statistical data provided by Eurostat (http://epp.eurostat.ec.europa.eu/, 2013 April). To reveal the impact of economic downturn on the supply‐side determinants of innovativeness, the analysis of R&D activity was conducted, regarding the gross domestic expenditure on R&D (GERD) in PPS per inhabitant and the intensity of R&D in 2006‐2011, basing on the statistical data provided by Eurostat (Ibidem). In order to reach the aim of the paper, the innovativeness of Polish industrial enterprises was examined. Additionally, the comparative analysis of the impact of the size of enterprises on their resistance to unfavourable economic conditions during the latest global crisis was conducted. The share of enterprises with expenditures on innovative activity, with introduction of new or significantly improved products and the revenues from sales of new or significantly improved products achieved in each size class of enterprises were examined, during the period 2006‐2011. The analysis was based on the statistical data provided by Central Statistical Office of Poland for Polish industrial enterprises, with employment over 9 persons (http://stat.gov.pl/, 2013 April). The data are the results of surveys on innovation, which were conducted on the basis of an international standard methodology outlined in the Oslo Manual (2005), developed under the aegis of the OECD and Eurostat. The firm size was determined according to the number of employees. Due to this determinant the small enterprise is the one that employs up to 49 persons, medium – 50 to 249 and large – over 249 persons.

3.2 Results

8,0

6,0 4,0

2,0 15 0,0 10

Real GDP growth rate

GDP in PPS per inhabitan

Poland is one of the least developed countries of the European Union. As innovativeness is strongly correlated with economic performance, the lower level of development of Poland should result in a worse innovative performance in comparison to more developed economies. As data presented on Figure 1. shows, GDP per capita in PPS in 2006 was nearly two times lower than the average in EU 27. However during the analysed period the examined gap has diminished to 1,5. The positive change in Polish economy is attributable to a significantly higher real GDP growth rate than in other EU 27 countries in Poland . Therefore, it could be stated that the economic disturbances did not impact the economic performance, (measured by the GDP growth and its absolute value per inhabitant) so negatively in comparison to other EU 27 countries.

-2,0

-4,0

-6,0 2006

2007

2008

2009

GDP in PPS per inhabitant in EU 27 Real GDP grow th rate in EU 27

2010

2011

GDP in PPS per inhabitant in Poland Real GDP grow th rate in Poland

Source: Own compilation on the base of statistical data provided by (http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database 2013 April). Figure 1: GDP in PPS per inhabitant and Real GDP growth rate in Poland and EU 27 in 2006‐2011

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Eurostat,

Anna Matras‐Bolibok Innovation is the market process, hence its impulses may be found on both supply‐ and demand‐side factors. As far as the demand‐side group of determinants of innovativeness is concerned, it is worth noticing that economic downturn has not resulted in the decrease of domestic demand in Polish market. Conversely, the value of domestic demand increased more than 30 % in analysed period. Moreover, it is worth to point out, that this increase was nearly six times higher than in EU 27 on average (Table 1). Table 1: Domestic demand in PPS per inhabitant in Poland and EU 27 in 2006‐2011 2006 2007 2008 2009 2010 2011 Dynamics 2006‐2011 EU 27 23,6 24,9 25,0 23,3 24,2 24,8 1,057 Poland 12,5 14,0 14,7 14,2 15,5 16,4 1,312

500

2,25

450

400

1,75

350

1,5

300

1,25

250

200

R&D intensity in %

GERD in PPS per inhabitan

Source: as in Figure 1. Regarding the supply‐side impulses, one of the key determinants of innovation is R&D activity. The main variable used to present the R&D performance is R&D intensity, i.e. R&D expenditure as a percentage of GDP. One of the five headline targets of Europe 2020 Strategy is to achieve an R&D intensity of 3% in the EU member countries (Europe 2020, 2010). In 2011 the R&D intensity in Poland was equal only 0,77%, so it was nearly four times lower than the determined strategic level. Moreover, it was more than 2,5‐times lower than the average R&D intensity in the EU‐27 that stood at 2,03% in 2011 (Figure 2). However, a positive effect, is the 38% increase of the examined variable during the period 2006‐2011 (from the level of 0,56%), whereas in the EU 27 the average increase was equal 10%. On this base it should be noted, that the economic downturn has not impacted negatively the R&D performance in Polish economy. The results of the analysis revealed that the economic downturn has neither influenced negatively the value of expenditures on R&D. As the data presented in Figure 2 shows the GERD in purchasing power standard per inhabitant (at constant prices of the year 2000) increased more than 70% during 2006‐2011, whereas in the EU 27 the increase was equal 28%. It could be therefore stated, that during the years of economic disturbances Poland diminished the gap to the EU average in the field of R&D performance.

0,75

150 100

0,5

0,25

0 2006

2007

2008

2009

2010

2011

GERD in PPS per inhabitant in EU 27

GERD in PPS per inhabitant in Poland

R&D intensity in EU 27

R&D intensity in Poland

Source: as in Figure 1. Figure 2: GERD in PPS per inhabitant and R&D intensity in Poland and EU 27 in 2006‐2011. Important dimension of innovative performance of the economy is the patent activity. In this field, Poland obtained very poor results in comparison to the other EU countries. In 2005, the number of patent applications to the EPO per million inhabitants in Poland equalled only 3, whereas in EU 27 – 116. During the next five years the examined factor increased in Poland to 8, whereas in the EU 27 decreased to 109. When we consider the absolute total number of patents, in Poland it was equal 128 in 2005, that constituted only for 0,23% of EU total number of patents, and 308 in 2010, that was equal 0,56% of total number of patents in EU 27. Therefore it could be stated that the economic crisis did not influenced negatively the patent activity in Poland.

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Anna Matras‐Bolibok Figure 3. presents the share of industrial enterprises with expenditures on innovation activity and their value in the period 2006‐2011. It shows that on average more than a half of large enterprises, more than a quarter of medium size and less than 9% of the small ones bore expenditures on innovation activity in the analysed period. Large enterprises had definitely the highest share. The latest economic crisis influenced adversely the share of firms with expenditures on innovation activity in each size class. However, the group of large enterprises displayed a relatively lowest decrease of the share of enterprises with expenditures on innovation activity, i.e. 10% in comparison to 25% in the group of medium and 46% in small size enterprises. Moreover, in each size class of enterprises the increase of the value of expenditures took place. It could be therefore concluded that there was occurring a process of concentration in the field of innovation activity among Polish enterprises. mln PLN 20 18

% 70 60

16 14

12 10 8

6 4

2 0

0 2006

2008

2009

Expenditures in small enterprises Expenditures in large enterprises Share of medium enterprises

2010

2011

Expenditures in medium enterprises Share of small enterprises Share of large enterprises

Source: Own compilation on the base of statistical data provided by GUS (http://stat.gov.pl 2013 April). Figure 3: Industrial enterprises with expenditures on innovation activity (as % of total industrial enterprises) and their value by size classes in Poland during 2006‐2011 The Figure 4 presents the share of innovative industrial enterprises which introduced new to the market or significantly improved products in the period 2006‐2011. On this base the conclusion could be drawn that the economic disturbances contributed to a significant decrease – of more than 30% ‐ of innovative enterprises in Poland. The lowest proneness to innovate among industrial enterprises in Poland during the examined period was found in the case of small enterprises. In 2006 the share of innovative large industrial enterprises was more than a 4,5‐fold and 1,75‐fold higher than share of small and medium size enterprises, respectively. In 2011, the share of large innovative industrial enterprises turned out to be more than sixfold and almost twofold higher than respectively share of small and medium size enterprises. These results show that economic crisis has widened the divergence in the analysed field between enterprises of different size. On the base of Figure 5. conclusion could be drawn that the economic downturn affected negatively the effectiveness of innovative activity of Polish enterprises, measured by the share of revenues from sales of new or significantly improved products in total revenues of sales. The share of examined revenues in Polish industrial enterprises decreased by one third during the period 2006‐2011. The largest decrease ‐ of more than a half ‐ was noted in the group of small enterprises. It is worth to point out, that Polish enterprises displayed a very low share of revenues from sales of innovative products. Moreover, significant disparities occured in the level of performance regarding the size of the firm. The mean share of the examined revenues in 2006‐2011 was respectively more than fourfold and twofold higher in large enterprises (13,9%) in comparison to small and medium ones (3,1% and 7,1%, respectively). However, the advantage of large enterprises during the analysed period, increased, as in 2011 this group achieved more than sixfold and threefold higher effectiveness of innovative activity the in comparison to small

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Anna Matras‐Bolibok and medium ones, respectively. The results indicate that the economic disturbances contributed to increase of the level of divergence in the field of the effectiveness of innovation activities between large and small or medium enterprises. %

70 60 50 40 30 20 10 0 2006

2008

small

2009

medium

2010

2011

large

total

Source: as in Figure 3. Figure 4: Industrial enterprises which introduced new or significantly improved products and new to the market products by size classes in Poland during 2006‐2010 (as % of total industrial enterprises) % 18 16 14 12 10 8 6 4 2 0 2006

small

2008

2009

medium

2010

large

2011

total

Source: as in Figure 3. Figure 5: Revenues from sales of new or significantly improved products in Polish industrial enterprises by size classes in period 2006‐2010 (as % of total revenues from sales). The way to improve innovative performance of Polish enterprises, especially smaller ones is to undertake interorganizational collaboration, enabling them to act like larger ones and gain their advantages. Linkages and networks are key vehicles through which firms could obtain access to wider range of external resources, especially sophisticated knowledge, which they cannot acquire by themselves. Moreover, in networks of collaboration firms could share risk and costs immanently connected with innovation activities and consequently strengthen resistance to economic disturbances. The results of many studies in developed countries confirm positive correlation between collaboration of enterprises on innovation activity and their innovation performance (Matras‐Bolibok 2012, Nieto and Santamaria 2007, Schilling and Phelps 2007, Faems et al. 2005, Ahuja 2000). Interaction between market entities affects consequently the rate of innovation diffusion in the market (Kijek and Kijek 2010).

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Anna Matras‐Bolibok Collaboration among enterprises, especially those small and medium, and between R&D units and business could therefore be a critical factor in improving the capabilities and innovativeness of Polish enterprises and strengthening their resistance to economic turbulences. A key part in this field is undoubtedly assigned to regional authorities, which should facilitate emergence of networks of collaboration, by using instruments of regional and innovation policies. Moreover, the stimulus for strengthening innovative potential of Polish regions is the possibility of exploiting the EU funds oriented to support innovativeness. This support becomes an important factor diminishing the risk and costs immanently connected with innovative activity, that is particularly significant in the context of a relative economic weakness of Polish enterprises or scientific and research units and in the time of economic turbulences.

4. Conclusions The main conclusions derived from the conducted analysis are as follows:

The relatively less severe economic downturn in Poland in comparison to other European Union countries was observed. The economic disturbances did not impact the economic performance, (measured by the GDP growth and its absolute value per inhabitant) so negatively in comparison to other EU 27 countries. It may prove a significant accelerator of the convergence process.

The analysis revealed increase of R&D expenditures intensity and patent activity. As R&D expenditures in Poland are financed mainly by public funds these results imply that the innovative activity during the economic downturn may be focused increasingly on basic instead of applied research. This indicates the potential weakening of connection between the sectors of science and business.

The results of the analysis indicate that the uncertainty caused by the global economic crisis affected adversely the overall innovative performance of Polish industrial enterprises.

Larger enterprises proved relatively more resistant to economic turbulences. Furthermore, economic crisis turned out to be a factor that contributed to increase of the level of divergence between large and small or medium enterprises.

Collaboration among enterprises, especially those small and medium, and between R&D units and business could therefore be a critical factor in improving innovative performance of Polish enterprises and strengthening their resistance to economic turbulences

References: Acs, Z.J., Audretsch D.B. and Feldman, M. P. (1992) “The Real Effects of Academic Research: A Comment”, American Economics Review, Vol. 82, pp. 363‐367. Ahuja, G. (2000) “Collaboration networks, structural holes, and innovation: A longitudinal study”, Administrative Science Quarterly, Vol. 45, No. 3, pp. 425‐455. Archibugi, D. and Filippetti, A. (2011) “Is the Economic Crisis Impairing Convergence in Innovation Performance across Europe?” Journal of Common Market Studies, Vol. 49, Issue 6, November, pp. 1153–1182. Archibugi, D., Filippetti, A. and Frenz, M. (2013) “Economic crisis and innovation: Is destruction prevailing over accumulation?”, Research Policy, Vol. 42, Issue 2, March, pp. 303‐314. Bolibok, P. (2007) “Value‐based management from micro‐ and macroeconomic perspective”, Annales Universitatis Mariae Curie‐Sklodowska, Sectio H, Vol. XLI, pp. 241‐254. Economic Crisis in Europe: Causes, Consequences and Responses (2009), European Economy 7, European Commission, Directorate‐General for Economic and Financial Affairs, Luxembourg: Office for Official Publications of the European Communities. Europe 2020. A strategy for smart, sustainable and inclusive growth, Communication from the Commission (2010), Brussels, 3.3.2010, COM(2010)2020. Faems, D., Van Looy, B. and Debackere, K. (2005) “Interorganizational Collaboration and Innovation: Toward a Portfolio Approach”, Journal of Product Innovation Management, Vol. 22, No. 3, pp. 238–250. Fagerberg, J. and Godinho, M.M. (2006) Innovation and catching‐up [in:] The Oxford Handbook of Innovation, eds. Fagerberg, J., Mowery, D.C. and Nelson R.R., Oxford University Press, Oxford. Grossman, G.M. and Helpman, E. (2001), Innovation and Growth in the Global Environment, Massachusetts Institute of Technology. http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database 2013 April http://stat.gov.pl 2013 April Jaffe, A.B. (1989) “Real Effects of Academic Research”, American Economics Review, Vol. 79, pp. 957‐ 970.

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Anna Matras‐Bolibok Kijek, T. (2012), “Innovation Capital and its Measurement”, Journal of Entrepreneurship, Management and Innovation, Vol. 8, Issue 4, pp. 52‐68. Kijek, T. and Kijek, A. (2010) ”Modelling of innovation diffusion”, Operations Research and Decisions, No. 3/4, pp. 53‐68. Kline, S. J., and Rosenberg, N. (1986) ”An Overview of Innovation” [in:] The Positive Sum Strategy. Harnessing Technology for Economic Growth, eds. Landau, R. and Rosenberg, N., National Academy Press, Washington, pp. 275‐305. Mansfield, E.J. (1991) “Academic Research and Industrial Innovation”, Research Policy, Vol. 20, pp. 1‐12. Matras‐Bolibok, A. (2007) „Realization of Lizbon Strategy in the field of research and development in regional scope”, Annales Universitatis Mariae Curie‐Sklodowska, Sectio H, Vol. XLI, pp. 93‐102. Matras‐Bolibok, A. (2008) „ Research and development potential and competitiveness of region”, Annals of the Polish Association of Agricultural and Agribusiness Economists, Vol. 10, No. 2, pp. 174‐179. Matras‐Bolibok, A. (2012) “The Influence of Collaboration on Effectiveness of Innovation Activity in Polish Regions” [in:] Proceedings of International Conference for Entrepreneurship, Innovation and Regional Development, ICEIRD 2012, eds. Birov, D. and Todorova, Y., Sofia University, Sofia, pp. 116‐123. Nieto, M.J. and Santamaria, L. (2007) “The importance of diverse collaborative networks for the novelty of product innovation”, Technovation, Vol. 27, No.6‐7, pp. 367‐377. Paunov, C. (2012) “The global crisis and firms’ investments in innovation”, Research Policy, Vol. 41, Issue 1, February, pp. 24‐35. OECD Science, Technology and Industry Outlook 2012 (2012), OECD, pp.21‐57. Oslo Manual. Guidelines For Collecting and Interpreting Innovation Data. Third edition. (2005), OECD, Eurostat. Rothwell, R. (1994) “Towards the Fifth‐generation Innovation Process”, International Marketing Review, Vol. 11 No. 1, pp. 7‐31 Schilling, M.A. and Phelps, C.C. (2007) “Interfirm Collaboration Networks: The Impact of Large‐Scale Network Structure on Firm Innovation”, Management Science, Vol. 53, No. 7, pp. 1113‐26. Schumpeter, J.A. (1942) Capitalism, Socialism, and Democracy, Harper, New York, pp. 82‐85. Staszczak, D.E. (2011) “Theoretical Interpretations of the European Union Enlargement: Perspectives from a New Global Paradigm”, Journal of Knowledge Globalization, Vol. 4, No. 1, pp. 71‐92. Verspagen B. (2006) Innovation and Economic Growth [in:] The Oxford Handbook of Innovation, eds. Fagerberg, J., Mowery, D.C. and Nelson R.R , Oxford University Press, Oxford.

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How to Conciliate Best Enemies? The Case of Competitive Chemical Industries in Ecofriendly Cultures Céline Maximin‐Tieu ISTEC Paris – SEE‐PRISM Panthéon‐Sorbonne, France c.maximin@istec.fr Abstract: Article 3.5 of the 1992 UN Framework Convention on Climate Change (UNFCCC) stated, “The Parties should cooperate to promote a supportive and open international economic system that would lead to sustainable economic growth and development in all Parties.” In other words, the main actors in modern economies, namely, public authorities, companies and consumers, are urged to become actively involved in their living and working conditions in order to promote sustainable development in member states. As a result, a number of complex interactions come into play, which must be adapted to accommodate the national, cultural and industrial specificities at issue (viz. “Grenelle de l’Environnement,” in France, 2007). In that light, the goals of environmental sustainability are, first of all, a matter of public policy, in as much as they consist in promoting public welfare and enhancing the quality of life of present and future generations. In response to growing concern for the quality of the environment, business firms must be able to rely on this lever to boost toward eco‐tech innovation. When presenting economic approaches for improving environmental performance, we will propose an alternative managerial system. Finally, we shall see how addressing the specificities of a region, while considering all of the internal and external stakeholders (public authorities, training establishments, and the general population) of businesses within a competitiveness cluster, may strengthen and catalyze efforts to promote sustainable development in the chemistry sector in France. Keywords: knowledge management, clusters, sustainable development

1. Introduction The advent of the wide‐scale ecological crises, economic globalization, not to mention the rapid development of the IT sector, have heightened collective awareness of the principle of “common‐but‐differentiated‐ responsibilities” in promoting sustainable development (United Nations, Rio Earth Summit, 1992). The industrial era fostered an inexorable deterioration of the environment, owing to the use and processing of energy derived from more or less renewable natural resources. In all cases, the process of dematerialization, together with consumers’ growing awareness of the importance of environmental protection, has led to greater demand for environmental quality. At the same time, public authorities have been pressed into taking action, as they are called upon to exercise their sovereign powers in support this preference, by protecting public health and ensuring that producers of pollutants face up to their responsibilities. The debate on how best to maintain and encourage competitive advantage while simultaneously seeking to protect the environment rages on. Faced with this pressing demand for environmental quality, coupled with in‐firm voluntary, proactive efforts, high‐tech companies have introduced changes in their competitive strategy. In particular, what has made R&D an obvious key success factor in their activities is that industrial firms have implemented their strategy by taking advantage of both potential spillover benefits and the pooling of knowledge, in a sector as risky as sustainable Research and Development. At this stage, specific competences ought to be deployed within the firms regarding the complexity of such activities. When presenting economic approaches for improving environmental performance, we will propose an alternative managerial system. Territorial attractiveness coupled with regional interactions of strategic stakeholders appears to be success key factors. Thus, we shall see how addressing the specificities of a region, while considering all of the internal and external stakeholders (public authorities, training establishments, and the general population) of businesses within a competitiveness cluster, may strengthen and catalyze efforts to promote sustainable development in the chemistry sector in France. Lastly, we shall look more specifically at an experiment conducted within the Axelera competitiveness cluster, which will enable us to show that the complementary relationship between innovation and human capital as generators of positive externalities can offset negative externalities inherent in certain business activities in a sector such as the chemical industry. In light of these developments, firms in the French chemical sector have

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Céline Maximin‐Tieu rallied behind efforts to tap into the dynamic of the competitiveness cluster, with the goal of optimizing the synergies generated between their researchers on environmental issues.

2. An economic approach to corporate environmental performance The instrumental value of non‐human species is often underestimated in economic terms. However, aside from the shadow price (Desaigues, 2001)that may be attributed to certain non‐market goods, there is also the issue of production which, when accompanied by certain undesirable activities, may cause damage to environmental quality. It would appear, as well, that the individual’s position in the social process determines his preferences

2.1 The leverage effect created by the demand for environmental quality The theoretical contributions of Schmookler (1996) came as the first attempt to reexamine the economics of technological change, in response to the neo‐classical theory under which such change was considered to be an endogenous factor. In a word, it was argued that demand conditions affect the need for an invention, in as much as the expected profitability, together with growing market shares, are crucial incentives for the development of innovation initiatives. The hypothesis of a leverage effect derived from demand was challenged on both theoretical and empirical grounds. One of the main criticisms focused on the fact that knowledge capital is a determining factor for innovation but is also necessary for the very development of innovation. Furthermore, it was not demonstrated that demand factors had a greater effect on innovation than supply factors. In other words, the concepts of demand‐pull or technology‐push both relate to the sources of innovation, when the motivations that drive innovators are taken into account (Mowery and Rosenberg, 1979). In reality, these two forces can only occur in tandem. In that context, technological competitiveness and the emergence of new markets play a complementary and decisive role in the success of innovation activities (Crespi and Pianta, 2005). Moreover, environmental quality in the field of innovation is also defined according to the company’s objectives, which may vary depending on market share changes for new products, public policy, the social benefit sought, and other factors. In that light, good environmental management is characterized, first, by the companies’ ability to take advantage of benefits and cost savings arising from environmental protection measures. However, such a strategy must increase the company’s shareholder value. It must also ensure that the company achieve success on the market (increased profit) by differentiating itself from others in the area of environmental protection, through the creation of new products, and pursue excellence in cost reduction, thereby enhancing eco‐efficiency (Wagner and Schaltegger, 2001). In the first case, a market‐oriented environmental policy is equally concerned about increasing the company’s revenues. The company and its products can then achieve the position of recognized quality leaders In other words, the general factors of economic success, such as shareholder satisfaction and corporate reputation, must be constantly considered, in order to offset any eventual acts of environmental dumping. In the second case, production processes are optimized toward reducing costs, by redeploying environmental policy instruments proposed by public authorities, and are supported by measures identified as having a high potential for fostering eco‐efficiency. To pursue this desired cost minimization and achieve "cleaner production" solutions, managers explore and compare technological alternatives while taking into account their environmental and financial consequences (Epstein, 1996).

2.2 Eco‐tech innovation as a driver of growth The promotion of environmental protection has an impact on the company’s economic performance, to the extent that this objective can be expressed in terms of costs as well as revenue (Repetto et al. 1997). In addition, good economic performances also lead to improvement in environmental performances, considering that quality in this area represents an output that may be regarded as a differentiated product, from the company’s perspective (Ytterhus and Sjaker, 1998; Day, 1998). In reality, this causative effect between economic and environmental performances does not occur automatically. The scale of interdependence between a firm’s economic results and environmental progress depends on a well thought out effort to that end (Schaltegger, Synnestvedt; 2002).

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Céline Maximin‐Tieu Technological change is thus oriented toward techniques that are most environmentally efficient, fostered by political decisions made outside the company. In other words, public authorities today can strengthen the levels of environmental regulation, while making firms more competitive (Porter, 1991 and Porter and Linde, 1995). This hypothesis, known as the "Porter Hypothesis" is at the heart of a debate among certain economists (notably Palmer, et alii, 1995). Relying on empirical studies, Porter (op. cit.) demonstrates that environmental regulations enable (American) firms to increase their profits, when they can exploit a first mover advantage or because they use fewer inputs, leading to lower costs. Later, Porter et al (op. cit.) state that such firms owe their success more to their efficiency and good management of the use of inputs than to the low costs associated with them. Hence, the promotion of innovation as an in‐firm strategy for avoiding or exceeding local and international environmental regulations makes it possible to lower costs and, ultimately, ensure the firm’s competitiveness both nationally and internationally. In this way, firms often anticipate environmental requirements and pollution standards, and try to stay one step ahead of plans to tighten environmental policies that they must comply with. (Innes and Bial, 2002). Studies on anti‐pollution innovation have consequently focused on the choice of regulatory instruments (regulations and tax policy; viz. Freeman and Soete, 2004). However, they have not adequately taken into account the compromises made between environmental quality and the firm’s essential goal of remaining competitive. Mohr (2002) and Greaker (2006) are among those authors who contend that the existence of a stricter environmental policy does not rule out the pursuit of research and the adoption of innovations that are less harmful to the environment. Indeed, in all likelihood, a firm faced by tightening environmental policies will have to increase its expenditures and its investment in research into greener innovation, in order to enlarge its market share. These new regulatory requirements are, moreover, the source of numerous externalities (Mohr, op. cit.), which, in turn, encourage the development of cleaner technologies. In other words, in the wake of a given governmental policy, new businesses will enter the market, thereby sharpening competition, which will then allow them to take advantage of the reduction of pollution abatement costs.

3. Proactive corporate environmental strategies The growing consensus in favor of sustainable development – whether in terms of regulatory practices or customer preferences for eco‐friendly products – has served as a call for businesses to define a genuine strategy to " maintain and develop, over the long term, the potential for value creation for stakeholders by cultivating interdependences with the environment" (Martinet and Reynaud, 2004).

3.1 Sustainable development strategies: What advantage do they offer? As pointedoutinprinciple16 of the Rio Declaration (1992) 1 , firms can regard sustainable development strategies as a new form of innovation. Indeed, they represent a break in the evolution of corporate governance and have brought about a transformation in the key drivers of business. Hamal and Prahalad (1990) place particular emphasis on the interest of a strategy in relation to corporate competences building, notably as regards societal variables and, here, sustainable development. Innovation, in that instance, resembles more what is found in a “groundbreaking technology” firm than in a “planning‐oriented” firm. In that light, the notion of dynamic competencies also makes it possible to describe the nature of the relationship between innovation and corporate sustainability strategy (Teece et al., 1997). Relying on a solid base of resources, certain firms adjust to serve the imperatives of sustainable development, whereas others use them to successfully secure a strategic position in new markets. Formulating a sustainability strategy is no longer merely a matter of orienting innovation but, rather, a matter of a conscious corporate choice. It is built around a change in management practices, promoting communication around eco friendliness and is synonymous with progress. The sustainability of corporate strategy (Glavic and Lukman, 2007) is based on broad themes whose objective criteria are: natural resources usage, dematerialization of production, waste recycling, regeneration, purification and the technology chain. 1

“National authorities should endeavour to promote the internalization of environmental costs and the use of economic instruments, taking into account the approach that the polluter should, in principle, bear the cost of pollution, with due regard to the public interest and without distorting international trade and investment.”; Principle 16; Rio Declaration on Environment and Development; UN 1992.

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Céline Maximin‐Tieu Lastly, the integration and assimilation of sustainable development variables, especially in relation to research policy, lead the firm to move toward becoming an innovative organization (Nonaka et al., 1997). That organization is then in a position to "modify and increase individuals’ knowledge (their human capital) in order to create a spiral where explicit and tacit knowledge interact.” That is achieved through encouraging the sharing of knowledge between the actors”. In this way, it becomes a learning organization in the face of sustainable development constraints. Encouraging the proposal of ideas acquired through accumulated experience and a policy of (internal or external) cooperation also play a large role in the analogous development of sustainable development, which could be carried out in the framework of a Total Quality Management system (Easton and Jarell, 1998).

3.2 A specific advantage Consequently and following principle 9 of the Rio Declaration 2 , financial performance is no longer the sole "spearhead” of the company’s business. It can and must be gradually oriented toward social and environmental concerns. Stakeholder theory promotes a symmetrical approach, combining the search for locally based financial solutions (shareholder theory) and a more global and systematic vision aimed at satisfying all relevant actors coming within the company’s sphere of influence (Beckman, 2004). If the stakeholders’ commitment to the challenges of sustainable development has become an integral part of the pursuit of a corporate environmental, it is also because their activities have an impact the stakeholders themselves (Mercier, 2004). In reality, the necessary participation of stakeholders in implementing effective corporate management is also a result of the fact that they assume a certain degree of risk, insofar as they invest in human or physical capital. These investments can have various impacts or externalities on the environment, nature, and health. In this context, stakeholders take part not only in value creation within firms but also in the quest for durable growth. That is why environmental quality has come to be integrated into their considerations (Driscoll and Starik; 2004). Drawing on data contained in an OECD survey into German manufacturing firms, Frondel, Horbach and Rennings (2004) sought to determine whether environmental management plans (voluntary management‐ oriented organizational innovation) and innovations aimed at abating pollution, were correlated. They found that the enhancement of the company’s image and, consequently, its reputation, is also a potential source of strength for the adoption of an E.M.S. (Environmental Management System), whereas upstream, pro‐active policies do not seem to fundamentally influence the adaptation of innovation practices. Sustainable development strategy is partially based on tacit knowledge that is business‐ and industry‐specific, and therefore difficult for rivals to replicate. The firm bases such innovation on the mobilization of knowledge about ecological and societal sustainability issues, which serve as sources of a new competitive mindset (Sharma, 2001). The sustainable development strategy also mobilizes new competencies that are codified and deployed firm wide. Collaboration, communication and peripheral interactions in a complex environment lead to the need of a less fragmented and thus more holistic base of competence. Transdisciplinary approach shall ease offer a distinct advantage, which in turn creates a new knowledge base safeguarding firms’ competitiveness (de Kraker et al.; 2007). These forms of ‘transboundary’ competence entail specific managerial involvement.

4. An environmental sustainability solution: The competitiveness cluster The geographical proximity of industrial activities generates synergies and efficiency gains capable of stimulating innovation in skill‐intensive industries such as the chemistry sector.

4.1 Complementary skills and spatial concentration of R&D activities Two major conceptions are used to provide an overview of interest in spatial concentration in R&D and skills within a technological cluster (Giuliani, 2002). 2

“States should cooperate to strengthen endogenous capacity‐building for sustainable development by improving scientific understanding through exchanges of scientific and technological knowledge, and by enhancing the development, adaptation, diffusion and transfer of technologies, including new and innovative technologies.” Principle 9; Rio Declaration on Environment and Development; UN 1992.

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Céline Maximin‐Tieu First, there is the neo‐Marshallian approach (Becattini, 1991), which deals with an environment grouping together knowledge/learning activities, which generate spillover effects of research, as opposed to an isolated, in‐firm research laboratory. In such a context, collective learning plays an important role in creating competencies. The presence of knowledge‐oriented infrastructures (public and private laboratories or universities) helps contribute to the effectiveness of R&D (Audretsch and Feldman, 1996). The second concept, a Neo Schumpeterism approach, focuses on the role played by un‐codified, tacit knowledge, resulting from direct contacts, closely associated with the presence of the types of knowledge sought, grouped together onsite, but which are difficult to transfer (Cohen and Levinthal, 1990). Firms and research centers brought together within the cluster must be mutually complementary, to generate the creative process that characterizes research initiatives and, as such, are capable of stimulating eco‐ technologies (Antonelli, 2000). Beyond the geographical aspect, proximity is also based on strategic needs and behavioral approaches (Barabel et al., 2009). The technological cluster is intended to regroup related firms, bringing together a set of scientific qualifications as well as public institutions capable of promoting R&D, in a relatively restricted geographical area, while offering new products catering to changes in demand. Firms are able to create organizational innovations that are more open to the development of the potentials offered by their production environment. The genesis of these local competencies and local learning pools (Zuliani, 2008) will enable this new competitive structure to better respond to the demand for increasingly skill‐intensive labor. In addition, the creation of a local labor market will stimulate the development of infrastructures that are conducive to innovation: R&D policies, basic research, an enriched stock of knowledge, and regional planning (Furlan et al., 2002). Indeed, a firm cannot secure certain highly specialized knowledge unless it can build close interactions with researchers possessing this type of competence. Lastly, new strategic options of vertical fragmentation are adopted, in favor of horizontal cluster structures (Scott, 2001), favoring cooperative operations situated upstream of the R&D process, which thereby share the risks and investments inherent in this type of activity. Thus, on the firm level, sustainability entails a serious questioning of the internal mechanisms for coordinating and integrating resources. Similarly, knowledge‐based clusters being established on the bases of the triple helix government‐industry‐academia, their deployment challenges traditional organizational structures (Lansu et al.; 2013). Then, either organizational attractiveness within the delocalized business unit as well as the attractiveness of the concerned region really ought to enhance global performance of a firm through its sustainably oriented HRM policies (Beaupré et al., 2008).

4.2 Promoting sustainable development through chemistry: The Axelera competitiveness cluster As a high‐tech and skill‐intensive sector, the French chemical industry (49% of whose workforce was made up of highly skilled personnel in 2007, compared to 45 % for the rest of the French working population – [Source Insee –2007 Employment Survey]), provides an insightful case study to illustrate our point. The chemical industry companies were the second most energy‐intensive nationwide, notably as regards the consumption of petroleum products. To alleviate these negative effects, these companies have directed their investments toward eco‐friendly innovations. They have openly expressed their commitment to Green Chemistry principles, following the example of the American “Pollution Prevention Act” of 1990, enhancing the use of chemistry in preventing pollution. Green Chemistry principles apply to all chemical products and processes that contribute to the reduction or elimination of the use of hazardous substances. These practices make it possible, over time, to improve the sustainability of production processes and chemical products (Anastas and Warner, 1998). Supported by the involvement of the agglomeration of the Greater Lyon, the Axelera Chemistry‐Environment cluster serves as a good illustration of the promotion of competencies and regional activities specialized in the chemical sector. Indeed, actors from industry, education and research in chemistry, who are particularly concerned with the issue of protecting the environment in the Rhône‐Alpes region, have set up a skills development project aimed at bringing about a convergence of the regional chemical and environmental sectors. That is how the two largest French chemical firms, Arkema and Rhodia, came to join forces with Suez, a major player in environment sector, as well as with the CNRS thinking tank and IFP (Institut Français du

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Céline Maximin‐Tieu Pétrole), the French Institute of Petroleum, to implement a sustainability program in the fields of energy, transportation, and the eco innovative chemistry industry. Having implemented several mechanisms for coordinating and managing the member firms and institutions, the competitiveness cluster initiated by the Axelera alliance effectively ensures a flow of information that promotes exchanges and the pooling of knowledge. Benefiting from training systems, specialized advice, and collaborations with local public authorities, Axelera has ensured the continuity and systematic rotation of these competencies, which are increasingly specific and distinctive but necessary for the development of such a specialized and complex area of activity, such as the chemical sector. By encouraging social networks, through professional communication, the availability of contact details, and the organization of weekly brainstorming meetings, the Axelera cluster has succeeded in creating a dynamic ecosystem (Suire and Vicente, 2008) that is attractive to environmentally conscious firms. (see Table1). Table 1: Evolution of sales turnover figures for the Axelera cluster

2010

2011

(112.9%)*

(119.3%)*

(75%)*

(125%)*

Industrialization Decentralized units in the cluster belonging to a large group SMEs in the cluster

Competence management – Public intervention 5550

627

(141.3%)*

(‐72.7%)*

New educational cursus due to Axelera’s objectives

Axelera’s governance membership in an educational institution

18396

19327

(‐27.9%)*

(‐24.2%)*

6 538

6856

(‐48%)*

(‐45.5%)*

Local Communities Funds

Employment Area Number of employees

Including managers * growth rate from creation

Sources: DGCIS ‐ data collected from clusters, Insee DGCIS / Diact ‐ 4 / 5 11; Axelera.org Also, the local organizational structure tends, firstly, to initiate social interactions while keeping them within predefined limits, and, secondly, to establish common working methods and participate in drawing up collective agreements tailored to meet the parties’ specific needs (Lascoume and Le Bourhis, 1998). Within this framework, stakeholders are not merely kept informed, they are also called upon to interact on different platforms and on different levels (from the workshop/division level to the firm‐wide level). Stakeholders’ investments are best seen, then, as a means of militating for the appropriateness of certain organizational choices, with the goal of increasing their responsiveness, competitiveness and, ultimately, there social acceptance. As pointed out in Olszak (2012), through the establishment of an eco‐industrial system, blending spatial proximity between commercial partners and sustainable development of services, the Great Lyon stimulates efficiently Axelera in its objectives towards a sustainable development. The construction of an institutionalized network of competencies within the Axelera cluster serves as a basis for advancing sustainable management practices along a trajectory that builds on the interdependence between the activities of leading firms and those of SME/SMI partners, thereby creating synergy that drives competitiveness. For example, Rhodia obtained its ISO 9001 certification, partly on the merits of its internal program, designed to organize and synchronize its "Product Stewardship" efforts. This program set out to anticipate hazards associated with product storage and transportation, and to recommend risk‐prevention

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Céline Maximin‐Tieu principles at as early a stage as possible (in the R&D process and during production), while identifying the various factors necessary to reduce uncertainty. Their efforts in communication and internal organization benefit the partners as a whole, insofar as they are prompted to adjust their operations and work toward implementing quality and sustainability practices likely to affect this key player in the regional network.

5. Conclusion In light of the growing need to integrate sustainable performances into their business activities, companies are seeking to gain efficiency in their production process as well as in their organizational systems. The new challenges of environmental and social responsibility have redefined managerial behavior related to the specific culture of each business as a strategic development tool to create competitive advantage and achieve sustainability. By looking at the example of the Axelera technological cluster to illustrate our arguments, while highlighting the success of the eco innovation strategies, this paper has sought to give insight into how, in a knowledge economy, firms can modify their behavior in order to take advantage of knowledge spillover benefits (notably, geographical externalities) while avoiding negative externalities related to environmental degradation. Now, a number of firms place sustainable development at the center of their strategy and treat the issue with the same seriousness as productivity or shareholder value. In fact, sustainable development is seen as directly impacting the firm’s profitability and value creation process through the performance it helps to generate. The firm’s sustainability consciousness is predicated on the adoption of knowledge management and innovation activities, whose intangible component is crucially important. Sustainability can be exploited to become the firm’s primary driver of competitive advantage. It can also serve as a means for it to integrate environmental awareness into its efforts to respond to environmental challenges. To do so, it must adapt its approaches to skill and knowledge management in order to promote organizational performance. It is mainly reckon that managerial references to promote sustainable development remains a symbolic plaster to preserve economic performance in taking into consideration some social and environmental risks. Nevertheless, this paper shows that by enhancing the network effect, the transmission of knowledge, and managerial aiming practices, and relaying support from local public authorities, the Axelera cluster offers a valuable opportunity to see how firms perpetuate efficiently environmental practices within business organizations.

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