ECIC 2013 Volume 2 Proceedings of The 5th European Conference on Intellectual Capital by ACPIL

Proceedings of the 5th European Conference on Intellectual Capital VOLUME TWO University y of the Basque q Country, y, Bilbao, Spain 11-12 April 2013

Edited by Lidia Garcia, Arturo Rodriguez-Castellanos and Jon Barrutia-Guenaga University of the Basque Country

A conference managed by ACPIL, UK

Proceedings of The 5th European Conference on Intellectual Capital University of the Basque Country Bilbao, Spain 11-12 April 2013 Edited by Lidia Garcia, Arturo Rodriguez-Castellanos and Jon Barrutia-Guenaga University of the Basque Country Bilbao, Spain

VOLUME TWO

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. Further copies of this book and previous yearâ&#x20AC;&#x2122;s proceedings can be purchased from http://academic-bookshop.com E-Book ISBN: 978-1-909507-15-9 E-Book ISSN: 2049-0941 Book version ISBN: 978-1-909507-13-5 Book Version ISSN: 2049-0933 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 search for the conference name. 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

Committee

Biographies

viii

The Effect of Transformational Leadership on Product and Process Innovation in Higher Education: An Empirical Study in Iraq

Sawasn Al-Husseini, Ibrahim Elbeltagi and Talib Dosa

From Taxonomic to Networked Models of Intellectual Capital and its Development

Eckhard Ammann

Structural Capital, Innovation Capability, and Company Performance in Technology-Based Colombian Firms

Nekane Aramburu, Josune Sáenz and Carlos Blanco

A Structural Model for Organizational Justice in Universities Based on Intellectual Capital

Azizi Balvand, Fattah Nazem, Alireza Chenar and Omalbanin Sadeghi

What Makes an Enterprise Sustainable? Or: is “Green” Really “Green”?

Dina Barbian

Creating Virtual Mentoring Programs for Developing Intellectual Capital

Bob Barrett

The Impact of Intangibles on Value Creation: Comparative Analysis of the Gu&Lev Methodology for the United States Software and Hardware Sector

Leonardo Basso, Herbert Kimura, Juliana Saliba and Erica Braune¹

The Existence and Disclosure of Intangibles versus Corporate Financial Performance in France

Leonardo Fernando Cruz Basso, Evelyn Seligmann-Feitosa, Diógenes Bido and Herbert Kimura

The Influence of the Process of Measuring IC on Performance

Donley Carrington

The Distinctiveness of Knowledge Sharing Processes Within Multinational Companies

Vincenzo Cavaliere and Sara Lombardi

The Influence of Relational Capital on Product Innovation Performance at Innovative SMEs

Pedro Figueroa Dorrego, Ricardo Costa and Carlos Fernández-Jardon Fernández

The Role of ISO 14001 in Sustainable Enterprise Excellence

Tijana Durdevic, Cory Searcy and Stanislav Karapetrovic

Measuring the Impact of Services Innovation: What do we Know?

Susanne Durst and Anne-Laure Mention

108

Socio-Ecological Innovation: Strategic Integration of Innovation for Sustainability and Sustainable Innovation

Rick Edgeman and Jacob Eskildsen

114

Sustainable Enterprise Excellence: The Springboard Model and Assessment

Rick Edgeman and Jacob Eskildsen

123

Coupling with Standardisation and Diversity: Intellectual Capital Reporting Guidelines for European Universities

Susana Elena and Karl-Heinz Leitner

132

IC Management in Universities: Where is Teaching?

Susana Elena and Katja Pook

142

Paper Title

Author(s)

Page No.

The Role of Human Capital and Customer Capital in Supporting Product Innovation

Ahmed Elsetouhi and Ibrahim Elbeltagi

154

Effect of Investments on Training and Advertising on the Market Value Relevance of Intangibles

Lidia Garcia-Zambrano, Arturo RodriguezCastellanos and Jose Domingo Garcia-Merino

164

Intellectual Capital: An Accounting Change Perspective

Marco Giuliani

174

The Five Cs of Intellectual Capital: Two Additional Dimensions of Assessment

Uma Gupta and Joseph Azzopardi

182

Developing & Measuring Intellectual Capital: A Conceptual Model for High Technology Companies

Harold Harlow

187

The Impact of Gender and age on Knowledge Absorption: An Empirical Study on NGO Beneficiaries in Bangladesh

Sheikh Shamim Hasnain

195

Intellectual Capital in Developing Micro-States: The Case of Caribbean SMEs

Lennox Henry and David Watkins

204

Towards a Model for Measuring University Sustainability

Raine Isaksson, Mikael Johnson and Rickard Garvare

213

Architecting the Dynamics of Innovation

Ton Jörg and Stephanie Akkaoui Hughes

222

The Identification of Polish Banks Intangibles’ Significance and Efficiency

Monika Klimontowicz and Janina Harasim

231

A Structural Model for Social Capital in Banks based on Quality of Work Life

Anahita Madankar and Fattah Nazem

241

The Effect of Intellectual Assets and Intellectual Liabilities Disclosure on Financial Performance: An Empirical Analysis of Publicly Listed Companies in the United Arab Emirates

George Majdalany and Jeffrey Henderson

248

Intellectual Capital Development in Business Schools: The Role of “Soft Skills” in Italian Business Schools

Maurizio Massaro, Roland Bardy, Maria Teresa Lepeley and Francesca Dal Mas

259

Intellectual Capital Management: From Theoretical Model to a Practice Model

Florinda Matos

266

What is Intellectual Capital Management Accreditation?

Florinda Matos, Albino Lopes and Nuno Matos

279

Intellectual Capital and the System of Organisational Management

Ludmila Mládková

290

Validation Scale for Measuring Social Capital in Higher Education Institutions

Fattah Nazem and Madankar Anahita

297

Intellectual Capital’s Leverage on Shareholder Value Growth: A Lesson for Developing Economies

Bongani Ngwenya

303

Managing Intellectual Capital in the Information and Communication Industry: The Spanish Case

Maria Obeso, Maria Jesus Luengo and Maria Angeles Intxausti

314

Towards Corporate Sustainability – a Small and Medium-Sized Enterprise Perspective

Ronald Orth and Holger Kohl

323

Intellectual Capital Growth Model: Using IC Measurement Logic on AK Endogenous Model

Stevo Pucar

333

Paper Title

Author(s)

Page No.

How to Build Innovative Knowledge High-Tech Companies: An Exploratory Analysis of 22@ Companies

Maria Pujol-Jover and Enric Serradell-Lopez

344

The Impact of Corporate Governance Indicators on Intellectual Capital Disclosure: An Empirical Analysis From the Banking Sector in the United Arab Emirates

Muhieddine Ramadan and George Majdalany

351

Knowledge Management Practices as the Basis of Innovation: An Integrated Perspective

Maria João Nicolau Santos and Raky Martins Wane

362

Product Innovation Building, the Relevance of Human Capital: A Case Study

Helena Santos-Rodrigues, Luis Lousinha and Desireé Cranfield

371

Intellectual Capital and Innovation: A Hospital Case Study

Helena Santos-Rodrigues, João Faria, Carminda Morais and Desireé Cranfield

376

Human Capital and Financial Results: A Case Study

Helena Santos-Rodrigues, Guiomar PereiraRodrigues and Desireé Cranfield

384

Measurement of Intellectual Capital for Innovation

Sabina Scarpellini, Miguel Marco, Alfonso Aranda and Estrella Bernal

389

Intellectual Capital Formation in EU Cross Border Regions: Theory and Application

Klaus Bruno Schebesch and Eduardo Tomé

398

Intellectual Capital Factors as the Basis for a Brazilian Competitive Intelligence System

Camilo Augusto Sequeira, Markus Will, Eloi Fernández y Fernández, Holger Kohl and Adeline Du Toit

409

Disclosing Intellectual Capital in Tertiary Education: From Necessity to Reality

Marta-Christina Suciu, Luciana Picioruş and Cosmin Ionuţ Imbrişcă

419

Specificity of Corporate Value Creation in Different Types of Companies

Grigorii Teplykh

428

Millionaires and Intellectual Capital: An Empirical Study

Eduardo Tomé, Luliia Naidenova and Marina Oskolkova

436

ICBS Intellectual Capital Benchmarking System: A Practical Methodology for Successful Strategy Formulation in the Knowledge Economy

José Viedma Marti and Maria do Rosário Cabrita

445

Intellectual Capital (IC) in Social Media Companies: Its Positive and Negative Outcomes

Piotr Wiśniewski

455

Revived Brands as Intangible Assets: Two Qualitative Case Studies

Aleksandra Zaleśna

464

Building Intellectual Capital by Using Computer Technology for Vernacular Creativity and Well Being in Nursing Home Residents: An Action Learning Approach

John Zanetich

471

Human Capital Intangibles in Family Firms: Identification and Measurement

Patrocinio Zaragoza-Sáez, Enrique ClaverCortés and Hipólito Molina-Manchón

477

PHD Papers

485

Does National Culture Affect Intercultural Knowledge Transfer?

Dolores Bengoa

487

Intellectual Capital in the Higher Education Institutions of Latvia in the Context of International Trade

Airita Brenča and Rasma Garleja

495

iii

Paper Title

Author(s)

Page No.

The Impact of Customer Knowledge Management Process on Service Recovery Performance

Nehal El-Helaly, Ahmad Ebeid and Azza ElMenbawey

506

Questioning Prevailing Methodologies on IC, Knowledge-Intensity and Knowledge Creation

Yasmina Khadir-Poggi and Mary Keating

516

Innovation and Earnings for SMEs

José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García

523

The Quality of Information in Project Management

Jana Malá, Ľubica Černá and Dagmar Rusková

532

Relational Capital: The Role of Sustainability in Developing Corporate Reputation

Patricia Martínez García de Leaniz and Ignacio Rodríguez del Bosque

539

Adopting a Trust-Based Framework to Generate Social Capital: Espousing Social Learning and Social Capital for Enhanced Innovation, Improved Performance and Competitive Advantage

Athar Mahmood Ahmed Qureshi and Nina Evans

548

Intellectual Capital Evaluation: Return on Assets Methods Versus Market Capitalization Methods

Agne Ramanauskaite and Kristina Rudzioniene

557

University Missions: Compatible and Complementary? Theory and Empirical Analysis Through Indicators

Mabel Sánchez-Barrioluengo

564

A Conceptualization Linking Intellectual Capital, Dynamic Capabilities and Performance of Knowledge-Intensive Service Firms

Corentin Vermeulen

573

Intellectual Capital Information in Organizations Prevalence and Correlations With Organizational Performance

Janet Wee and Alton Chua

581

WIP papers

591

Particular Aspects in the Intellectual Capital Management of the Romanian SMEs

Roxana Mironescu, Andreea Feraru and Catalin Drob

593

The Role of Intellectual Capital in the Entrepreneurial Firm Innovation

Helena Santos-Rodrigues and Liliana Alves

597

Non Academic The Aleatoric leadership role - The choreography of intellectual capital in the NGO (non-profit organization)

601 Paulina Święcańska

603

Preface These proceedings represent the work of presenters at the 5th European Conference on Intellectual Capital (ECIC 2013). The Conference is hosted this year by the University of the Basque Country, Bilbao, Spain on 11-12 April 2013. The Conference Chair Professor Jon Barrutia and the Programme Chair is Lidia Garcia, both from the University of the Basque Country in Bilbao. The opening keynote address is given by Philippe Leliaert from the Maastricht School of Management, United International Business Schools, University of Brussels, Belgium and Philippe will be talking about "Reputation: Currency in the Knowledge Economy". The second day of the conference will be opened Dr Eduardo Bueno Campos from the Faculty of Economics, Universidad Aut贸noma de Madrid, Spain. Eduardo will address the issue of Dynamic analysis of The Intellectual Capital: The role of The Entrepreneurship & Innovation Capital A third keynote will be presented by Dr Jos茅 M. Viedma from UPC Polytechnic University of Catalonia, Barcelona, Spain on the subject of "Wealth creation in the knowledge economy: The microeconomic dimension" A primary aim of this conference is to contribute to the further advancement of intellectual capital theory and practice. The conference provides a platform for presenting findings and ideas for the intellectual capital community and associated fields. The range of people, issues, and the mix of approaches followed will ensure an interesting two days. 141 abstracts were received for this conference. After the double blind, peer review process there are 45 academic papers, 12 PhD papers and 2 work-in-progress papers published in these Conference Proceedings. These papers represent truly global research from some 27 different countries, including Australia, Barbados, Belgium, Boznia and Herzegovina, Canada, Czech Republic, Finland, Germany, India, Indonesia, Iran, Ireland, Italy, Luxembourg, Poland, Portugal, Romania, Russia, Serbia,, Slovak Republic, Spain, Sweden, Switzerland, Turkey, United Arab Emirates, United Kingdom and the USA. We hope that you have an enjoyable conference. Lidia Garcia Programme Chair April 2013

Conference Committee Conference Executive Lidia Garcia, University of the Basque Country, Spain Dr Jan-Erik Krusberg, Arcada University of Applied Sciences. Helsinki, Finlnd Dr Jukka Surakka, Arcada University of Applied Sciences. Helsinki, Finland Arturo Rodriguez-Castellanos, University of the Basque Country, Spain Jon Barrutia-Güenaga, University of the Basque Country, Spain Min Track Chairs Dr. Anne-Laure Mention, Public Research Centre Henri Tudor, Luxembourg Dr. Bob Barrett, American Public University, USA Dr Karl-Heinz Leitner, Austrian Institute of Technology, Vienna, Austria Dr Susana Elena-Pérez, Institute for Prospective and Technological Studies (IPTS), European Commission Florinda Matos, School of Management and Technology – Polytechnic Institute of Leiria, Portugal and ICAA - Intellectual Capital Accreditation Association Rick Edgeman, Aarhus University, Denmark Dr Piotr Wiśniewski, Warsaw School of Economics, Warsaw, Poland Dr Helena Santos Rodrigues, School of Technology and Management, Viana do Castelo Polytechnic Institute (IPVC), Portugal Dr Kent V Rondeau, University of Alberta, Edmonton, Canada

Conference committee The conference programme committee consists of key individuals from countries around the world working and researching in the intellectual capital community. The following have confirmed their participation: Dr Carl Adams (University of Portsmouth, UK); Dr. Jose-Luis Alfaro Navarro (Universidad De Castilla-La Mancha, Spain); Prof. Dr. Eckhard Ammann(Reutlingen University, Germany); Dr Heli Aramo-Immonen (Tampere university of technology, Finland); Dr Derek Asoh (Ministry of Government Services, Ontario , Canada); Dr Bob Barrett (American Public University, USA); DR Denise Bedford (Kent State University, USA); Prof Luis Borges Gouveia(University Fernando Pessoa, Portugal); Dr Ahmed Bounfour (University Paris-Sud, France); Prof/Dr Constantin Bratianu (Academy of Economic Studies, Bucharest, Romania); Dr Edgardo Bucciarelli (University of ChietiPescara, Italy); Dr Sheryl Buckley (Unisa, South Africa); Dr Acma Bulent (Anadolu University, Eskisehir, Turkey); Dr Sladjana Čabrilo (University Educons, Sremska Kamenica, Serbia); Assoc. prof. Dagmar Caganova (Faculty of Materials Science and Technology, Slovak University of Technology, Slovakia); Assoc. prof. Milos Cambal (Faculty of Materials Science and Technology, Slovak University of Technology, Slovakia); Prof. Leonor Cardoso (University of Coimbra, Portugal); Dr Daniela Carlucci (University of Basilicata, Potenza, Italy); DrDonley Carrington (University of the West Indies, Barbados ); Dr. Shulien Chang (Ming-Chuan University, Taipei, Taiwan); Dr Yuan-Chieh Chang (National Tsing Hua University, Hsinchu, Taiwan); Dr Eggert Claessens (Reykjavik University, Iceland); Prof Magdolna Csath (Kodolanyi Janos University of Applied Sciences, Budapest, Hungary); Prof. Dr. Robert De Hoog (University of Twente, The Netherlands); Dr Maria de Lourdes Machado-Taylor (CIPES, Portugal); Dr Izabela Dembinska (University of Szczecin, Poland): Associate professor Mihaela Alina Dima (Bucharest University of Economic Studies, Romania); Dr John Dumay (The University of Sydney, Australia); Dr Magdi El-Bannany (University of sharjah - College of Business Administration, United Arab Emirates); Dr. Ibrahim M. Elbeltagi (Plymouth University, UK); Dr Susana Elena-Perez (Institute for Prospective Technological Studies (IPTS) and European Commission - Joint Research Centre, Spain); Dr Scott Erickson (Ithaca College, USA); Dr Olusegun Folorunso (University of Agriculture, Nigeria); Libor Friedel (NOVATIO Consulting, Czech Republic); Dr. Albrecht Fritzsche (Capgemini, Germany); Dr Tatiana Garanina (Graduate School of Management St. Petersburg State University, Russia); Lidia Garcia (University of the Basque Country, Spain); Dr. Santanu Ghosh (University of Burdwan, India); Dr Marco Giuliani (University of The Marche, Ancona, Italy); Dr. Valerie Priscilla Goby (Zayed University, United Arab Emirates); Gerald Guan Gan Goh (Multimedia University, Melaka, Malaysia); Dr Jorge F. S. G. Gomes (ISEG-UTL and CIS/ISCTE-LUI, Portugal); Dr Miguel González-Loureiro(University of Vigo, Spain); Dr Annie Green (George Washington University , USA); Dr Tuulikki Haaranen ( Arcada University of Applied Sciences. Helsinki, Finland); Dr Markus Hagemeister (Institute of Applied Business Economics, Spain); Aki Jääskeläinen (Tampere University of Technology, Finland); Ivan Janeš (Koncar - Power Plant and Electric Traction Engineering Inc. Zagreb, Croatia); Dr Aino Kianto (Lappeenranta University of Technology, Finland); Gan Kin (MARA University of Technology, Malacca, Malaysia); Mart Kivikas (Clausthal University of Technology , Germany); Prof. DI Guenter Koch(Execupery, Vienna, Austria); Dr Jan-Erik Krusberg ( Arcada University of Applied Sciences. Helsinki, Finland); Josephine Lappia (Hogeschool Rotterdam, The Netherlands ); Prof Rongbin Lee (The Hong Kong Polytechnic University, Hong Kong); Prof. João Leitão (Polytechnic Institute of Portalegre, Portugal); Karl-Heinz Leitner (Austrian Reseach Centers, Austria); Phillipe Leliaert (Maastricht School of Management, The Netherlands); Dr Antti Lönnqvist(Tampere University of Technology, vi

Finland); DR Victor Raul Lopez (University Of Castilla La Mancha, Spain); Dr Soulla Louca (Department of Management and MIS, School of Business, University of Nicosia, Cyprus );Prof Eugenio Lucas (Instituto politcnico de leiria, Portugal); Paul Lumbantobing (PT. Telekomunikasi Indonesia, Tbk, Indonesia); Dr Agnes Maciocha (Institute of Art Design and Technology, Ireland); Prof Maurizio Massaro (University of Udine, Italy); Florinda Matos (ISCTE-IUL, Lisbon, Portugal, Portugal); Dr Gordon McConnachie (Asia Pacific IC Centre, Hong Kong, Hong Kong); Dr Anne-Laure Mention (Centre de recherche public Henri Tudor, Luxembourg); Prof. Dr. Kai Mertins (Fraunhofer IPK, Berlin, Germany); Dr Clemente Minnone(Department of General Management, School of Management and Law, Zurich University of Applied Sciences, Switzerland); Sue Molesworth (Management Suite Harplands Hospital, UK); Maria Cristina Morariu (The Academy of Economic Studies, Romania); Dr Arturo MoraSoto (Carlos III University of Madrid, Leganes, Spain); Dr Kavida Mourouganandane (Pondicherry University, India); Dr Birasnav Muthuraj (New York Institute of Technology, Bahrain); Dr Domingo Nevado Peña (Facultad de Derecho y Cien, Spain); Dr Emanuela-Alisa Nica (Center for Ethics and Health Policy (CEPS) and University "Petre Andrei" Iasi, Romania); PhD Bibiana Njogo (Unversity of Nigeria Nsukka. Enugu Campus, Nigeria); Dr Jussi Okkonen (Tampere University of Technology, Finland); Dr Abdelnaser Omran (School of Housing, Building and Planning, Universiti Sains Malaysia, Malaysia); Dr Pavlos Pavlou (Department of Management and MIS, School of Business, University of Cyprus , Cyprus ); Dr Kalin Penev (Southampton Solent University, UK); Dr. Milly Perry (The Open University of Israel, Israel); Dr Stephen Pike (Intellectual Capital Services Ltd, London, UK); Dr Michael Pitts (Virginia Commonwealth University, USA); Roman Povalej (JPS Software GmbH, Germany); Dr Agnieta Pretorius (Tshwane University of Technology (TUT), South Africa); Visisting Prof. ludo Pyis(Hong Kong, Hong Kong); Prof Thurasamy Ramayah (Universiti Sains Malaysia, Malaysia); Dr Susana Rodrigues (Polytechnic University of Leiria, Portugal); Dr Kent Rondeau (School of Public Health, University of Alberta, Canada); Mukta Samtani (University of Pune, India); Dr María-Isabel Sanchez-Segura (Carlos III University of Madrid, Spain); Prof Helena Santos-Rodrigues (IPVC, Portugal); Dr Charles Savage (FOM Fachhochschule für Ökonomie und Management, Germany); Prof Dr Klaus Bruno Schebesch (Vasile Goldis Western University Arad, Romania); Prof Georg Simet (Neuss University for International Business, Germany); Dr Vinod Singh (Gurukul Kangri University Haridwar , India); Dr Christiaan Stam (INHolland University of Applied Sciences, The Netherlands); Constantinos Stavropoulos (InnoValue, Greece); Prof.Dr. Marta-Christina Suciu (Academy Of Economic Studies Bucharest, Romania); PhD. Jukka Surakka (Arcada-University of Applied Science, Helsinki, Finland); Dr Marzena Swigon (University of Warmia and Mazury, Poland); Christine Nya-Ling Tan (Multimedia University, Melaka, Malaysia); Dr. Eduardo Tomé (Universidade Lusíada, Famalicão, Portugal); Dr Mihaela Tudor(University Paul Valery of Montpellier 3, France); Ann Turner (Queen Margaret University, Edinburgh, UK); Geoff Turner (University of Nicosia, Cyprus); Dr Belén Vallejo (University of the Basque Country, Bilbao, Spain); Professor Jose Maria Viedma (Polytechnic University of Catalonia, Spain); Dr Orestes Vlismas ( Athens University of Economics and Business (AUEB), Greece); Vilma Vuori (Tampere University of Technology, Finland); Dr Jui Chi Wang(Hsing Wu College, Taipei County , Taiwan); Maria Weir (Independent Consultant, Italy); Dr. Piotr Wisniewski (Warsaw School of Economics, Poland); Prof Inge Wulf (Clausthal University of Technolog , Germany); Dr Malgorzata Zieba (Gdansk University of Technology, Poland); Dr Mahmoud Hassanin (Pharos University,Alexandria, Eygpt); Dr Amrizah Kamaluddin (Universiti Teknologi MARA, Malaysia);

vii

Biographies Conference Chair Jon Barrutia is a Professor of Management and Business Economics at the UPV/EHU (University of the Basque Country). At the same time, on the one hand, he is a researcher of Business and Economy Research Institute of the Basque Country University since 1985, and the head of management and Business Economics department of the UPV since 2009; on the other hand, he teaches in courses related to the subject matter of Organizational Theory and Public Management, and the Undergraduate, MBA, Doctoral courses and the Executive Education.

Programme Chair Lidia Garcia Zambrano is a Researcher and Teacher in the Department of Financial Economics at the University of the Basque Country. Her research activities are oriented towards the fields of the knowledge management: assessment and financial valuation of intangibles. She is co-author of various articles in international scientific magazines. She is working on her thesis about financial valuation of intangibles.

Keynote Speakers Philippe Leliaert has over twenty years of experience in critically assessing and improving business performance. He gives advice on the strategic opportunities and challenges of the Knowledge Economy, and helps implement related organisational development & change. He focuses in particular of processes of collaborationand knowledge sharing as critical sources of sustainable competitive advantage. He is a visiting lecturer at several Business Schools, spanning South America, Europe and South East Asia. He is a regular presenter at conferences and seminars on the identification, measurement and management of Intellectual Capital, and facilitator of workshops on Performance Management and Change. Philippe has a Master of Science in Electronic Engineering (Ghent) and in Opto-Electronic and LASER Devices (Heriot-Watt, Edinburgh), and obtained his MBA at INSEAD (France). He is Certified Internal Auditor (CIA) at the Institute of Internal Auditorssince 1988. He is presently enrolled in a DBA program at United International Business Schools, which he aims to complete by July 2013. Dr Eduardo Bueno Campos is Professor of Strategic Management in the Faculty of Economics at the Universidad Autónoma de Madrid. He is a Director in the Knowledge Management Research Area of the Scientific Park in Madrid and Chair of Business Administration and Director of the Knowledge Research Society . He is CEO at the University Institute of Research in knowledge and Innovation of Business Administration (IADE) and he is Vice President of the Spanish Association of Accountability and Business Administration (AECA). He is also CEO of the Iberoramerican Knowledge Network. Dr José María Viedma Marti is a Doctor of Industrial Engineering, a graduate in Economics and Professor at the U.P.C., Polytechnic University of Catalonia in Barcelona, Spain. He teaches on the subject of knowledge management, intellectual capital management and Knowledge-based development. He has held top executive positions in computer services and management consultancy firms. Actually he is the president of "Intellectual Capital Management Systems" and a founding partner of "M.A. Fusiones y Adquisiciones". He is an advisory board member of different journals. He is a regular speaker in international conferences and congresses, his current field of research and interest is focused on knowledge and intellectual capital management and he has consulted and developed management frameworks and systems worldwide on those matters.

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Biographies of Presenting Authors Ercilia Garcia Alvarez is a Professor at the Business Management Department at the Universitat Rovira i Virgili. Ercilia is the Principal researcher of the Qualitative Research in Leisure Markets and Organizations (Qualocio) research group and senior researcher of Consumption, Markets and Culture (CMC) research group of the Universitat Autònoma de Barcelona.President of the Spanish Association for the Advancement of Qualitative Research (Espacual). Prof. Dr. Eckhard Ammann is a professor for computer science at the Reutlingen University, Germany, since 1992. Before that, he spent 8 years with the IBM Company doing research and development in parallel systems and system structures. His research interests include knowledge management, intellectual capital, business process modeling, distributed systems, and virtual organisations. Nekane Aramburu is PhD in Economics and Business Administration and member of the Strategy and Information Systems Department of Deusto Business School (University of Deusto, Spain). She specializes in the fields of Organizational Learning, Change Management, and Business Organization. Her research focus is currently on Organizational Learning, Knowledge Management, and Innovation. Zeinab Azizi Blavand has eight years of research experience at university, authored international article and her study field of interest is intellectual capital. Dr Joseph Azzopardi BA(Hons), MSc(Manc), PhD(Manc) .Joseph is Head of the Department of Management at the University of Malta. His research interests include all aspects of Human Resource Management and Development with special focus on small enterprise, Action Learning and Action Research, business and community development, organisational learning and knowledge management. Dr. Dina Barbian is Research Assistant at the Chair for Information Systems, Friedrich Alexander University of ErlangenNuremberg (Germany). Her main research interest lies in Sustainable Development. She holds a Master’s Degree in Industrial Engineering and a Doctoral Degree from the Faculty of Economics, University of Kaiserslautern (Germany). She lectures on "Sustainable Development and Macroeconomics". Dr. Bob Barrett is a professor for the School of Business at the American Public University in Charles Town, West Virginia, USA. He lectures both nationally and internationally on the topics of Intellectual Capital, Knowledge Management, Disability in the Workplace, e-Portfolios, and e-Learning. Leonardo Basso Ph.D: New School for Social Research - New York. Professor of finance: Graduate program in Business Administration - Mackenzie Presbyterian University, São Paulo, Brazil. Dolores Bengoa Ass. Prof. International Business School at Vilnius University, Lithuania is an experienced international coach and lecturer since 1992 in the field of cross cultural management, communication and intercultural knowledge transfer. She has a doctoral degree from Leeds Metropolitan University (England) as a result of her degree uses innovative and proprietary tools and techniques to improve the transferability of knowledge in cross-border business co-operations. Carlos Blanco has a PhD in Economics and Business Administration. He has been Associate Professor in the Pontificia Universidad Javeriana (Bogotá, Colombia), in the fields of Knowledge Management and Innovation. Nowadays he is consultant in these domains, having worked for different organizations: Ministry of National Education of Colombia, TES-America, Universidad Eafit, etc. Airita Brenča is a third year PhD student at the University of Latvia; she worked at the private University, Higher School of Management and Social Work ‘Attīstība’ for 15 years as an academic and administrative staff and at present she is the Head of the Department of Development Planning and Project Management in Lielvarde Municipality. Maria Do Rosario Cabrita holds a PhD and is Assistant Professor and researcher at the Universidade Nova de Lisboa, Portugal, and teaches at the Portuguese Banking Management School in Lisbon. She has several years of experience in executive positions in international banks. Her current field of research is focused on intellectual capital, knowledge management and measuring intangibles. Donley Carrington is a Lecturer in Accounting, at the University of West Indies, Cavehill Campus, Barbados. Donley Graduated UWI, Iowa State University, USA, Institute of Management Accountants USA and University of Hull, UK. Donley’s PhD thesis “An exploratory study of Intellectual Capital in the hospitality industry in the Caribbean”. Donley researches Intellectual Capital, Strategic Cost and Management Accounting. ix

Vincenzo Cavaliere is Associate Professor of Business Organization at Department of Business Administration – University of Florence. His research interests include entrepreneurship and organization learning in SMEs, knowledge sharing and strategic human resource management. He is member of AIDEA (Accademia Italiana di Economia Aziendale). Ľubica Černá, PhD has been working since 2001 on MaterialsEngineering Faculty, STU, mainly dealing with business economics/business ethics, and social dialogue. Ľubica is an author of over 90 scientific publications/publications in field of economics, economic ethics and project management. Member of team of authors working on research projects in field ofproject management/economics. Ricardo V. Costa is an Auxiliary Professor at ISMAI - Instituto Superior da Maia and a researcher at UNICES. He graduated in Economics at Universidade do Porto, and received is Phd in Business Management from Universidade de Vigo, in Spain. He got an Executive MBA in Business Strategy from Escuela de Negocios Caixanova, in Vigo, and attended the “Program in International Management” at Georgetown University in Washington. Luís Mesquita Diniz, Master`s degree in Economics from the Lusíada University of Lisbon. Attending a PhD in Economics at the Lusíada University. The thematic research focuses on Intellectual Capital and Training. Author of a paper on UFHRD EUROPE 2012 entitled “The influence of training in labor productivity”. Catalin Drob, Phd. in Management is working as a lecturer, at the “Vasile Alecsandri” University of Bacau, Engineering Faculty. His main areas of interest in teaching and research are: investment, management, project management and financial management. Tijana Durdevic is a grad student of Mechanical Engineering at the University of Alberta in Edmonton, Canada. She holds a Master of Industrial Engineering (MSc) from the University of Belgrade in Belgrade, Serbia. Currently, her research areas are Management System Standards and Implementation, Integration, and Auditing of Management Systems. Susanne Durst is Researcher at the Center for Knowledge and Innovation Research (CKIR) at Aalto University School of Economics and Assistant Professor at the Chair in International Management, Institute for Entrepreneurship, at the University of Liechtenstein. Her research interests include small business management, SME succession/transfer, IC management, knowledge management, innovation and corporate governance. Rick Edgeman is Professor of Sustainability and Performance in the Interdisciplinary Centre for Organizational Architecture at Aarhus University. He has previously chaired the Statistical Science Department at the University of Idaho (USA) and was QUEST Professor & Executive Director of the QUEST Honors Program at the University of Maryland. He has authored approximately 175 publications. Ibrahim Elbeltagi. Is a Senior lecturer in information and knowledge management, School of Management, University of Plymouth. Publications largely related to electronic commerce, adoption of ICT, information systems in developing countries, social networking and knowledge management. I have more than 40 journal and conferences papers published or accepted for publication in many national and international journals and conferences. Nehal El-Helal received her Bachelor degree in business administration from the faculty of commerce-Mansoura University. She is currently working as demonstrator in business administration department in the faculty of commerce-Mansoura University and is preparing for her masters thesis in customer knowledge management topic. Dr. Susana Elena Perez is currently a Scientific Fellow at the IPTS (European Commission). Worked as Lecturer at the Pablo de Olavide University (Spain), member of the PRIME Network of Excellence and participated in various European projects. She holds a PhD in Economics and Management of Innovation. Research interests: universities, management and governance, intellectual capital, and science and technology policy. Mr Ahmed Elsetouhi is assistant lecturer at Faculty of commerce, Mansoura University, Egypt. In 2009 till now, he is a PhD student at Business Management – Plymouth University. His research interests focus on intellectual capital, innovation, knowledge management, e-commerce- ICT and SEMs. He has published a paper at Journal of Global Information Management (3 star), and two conference papers. Jacob Eskildsen is professor of business performance management at Aarhus University and a member of the Interdisciplinary Centre for Organizational Architecture. Before entering academia Jacob worked as quality manager in a large multinational company. He holds an MSc and a PhD from the Aarhus University and is the author of more than 100 publications.

Andreea Feraru, doctorate student in Business Administration, is working as a assistant, in the “Vasile Alecsandri” University of Bacau, Faculty of Economics. His areas of interest in teaching and research are: management, knowledge management, intellectual capital, small and medium enterprises management, projects and business plans, human resources. Eloi Fernández y Fernández is a Mechanical Engineer, and is Professor of Mechanical Engineering at PUC-Rio and General Director of ONIP (National Organization of the Petroleum Industry - Brazil). Fernandez was Director of ANP (National Petroleum Agency – Brazil), State Secretary for Science and Technology, and Manager Superintendent at FAPERJ (Foundation for Research Support – Rio de Janeiro). Lidia Garcia Zambrano is a Researcher and Teacher in Department of Financial Economics at University of Basque Country. Her research activities are oriented towards the fields of the knowledge management: assessment and financial valuation of intangibles. She is co-author of various articles in international scientific magazines. She is working on her thesis about financial valuation of intangibles. Rasma Garleja is an Emeritus professor, Dr.paed., Dr.oec. She has been working as a professor at the University of Latvia since 1990; an author of the 6 monographs and 260 publications; at the moment continues to provide contribution to science at the Department of Development and Planning, University of Latvia. Rickard Garvare, Professor of Quality Management at the Division of Business Administration and Industrial Engineering, Luleå University of Technology, Sweden. Present research efforts are focused on adoption and implementation of quality related methodologies, exploring transitions from knowledge and practice. Marco Giuliani is assistant professor of Accounting and Business Administration at the Università Politecnica delle Marche (Ancona - Italy). His main research interests are in financial accounting, Intellectual Capital accounting and time accounting. He is member of national and international research groups on Intellectual Capital, financial accounting and company valuation. Dr. Uma Gupta is Professor of Management. She served as President of the State University of New York, Dean of Technology at the University of Houston, and Endowed Chair at Creighton University. She holds an MBA and PhD from University of Central Florida. She has authored two text books and more than 65 publications. Dr. Harold D. Harlow has over twenty years of experience developing new products, managing emerging businesses in wireless , aerospace and communications working for leading technology companies such as QUALCOMM, IBM, GE and Rockwell Collins as a vice president, director and product manager. Dr. Harlow researches and publishes in the areas of intellectual property and technology. Dr Sheikh Shamim Hasnain MBA and a PhD in Business and Management. Research mainly focuses on Knowledge Management, NGOs, Strategic Management, Operations Management and Military Strategies. Published in various international peer-reviewed journals. Prior to becoming an academic worked as a commissioned military officer (Major) in the Army. He has also worked as a peace-keeper under the United Nations. Lennox J Henry is a PhD student at Southampton Solent University who is in the final stage of his research; an accountant by profession, he has great interest in academia and the operationalization of IC as a tool for strategic management within organisations. Maria Angeles Intxausti is an Assistant Professor at Department of Applied Economics V at the University of the Basque Country, Spain. She has contributed to scholar area with articles and books. Her current work focuses on intellectual capital and innovation in the regional areas and clusters. Raine Isaksson is a Senior University Lecturer in Gotland University. Research interest is focused on synergies between process management and sustainable development. Another area of interest is sustainability in building supply chains with focus on building activities in Sub Saharan Africa. Additional work as cement and process consultant Dr. Eisa Ali Johali is a Saudi Expert in Health Education and Health Sciences Education born 11 Jan 1959, holding PhD in Health Sciences Hill University, USA with long experiences in curriculum, teaching and learning of Allied and Applied Medical Professions (AMPs). He has wide interests on philosophy, science, ethics and quality of AMPs Ton Jorg’s profession ion has been educational research. During the last 15 years, I got interested in complexity and education. I wrote a book about new thinking in complexity for the social sciences and humanities. Now I am seeking applications of such thinking for learning, education, complex (learning) organizations and innovation. xi

Stanislav Karapetrovic is a Professor of Mechanical Engineering at the University of Alberta in Edmonton, Canada, where he leads the Auditing and Integration of Management Systems Research Laboratory. Stanislav is spending the 2012/2013 academic year on a sabbatical leave, currently in Cartagena, Spain.

Yasmina Khadir-Poggi is a Doctoral student in the School of Business Studies at Trinity College Dublin. Besides, she lectures on International Business at American College Dublin. Her research interests include knowledge intensity in organisation, knowledge workers management and the subsequent knowledge-based development. Monika Klimontowicz is lecturer and a Ph.D. student at University of Economics in Katowice. Her latest research focuses on the role of intangibles in the process of achieving banks’ competitive advantage. Her interests include business strategy, innovation, knowledge and intellectual capital. She has been working as a marketing manager and business consultant. Karl-Heinz Leitner is a Senior Scientist, at the Austrian Institute of Technology and visiting Research Scholar at Copenhagen Business School. He Teaches Innovation Management at Technical University of Vienna. Karl Researches R&D and innovation processes, strategic management, research policy and valuation of intellectual capital. He has helped develop Austrian Intellectual Capital Model. José Manuel López Fernández. Assistant Professor, Coordinator of the Cantabrian SME Observatory`s proyects, Department of Business Administration. Area of Finance and Accounting, University of Cantabria, Spain. Maria Jesus Luengo , PhD, is Associate Professor at Department of Evaluation of Management an Busines Innovation at the University of Basque Country, Spain. She has been part of the university management as director of student and EFQM evaluator. Her current work focuses on intellectual capital and innovation in the regional areas. Anahita Madankar MA in Educational Management, with two articles in the International Conference and She is the scope of social capital. George Majdalany has a PhD and DPhil in Finance and Accounting, UGSM Monarch Business School, Switzerland. George has a CMA from USA; MBA in Finance and Accounting. Career includes working in Lebanon, Jordan, and United Arab Emirates in regional managerial positions in Finance and Accounting since 2001. Associate faculty, Departments of Finance and Accounting in several universities in United Arab Emirates since 2009. Senior CMA instructor since 2008. Patricia Martinez is a Associate Professor in Marketing and Market Research at University of Cantabria (Spain). Research interests include corporate social responsibility, corporate image and reputation, and consumer behaviour. Patricia has published in international impact journals such as International Journal of Advances in Management and Economics, Service Business or Journal of Travel and Tourism Marketing. Evandro Francisco Marques Vargas is a Professor-tutor presence of Pedagogy . Consortium UNIRIO/CEDERJ/UAB- RJ / BRAZIL . Special student of the MA in Political Sociology. State University of North Fluminense (UENF) -RJ/BRAZIL Luiz Eduardo Marques da Silva has a Ph.D. in Educational Policy. Master of Education. Teacher's Degree in Pedagogy in acting Discipline of Public Policy in Education. Federal University of the State of Rio de Janeiro (UNIRIO/Brazil)), Coordinator of Special Projects in Education and Culture (NUPEC). Maurizio Massaro is a aggregate professor, Udine University since 2008, having worked as teacher at Udine University since 2001. Maurizio is a visiting scholar, at the Florida Gulf Coast University, Florida, USA, in 2010. Academic interests primarily in measurement of business performance, intangible assets and entrepreneurship. He wrote several publications on these topics, and has some more forthcoming. Florinda Matos is completing her PhD in the area of Social Sciences. She was awarded a master's degree in business sciences by ISCTE Business School. She lectures at ISCTE - IUL, at Polytechnic Institute of Leiria and at Polytechnic Institute of Santarém. Currently, she is Intellectual Capital Accreditation Association president. Anne-Laure Mention is leading a research unit focusing on innovation economics and management within Public Research Centre Henri Tudor (Luxembourg). She is actively involved in research projects, mainly focusing on innovation and performance measurement and management in financial and business to business services industries. Research interests mainly concentrate on open and collaborative innovation, intellectual capital measurement and management, innovation and technology management. xii

Dr. Roxana Mironescu doctorate in Management, is working as a Senior lecturer, in the “ Vasile Alecsandri” University of Bacau, Faculty of Economics. His areas of interest in teaching and research are: management, human resources management, organizational behaviour, communication and negotiation. She also collaborates with some other educational professional institutions in Romania. Ludmila Mládková works as an associate professor at the University of Economics Prague, Faculty of Business Administration, Department of Management. She specializes in knowledge management, management of knowledge workers and managerial leadership. Her activities involve lecturing, writing and work with Ph.D. students. Fattah Nazem is an Associate Professor. He has been vice-president of the research department for the last five years. His research interests are in the field of Higher Education Management. He has written 2 books and 90 articles. He is Chief Executive of the Quarterly Journal of Educational Science. Bongani Ngwenya. Is the Dean at the Faculty of Business, MBA Thesis Defense Panel Chair, Lecturer/Master’s thesis supervisor at Solusi University, Zimbabwe. Many years work experience in public/private sectors. Studying PhD in Business Management and Administration, specialising in Strategic Management (Grounded Theory Research), with North West University, Mafeking Campus, South Africa. Research interests in Organisational Decision-Making Research and general business Maria 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 and organizational behaviour. Ronald Orth MBA degree from Free University of Berlin. He has gained practical experience in banking business and media industry. Since 2003 is working as senior researcher for Competence Centre Knowledge Management at Corporate Management Division of Fraunhofer IPK, Berlin, focusing on research in intellectual capital management and business processoriented knowledge management as well as sustainability management and benchmarking. Marina Oskolkova was educated at Higher School of Economics University in Perm (Russia) and became a member of Center of Applied Economics at 2008. Since 2010 became an assistant professor of Department of Financial management (Faculty of Economics). Research interests related with intellectual capital valuation, value-based management and capital structure. Dr. Katja Pook is currently managing a faculty at University of Koblenz-Landau. Katja Studies in psychology, PhD thesis on process-oriented knowledge management. Katja has worked in different companies of industry and service branches and three European projects. Since 2008 Katja has been a independent consultant. Certified Systemic Consultant, ICR facilitator. Areas of expertise: Human factors in organizational development, Knowledge Management, ICM Stevo Pucar is an Assistant Professor at the University of Banja Luka, Banja Luka, Bosnia and Herzegovina. His main teaching and research areas are economic development, economic growth theory, intellectual capital, knowledge economy. He has authored significant number of academic articles and papers and has presented worldwide. He also works as a consultant for business and in public sector. Dr. Maria Pujol-Jover has a PhD in Business Studies by the UB. She is an assistant Professor at UOC and Lecturer at UB. She is a researcher of the IN3 in the group Observatory of New Economy. During 2010/11 Maria was a co-director of the group (2009 SGR 513). Focus research: SMEs in knowledge economy and the impact of ICT in SMEs productivity and competitiveness. Athar Qureshi graduated with honours degree in computer sciences, Masters in ICT Management and is now pursuing his PhD in Knowledge Management. He started his academic career with research and teaching assistantships, lectureship and consultation. Along with his academic commitments, Athar also advise voluntarily to not-for-profit academic associations. Agne Ramanauskaite is a PhD student of economics at the Vilnius University, which is the biggest high school in Lithuania. Her PhD research interests are evaluation of the intellectual capital of an enterprise, its disclosure and analysis. Agne’s practical work is financial auditing – she holds an auditor's certificate. She also teaches audit and tax policy at the Vilnius University. Dr. Muhieddine Ramadan is an Assistant Professor at University of Wollongong in Dubai “Faculty of Finance and Accounting”. Extensive knowledge in business procedures with strong background in Finance, Accounting, Economics and Statistics. Years of multinational corporate experience within IT and Telecommunications industries. Research interests include Financial Institutions and Markets, Corporate Finance, Business Finance, International Finance and Corporate Governance.

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Ignacio Rodriguez del Bosque Professor in Marketing and Market Research at University of Cantabria (Spain). Research interests include consumer behaviour, corporate image, ethics and corporate social responsibility. Published in international impact journals such as Tourism Management, European Journal of Marketing, Journal of Business Ethics, and International Journal of Research in Marketing, among others. Participates regularly in international conferences and colloquiums. Dr Dagmar Ruskova, PhD has been working at the Slovak University of Technology at the Faculty of Materials Science and Technology since 1990. She has been dealing mainly with teaching Russian and English languages, language projects and their presentations. She is the author of about 60 articles and she also translates the papers from management. Josune Sáenz is PhD in Economics and Business Administration and member of the Finance and Accounting department of Deusto Business School (DBS). She is also main researcher of the Innovation chair sponsored by BBVA at DBS. Her research focus is currently on Innovation, Intellectual Capital, and Knowledge Management. Bahram Salavati Ph.D. candidate in labor studies program at social and political sciences department, State University of Milan, Italy. Strong interest in high-skill labour markets, working on research themes related to high-skill workers mobility & migration, skill formation systems, human capital formation and development, education and vocational training systems, skill ecosystems and high-low skill equilibrium. Mabel Sánchez-Barrioluengo is a M. fellowship to develop her PhD at INGENIO (CSIC-UPV). Her research is based on economy of education: missions of the university, university-industry relationship and human capital. Simultaneously, she collaborates with medical researchers as a consultant in statistics, having published some scientific papers in this field. Maria Santos is an Assistant Professor at the School of Economics and Management, Technical University of Lisbon and Researcher at the SOCIUS/ ISEG. She received her Ph.D. in Economic Sociology and Organizations from the Technical University of Lisbon. Her research interests include Sustainable Development, Corporate Social Responsibility, Knowledge Management and Innovation. Helena Santos-Rodrigues is a European PhD in Business Management by the University of Vigo (Spain) and holds a MBA in International Marketing and Finances. Her research interests are: intellectual Capital, Knowledge Management and Innovation. She published many papers on intellectual capital, knowledge management and innovation issues. Dr. Sabina Scarpellini is Director of Socio-Economics Area at CIRCE and Part-time associate professor at the Department of Business of the University of Zaragoza (Faculty of Economy and Business). She is Masters in Energy Markets and PhD in Renewable Energy and Energy Efficiency (University of Zaragoza). She gained her professional experience in socioeconomics, management and energy at CIRCE Klaus Bruno Schebesch Professor of Marketing Research and Computational Management Science at Faculty of Economics and Faculty of Informatics, Vasile Goldiş Western University, Arad, Romania. PhD (1990) and post-doctoral Habilitation (2002), both from University of Bremen, Germany. Research interests: automated classification by statistical learning, knowledge and cultural features, e-learning and e-collaboration for new product design, innovation processes, social network dynamics. Cory Searcy is an Associate Professor and Director of Industrial Engineering at Ryerson University in Toronto, Canada. His current research interests are in sustainability indicators, sustainable supply chain management, and integrated management systems Camilo Sequeira has a Master’s degree in Electronic Engineering from Catholic University, Rio de Janeiro, and has taught in both undergraduate and graduate programs. He has an MBA from Salford University, England. Camilo has been top executive for multinational companies. He is currently a consultant and a researcher for the Institute of Energy of PUC-Rio. João José Soares Faria is a European Master in Management of Health Units by the Polytechnic Institute of Viana do Castelo (Portugal) and holds a Post Graduation in Management of Health Facilities and Social Institutions. His research interests are: Intellectual Capital, Knowledge Management and Innovation. He published a paper on intellectual capital, knowledge management and innovation issues. Prof. Ana Kerlly Souza da Costa Ma. in Public Policy and Human Formation. NUPEC - Center for Research and Special Projects in Education and Culture. University of the State of Rio de Janeiro - UERJ (Brazil) Professor Marta-Christina Suciu has a Phd in Economics. Graduate of Cybernetics Faculty, Academy of Economic Studies Bucharest (ASE), 1981. Research fellow, National Institute for Economic Research, Romanian Academy. Since 1993 teaching & xiv

research at ASE. Now full professor & PhD supervisor in Economics, ASE. Topic of interest: Knowledge-based society, intellectual capital, KM, creative economy, investing in people and skills. Paulina Święcańska Cultural event researcher, choreographer, performer, coach and manager educated at universities in Zielona Góra, Łódź and Warsaw (Poland). Professional experience through coaching programmes in most European countries, Israel, Brazil, India and Turkey. As culture leader and manager, co-organised Warsaw Independent Art Festival. Grigorii Teplykh has graduated from Perm State Technical University and National Research University Higher School of Economics (Perm, Russia). Since 2007 he works at Higher School of Economics. He is a professor of Department of Financial management and a researcher in Laboratory of investment analysis. His interests' area embraces corporate finance, innovation economy, intellectual capital and econometrics. EduardoTome is a Portuguese economist and made is PhD thesis on Vocational Training and the European Social Fund in the Institute for Economics and Management, Technical University in Lisbon (ISEG . UTL). Since then he pubilshed more than 20 papers in refereed Journals and more than 40 papers in Conferences Proceedings, He also organized MSKE 2009, ECKM 2010, MSKE 2010 and UFHRD Europe 2012 Conferences in Lusidada Famalicão University. His main interest is intangibles in any form: IC, KM, HRD, or even Social Policies and International Economics. Corentin Vermeulen is a PhD student at HEC Liège, ULg, Belgium and researcher at the Public Research Centre Henri Tudor in Luxembourg. Before starting his research career, he worked approximately two years at Ernst & Young, Luxembourg as a financial auditor. His research interests cover the link between intellectual capital and performance of service firms. Raky Wane is an Invited Researcher at the SOCIUS - ISEG (Research Center in Economic and Organizational Sociology) and Ph.D. student at the School of Economics and Management, Technical University of Lisbon (ISEG – UTL). Her research interests include Knowledge Management, Creativity and Innovation Processes. Janet CN Wee is currently a PhD student at Nanyang Technological University (NTU). Her research areas include knowledge management and intellectual capital information. Janet has worked for two international accounting firms in their knowledge management centers. She holds a MSc (Knowledge Management) (NTU) and a BSc (Mathematics) (National University of Singapore). Dr Piotr Wiśniewski is an Associate Professor, Corporate Finance, Warsaw School of Economics. Authored numerous publications focused on performance and socioeconomic ramifications of international collective investment schemes. Interested in intellectual capital centre on growth drivers existing within economic entities – particularly financial institutions. Executive experience in European financial services; chartered membership. Aleksandra Zalesna studied at Warsaw University of Technology at the Production Engineering Faculty. In 2005 I received a Ph.D. doctorate. My doctoral thesis was on the impact of motivation systems for managers on the business performance. Now I am interested in the field of intellectual capital. John Zanetich is a Full-time Professor with a BA in Psychology, MA in Clinical Psychology, MGA (Masters in Government Administration) , and a PhD in Organizational Sciences. I have worked in state, county and city government as Director of Mental Health Programs, Regional Director of Finance and Administration and Deputy Health Commissioner. Patrocinio Zaragoza-Sáez (PhD, University of Alicante, Spain) Associate Professor, Department of Management, University of Alicante, Spain. Researches knowledge management and intellectual capital in multinationals and family firms, and identification of intangible assets. Published in many Journals.

Managing Intellectual Capital in the Information and Communication Industry: The Spanish Case Maria Obeso1, Maria Jesus Luengo2 and Maria Angeles Intxausti2 1 Department of Business Administration, Faculty of Business and Economics, University of Cantabria, Santander, Spain 2 Department of Management Evaluation and Business Innovation, School of Business Studies, University of Basque Country, Bilbao, Spain maria.obeso@unican.es mariajesus.luengo@ehu.es marian.intxausti@ehu.es Abstract: Presently, we are in a knowledge‐based economy where intellectual capital is an essential asset to improve performance in organizations. Given its importance, we present an original study about how Spanish firms manage their intellectual capital in the information and communication industry. With this study, we contribute to the literature identifying underlying factors in this process in order to examen what efforts enterprises are making. In this sense, we know that these firms pay attention to structural and human capital, especially focusing their efforts on structural capital. However, relational capital is overlooked by Spanish managers in this sector. This contribution is very important in a country in which the economic situation is very difficult. We contribute to the Spanish situation by identifying an important action (invest more in relational capital) that enterprises can do if they want to improve their situation. For this analysis, we use data obtained by Spanish National Institute of Statistics (INE) in 2010. In this sense, we use variables linked with the most common classification of intellectual capital: structural capital, human capital and relational capital. Also we include a variable linked with the general results. Using factor analysis technique, we identify eleven underlying factors that explain more than 70 percent of data variability. The paper is structured as follows: first, we realize a short introduction to the topic. In the second section, we review the concept of intellectual capital and others related terms. Then, we present our methodology. In the fourth section we present the results and a short discussion. And finally we present the principal findings of our research, limitations and future researches possibilities in the conclusions. Keywords: intellectual capital, Spanish firms, information and communication industry, factor analysis

1. Introduction In the new knowledge‐based economy, intellectual capital in enterprises supposes a strategic key in order to obtain competitive advantages (Edvinsson et al., 1996; Roos et al., 1998; Lynn, 1999; McElroy, 2002; Ming‐Chin et al., 2005; Luengo, 2011). In this sense, Bueno (1998, pp. 207‐208) defines intellectual capital as “distinctive basic skills related with intangible character that create and sustain the competitive advantage”. This definition summarizes the studies about this topic. An economy based on knowledge that has creation and cooperation in the centre of its social and economic activity (Ayestaran and Gomez, 2010) is linked to an innovation economy where organizations develop values that promote ideas and challenges (Ortiz, 2012). These ideas and challenges promote competitiveness and the sustainability of organizations over time. There is a clear relevance to studies linked with this topic and in thus the aim of this article is to identify the critical factors in intellectual capital management within the innovation process, because innovation is a fundamental value in order to create competitive advantages and intellectual capital (Luengo, 2011). In this way, innovation is based on applying talent to daily activities of knowledge workers. We use a factor analysis technique applied to the Spanish information and communication industry using the results of an innovation questionnaire of enterprises in 2010. In this sense, managers know where they should focus their efforts if they want to improve their organization´s performance managing intellectual capital. We structure the paper as follows: first we review the most important concepts about the topic in order to put in context the research, highlighting intellectual capital in organizations and we detail the aims of our article. In the next section, we describe the methodology explaining the database, variables and statistical techniques used. Then, we present the results of the analysis and a discussion. And finally, we conclude with a short conclusion about the research, limitations and future research possibilities.

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Maria Obeso, Maria Jesus Luengo and Maria Angeles Intxausti

2. Definition of concepts and the aims of the analysis In the present economic environment, cooperation between enterprises and the use of strategic resources (transferable, limited and difficult to imitate) are essential in order to maintain competitive advantages (Luengo, 2011). Intellectual capital is a term introduced by John Kenneth Galbraith in 1969 (Hsu and Fang, 2009) who identified it as the difference between a firm´s market value and book value (Edvinsson and Malone, 1997). This difference is an intangible value and is defined as a sum of individual knowledge that supposes a competitive advantage. Its link to the identification of the intangible characteristics of competitive advantage is difficult to establish (Stewart, 1997). In addition, these intangible characteristics are connected to innovation and to the difficulty of imitation by competitors, thus the competitive advantage related to intellectual capital is sustainable over time (Nahapiet and Ghoshal, 1998). Although there are several classifications of intellectual capital, the more common distinguishes three types: human capital, relational capital and structural capital (for example, following Ross et al.,1998; Bontis, 2002; or Johnson, 1998). First, human capital is linked to employees and this category includes their competence, motivation, knowledge and other intangible elements linked with people (Ming‐Chin et al., 2005). In this sense, human capital is considered the heart of intellectual capital (Pennings et al., 1998) and its management is very important because if managers don´t manage this intangible element correctly and workers leave the enterprise, the firm will lose a highlight competitive advantage (Bontis, 1999). There are some explanations about the concept of human capital given by different authors. For example, following Edvinsson and Malone (1997) human capital includes knowledge, skills, experiences and individual capabilities. However Hudson (1993) explains human capital as a combination of genetic inheritance, education, experience and attitudes that people have (Diez et al., 2010). Thus, despite the fact that both definitions are related to people, they include different aspects of people. Second structural capital is defined as the necessary infrastructure in order to create and share knowledge within the organization (Edvinsson and Malone, 1997) and we can define it as knowledge in an organization that can be explicit, systematic and internalized within people and equipments (CIC‐IADE, 2003). This is related to the organizational infrastructure in enterprises including two important terms: processing capital and innovative capital (Johnson, 1999). Processing capital is understood as operations, plans, information technology systems and others parts of the enterprises linked with its processes. And innovative capital is related to patents, copyrights, trademarks and know‐how (Hsu and Fang, 2009). Whereas human capital is linked to people more than to the organization, structural capital is related only to the firm (Diez et al., 2010). Consequently, this category includes databases, procedural manuals, strategies and routines (Bontis et al., 2000; Roos et al., 2001; Diez et al., 2010). Finally relational capital is linked to the personnel links between the organization and the stakeholders such as clients and suppliers (Jacobs, 1965; Johnson, 1999; Choong, 2008). A client base with quality, sustainability and potential in the future is a key element in an enterprise. At the same time, knowledge derived by others agents in the environment (like for example suppliers or allies) is an important intangible. In this sense, Autry and Griffis explain “investment in relational supply chain capital presents both challenges and opportunities for improved performance” (2008, p. 168). From this information, there is an important relationship between innovation and intellectual capital: the components of intellectual capital promote innovation, an activity essential in order to generate value and sustainable competitiveness. Innovation is based on people, knowledge and differentiation (Euskalit, 2011) and the EFQM model uses social interaction to innovate in order to obtain products, services, process, systems and ideas. Consequently, innovation should be a process (structural capital) composed by a combination of internal and external ideas (human and relational capital respectively) (Ortiz, 2012). In this scenario, we propose an interesting study about how Spanish firms in the information and communication industry manage their intellectual capital. Using variables linked with the three categories, we

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identify the critical factors in intellectual capital management process. Consequently, the study identifies where enterprises in Spain focus their efforts in this topic, and we identify where they should invest more. In this sense, we have chosen the Spanish case because at this time Spain is a country experiencing a difficult economic situation (Suarez, 2010), and intellectual capital management could help enterprises to improve their situation.

3. Methodology 3.1 Database and sample The sample is formed from 1856 Spanish enterprises that have paid staff. All of them operate in the information and communication industry (following the Statistical classification of economic activities in the European Communities ‐NACE). This sector is composed of NACE 60 Programming and broadcasting activities, NACE 61 Telecommunications, NACE 62 Computer programming, consultancy and related activities and NACE 63 Information service activities. Data has been obtained by the Spanish National Institute of Statistics (INE) in 2010 through a questionnaire about innovation in enterprises. This questionnaire offers information about the innovation process structure and it shows the relationship between this process and technology strategy. It was conducted following the methodology guidelines defined in the Oslo Mannual in 2002, and the directory of enterprises are composed of firms with innovation potential, firms with more than 200 workers and firms selected randomly by the DIRCE (Centralized Directory of Enterprises), obtaining a final sample composed of more than 40.000 firms in all sectors.

3.2 Variables We use different variables for our analysis, all of them related to intellectual capital. In order to follow the objectives of the paper, we select variables according to the intellectual capital categories explained in the previous section because it is the best means of identifying how Spanish firms in the Information and Communication Industry manage this topic. In addition, we add an interesting category in order to classify the enterprises: General results (see Table 1). This is important because in future research we can analyze not only what enterprises do, but also what results these enterprises obtain. We could pose such questions as: Are enterprises with better results investing in structural capital? Consequently, the categories are:

Human capital.

Structural capital.

Relational capital.

General results.

Table 1: Typology of variables, codes and descriptions Code FORMACION RETRITEC RETRINV INV AUXILIA TECNICOS BECARIOS OBJ1 OBJ2 OBJ3 OBJ4 OBJ5 OBJ6

Description Human capital Investment in training for innovation activities Salaries of technicians and assistants Salaries of researchers Researchers dedicated to R+D Assistants dedicated to R+D Technicians dedicated to R+D Scholars dedicated to R+D Structural capital The aim of the innovation activity has been oriented to improving the quality of products and/or services The aim of the innovation activity has been oriented to increasing the capacity of production The aim of the innovation activity has been oriented to increasing flexibility The aim of the innovation activity has been oriented to increasing market share The aim of the innovation activity has been oriented to reducing labor costs The aim of the innovation activity has been oriented to reducing energy consumption

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Description The aim of the innovation activity has been oriented to extending product range The aim of the innovation activity has been oriented to reducing material needs The aim of the innovation activity has been oriented to introducing in new markets The aim of the innovation activity has been oriented to increasing employement The aim of the innovation activity has been oriented to improving health and safeting The aim of the innovation activity has been oriented to increasing skilled employment The aim of the innovation activity has been oriented to reducing environmental impact The aim of the innovation activity has been oriented to maintaining employment The aim of the innovation activity has been oriented to satisfying with regulatory requirements about environmental, health or safety The aim of the innovation activity has been oriented to replacing outdated products or processes Total patents in the period 2007‐2009 Patents applied for from the Spanish office of patents and trademark (OEPM) Patents applied for from the American office of patents and trademark (USPTO) Patents applied for from the European office of patents (EPO) Patents applied for from the patents cooperation treaty (PCT) Investment in design activities and other production preparations Investment in innovations introduction in the market Investment in applied research in R+D Investment in R+D technological development Investment in basic research in R+D Investment in R+D in order to obtain products Investment in machineries and equipment in order to obtain products Investment in specific software for research and development (R+D) Relational capital External consultants dedicated to R+D Investment in external consulting for R+D Investment in other external knowledge for innovation General results Turnover Exports to the European Union Total exports

3.3 Statistical techniques We conducted an exploratory factor analysis using the SPSS program (Statistical Package for the Social Sciences). This technique is described as a “variety of statistical techniques whose objective is to represent a set of variables in terms of a smaller number of underlying variables or factors” (Kim & Mueller, 1994: p. 1). Principal component analysis (PCA) with Varimax rotation is also used in the study. Hair et al. (1995) recommend rotation because it “simplifies the factor structure and usually results in more meaningful factors” (p.380).

4. Results 4.1 Adequacy Using factor analysis, we identify eleven highlighted factors in intellectual capital management processes that explain a 74,880 per cent of the variability (see Table 2). In this sense, following Hair et al., (1995) a solution with variance explaining more than 60 percent is satisfactory, therefore our study is considered suitable. Table 2: Total variance explained

Rotation sums of squared loadings

Factor 1

Total 13,170

Percentage of variance 31,358

Cumulative pertengage 31,358

2,851

6,787

38,145

2,556

6,087

44,232

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Maria Obeso, Maria Jesus Luengo and Maria Angeles Intxausti Rotation sums of squared loadings

Factor 4

Total 2,013

Percentage of variance 4,793

Cumulative pertengage 49,025

1,961

4,668

53,693

1,925

4,583

58,276

1,851

4,407

62,683

1,533

3,651

66,334

1,225

2,917

69,251

1,196

2,846

72,097

1,169

2,782

74,880

Extracted method: Principal component analysis

4.2 Highlight factors Through the rotated component matrix, we identify eleven factors in intellectual capital management (see Table 3). Factor 1: Orientation of innovation activity The first factor is composed of all of the variables regarding the orientation of innovation activity and explains about 31 percent of the variability. In this sense, results suggest that the most important factor in manage intellectual capital is the orientation of innovation activity. In the questionnaire, managers define the degree of emphasis on different aims of innovation activity: aims oriented to products, aims oriented to processes, aims oriented to employment and other aims. It is important because these variables are categorized as structural capital; they are the managers’ intentions, and consequent changes in this vision are very difficult to measure. That means managers are essential pieces in the intellectual capital management process. Additionally, an important point is linked to the change of leaders in an organization, because when the leader changes, most likely the orientation of innovation activity changes too and it’s influences on intellectual capital management. Table 3: Rotated component matrix

Component OBJ1 OBJ2 OBJ3 OBJ4 OBJ5 OBJ6 OBJ7 OBJ8 OBJ9 OBJ10 OBJ11 OBJ12 OBJ13 OBJ14 OBJ15 OBJ16 RETRITEC RETRINV INV EXPORT EXPORTUE

1 ,911 ,909 ,902 ,898 ,897 ,892 ,891 ,889 ,882 ,879 ,875 ,874 ,873 ,873 ,871 ,859 ‐,218 ‐,218 ‐,235 ‐ ‐

2 ‐ ‐ ‐ ‐,118 ‐ ‐ ‐,121 ‐ ‐,166 ‐,147 ‐ ‐,152 ‐ ‐,114 ‐ ‐ ,937 ,937 ,831 ‐ ‐

3 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,942 ,902

4 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

5 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

318

6 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

7 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,162 ‐ ‐

8 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

9 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

10 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

11 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,117 ‐ ‐

Maria Obeso, Maria Jesus Luengo and Maria Angeles Intxausti Component CIFRA ADQMAQUI ADQUICONO FORMACION PATOEMP PATENTES INVERSOFT PATUSPTO PATEPO PATPCT CONSUL INVERCONSUL INVERDISE INVERINNO INVERINVAPLI INVERDESA AUXILIA TECNICOS BECARIOS INVERINVBA INVERID

1 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐,254 ‐,506 ‐,106 ‐,269 ‐ ‐,122 ‐

2 ‐ ‐ ‐ ‐ ‐ ‐ ,160 ‐ ‐ ‐ ,127 ‐ ‐ ‐ ,185 ,272 ‐ ‐ ,158 ‐ ,245

3 ,878 ,274 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

4 ‐ ‐ ,997 ,997 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,106

5 ‐ ‐ ‐ ‐ ,879 ,828 ,555 ‐ ‐ ,263 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,146 ,105 ‐ ,247

6 ‐ ‐ ‐ ‐ ,248 ,460 ‐,261 ,750 ,716 ,675 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐

7 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,898 ,888 ‐ ‐ ‐ ‐ ‐ ,432 ‐ ‐ ‐

8 9 10 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,127 ,148 ,196 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ,873 ‐ ‐ ,849 ‐ ‐ ‐ ,848 ‐ ‐ ‐,643 ,222 ‐ ‐ ,829 ‐ ‐ ,514 ‐ ‐ ‐ ‐ ,169 ,281 ‐ ,117 ,119

11 ‐ ‐ ‐ ‐ ,140 ,116 ‐,240 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐,120 ,127 ‐ ,721 ,624 ‐,274

Values less tan 0,1 have been deleted Factor 2: Workers’ salaries The second factor is composed of salaries of researches, technicians and assistants, dedicated at R+D. Factor two explains 6,7 percent of the variability and again, we can see the description variables. This factor is linked to people, that is to say, to human capital. Factor 3: General results The third factor, that explains around 6,087 percent of the variance, is composed of general results of enterprises: revenue in 2010, general exports, exports in the European Union and also it is composed of investment in machineries and equipment in order to obtain products. Studies like for example Ming‐Chin et al. (2005) provide empirical evidence about the relationship between better intellectual capital efficiency and revenue growth, and their result are linked to the General results factor that emphasizes it. On the other hand, there are studies about the relationship between human capital and exports in enterprises identifying a positive link (Munch and Skaksen, 2008). Factor 4: Innovation investment The fourth factor is composed of investment in innovation: investment in training for innovation activities and investment in other external knowledge for innovation, and it represents about 4,793 percent of the data variability. Again this factor is linked to human capital and also to relational capital. Factor 5: Patents Factor 5 explains around 4,668 percent of the variability, and it is composed of general patents, patents applied for from the Spanish office of patents and trademarks and investment in specific software for research and development. So this factor is linked to structural capital and also it is related to the results of innovation activity.

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Factor 6: Special patents Meanwhile, the sixth factor is composed of special patents: patents applied for from the American office of patents and trademarks, patents applied for from the European office of patents and finally patents applied for from the patents cooperation treaty, and it explains around 4,583 percent of the variability. In this sense, this factor is linked with Factor 5 and consequently, with structural capital and results of innovation. This factor is different from the previous factor because Factor 6 explains international patents, and in which the procedures are different from domestic patents. Factor 7: Consultants Factor 7 is composed of variables linked to external consults for innovation activities: external consultants dedicated to R+D and investment in external consulting for R+D. This factor alone represents about 4,407 percent of the variance. This factor is the only factor associated with relational capital. Factor 8: Introducing innovations This factor is composed of investment in design activities and investment in innovations introduced in the market, and it is explains around 3,651 percent of data variability. Thus it is linked to structural capital. Factor 9: Specifically investment The ninth factor represents around 2,917 percent of the variance and it is composed of investment in applied research in R+D and investment in R+D technological development. Therefore, factor 9 is linked with structural capital again. Factor 10: Personnel R+D Factor 10 is composed of some specifically personnel dedicated to innovation activity: assistants and technicians, and it explains about 2,846 percent of data variability. Personnel R+D is related with human capital. Factor 11: General investment in R+D Finally, factor 11 is composed of scholars, investment in basic research in R+D and investment in order to obtain products, and it represents around 2,782 percent of the variance. As consequently, this final factor is linked simultaneously to structural and human capital.

4.3 Discussion We identify eleven highlight factors that managers in enterprises should analyze in order to improve their performance and create an adequate strategy regarding intellectual capital. Results show that structural capital is the most used by Spanish managers to manage intellectual capital as the first factor Orientation of innovation activities, composed of variables linked to structural capital, explains more than 31 percent of the variance. It is linked with the improvement, adaptation and implementation of organizational processes. In addition, if we add all of the explained variance of factors linked with structural capital, we explain almost the 50 percent of the variability. Human capital is the second pillar of the intellectual capital strategy, and it is reflected in factors 2, 4 and 10 linked to knowledge workers. They represent more than 14 percent of the variance. However, relational capital has a poor influence on intellectual capital strategy linked to innovation activity, because it represents only 4,407 percent of the variability across factor 7. In summary, Spanish leaders in the information and communication industry base their intellectual capital strategy on improving structural capital (knowledge within the organization). This structural capital is essential in order to support human capital, the second pillar. And finally relational capital is overlooked by Spanish managers.

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5. Conclusions At present time, we are in a knowledge‐based economy where intellectual capital is an important asset. Given its importance, we present an original study about how Spanish firms in the information and communication industry manage their intellectual capital. The aim is contribute to the literature identifying underlying factors in this process in order to know what the efforts enterprises make. In this sense, we know that these firms pay attention to structural and human capital, especially focusing their efforts on structural capital. However relational capital is overlooked by Spanish managers in this sector. This contribution is very important in a country where the economic situation is very difficult. As we know that relational capital is important, and in this study we find that it is overlooked by managers, we contribute to the Spanish situation by identifying an important action that enterprises can do if they want to improve their situation. Related to this contribution, we make a contribution to the area of intellectual capital with an original study that could serve as a starting point for further research. 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 afterwards. Another interesting future investigation could be to compare the situation between different sectors: Do enterprises in different sectors manage their intellectual capital 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 intellectual capital like 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.

References Autry, C.W. and Griffis, S.E. (2008) Supply chain capital: The impact of structural and relational linkages on firm execution and innovation, Journal of Business Logistics, Vol 29 No. 1, pp. 157‐174 Ayestaran, S. and Gómez, O. (2010) Equipos de Innovación: Motores de transformación social y económica en las organizaciones, Innobasque, Bilbao, España Bontis, N. (1998) Intellectual capital: An exploratory study that develops measures and models, Management Decision, Vol 36 No. 2, pp. 63‐76. Bontis, N. (1999) Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field, International Journal of Technology Management, Vol 18 Nos. 5/6/7/8, pp. 433‐62. Bueno, E. (1998) El capital intangible como clave estratégica en la competencia actual, Boletín de Estudios Económicos, Vol LIII No. 164, pp. 207‐229. Choong, K.K. (2008) Intellectual capital: definitions, categorization and reporting models, Journal of Intellectual Capital, Vol 9 No. 4, pp. 609‐638. Diez, J.M., Ochoa, M.L., Prieto, M.B. and Santidrian, A. (2010) Intellectual capital and value creation in Spanish firms, Journal of Intellectual Capital, Vol 11 No.3, pp. 348‐ Edvinsson, L. and Malone, M.S. (1997) Intellectual capital: Realizing your company´s true value by findings its hidden brainpower, HarperCollins Publishers, New York, NY. Edvinsson, L. and Suvillan, P. (1996) Developing a model for managing intellectual capital, European Management Journal, Vol 14 No. 4, pp. 356‐364. Hair, J.F., Anderson, R.E., Tatham, R. and Black, W. (1995) Multivariate data analysis, Prentice Hall, Englewood Cliffs, NJ. Hsu, Y‐H and Fang, W. (2009) Intellectual capital and new product development performance: The mediating role of organizational learning capability, Technological Forecasting & Social Change, vol.76, pp. 664‐677. Hudson, W. (1993) Intellectual capital: How to build it, enhance it, use it, Wiley & Sons, New York, NY. Jacobs, J. (1965) The death and life of great American cities, Penguin, New York, NY. Johnson, W.H.A. (1999) An integrative taxonomy of intellectual capital: measuring the stock and flow of intellectual capital components in the firm, International Journal of Technology Management, Vol 18, pp. 562‐575.

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Kim, J‐O and Mueller, C.W. (1994) Factor analysis: statistical methods and practical issues. Part II, in Lewis‐Beck, M.S. (ed.), Factor analysis and related techniques, Sage, London. Luengo, M.J. (2011) Componentes de valor de los intangibles: El caso del cluster del conocimiento, Lambert Academic Publishing GmbH & Co, Leipzig, Alemania. Lynn, B.E. (1999) Culture and intellectual capital management: A key factor in successful ICM implementation, International Journal of Technology Management, Vol 18, pp. 591‐603. McElroy, M.W. (2002) Social innovation capital, Journal of Intellectual Capital, Vol 3 No. 1, pp. 30‐39. Ming‐Chin, C., Shu‐Ju, C. and Hwang, Y. (2005) An empirical investigation of the relationship between intellectual capital and firms´ market value and financial performance, Journal of Intellectual Capital, Vol 6 No. 2, pp. 159‐176. Munch, J.R. and Skaksen, J.R. (2008) Human capital and wages in exporting firms, Journal of International Economics, Vol 75, pp. 363‐372. Nahapiet, J. and Ghoshal, S. (1998) Social capital, intellectual capital and the organizational advantage, Academy of Management Review, Vol 23, pp. 242‐266. Ortiz, A. (2012) Innovación extendida: un Nuevo estadio para la innovación, Forum Calidad‐Estrategias de Excelencia Empresarial, No. 235, pp. 32‐35. Pennings, J.M., Lee, K. and Witteloostuign, A. (1998) Human capital, social capital and firm dissolution, Academid Management Journal, Vol 41, pp. 425‐440. Roos, J., Roos, R., Edvinnsson, L. and Dragonetti, N. (1998) Intellectual capital: Navigating in the new business landscape, New York University Press, New York, NY. Stewart, T.A. (1997) La nueva riqueza de las organizaciones: El capital intelectual, Granica, Barcelona. Suarez, J. (2010) The Spanish crisis: Background and policy chanllenges, CEPR Discussion Paper No. DP7909. Available at: http://ssrn.com/abstract=1640986.

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Towards Corporate Sustainability – a Small and Medium‐Sized Enterprise Perspective Ronald Orth and Holger Kohl Business Excellence Department, Fraunhofer IPK, Berlin, Germany ronald.orth@ipk.fraunhofer.de holger.kohl@ipk.fraunhofer.de Abstract: Corporate sustainability can be defined as a business approach that creates and sustains the long‐term value of a company by embracing opportunities and managing risks from three dimensions: the economic, environmental, and social perspective (Lo and Sheu 2007). In this context the development and use of intellectual capital (IC) provides an important lever for the implementation of sustainability management due to the fact that the IC of an organisation affects the performance of the three sustainability dimensions equally. A variety of sustainability management concepts point out the relevance of intangible resources whereas appropriate assessment and management approaches which reveal the contribution of IC are not or only very limited provided. Study results prove that the number of enterprises which are oriented towards sustainability has increased in recent years, but the implementation still encounters a variety of limits. This especially applies to small and medium sized enterprises (SME). Due to time and financial restrictions, many SMEs do not see themselves in a position to implement sustainable development as a part of the corporate strategy (Drenk 2009). Therefore concepts and methods have to be found in order to provide new and promising instruments in particular for SMEs which constitute the majority of Europe’s economic strength. Within this research paper different aspects regarding the integration of Intellectual Capital and Sustainability Management in a SME context should be examined in detail. Against the background of the “Fraunhofer Integrated Model” the relevance of indicators for an integrated management approach will be highlighted. In the past, in particular quantitative indicators represented the largest share of measured variables. However, more and more non‐monetary, qualitative indicators are increasingly included in the catalogues (Hirsch et al. 2004). Based on a systematic review of existing indicator catalogues, requirements and initial content for an integrated indicator format will be formulated. Against this background the aspect of benchmarking will be taken into account. The developed methodology is currently tested in a SME from the manufacturing sector. The last chapter of this paper will outline the preliminary results of this practical implementation. Keywords: sustainability, benchmarking, intellectual capital, indicators, SME, triple bottom line

1. Corporate sustainability: The Fraunhofer integrated model In recent research papers the integration potentials of intellectual capital and sustainability management were examined in more detail (Mertins and Orth 2011, 2012). Among other things different approaches of the respective areas were reviewed in a systematic way using selected criteria based on the concept of methods engineering. As a result of this work, a conceptual framework and an implementation model for an integrated perspective have been developed (Figure 1).

1.1 Conceptual framework The conceptual framework defines the basic structure and vocabulary as well as the interrelations between the single elements of the Fraunhofer Integrated Model (figure 1). Organizations are embedded in a social‐economic context. Thereby, stakeholders – representing the external environment – are given a special importance. They are interested parties claim groups which are affected by the activities, products and services of the enterprise in any manner and vice versa have effect on the enterprise at the strategy implementation and achievement of objectives (Freeman 1984). Stakeholders can appear in the form of natural persons or legal entities and they differ by their specific ethical, social and economic interests. The spectrum of potential stakeholders ranges from employees, owners as well as suppliers, customers and competitors up to authorities, trade unions, media and many more. The model also emphasizes, that an organization has at least two linkages with its external environment. On the one side, organizational activities have an impact on the external environment – in an economic, social and environmental sphere (performance perspective). On the other side the organization requires resources as input from outside of the enterprise (resource perspective).

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Figure 1: Fraunhofer integrated model: The conceptual framework To deliver its products or services an organization will combine different types of resources like human skills and knowledge, natural materials and social structures, using machinery and infrastructure and financial investment. A sustainable organization will maintain and, wherever possible, enhance these capital assets, rather than exhausting them (“capital stewardship”) (Knight 2006). In this context the capital based approach refers to the relevance of different types of resources and makes a basic distinction between tangible and intangible resources. These resources are used in business processes to improve the organizational performance. Business processes are chains of organizational activities and can be divided in primary business processes and secondary business processes. The outcome’s perspective will measure the organizational performance according to the triple bottom line dimensions: economic, social and environmental results. Table 1 provides a detailed overview on the main elements of the framework. Further details are presented and discussed in Mertins et al. (2012). Table 1: Central elements of the conceptual framework Financial Capital

Manufactured Capital

Natural Capital

Human Capital

Structural Capital

Relational Capital

Primary Business Processes Secondary Business Processes

Tangible Resources The pool of funds that is available to the organization for use in the production of goods or the provision of services, and obtained through financing, such as debt, equity or grants, or generated through operations or investments. Manufactured physical objects that are available to the organization for use in the production of goods or the provision of services, including buildings, equipment, and infrastructure. Natural capital is an input to the production of goods or the provision of services. The activities of an organization also have an impact, positively or negatively, on natural capital (e.g. water, land, eco‐system, health). Intangible Resources Human Capital includes the staff’s competencies, skills, attitudes and the employee’s motivation. Human Capital is owned by the employee and can be taken home or onto the next employer. Structural Capital comprises all structures and processes needed by the employee in order to be productive and innovative. It “consists of those intangible structures which remain with the organisation when the employee leaves” (Edvinsson and Malone 1997). Relational Capital sums up all relationships to external groups and persons established by the organization, e.g. customers, suppliers, partners and the public. Business Processes Value creation processes, e.g. innovation process, product development, manufacturing, sales, service. Management and support processes, e.g. strategy and planning process, human resource management, IT process, controlling, resource management. Performance / Outcomes

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Ronald Orth and Holger Kohl Economic Performance Social Performance Environmental Performance

Long‐term plan for securing the company's existence; incorporates stability, growth and innovation (business case of sustainability). Stakeholder Perspective: Responsibility for the society and for the employees (license to operate). Resource efficiency, e.g. energy consumption and waste, recycling concepts (e.g. cradle‐ to‐cradle).

1.2 Implementation model Against the background of the conceptual framework, the implementation model describes the four phases as well as methodologies for the implementation of the integrated management approach (figure 2).

Figure 2: Implementation model Based on the Business Model and objectives of the company (phase 1) an analysis will be conducted (phase 2). Against this background the company will define and implement actions as well as control the results (phase 3). Furthermore this can be used for the company’s internal and external communication (phase 4). Each phase can be broken down into specific actions. Table 2 provides an overview of the respective phases and activities. Table 2: Implementation procedure of the Fraunhofer integrated management model Phase Business Model

Assessment and Measurement

Implementation and Monitoring

Integrated Reporting

Activities Describe the corporate strategy and the corresponding sustainability strategy as well as the company’s value creation activities (business processes) and objectives Describe the business environment and identify stakeholders relevant to the company Define parameters and indicators for the company’s specific sustainability performance (outcome perspective) Define the company’s specific tangible and intangible resources (“capitals”) and indicators (input perspective) Conduct self‐assessments to identify strengths and weaknesses, based on the three dimensions quality, quantity and systematic management (qualitative QQS‐Assessment) Collect indicators for quantitative measurement Identify causal relations between and among the input and output factors (sensitivity analysis) Derive an integrated IC and sustainability program – including targets and actions – to improve the corporate sustainability performance Monitor and review the deployed programs and KPIs Establish a control process and conduct audits Prepare an integrated report to communicate the results internally and externally Guarantee the assurance of the reporting principles

2. Towards an integrated set of indicators Indicators should describe a quantitatively measurable fact and additionally illustrate relevant facts and relationships in a simple condensed form. At company level indicators have different functions. They can serve as targets and thus be used as a monitoring standard. Furthermore, indicators can be used as a medium for comparison, communication and illustration (Küpper 2005). Against this background indicators can add value to different phases of the implementation model described above: the definition, evaluation and external comparison of key figures lead to the identification of performance gaps. This analysis will bring valuable input for the formulation of an action plan. Results from the quantitative indicator analysis can be combined with qualitative methods like the sensitivity analysis and self‐ assessments. Indicators and their benchmarks can support the monitoring of implemented actions. Additionally the KPI analysis can add value to the internal and external reporting of an organisation.

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Ronald Orth and Holger Kohl So far a harmonized set of indicators for an integrated perspective in SME is not available. Within this paper it is aimed to analyse how quantitative and qualitative indicators can be combined in an integrated measurement system. Against this background, four indicator catalogues were selected. The choice was based on a broad research of different indicator systems. Key selection criterion was the SME focus. Furthermore, additional criteria were taken into account, i.e. consideration of sustainability issues and intangible resources. The following SME‐oriented indicator catalogues were selected on the criteria mentioned above and will be considered in more detail in the following sections: (1) BenchmarkIndex (BMI), (2) VDI Guideline 4070 (VDI), (3) Sustainable Excellence (SusEx), (4) Intellectual Capital Statement – Made in Germany (ICS). The following table shows a quantitative evaluation of the mentioned catalogues in a general overview (average values rounded). Table 3: Indicator catalogues – overview on the basic data BMI VDI SusEx ICS Avg. Min. Max. Total number of indicators 66 55 53 70 61 53 70 Number of dimensions 4 3 3 3 3 3 4 Average number of indicators per dimension 17 18 18 23 19 17 23

2.1 BenchmarkIndex Based on the widespread concept of the Balanced Scorecard (BSC), the BenchmarkIndex can be used for a comprehensive analysis and comparison of a company’s key performance indicators (Kohl 2007). The BSC serves as a holistic performance measurement based on four perspectives (Kaplan, Norton 1992). To structure the indicators, the BMI draws on this classification and assigns altogether 66 indicators in the four dimensions. Most pronounced are the internal process perspective and financial perspective (together about ¾ of all indicators). ¼ of the indicators is distributed over the dimensions customer perspective as well as learning and growth perspective (table 4). Table 4: BenchmarkIndex: overview on dimensions and indicators Number of indicators per dimension Financial perspective 22 Customer perspective 6 Learning and growth perspective 11 Internal process perspective 27 Total number of indicators 66

Procedure: In a first step, the input data for the calculation of the indicators within the own company are collected. For this, a standardized questionnaire is used. In a second step, the measured values (absolute indicators) are anonymously entered online in the BMI database and checked on plausibility. Then, based on the input data, the company‐specific indicators are calculated. Further, based on defined criteria, e.g. number of employees, turnover, industry sector, a peer group is formed. The calculated indicators of the own company are compared to the data of the previously defined peer group and then combined and visualized in a BenchmarkIndex report. Evaluation: Standard method and high international utilization rate. Beside the collection of company‐specific figures (status quo measurement) an additional value of BMI is particularly the comparison of these values with the values of an external reference group. The benchmarking of indicators is largely based on ratio indices. The majority of indicators derive from the financial and process perspective. The scope of indicators in the customer perspective (6 of 66), and learning and growth perspective (11 of 66) is relatively small.

2.2 VDI 4070 – sustainable management in SMEs The VDI guideline 4070 ("Sustainable management in small and medium-sized enterprises") shall provide particularly SMEs with a simplified and sustainability‐oriented management system. An essential part of the VDI guideline 4070 is the compilation of a total of 55 indicators to measure the sustainability performance of a company (VDI 2006). These indicators are assigned to the area of economy, environment and social issues in a quite balanced way, with a slight predominance of the ecological indicators (38%). In order to reduce entry barriers, the indicators are divided in recommended, continuative and additional figures (table 5).

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Ronald Orth and Holger Kohl Table 5: VDI 4070: overview on dimensions and indicator distribution Number of indicators per dimension Economic Ecological Social Total number of indicators

Total 17 21 17 55

Recommended 6 7 5 18

Additional 9 12 8 29

Complementary 2 2 4 8

Procedure: In addition to the survey of the indicators mentioned in the guideline, other company specific parameters can be defined and collected. It is also recommended to collect the selected indicators over several periods. Only in this way it will be possible to evaluate the development of the company in terms of sustainability or sustainable business development. The possibility of an external comparison of indicators (e.g. based on industry averages) is mentioned, but is not part of the management system described in the guideline. Evaluation: The VDI Guideline emerged through standardization and harmonization processes ("accepted consensus"). The indicator catalogue offers SMEs a good support to enter the area of "Sustainability Management" – in particular by distinguishing between recommended, additional and complementary indicators. In the context of the "social dimension", however, exclusively internal aspects are covered (employee perspective). Further, an integrative analysis of the connection between the three sustainability perspectives hardly takes place – neither conceptually nor at the level of indicators (cf. Kleine and Petrovic 2006).

2.3 Sustainable excellence The "Sustainable Excellence Approach" (SusEx) describes a sustainability oriented management system based on the Excellence Model of the European Foundation for Quality Management (EFQM). The approach was developed by the Sustainable Excellence Group (SEG) in cooperation with the Federal Foundation for the Environment. It has been updated and expanded in 2006 (SEG 2006). Against this background, possibilities of a sustainability benchmarking are described amongst others (Kaldschmidt 2009). In this context, a catalogue with 53 indicators arose. These are assigned to the three sustainability dimensions with a slight predominance (42%) of social and employee‐related indicators (table 7). Table 6: Sustainable excellence: overview on dimensions and indicators Number of indicators per dimension Financial / economic indicators Environmental indicators Social and employee related indicators Total number of indicators

15 16 22 53

Procedure: A structured questionnaire for the survey of the key figures in the three sustainability perspectives is provided. The current size of the database is not known, therefore, statements on actual results or adequacy of the sustainability benchmarking is not possible. Evaluation: In addition to the measures described in the catalogue, the SusEx approach provides further conceptual proposals which extend the present "standard key figures" by "innovative measures". While standard key figures are known by most of the companies from the classical controlling or from recognized sustainability concepts, innovative sustainability indicators are so far only used by few companies. They are usually more difficult to collect and therefore at present only to a small extent useful for an external comparison (Kaldschmidt 2009).

2.4 Intellectual capital statement – Made in Germany The "Intellectual Capital Statement – Made in Germany" is a strategic management instrument that allows SMEs to describe and evaluate their intangible resources as well as communicate their value to important stakeholder groups. For this purpose, the German ICS‐Guideline (2008) presents a total of 70 standard indicators. The indicators are used to measure intellectual capital on the basis of the dimensions of human, structural and relational capital whereby the distribution of the indicators is relatively balanced with a light predominance structural capital perspective (39%) (table 8).

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Ronald Orth and Holger Kohl Table 7: Intellectual capital statement: overview on dimensions and indicators Number of indicators per dimension Human capital 22 Structural capital 27 Relational capital 21 Total number of indicators 70

Procedure: The creation of an intellectual capital statement proceeds in eight steps and is supported by the software ICS toolbox. During the analysis phase the collection and classification of indicators is performed. Evaluation: The Intellectual Capital Statement – Made in Germany is a widely used method by small and medium‐sized enterprises in Germany (approx. 1.000 implementations). A proposal of so called standard indicators is described in the ICS Guideline (Alwert et al. 2008). In order to meet the company's individual circumstances it is recommended to add company‐specific indicators, if necessary. The indicators collected for the intellectual capital statement complement (the validation of) the qualitative self‐assessment of the so‐ called QQS workshops. The indicators proposed in the guidelines are almost exclusively absolute indicators. However, this complicates the external comparison, because a bias, e.g. by different company sizes or number of employees would be the consequence. Furthermore, financial aspects (e.g. profit, growth, profitability) are not considered within the catalogue.

3. Integration procedure – two steps In order to develop an integrated set of indicators the elements described above ‐ the conceptual framework with its specific components and the four indicator catalogues ‐ were combined in a two stage process. Result of the first stage was an assignment of more than 600 indicators on the different elements of the structural model (including multiple assignments). At the top level, the results can be summarized as follows: Resources (354 indicators), Processes (54 indicators), Results (199 indicators). The figures were further broken down for each dimension using the other elements of the structural framework (e.g. tangible and intangible resources, primary and secondary business processes, etc.). Against this background, the results were consolidated in stage two. The aim of this procedure was to identify overlaps, differences and synergies between the four catalogues. In particular, these overlaps provide information on relevant issues which play an important role within the different approaches. Here indicators which were stated several times respectively providing similar statements were grouped. Based on these preliminary results a pilot run on SME level was conducted and further expert interviews are planned. This will provide valuable input for the finalization of the integrated indicator protocol regarding the measurement of corporate sustainability – taking tangible and intangible resources into account. The allocation of the key figures is based on the framework elements mentioned above. In addition to this general relevance, the quantitative weighting of the indicators possible selection criteria can be, for example, the fundamental balance between the dimensions of the structural model ("balanced"). Also a high degree of external comparability (as basis for indicator benchmarking) is an important criterion. Therefore the objective of the SME capability should not be forgotten: The measure catalogue must not exceed a certain size and also the costs of the collection of data must remain reasonable.

4. The BenchmarkIndex as a starting point for the KPI comparison Standardised indicators can serve as a basis for the comparison of tangible and intangible resources as well as processes and performance measures. In recent years several approaches have been developed comparing companies on the basis of common indicators. These approaches can be located in the field of benchmarking or rating methodologies. While most benchmarking approaches focus on a comparison of indicators to display the company’s financial performance, intellectual capital and sustainability‐based approaches are still at the very beginning (Mertins et al. 2011, Sarkis 2012). As a starting point for an integrated perspective and in order to identify synergies, the above mentioned BenchmarkIndex (see paragraph 2.1) will be examined in more detail. The BMI seems to be meaningful for this purpose due to several reasons. The indicators of the BMI are structured along the four dimensions of the Balanced Scorecard (financial, customer, internal processes and learning/growth perspective). The BSC has

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Ronald Orth and Holger Kohl been used from several researchers as a starting point for the implementation of a corporate sustainability management (cf. the concept of the Sustainability Balanced Scorecard by Schaltegger and Dyllick 2002, Schaltegger 2011). In this context it becomes obvious that the (Sustainability) BSC concept already considers intangible aspects to some extent. In terms of a KPI based benchmarking analysis for SME, the BenchmarkIndex provides a distinctive indicator comparison with industry specific peer groups. The European BenchmarkIndex database was developed within the European project REACTE (Cranfield 2002). In order to carry out the industry specific KPI comparisons, the database is classifying enterprises according to the NACE classification code. Since the BenchmarkIndex analysis is used in more than 20 countries today, national and international indicator comparisons in more than 950 detailed structured branches of SMEs are possible. Today the BMI database contains data from more than 100,000 SME (Mertins and Kohl 2009). The benchmarking analysis consists of different steps starting with the collection of data and completing the questionnaire – available for manufacturing as well as for service companies. The effort for doing this differs depending on data availability. In general, the comparative data can be taken primarily from the balance sheet and the income statement or other controlling systems. Data, which is not included in these sources, has to be collected manually by divisional experts. After the collection, the data will be validated and entered into the data base anonymously. Thereby, the selection of the benchmarking criteria (turnover, number of employees, industry, and location) are used to identify a suitable peer group for the comparison. The results – structured along the classical dimensions of the Balanced Scorecard – are pooled in a report. In this way companies get a profile of its strengths and weaknesses on the basis of their data. The annual repetition of the comparison of the indicators is recommended. The report shows the relative position of the analysed enterprise performance within the respective peer group for each KPI. The results are illustrated statistically as well as a graphically and can be used to discuss the relevant strengths and potentials of the company (see figure 3).

. Figure 3: Extract of the BenchmarkIndex‐Report “financial perspective” (Mertins et al. 2011) As shown in figure 3 the BenchmarkIndex‐Report contains a classification scheme which shows the allocation of the performance (KPI) within the peer group according to the following five categories (Table 3): Table 8: Classification of company performances compared with peer group Weakest Figure of the company with the relatively worst result of the peer group Weak Figure of the company with a result worse than 25% of the peer group Median Figure of the company with a result worse than 50% of the peer group Strong Figure of the company with a result worse than 75% of the peer group Strongest Figure of the company with the relatively best result of the peer group

Discussion: Even though the underlying Balanced Scorecard structure of the BenchmarkIndex provides insights of a company’s performance, different issues can be identified to enhance the usage of the BMI to a more sustainability oriented instrument. Here, a more “balanced” set of indicators for measuring the sustainability performance and the resource base of a company is meaningful. Currently the most part of the

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Ronald Orth and Holger Kohl BenchmarkIndex results focuses on short and medium‐term economic improvement. Essentially this is associated with certain aspects of the social dimension of sustainability, however, the environmental dimension was until recently neglected. Therefore new conceptual developments (Mertins et al. 2011) pay attention to the incorporation of economic, social and environmental aspects of sustainability by enhancing the classical dimensions of the BSC by more sustainability oriented criteria. Furthermore it would be problematic if only typical financial figures will be used for the evaluation of the company’s success and future perspective. Most of the economic indicators are lagging indicators. They are past oriented and give little information about the expected future in the long‐term view. Many social and environmental indicators are leading indicators. They are linked to the future economic development of an organization, e.g. the customer and employee satisfaction are considered as leading indicators of sales performance (Mertins et al. 2011). Furthermore the quantitative indicators on their own provide only little insights regarding the factors behind these figures as well as the interdependencies between them.

5. Towards corporate sustainability – preliminary results on SME level The implementation model mentioned above (see paragraph 1.2) proposes four steps towards corporate sustainability: (1) definition of the ‘sustainable business model’, (2) assessment and measurement, (3) actions and monitoring and (4) integrated reporting. For this purpose a workshop based self‐assessment will be conducted to identify strengths and weaknesses, based on the three dimensions quality, quantity and systematic management (qualitative QQS Assessment) in phase two. The QQS Assessment corresponds to the specific strategic objectives defined by the company in phase one (Business Model). The evaluation of each factor is conducted according to the evaluation scale from 0‐100% (0%=not sufficient, 30%=partly sufficient, 60%=mostly sufficient, 100%=always/absolutely sufficient), whereby the strategic objectives serve as the level of reference. These qualitative findings can be combined with a quantitative analysis using measurement indicators. The results can be pooled in a reporting sheet (see figure 4) which is structured along the dimensions of the conceptual framework: resources, processes and results (see paragraph 1). In this context the reporting sheet allows a view on the companies assessment results on three levels. Level 0 shows the summarized overall results on a top level perspective using tachometer diagrams. Level 1 presents the more detailed results for a selected domain. Figure 4 for instance shows an illustration for the “Human Capital” perspective, which represents a significant part of the company’s resource base. The so called QQS bar chart – which summarizes the results of the described self‐assessment procedure – makes a distinction between the HC factors professional competence, social competence and motivation as well as leadership ability. The results can be also aggregated and visualized in tachometer diagrams showing average values for respected dimensions and/or factors. Level 2 illustrates more detailed results for selected factors; in this case, professional competence as a part of the human capital. The right hand side depicts selected indicators. They can be visualized in a time series, when collected for several periods, e.g. the development of the number of employees, the average job tenure or age distribution. Furthermore (for some selected indicators) benchmarking results can be added to the reporting sheet – based on KPI comparison using the online database of the BenchmarkIndex. This allows the company to add an additional perspective and quality of the assessment because the self‐assessment results and company specific indicators can be compared with the results of a sector specific peer group. Figure 4 for instance shows selected key figures for the factor “professional competence”, e.g. the share of new employees per all employees, total leavers or qualification or training expenditures to revenue and the values of the peer group (n=102). By the reporting sheet companies get a profile of its strengths and weaknesses on different levels. The results can be used to define and implement actions as well as control the results. Furthermore selected parts of the results can be used further for the company’s internal and external communication.

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Figure 4: Reporting Sheet for SME: An example with 3 levels of an integrated sustainability management system – illustrated with focus on the human capital perspective

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6. Conclusion A structured approach towards corporate sustainability provides the basis for a transparent assessment of the enterprise’s performance and the continual improvement of its processes, products and services along with opportunities for innovation. Benefits deriving from such an approach are resource efficiency, a high‐quality workforce, customer satisfaction and public acceptance. Based on the Fraunhofer Integrated Model this research paper described a conceptual framework and implementation model for a sustainability management system. The methodology is currently tested in a SME from the manufacturing sector. An important aspect of the approach is the development of an integrated set of indicators – which can be used for benchmarking purposes as well. One major problem of sustainability benchmarking currently is the most important requirement for any working benchmarking method: A solid KPI system. If the chosen KPIs are too particular or only company specific, the cross sector comparison sector is not possible. Therefore a harmonized set of indicators for the measurement of the sustainability performance is of enormous importance for the indicator comparison with appropriate peer groups.

References Alwert, K.; Bornemann, M. and Will, M. (2008) Wissensbilanz – Made in Germany. Leitfaden 2.0 zur Erstellung einer Wissensbilanz, Bundesministerium für Wirtschaft und Technologie (Ed.), Dokumentation Nr. 574, Berlin, [online]. Camp, R. C. (1994) Benchmarking, Hanser, Munich. Cranfield School of Management (2002) Benchmark‐Index – A European Study, Cranfield University. Drenk, D. (2009) Nachhaltiges Wirtschaften bei kleinen und mittleren Unternehmen, Kovac, Hamburg. Edvinsson, L. and Malone, T. (1997) Intellectual Capital, Harper, New York. Freeman, R.E. (1984) Strategic Management: A Stakeholder Approach, Pitman, Boston. Hirsch et al. (2004) Wertorientierte Unternehmenssteuerung, Gabler, Wiesbaden. Kaldschmidt, S. (2009) Benchmarking zur Messung und Steigerung der Nachhaltigkeit, in Mertins, K. and Kohl, H. (Ed.): Benchmarking. Leitfaden für den Vergleich mit den Besten. 2nd Edition, Symposion, Düsseldorf. Kaplan, R. S. and Norton, D. P. (1992) The Balanced Score Card. Translating Strategy into Action,Harvard Business School Press, Boston. Kleine, A. and Petrovic, T. (2006) Einspruch zur VDI‐Richtlinie 4070, Blatt 1 "Anleitung zum Nachhaltigen Wirtschaften" Dimensionen und Herausforderungen der Nachhaltigkeit, in: Schriftenreihe des Doktoranden‐Netzwerkes Nachhaltiges Wirtschaften, Vol. 8, pp 35‐40. Knight, D. (2006) The SIGMA Management Model, in: Jonker, J. and de Witte, M. (Ed.): Management Models for Corporate Social Responsibility, Springer, Berlin/ Heidelberg, pp 11‐18. Kohl, H. (2007) Integriertes Benchmarking für kleine und mittlere Unternehmen, IRB, Berlin. Küpper, H.‐U. (2005) Controlling. Konzeption, Aufgaben, Instrumente, 4th Edition, Schäffer‐Poeschel, Stuttgart. Lo, S. and Sheu, H. (2007) Is corporate sustainability a value‐increasing strategy for business? in: Corporate Governance: An International Review, Vol. 15, No. 2, pp 345–358. Mertins, K. and Kohl, H. (2009) Benchmarking, Symposion, Düsseldorf. Mertins, K.; Kohl, H. and Orth, R. (2012): Integrated Reporting and Integrated Thinking in small and medium‐sized enterprises – A Resource oriented Perspective, Proceedings 8th Interdisciplinary Workshop on Intangibles, Intellectual Capital and Extra‐Financial Information, Grenoble, France. Mertins, K., Kohl, H. and Riebartsch, O. (2011) Sustainable key‐figure Benchmarking for small and medium sized Enterprises, Proceedings 9th Global Conference on Sustainable Manufacturing, St. Petersburg. Mertins, K. and Orth, R. (2011) Integrating Intellectual Capital and Sustainability Management: Perspectives for the Internal Management and External Reporting in Small and Medium Sized Enterprises, Proceedings 3rd European Conference on Intellectual Capital; Academic Publishing International, pp 527‐536. Mertins, K. and Orth, R. (2012) Intellectual Capital and the Triple Bottom Line: Overview, Concepts and Requirements for an integrated Sustainability Management System, Proceedings 4th European Conference on Intellectual Capital, Helsinki. Mertins, K.; Will, M. and Meyer, C. (2009) InCaS: Intellectual Capital Statement. Measuring Intellectual Capital in European Small‐ and Medium sized Enterprises, Proceedings of the European Conference on Intellectual Capital 2009. Sarkis, J. (2012) Benchmarking and Process Change for Green Supply Chain Management, in: Madu, C.N. and Kuei, C‐H. (Ed.), Handbook of Sustainability Management, World Scientific Publishing, pp 87‐108. Schaltegger, S. and Dyllick, T. (2002) Nachhaltig managen mit der Balanced Scorecard. Gabler. Wiesbaden. Schaltegger, S. (2011): Sustainability as a driver for corporate economic success. Consequences for the Development of Sustainability Management Control.in: Society and Economy 33 (2011) 1, pp. 15–28. SEG – Sustainable Excellence Group (2006): Sustainable Excellence. Excellent führen – nachhaltig handeln. VDI (2006): Sustainable management in small and medium‐sized enterprises ‐ Guidance notes for sustainable management. Verein Deutscher Ingenieure, VDI Guidance 4070, Beuth, Berlin.

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Intellectual Capital Growth Model: Using IC Measurement Logic on AK Endogenous Model Stevo Pucar Faculty of Economics, University of Banja Luka, Banja Luka, Bosnia and Herzegovina stevo.pucar@blic.net Abstract: The theory of intellectual capital has experienced a boom in the first decade of 21st century. Most of the research work in this area focuses on enterprises and organizations, although there is an effort, especially lately, to provide answers concerning development of national economy. This theory has a lot of potential to create new insights and it is expected that it becomes even more incorporated into mainstream economics. This paper is an attempt to incorporate intellectual capital theory insights into endogenous growth theory as part of modern macroeconomics. In this paper, simple AK endogenous growth model is used as a basis. The intellectual capital growth model presented here also takes “A” or Total Factor Productivity as an average total productivity but with one fundamental distinction. It is using the logic of Calculated Intangible Value and/or Knowledge Capital Earnings by Baruch Lev where higher than average returns indicate higher intellectual capital. The model presented here applies this logic to Total Factor Productivity. In cases where TFP is equal to the average, the intellectual capital performance is also equal to the average, and the model is with constant returns as the AK model. But in cases where TFP is larger than average, the intellectual capital performance is also better than average, and the model is with increasing returns, and in cases where TFP is less than average, the intellectual capital performance is worse, and the model is with diminishing returns. The most important implication of the model is that savings and investments have a long‐term effect on growth only if intellectual capital performance is equal or better than average. If intellectual capital is worse than average there is no such an effect because of diminishing returns. In such a situation the policy should be first to increase intellectual capital to at least average performance and then to increase investments. Keywords: intellectual capital growth model, endogenous growth model, AK model, total factor productivity, calculated intangible value, knowledge capital earnings

1. Introduction The theory of intellectual capital has experienced a boom in the first decade of 21st century. In 1997 Sveiby published his book "The New Organizational Wealth," Stewart published his book "Intellectual Capital" and Edvinsson and Malone published book "Intellectual Capital". After that and after Bontis and McMaster University, Hamilton, Canada organized the World Congress on Intellectual Capital, from 1998 until today we have an abundance of articles, books, studies and conferences dealing with intellectual capital. Most of the research work in this area focuses on enterprises and organizations, although there is an effort, especially lately, to provide answers concerning development of national economy.

On the other hand, the new growth theory or endogenous growth theory, as part of mainstream macroeconomic growth theory, argues that economic growth is an endogenous result of the economic system, especially concerning relation of human capital and technology. What should be stressed here is that there is still an intensive work on developing new growth models, so that the endogenous theory still cannot be considered completed. This presents an opportunity to incorporate new insights from the theory of intellectual capital into the endogenous growth theory. This paper is an attempt in that direction.

First part of this paper elaborates simple AK endogenous model as basis for new model that is presented in a third part. Second part of the paper explains intellectual capital measurement logic as basis for advancing AK model. Third part is presenting a new model – Intellectual Capital Growth Model and at the end there are some concluding remarks.

2. AK model AK model is one of endogenous models within the macroeconomic theory of growth. Endogenous growth theory has emerged as an upgrade of the standard neoclassical theory of growth. Specifically, the neoclassical growth model, the so‐called Solow model is based on the law of diminishing returns, where capital and output per capita reach a steady state regardless of the initial conditions.

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Stevo Pucar The key feature of the AK endogenous growth model (Rebelo, 1992, and others) is that this model assumes that there are no diminishing returns to capital. Unlike the neoclassical model, the AK model uses a linear model in which the output is a linear function of capital.

AK model is based on a simple premise. For each additional unit of capital, income will increase by constant amount, and the relationship between income and capital will always be proportional. To model this, it is only necessary to assume that share of capital in factor income equals 1. The income will depend on the capital

or in per capita terms

(1)

(2)

A is a positive average that reflects the level of total productivity K is capital L is labor

The Figure 1 is showing the production function, savings and depreciation the same way as the Solow model.

Figure 1: Production function, savings and depreciation in AK model In this model, there are no diminishing returns on capital and production function is linear. With the growth of capital, output rises proportionately, and since savings are proportional to output, the savings function is also linear. The depreciation is linear as in the Solow model. The income here depends on the capital and the growth rate of output is equal to the growth rate of capital. First, growth of capital is (for the simplicity we will assume that population is constant):

s is rate of savings δ is rate of depreciation of capital

Δk = sf ( k ) − δk (3)

When we substitute f(k) with Ak we get: Growth rate of capital gk is:

Δk = sAk − δk (4)

Δk / k = sAk / k − δk / k

Since gk = gy then

gk = sA − δ

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(5)

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gy = sA − δ

(6)

The basic implication of the model is the fact that the savings function and the function of depreciation are straight lines which never intersect. As there is no intersection, savings will always, except at the origin, will be higher of depreciation and capital will continue to grow.

When we are talking about the AK model, the most interesting implication in terms of economic policy is the fact that the increase in the national savings rate raises living standards. Every public policy that increases the rate of savings accelerates economic growth. The model also implies a divergence between economies. If two economies start with different initial capital stocks, then the absolute gap will be increasing.

3. Intellectual capital measurement logic According to Bontis (1998) claims, the term "intellectual capital (IC)," was first introduced by John Kenneth Galbraith, who considered that, in addition to the classic, pure knowledge, creative knowledge is of great importance for the economic activity. The difference between the human capital and intellectual capital is in the fact that intellectual capital is not just knowledge and skills that can be acquired by learning and training. It is a whole set of intangible assets used to create value.

The theory of intellectual capital began to be more present in international public during the late 1990s of the last century. At that time one of the pioneers in this field, Stewart (1997) described intellectual capital as a brand new topic for that era, in which there are a lot of wandering.

Together with human capital, theory of intellectual capital is based on the structural and customer capital (Bontis, 1998, Edvinsson and Malone 1997, Stewart, 1997, etc.). Structural capital is created by work of human capital in the past and it consists of patents, concepts, models, networks, systems, and organizational culture. Customer capital includes relationships with customers and suppliers, brand names, trademarks and reputation or image of the company.

The study of intellectual capital means the study of the thing that is immaterial. Therefore the key problem in this area is its measurement. Unfortunately, the fact that it is intangible, regardless of the simplicity of the concept, becomes a problem for researchers when it is necessary to measure it.

According to Sveiby (2001, 2010) there are four categories of measurement approaches.

Direct Intellectual Capital methods (DIC) asses the monetary value of intangible assets through identification of its various components. Components are directly evaluated individually and/or as an aggregated coefficient.

Scorecard Methods (SC) also asses the intangible assets through identification of its various components. The difference from DIC method is that there is no monetary valuation since indicators of components are reported in scorecards.

Market Capitalization Methods (MCM) use difference between market capitalization and the book value as the value of intellectual capital of a company.

Return on Assets methods (ROA) divide average pre‐tax earnings by the average tangible assets of the company and then compare it with its industry average. The above‐average earnings are divided by the average cost of capital and the result is an estimated value of intellectual capital of the company.

Here we will pay attention to Return on Assets methods (ROA). It has always been recognised that the balance sheet of a company certainly does not represent the real value of an enterprise. Determining the value of a company by using Return on Assets methods has been common practice among investors for many years and is still used today. The method for ROA based intellectual capital calculation divides average pre‐tax income into average assets employed over a period in order to establish the rate of return achieved by the enterprise. This rate of return is then compared to the industry average to establish the performance of the enterprise in relation to its peers. Where the return generated by the enterprise is higher than the industry average, this is deemed to be as a result of the intellectual capital of the enterprise and the excess return is discounted using an appropriate

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Stevo Pucar discount factor in order to arrive at a present value for intellectual capital or the intangible asset value of the enterprise.

Stewart (1995) explains Calculated Intangible Value methodology by using an example of company Merck:

Calculation of average pre‐tax earnings for three years – $3.7 billion.

Calculation of average year‐end tangible assets for three years – $12.9 billion.

Dividing earnings by assets to get the return on assets (ROA) – 29 percent.

Calculation of industry’s average ROA for the same three years. For pharmaceuticals the average is 10 percent.

Calculation of the “excess return”. The industry average ROA is multiplied by the company’s average tangible assets – 10 percent x $12.9 billion. These are earnings of average drug company with the same tangible assets. This is subtracted from the company’s pre‐tax earnings. For Merck this is an excess of $2.4 billion. According to Stewart (1995), this is how much more that company earns from its assets than the average drug manufacturer.

Calculation of the three‐year‐average income tax rate, which has to be multiplied by the excess return. This result is subtracted from the excess return to get an after‐tax figure. This is the premium attributable to intangible assets. For Merck, with an average tax rate of 31 percent, this is $1.65 billion.

Calculation of the net present value (NPV) of the premium. This is done by dividing the premium by an appropriate percentage, such as the company’s cost of capital. Using an arbitrarily chosen 15 per cent rate, this yields Merck $11 billion. This is the CIV of Merck’s intangible assets.

Knowledge Capital Earnings (KCE) is methodology proposed by Lev (2001). First, he calculates earnings of the company (an average of earnings 3 years before and the forecasted earnings for 3 years after). From that earnings, he subtracts earnings of financial assets using given average after‐tax return on financial assets and earnings of physical assets using given average after‐tax return on physical assets. The result are earnings that cannot be atributed either to financial assets or to physical assets. According to Lev (2001) these earnings are knowledge capital earnings. He is using these earnings to calculate intellectual capital of the company and various other indexes and ratios. It must be emphasized here that the rate of return on financial assets and the rate of return on physical assets are taken as given averages.

4. Intellectual capital growth model 4.1 Description of the model Underlying thought of the model presented here is an assumption that ideas, i.e. intellectual capital plays a crucial role in economic growth. We will begin with equations (1) and (2) shown in AK model

or in per capita terms

A is a positive average that reflects the level of total productivity and represents all intangible factors of production, i.e., ideas. K is capital, and represents all tangible factors that are used in production process, i.e., things L is labor Until now everything is the same as in AK model. Now we make a crucial distinction. We will express Ak in the following way: Ai k=( A k)α (7) Ai is total factor productivity for a specific country

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A is average supranational total factor productivity (of the world or of group of similar countries or based on some specific criteria, structure of economy, etc.) α is an exponent or power that shows value of output with TFP of specific country as an α power of output with average supranational TFP We are now going to apply logic of IC measurement in explanation of this concept. In Calculated Intangible Value we use industry average ROA, use it to calculate earnings of average company within the same industry with the same tangible assets, compare it to actual ROA (same assets in both cases) and determine the difference which represents performance of intellectual capital. In this growth model the same logic is used. Output A k represents output that would be produced with average supranational total factor productivity. Output AiK is actual output produced with country specific total factor productivity using the same capital. The relation of those two outputs is considered as an indicator of intellectual capital performance in this model. Using this logic, power α is showing to what extent intellectual capital performance of specific country is better or worse than average intellectual capital performance. If α=1 intellectual capital performance is equal to average, if α>1 intellectual capital performance is better than average and if α<1 intellectual capital performance is worse than average. Since α is a power that shows a performance of intellectual capital we shall call it Intellectual Capital Power. We are going back to the model. First we will formulate the model: (8)

The Figure 2 is showing the production function, savings and depreciation for this model with α=1 when intellectual capital performance is equal to average.

Figure 2: Production function, savings and depreciation with α=1 This model is with constant returns and behaves as simple AK model. With the growth of capital, output rises proportionately, and since savings are proportional to output, the savings function is also linear. The depreciation function is also linear. The Figure 3 is showing the production function, savings and depreciation for this model with α<1 when intellectual capital performance is worse than average.

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Figure 3: Production function, savings and depreciation with α<1 This model is with diminishing returns. With the growth of capital, output function is with diminishing returns, and since savings are proportional to output, the savings function is also diminishing returns. The depreciation function is linear.

The Figure 4 is showing the production function, savings and depreciation for this model with α>1 when intellectual capital performance is better than average.

Figure 4: Production function, savings and depreciation with α>1 This model is with increasing returns. With the growth of capital, output function is with increasing returns, and the savings function is also with increasing returns. The depreciation function is linear. Concerning growth rate, as similar as in simple AK model, the income will depend on the capital and the growth rate of output is equal to the growth rate of capital. This is why we first have to determine the growth rate of capital. α First, we will use the equation (3) and substitute f(k) with ( A k) to get:

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Stevo Pucar (9)

Growth rate of capital gk is:

Since gk = gy then

(10)

(11)

It has to be noted that

is average/marginal product of capital calculated as ratio of output to capital

(y/k). Now, for the case when α=1 growth rate is determined as similar as in simple AK model:

(12)

The Figure 5 is showing the growth rate gy for this model with α=1 when intellectual capital performance is equal to average.

Figure 5: Growth rate gy with α=1 The growth of output is constant here and can be continued infinitely. For the case when α<1 growth rate is decreasing because with growth of capital k output‐capital ratio

is decreasing.

The Figure 6 is showing the growth rate gy for this model with α<1 when intellectual capital performance is worse than average.

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Figure 6: Growth rate gy with α<1

The growth of output can be continued here only until investments become equal to depreciation. This is similar to the Solow model.

For the case when α>1 growth rate is increasing because with growth of capital k output‐capital ratio

increasing. The Figure 7 is showing the growth rate gy for this model with α>1 when intellectual capital performance is better than average.

Figure 7: Growth rate gy with α>1 The growth of output is increasing here and can be continued infinitely.

The most important implication of the model is that savings and investments have a long‐term effect on growth only if intellectual capital performance is equal or better than average. If intellectual capital is worse than average there is no such an effect because of diminishing returns. In such a situation the policy should be first to increase intellectual capital performance to at least average and then to increase investments.

4.2 Discussion of the model This model claims that if the country keeps up with growth of knowledge, ideas, technology, i.e. intellectual capital or, even better, pushes its boundaries, it will grow in the long term. On the other hand, if it fails to do so, it will face diminishing returns and growth problems.

It must be emphasized here that this model is the one of the first attempts to introduce intellectual capital as a concept to macroeconomic growth theory. Even concerning knowledge, macroeconomic growth theory did not include it as a concept for many years. In the early nineties, mainly based on the work of American economist Paul Romer (1986, 1990, 1993), a new paradigm, now commonly known as "endogenous growth theory" is created.

Romer's crucial contribution to economic theory is the creation of growth model in which ideas play a crucial role in economic growth. Romer (1993) divides factors into ideas and things. Things are all physical objects that exist around us, whether natural or manmade. They are scarce, behave by the law of diminishing returns and cannot create economic growth by themselves. On the other hand, ideas are not scarce. He claims that human beings have unlimited ability to use new “recipes” for rearrangement of things. The fact of central importance, according to Romer (1993), is that the possibilities for new ideas are almost inexhaustible.

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Stevo Pucar As we said before, underlying thought of the model presented here is also an assumption that ideas, i.e. intellectual capital plays a crucial role in economic growth. This model is based on the assumption that TFP and intellectual capital are two sides of the same coin.

Since it was created, TFP is the one of most important issues in economic growth theory. Тhe impact of TFP on economic growth is also well documented. Among many others, Easterly and Levine (2002) find that Total Factor Productivity, measured as Solow residual, “accounts for most of the income and growth differences across nations.” The crucial problem of TFP is its real meaning. This is still an open question. TFP is still measured as a residual and is still “a measure of our ignorance” (Abramovitz, 1956). We still need deeper insights of what TFP really is, since Solow residual gives us pretty dismal notion of it. The stream of papers that treat TFP in alternative way as index number (Caves et al. 1982; Fare et a.l 1994; and others) offers more space to comprehend this issue.

The similar thing is with intellectual capital, since its definition is also dismal. As noted earlier, Sveiby (2001, 2010) systemized many different approaches to intellectual capital. The one of them considers intellectual capital as the sum of human, structural and customer/relational capital. The other one is defining intellectual capital of a company as difference between its market capitalization and the book value. There is also an approach that relates intellectual capital to above‐average earnings. Within those 3 approaches Sveiby (2001, 2010) distinguishes 42 different concepts of intellectual capital and its measurement.

Concerning national intellectual capital, first studies were based on the methodology created by Edvinsson and Malone (1997). Thus Rembe (1999), analyzed intellectual capital in Sweden. In other Scandinavian countries, similar projects were promoted (Malhotra, 2003). Israeli scientists have also identified the importance of intellectual capital for economic development (Pasher, 1999; Pasher and Shachar, 2007). A similar report was made in Poland and was based on the same methodology (Boni, 2009). Another group of studies examines the macroeconomic impact of intellectual capital as an economic driver. There are several such studies. For example Bounfour and Stahle (2008) measure the economic effects of intellectual capital on the macro level using a large number of indicators, on the sample of 51 countries. Some other studies have applied measurement models that were originally developed for the micro level. Corrado et al (2009) estimate intangible capital in the U.S. economy expanded by using their own methodology for microeconomic research. Recently, the large share of the national intellectual capital research use complex unique indexes created on the basis of a large number of different indicators. These models also rely on microeconomic foundations. The most common taxonomy that is used here is Edvinsson and Malone (1997). For example, Bontis (2005) has created a unique index that measured the situation in the Arab countries. Andriessen and Stam (2005) used a similar approach in assessing the state of intellectual capital in the European Union. All other studies of national intellectual capital used this methodology to a greater or lesser extent (Bounfour, 2005a; Lin and Edvinsson, 2011; Veziak, 2007). However, the key problem with the use of composite indexes is that they lack firm theoretical foundations which brings into question their validity (M'Pherson and Pike, 2001, Malhotra, 2003, Stahle, 2006). Based on our review of the literature, we can see that there is only one study that attempts to integrate this type of indicators in the framework of macroeconomic growth theory (Muhsam, 1970).

Since TFP is one of the most important topics in the theory of growth, a key direction in creation of this model was to connect the concept of productivity with the concept of intellectual capital. Concerning TFP, Romer (1990) sees it as set of instruction, designs or recipes, basically set of ideas for rearrangement of things. Although there are many definitions of intellectual capital, here in this paper we consider intellectual as a set of ideas (and relations) used to create value.

There is also more essential connection of these two concepts. The productivity, in essence, is the relation of output and inputs. Since it shows how much of output is created with given inputs, in value terms it entirely depends on the amount of new value that is created out of those given inputs. And the concept of intellectual capital is all about the creation of value. Intellectual capital represents an active transformation of knowledge into a new value, value‐added products or services. This is the reason why these two notions are linked in this model. If we prove that this is true then intellectual capital offers deeper explanation of what TFP really is and TFP could become the most important performance measure of intellectual capital on aggregate level.

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5. Conclusion In one of his famous papers on ideas and things Romer (1993) says: “A nation that lacks the knowledge used to create value in a modern economy suffers from an idea gap.” This thought was a leading thought in creation of this model. The model presented here gives theoretical framework in which it is clear that ideas or intellectual capital performance, measured as productivity, is most important for a long‐term growth. Intellectual Capital Power α is an indicator of idea gap. If it is less than 1, country suffers from an idea gap.

What could this model mean in the real world? Intuitively, this could mean that most enterprises in economies with α larger than 1, are leaders in competitiveness. In these economies enterprises do things in most effective and efficient way, push boundaries of existing technologies, innovate and create new technologies. Also it is probable that most enterprises in economies with α equal to 1 keep up with productivity changes or intellectual capital performance of their competition. In these economies most enterprises operate with average effectiveness and efficiency. For example, they could use up‐to‐date technologies but do not innovate enough to be able to push things beyond current technology. In both cases the policy would be to increase investments in order to achieve higher standard of living, since intellectual capital performance is enabling long‐term growth.

On the other hand, most enterprises in economies with α less than 1 probably lag behind productivity or intellectual capital performance of their competition. In other words, in these economies most enterprises do thing in less effective and efficient way or use older technologies. These economies suffer from an idea gap and, as we said, the policy should be first to increase intellectual capital performance to at least average and then to increase investments.

In spite of the simplicity of the concept that is underlying the model presented in this paper, empirical testing will probably be much more difficult. The current growth accounting methodologies and data sets that are adapted to those methodologies do not offer too many possibilities for empirical testing of the model. This is because Total Factor Productivity (TFP) is most often empirically measured as Solow residual, representing TFP growth rate. In order to make sense of this model, further theoretical and empirical work on TFP is needed especially using the intellectual capital theory. We need deeper insights of what TFP really is, since Solow residual gives us pretty dismal notion of it.

Another problem is the definition of the supranational average values. It is an open question shall we use averages of the world or of group of similar countries or based on some specific criteria, structure of economy, etc. This will need a careful analysis, since different averages can completely change whole picture. In addition to work on TFP, this will also need both theoretical and empirical analysis.

References Abramovitz, M. (1956) Resource and Output Trends in the U.S. since 1870, American Economic Review, 46(2), pp. 5‐23 Andriessen, D., Stam, C. (2005) Intellectual capital of the European Union, Hamilton, Ontario, Canada. Caves, D. W., Christensen, L. R. and Diewert, W. E. (1982), The economic theory of index numbers and the measurement of input, output and productivity, Econometrica, 50: 1393‐1414. Boni, M. (2009). Intellectual capital of Poland. Kancelaria Prezesa Rady Ministrów, lipiec 2009. Available at: http://www.swisschamber.pl/de/act/upl_imp/other_downloads /report _int_capital_poland_english.pdf. Bontis, N. (1998) Intellectual Capital: An exploratory study that develops measures and models, Management Decision, 36, 2, 63‐76. Bontis, N. (2005) National intellectual capital index: The benchmarking of Arab countries, In: Bounfour, R, A., Edvinsson, L. (ed.) Intellectual capital for communities: Nations, regions, and cities (pp. 113‐138). Oxford, UK: Elsevier Butterworth–Heinemann. Bounfour, A. (2005) Assessing performance of European innovations systems: An Intellectual Capital Indexes Perspective, In: Bounfour, R, A., Edvinsson, L. (ed.) Intellectual capital for communities: Nations, regions, and cities (pp. 97‐112). Oxford, UK: Elsevier Butterworth–Heinemann. Corrado, C., Hulten, C., Sichel, D. (2009) Intangible capital and U.S. economic growth, Review of Income and Wealth, 55, 661‐685. Easterly, W., Levine, R., (2002) It´s Not Factor Accumulation: Stylized Facts and Growth Models, Central Banking, Analysis, and Economic Policies Book Series, in: Norman Loayza & Raimundo Soto & Norman Loayza (Series Editor) & Klaus Schmidt‐Hebbel (Series Editor) (ed.), Economic Growth: Sources, Trends, and Cycles, edition 1, volume 6, chapter 3, pages 061‐114 Central Bank of Chile. Edvinsson, L. and Malone, M. (1997) Intellectual Capital, Harper Business, New York.

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Stevo Pucar Fare, R., Grosskopf, N., M. and Zhang, Z. (1994), Productivity growth, technical progress and efficiency changes in industrialized countries, American Economic Review, 84: 66‐83. Lev, B. (2001) Intangibles: Management, and Reporting. Brookings Institution Press, Washington, DC. Lin, C., Edvinsson, L. (2011) National intellectual capital: A comparison of 40 countries, New York Dordrecht Heidelberg London, Springer New York. M’Pherson, P., Pike, S. (2001) Accounting, empirical measurement and intellectual capital, Journal of Intellectual Capital, 2, 246‐260. Malhotra, Y. (2003) Measuring knowledge assets of a nation: Knowledge systems for development, UNDESA, UN. Available at: http://unpan1.un.org/intradoc/groups/public/documents/un/unpan011601.pdf Muhsam, H. V., (1970) The assessment of the validity of human resources indicators by means of Cobb‐Douglass production function, UNESCO: Division of socio‐economic analysis. Retrieved from http://unesdoc.unesco.org/images/0015/001585/158562eo.pdf. Pasher, E. (1999). The intellectual capital of the state of Israel, Herzlia Pituach, Edna Pasher PhD & Associates. Pasher, E., Shachar, S. (2007) The intellectual capital of the state of Israel: 60 years of achievement, Retrieved from http://www.moital.gov.il/ic Rembe, A. (1999) The governmental invest in Sweden Agency – ISA: Report 1999, Halls Offset AB, Stockholm. ISA: Report 1999. Halls Offset AB, Stockholm. Romer, P.M. (1986) Increasing Returns and Long Run Growth, Journal of Political Economy, 94, 1002–37. Romer, P.M. (1990) Endogenous Technological Change. National Bureau of Economic Research, Working Paper 3210, Cambridge MA, www.nber.org/papers/w3210.pdf Romer, P.M., (1993) Idea gaps and object gaps in economic development, Journal of Monetary Economics, Elsevier, vol. 32(3), pages 543‐573. Stahle, P., (2006) Intellectual capital and national competitiveness: Conceptual and methodological challenges. In: Bounfour, A. (ed.) Capital immatériel, connessaince et performance (pp. 415‐429). Paris: L’Harmattan. Stahle, P., Bounfour, A. (2008) Understanding dynamics of intellectual capital of nations, Journal of Intellectual Capital, special issue of Intellectuall Capital of Communities: The Next Step, 9, 164‐177. Stewart, T. (1995) Trying to grasp the intangible, Fortune Magazine, pp 52‐69. Stewart, T.A. (1997) Intellectual Capital: The New Wealth of Organizations, Doubleday/Currency, New York. Sveiby K. (1997) The New Organisational Wealth, Managing and Measuring Knowledge‐Based Assets, Berrett‐Koehler, San Fransisco. Sveiby, K.E., (2001, 2010) Methods for Measuring Intangible Assets, Available at: http://www.sveiby.com/Portals/0/articles/IntangibleMethods.htm Weziak, D. (2007) Measurement of national intellectual capital: application to EU countries, IRISS Working Paper Series, 2007, 1‐45.

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How to Build Innovative Knowledge High‐Tech Companies: An Exploratory Analysis of 22@ Companies Maria Pujol‐Jover and Enric Serradell‐Lopez Business and Management Department, Open University of Catalonia, Barcelona, Spain mpujoljo@uoc.edu eserradell@uoc.edu Abstract: In year 2000 the City of Barcelona launched the 22@ project, also known as districte de la innovació (innovation district). The aim of this project is to convert the Poblenou area into the city's technological and innovation district. During the last 10 years this district has attracted 10 universities with over 25,000 students, 12 R&D centres and 1,500 companies employing over 44,000 workers, most of which were highly qualified. The aim of this paper is to present the results of a field research conducted at 200 companies from 5 different sectors in the 22@ district. This field research consists of an exploratory statistical analysis of several key variables related to innovation strategy, organization, human resources policies and management systems. Other variables under study are related to the tools used in innovation (such as the degree of collaboration with other companies, universities and/or technology centres, and technological surveillance, as well as the participation in international markets) and the results of innovation in intellectual capital terms (patents, trademarks or designs). The results from this research allow identifying the main strategies used by companies to exploit the intellectual capital they possess, which are basically to arrange license agreements and to use it internally. The presented research is intended to be a useful reference for managers and public institutions interested in using the experience of 22@ as an insight for the creation of technology centres of excellence based on knowledge and innovation. Keywords: innovation, knowledge management, innovation outputs, business intelligence, multivariate analysis

1. Introduction The 22@ project was officially launched in 2000. The local authorities of Barcelona transformed two hundred hectares of industrial land located in Poblenou area into an innovative district offering modern spaces for the strategic concentration of intensive knowledge‐based activities. Its aim was to boost economic activity in emerging sectors in which Catalonia had the potential to achieve a competitive position in the international markets. This was done by means of promotion policies and the revaluation of the 22@ district. It is the most important project of urban transformation ever undertaken in Barcelona. This project can be compared in magnitude and importance to similar projects carried out in Europe. It had also a very high real‐estate potential and implied an investment of 180 million Euros by the public authorities. The location strategy undertaken by local authorities in the 22@ district consisted of establishing a close relationship with a management company, so that it could guide the industry cluster and therefore boost the competitiveness of these companies. Initially the project comprised four different clusters: (a) media, (b) information and communication technology (ICT), (c) medical (TecMed) and (d) energy technologies. However, in 2008 the design sector was absorbed by the project due to its relevance and strategic value. Clusters can be characterised as networks of strongly interdependent firms (including specialised suppliers), knowledge‐ producing agents (universities, research institutes, engineering companies), bridging institutions (brokers, consultants) and customers, linked to each other in a value‐adding production chain (DETR, 2000). Currently, 22@ district is composed by 83,640 business premises according to the City register, 42.5% more 2 than in 2002. This shows an average growth of the number of companies per m higher than the overall growth rate for the whole city. Additionally, 42% of its urban soil is occupied by premises used for economic or service activities, more than the 33% for the city as a whole. The latest available census of the 22@ district shows 7,064 companies and 4,400 freelance workers. The number of companies has grown by 105.5% since 2000, when there were 3,437 businesses. This increase is well above the average for both the province of Barcelona (57.3%) and Catalonia (60%). Besides, 4,500 companies have moved to the district since 2000, an average of 545 per year and 1.2 per day, although the most prolific period was 2003‐2006. 47.3% of these companies are new start‐ups, the remaining coming from other locations. Finally, 27% of companies in 22@ are knowledge‐intensive and 31% of the companies created after 2000 are knowledge‐ or technology‐intensive.

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Maria Pujol‐Jover and Enric Serradell‐Lopez The estimated number of workers in the district is 90,000 (excluding freelance workers), showing a growth rate of 62.5% with respect to the year 2000, when there were 56,200 workers. Additionally, the global business turnover of firms located in the 22@ district, for all types of economic activities, totals some 8,900 million Euros per year. Since 2001, the resident population in 22@ district has grown by 22.8%, from 73,464 inhabitants to 90,214 inhabitants. This increase is 15% higher than the average for the city of Barcelona, which experienced a growth of 8% between 2001 and 2009. The average growth in this time period was 13.7% for the metropolitan area and 17.9% for Catalonia. Some examples of companies and institutions located in the 22@ district are the College of Nursing, Voxel Group, Amphos 21 Consulting, Agencia EFE, Neo Advertising, Lunatus, Catalan Consumer Agency, Tecnogeo, Esabe Distributed Computing, Knowledge Innovation Market Barcelona, Madaus, ADP Employer Service Iberia among others. (Source: http://www.22barcelona.com). Based on previous contributions, Casanueva et al. (2010) stated that clusters are more innovative for two reasons. Firstly, they benefit from agglomeration economies, such as the size of nearby suppliers or direct observation of competitors. Secondly, they benefit from network effects increased by social interaction. With this in mind, this paper tries to understand the main aspects and attributes of the 22@ companies related to innovation and knowledge management in a cluster context by undertaking a statistical exploratory analysis. The main variables and the methodology are explained hereafter.

2. Methodology Sample description This paper is part of the ongoing research, focusing on KM and innovation. In order to study the 22@ companies a survey was implemented during the end of the year 2010. The companies analysed in this research belong to five clusters, are fairly heterogeneous and show different maturity levels. The company Kim Bcn (www.kimbcn.org) conducted a personal interview with each of the directors of the companies surveyed. This study is a first extraction of the information obtained. All answers were recorded in a database and were analyzed with standard statistical packages. The database has been checked for possible mistakes due to data entry inaccuracies. The whole questionnaire has been omitted for the sake of brevity. However, it is available upon request. The data and variables are presented in several subcategories

2.1 General information of the companies A percentage of 89% of the companies are SME (micro, small or medium size enterprises), which implies that they have 50 employees or less. Unlike some studies found in the literature, we haven’t excluded companies with few employees (see for example, Darroch and McNaughton 2002). Thus, the criterion used to select the companies has been purely geographical. Table 1: Company information Sector

Count

% Subtable

Food and Beverage

1.0%

Design

19.6%

Energy

4.5%

Industrial

3.5%

Media

13.6%

Services

0.5%

Business Services

5.5%

TecMed

15.6%

ICT

35.7%

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Count

% Subtable

Other

0.5%

Subtotal

199

100.0%

Large

11.1%

Medium

10.1%

Small

39.7%

Micro

39.2%

Subtotal

199

100.0%

Size

60,4% of the companies were created after the year 2000 and were classified according to the following sectors: food and beverage, design, industrial, media, services, business services, TecMed, ICT and others (see Table 1).

2.2 State of innovation Managers were asked about innovation following Oslo’s Manual guidelines. Innovations can be implemented either in products or processes. In any case, all managers who participated in the study were given the opportunity to mention all types of innovation they undertook. The combination of innovation in product and processes was the most common answer (24% of total, see Table 2 and 3). As Newman remarks, “So far, the competitive nature of knowledge in terms of value and time shows us that knowledge is not a static commodity, and its value lies in its exploitation to deliver New Market Values or expectations by destabilizing existing positions of competitive products in terms of entry to market and relative value” (Newman, 1997). In our case, the influence of innovation under the point of view of organization or marketing is complementary to the process or product innovation as shown in Table 3. Table 2: Innovation strategy descriptive statistics Different Types of Innovation Different Degrees of Innovation Persons in Dep. R & D & i Different Types of Innovation Strategies Different Management Systems Different Innovation Sponsors Valid N (listed)

Valid N 199 199 171 199 199 199 171

Mean 1.83 1.21 16.92 1.13 1.04 1.48

Std. Dev. .970 .571 121.814 .976 .299 .881

Another important factor to consider relates to the type of innovation. It must be noted that 5% of the companies conduct all three types of innovation. As it is known, radical innovation is likely to be competence‐destroying, often making existing skills and knowledge redundant (Tushman and Anderson, 1986). Incremental innovation does not require a significant departure from existing business practices, and is likely to enhance existing internal competences by providing the opportunity for those within the organization to build on existing know‐how (Tushman and Anderson, 1986). In our case, companies consider incremental innovation mainly as a tool in order to reduce costs or enhance products or processes. Continuous innovation applies small modifications in processes or products on a day to day basis.

2.3 Quality methodology There are generally three broad objectives of KM in organizations: leveraging the organization’s knowledge, creating new knowledge or promoting innovation, and increasing collaboration and therefore enhancing the skill level of employees (Bose, 2004). Table 3 shows how the companies introduce innovation. They can do so by using their own methodology or by following the rules and procedures of quality norms, such as UNE 166.002 or ISO 9000. We observe that most companies use their own methodology (61.3%).

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2.4 Leadership KM involves changes that may not easily gain the organization’s acceptance unless the leadership mobilizes the middle managers to provide an environment conducive to the widespread sharing of knowledge (Mohamed et al., 2004). Thus, Table 3 shows that the managers from the Top Management Team (TMT) are the strongest promoters of innovation (51.3%). The R+D department promotes as little as 4.5 %. Table 3: Innovation strategy

Innovation Type

Innovation Degree

Management System

Innovation Sponsors or Leadership

Product Process Organization Marketing Product & Process Product, Process & Organization Product, Process, Organization & Marketing Product & Organization Product & Marketing Process & Organization Process, Organization & Marketing Process & Marketing Organization & Marketing Missing Subtotal Radical Incremental Continuous Improvement Radical & Incremental Radical, Incremental & Continuous Improvement Radical & Continuous Improvement Incremental & Continuous Improvement Missing Subtotal Own Methodology UNE 166.002 ISO 9000 Day to Day Own Methodology & ISO 9000 Own Methodology, UNE 166.002 & ISO 9000 Missing Subtotal Management R & D & i / Technical Dept. Marketing Dept. Other Management & R & D & i / Technical Dept. Management & Marketing Dept. Management & Other Management, R & D & i / Tech. Dept. & Mkt. Dept. Management, R & D & i / Technical Dept. & Other Mngment, R & D & i / Tech. Dept., Mkt. Dept. & Other R & D & i / Technical Dept. & Marketing Dept. R & D & i / Technical Dept. & Other R & D & i / Technical Dept., Marketing Dept. & Other Missing Subtotal

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Count 61 13 6 4 48 13 17 3 10 6 5 4 5 4 199 35 32 89 9 10 2 16 6 199 122 1 13 48 7 1 4 196 102 9 2 5 29 3 5 19 6 5 1 1 1 11 199

% Subtable 30.7% 6.5% 3.0% 2.0% 24.1% 6.5% 8.5% 1.5% 5.0% 3.0% 2.5% 2.0% 2.5% 2.0% 100.0% 17.6% 16.1% 44.7% 4.5% 5.0% 1.0% 8.0% 3.0% 100.0% 62.2% 0.5% 6.6% 24.5% 3.6% 0.5% 2.0% 100.0% 51.3% 4.5% 1.0% 2.5% 14.6% 1.5% 2.5% 9.5% 3.0% 2.5% 0.5% 0.5% 0.5% 5.5% 100.0%

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2.5 External knowledge acquisition Knowledge depositories are created incorporating knowledge developed either internally or externally through imitation, benchmarking and collaborative agreements (Pérez‐Bustamante, 1999). In any case some tools are used in order to obtain the external knowledge and complementing the internal knowledge generated inside the company. Tools quoted by managers are Internet, patents database, journal or customer‐suppliers connectivity and networking are the more used. Table 4 offers more detailed information on these tools and how companies use them. Table 4: Innovation tools Technological Watch

Technological Watch Types

Technological Watch Tools

Yes No Subtotal Systematized External Systematized & External Missing Subtotal Traditional Technological Watch Modern Technological Watch Traditional & Modern Technological Watch Not Traditional or Modern Techn. Watch Subtotal Internet Patent databases (PD) Customer‐Supplier (CS) Journals Internet & Patent databases Internet & Customer‐Supplier Internet & Fairs Internet & Networking Internet & Journals Internet, Patent databases & CS Internet, Patent databases & Fairs Internet, Patent databases & Networking Internet, Customer‐Supplier & Fairs Internet, Customer‐Supplier & Networking Internet, Customer‐Supplier & Journals Internet, Fairs & Networking Internet, Networking & Journals Internet, Patent databases, CS & Fairs Internet, PD, CS & Networking Internet, CS, Fairs & Networking Internet, CS, Fairs & Journals Internet, CS, Networking & Journals Internet, Fires, Networking & Journals Internet, PD, Fairs & Networking Internet, PD, CS, Fairs & Networking Internet, PD, CS, Fairs & Journals Internet, PD, CS, Networking & Journals Internet, PD, Fairs, Networking & Journals Internet, CS, Fairs, Networking & Journals Internet, PD, CS, Fairs, Netw. & Journals Patent databases & Customer‐Supplier Customer‐Supplier & Fairs Missing Subtotal

348

Count 167 32 199 33 5 8 153 199 3 32 132 32 199 6 2 3 1 1 4 1 6 4 1 1 2 6 13 2 8 5 1 1 9 5 9 6 6 2 1 1 5 28 25 1 1 32 199

% Subtable 83.9% 16.1% 100.0% 16.6% 2.5% 4.0% 76.9% 100.0% 1.5% 16.1% 66.3% 16.1% 100.0% 3.0% 1.0% 1.5% 0.5% 0.5% 2.0% 0.5% 3.0% 2.0% 0.5% 0.5% 1.0% 3.0% 6.5% 1.0% 4.0% 2.5% 0.5% 0.5% 4.5% 2.5% 4.5% 3.0% 3.0% 1.0% 0.5% 0.5% 2.5% 14.1% 12.6% 0.5% 0.5% 16.1% 100.0%

Maria Pujol‐Jover and Enric Serradell‐Lopez

3. Conclusions This paper is a first approach to describing the main characteristics of companies in a dynamic and innovative area like the 22@ district. We have examined the characteristics of the companies’ profile regarding general information such as age, industry, organization, leadership, and quality methodology and its influence on innovation. Moreover, we have described what kinds of tools are used for acquiring external knowledge in order to complement the internal knowledge of the company. More work needs to be done in order to analyze the profile of the innovative companies in a cluster as is 22@ district in more detail. Firms need to balance incremental and radical innovations in a fast and challenging context. Continuous innovation seems to be a great way to acquire a good level of innovation in the company while incremental and radical innovations are accomplished. Leadership from the top management team is very common, but in many cases it acts in combination with other areas and departments. In future research we are to continue the analysis with the interaction and influence of knowledge management tools on innovation as it has been done in previous studies (Serradell‐Lopez, et al., 2010).

Appendix 1 As a brief advance of the present research we include the two dimension plot obtained from a multiple correspondence analysis. This analysis has been applied to some of the variables explained in the paper in order to understand their interrelation and reach other relevant conclusions for the ECIC13 conference. Dimension 1 discriminates venture capital, national R+D+i, international and local subsidies from the other variables more related to dimension 2 such as the change in 2008 turnover and innovation in organization.

References 22@ Barcelona (2012), http://www.22barcelona.com, last visited (7/12/2012). Bose, R. (2004) “Knowledge management metrics”, Industrial Management & Data Systems, 104, 6, 457‐468. Casanueva C., Castro, I. and Galán, J.L. (2010) “Capital social e innovación en clusters industriales”, Revista Europea de Dirección y Economía de la Empresa, vol. 19, 4, 37‐58.

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Maria Pujol‐Jover and Enric Serradell‐Lopez Darroch, J. and McNaughton, R. (2002) “Examining the link between knowledge management practices and types of innovation”, Journal of Intellectual Capital, 3(2), 210–222. doi:10.1108/14691930210435570 DETR (2000) Planning for clusters Department of the Environment. Research report, Transport and the Regions: London. Mohamed, M., Stankosky, M. and Murray, A. (2004) “Applying knowledge management principles to enhance cross‐ functional team performance”, Journal of Knowledge Management, 8, 3, 127‐142. Newman, V. (1997) “Redefining Knowledge Management to Deliver Competitive Advantage.” Journal of Knowledge Management, 1, no. 2, 123‐128. OECD (2005) Guidelines for Collecting and Interpreting Innovation Data, Third edition Pérez‐Bustamante, G. (1999), “Knowledge management in agile innovative organisations”, Journal of Knowledge Management, 3, 1, 6–17. Serradell‐López, E., Jiménez‐Zarco, A. I. and Martínez‐Ruiz, M. P. (2010) “Marketing and ICT integration as product innovation key factors”, International Journal of Technology Enhanced Learning, 2, 3, 183–200. Tushman, M. and Anderson, P. (1986) “Technological discontinuities and organizational environments”, Administrative Science Quarterly, 31, 439‐465.

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The Impact of Corporate Governance Indicators on Intellectual Capital Disclosure: An Empirical Analysis From the Banking Sector in the United Arab Emirates Muhieddine Ramadan1 and George Majdalany2 1 Department of Business Administration, Faculty of Finance and Accounting, University of Wollongong in Dubai, Dubai, United Arab Emirates 2 Department of Business Administration, Faculty of Accounting and Finance, UGSM Monarch Business School Switzerland, Hagendorn‐Zug, Switzerland mzr@eim.ae george.asaad.majdalany@ugsm‐monarch.ch Abstract: Corporate governance is a framework for legal, institutional, and cultural factors shaping the patterns of influence that stakeholders exert on managerial decision making. Managerial decision making is focused on creating value for stakeholders through competent uses of capital and accurate disclosure and communication of a firm’s resources. However, established management and reporting systems gradually lost their relevance due to their incapability to capture and provide important information for stakeholders in order to manage processes that are based on knowledge and intangible resources. Besides, it has been claimed that in the present knowledge economy, Intellectual Capital (IC) is a major driver of competitive advantage, innovation, and performance due to its ability to capture information which is not reported in traditional financial statements. Therefore, the aim of the present study is to explore through empirical analysis the impact of Corporate Governance on IC disclosure (ICD) in annual reports issued by the banking sector in the United Arab Emirates (UAE). The present study examines the influence of Corporate Governance indicators (bank size, leverage, profitability, board size, and ownership structure) as independent variables on the disclosure of IC elements (Human Capital, Relational Capital, Structural Capital) as dependent variables, while controlling for market listing age and bank age. The methodology employed is quantitative, using multivariate regression analysis to study the relationship between Corporate Governance indicators and ICD, which is measured using content analysis of the 2010 annual reports of publicly listed banks in the UAE. The present research has some limitations, which include the specificity of Corporate Governance proxies used, examination of only the 2010 annual reports, and generalization restriction inherent in the examination of the UAE markets alone. The present study has a theoretical implication, by providing an empirically tested conceptual model on the relationship between Corporate Governance and ICD in the banking sector of the UAE. In addition, it has a practical implication by providing information for regulating agencies to develop regulations aiming to increase the implementation of Corporate Governance practices incorporating IC elements. Keywords: corporate governance, intellectual capital, disclosure, annual reports, banks, United Arab Emirates

1. Introduction The main focus of the present study is two topics which have received increased, but separate importance in academia and practice: Corporate Governance and ICD. According to Keenan and Aggestam (2001), there are several factors that have contributed to the increased relevance of Corporate Governance, including the current global business world which has highlighted the importance of adequate accountability, corporate responsibility, and densities of corporate groups. Furthermore, Keenan and Aggestman (2001) opine that the economic focus has shifted from the entrepreneur in the nineteenth century to the management in the twentieth century, and finally into governance of the firms in the twenty‐first century. Moreover, several studies have highlighted that Corporate Governance and corporate disclosures are major ingredients of investor protection, efficient markets, reduction of agency costs, and decrease of information asymmetry (Cerbioni and Parbonetti, 2007). Despite the fact that the impact of Corporate Governance on financial disclosure has been widely studied (Beekes et al., 2004), there’s still a lot of research to be conducted on the impact of Corporate Governance on voluntary disclosures (Carcello and Neal, 2003; Cheng and Courtenay, 2006). According to Falikhatun et al. (2010), standard financial reporting has lost its relevance to users of financial information in the current “knowledge economy” where “soft assets”, such as intangibles, play a major role in investment decisions and evaluation of firm performance. Besides, several studies have highlighted the gap between the officially declared values of firms and their real worth (Brännström and Giuliani, 2009; Clacher, 2010). Furthermore, ICD includes information on a firm’s human resources, innovation, customers, and

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Muhieddine Ramadan and George Majdalany technology, which are not reported in financial statements due to identification, recognition, and measurement issues (Clacher, 2010). The present study is focused on voluntary ICD in publicly listed banks in the UAE from a Corporate Governance indicators perspective. Using content analysis and multivariate regression analysis, the present study examines the association between Corporate Governance indicators (bank size, leverage, profitability, board size, and ownership structure) and ICD (Human Capital, Relational Capital, and Structural Capital), while controlling for market listing age and bank age, using the 2010 annual reports. The remainder of this article is structured as: literature review and hypotheses development, research design and methodology, data presentation, statistical analysis and results, and finally, conclusions, limitations, and implications for future research.

2. Literature review and hypotheses development ICD provides valuable information to users of financial statements, as it reduces agency costs and information asymmetry, and it increases shareholder value (Brännström and Giuliani, 2009; Clacher, 2010). Therefore, several studies have called for increased disclosure of non‐financial indicators of investments in intangible and intellectual items (Brännström and Giuliani, 2009; Clacher, 2010). On the other hand, it has been claimed that the responsibility for prudent investments in IC resides with Corporate Governance, and that, depending on firm’s characteristics, the governance of publicly owned firms is ultimately responsible for the development of new processes for disclosure and communication of IC related elements (Brännström and Giuliani, 2009; Clacher, 2010). In fact, there is an undeniable increasing demand for more extensive corporate disclosures regarding IC amongst handlers of financial information (Brännström and Giuliani, 2009; Clacher, 2010). However, several studies claim that the cost associated with a radical change in the financial reporting systems to make them more relevant is unaffordable and may have negative impact on firm value (Clacher, 2010). Extant literature provides mixed evidence on the relationship between ICD and Corporate Governance (Falikhatun et al., 2010). Several studies have been conducted on the driving factors of voluntary ICD (Cerbioni and Parbonetti, 2007; F‐Jardón and Martos, 2009). However, most studies have been centered in developed countries. The study conducted by Barako et al. (2006) in Kenya seems to be one of the most extensive studies with regards to developing countries. Barako et al. (2006) consider the degree to which voluntary ICD practices are influenced by Corporate Governance indicators. Results revealed that firm’s Corporate Governance indicators, including, ownership structure and firm characteristics significantly influence the extent of voluntary ICD in Kenyan Stock Exchange listed firms (Barako et al., 2006). According to Barako et al. (2006), significant positive correlation also exists between voluntary ICD and levels of institutional and foreign ownership. Barako et al. (2006) also reveal that higher levels of disclosure are seen in companies of large size and high amounts of debt. However, no significant correlation is reported between ICD levels and factors such as liquidity, profitability, board leadership structure, and size or type of external audit firm (Barako et al., 2006). In another study conducted by Falikhatun et al. (2010) on the impact of Corporate Governance on voluntary ICD in the banking sector in Indonesia, total assets and leverage positively affect the level of ICD, while the existence of ownership management and auditor type negatively affect the level of disclosure; this contradicts with the findings of Hossain et al. (1995), who claim that ownership structure does not affect ICD levels. In addition, and in line with the findings of Mak and Li (2001) and Lakhal (2005), Falikhatun et al. (2010) claim that board size does not affect disclosure levels; however, this is contrary to the results obtained by Jensen (1993). In another study by Hidalgo et al. (2011) on the effect of Corporate Governance indicators on ICD in publicly listed Mexican companies, results reveal that board size positively affects the level of ICD; in addition, increase in the shareholder ownership by institutional investors negatively affects the level of ICD (Hidalgo et al., 2011). As revealed in the review of literature, there are contradictory findings with regards to the impact of Corporate Governance indicators on ICD level. In addition, the focus of most studies has been on Corporate Governance and voluntary disclosure in general, rather than voluntary ICD. Therefore, in order to bridge these gaps in literature, this study is aimed at examining the impact of Corporate Governance indicator on voluntary ICD in publicly listed banks in the UAE. The importance of UAE as an Arabic country in the Gulf Cooperation Council (GCC) region has been highlighted by Nsour (2001) who recommends that for Arab countries to be successful in the realm of the economical changes, they must replace the existing processes, mindsets, and methods by shifting from the industrial mentality to the human capital mentality. It was noted by Zineldin (1998) that within oil‐rich Arab countries, there has been an expansion of non‐oil industries, combined with

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Muhieddine Ramadan and George Majdalany the increase in the level of education, and the demand of high‐technology and sophisticated products in these countries. Doraid (2000) claims that the real wealth of the Arab nations is not in their oil, but rather in the capacities of the people who live and work in these countries, and whom in the long run, will form the Human Capital of these nations. The banking sector in the UAE has witnessed a fast development (DFM, 2012; ADX, 2012). However, due to the convolution of the banks’ operations and their related exposures and risks, banks have legal, ethical, and moral obligations of mitigating their risks in order to protect their stakeholders and improve their performance (Falikhatun et al., 2010). Therefore, to reduce risks and agency costs, banks need to comply with sound Corporate Governance practices by increasing transparency and disclosure, whether mandatory or voluntary (Carcello and Neal, 2003; Cheng and Courtenay, 2006). According to the UAE corporate governance code issued by the “Ministry of Economy’s Decision No. 518 of 2009”, publicly listed companies are encouraged to adopt good corporate governance principles and establish an effective framework for the protection of shareholder rights, fair treatment of shareholders, strengthening transparency and openness with and within the company, and specify the board of directors’ duties. Furthermore, according to the “Corporate Governance Guidelines for UAE Bank Directors” issued by the UAE Central Bank in June 2006, UAE banks and their directors need to pay attention to (Al‐Suwaidi, 2006): improving disclosure standards and transparency, managing conflicts of interest, and establishing board committees.

2.1 Hypotheses development Based on the conducted literature review, several related research questions were developed. These questions revolve around the impact of Corporate Governance indicators on ICD. Thus, in light of the above, a specifically defined research question has been developed as: “What is the impact of Corporate Governance indicators on ICD in publicly listed banks in the UAE?” In response to the main research question, the following hypotheses were developed: Table 1: Hypotheses H10

There is no statistically significant relationship between Bank Size and IC disclosure

Bank Size positively affects IC disclosure in a statistically significant way

H20

There is no statistically significant relationship between Leverage and IC disclosure

Leverage positively affects IC disclosure in a statistically significant way

H30

There is no statistically significant relationship between Profitability and IC disclosure

Profitability negatively affects IC disclosure in a statistically significant way

H40

There is no statistically significant relationship between Board Size and IC disclosure

Board Size positively affects IC disclosure in a statistically significant way

H50

There is no statistically significant relationship between Ownership Structure and IC disclosure

Ownership Structure positively affects IC disclosure in a statistically significant way

Source: Authors

The discrepancy in the literature regarding the effect of these variables on ICD was the main aspect taken into account in the present study to unfold the prevailing situation in the banking sector in the UAE.

3. Research design and methodology The present research is designed as an empirical study of the relationships between Corporate Governance indicators and ICD in publicly listed banks in the UAE. The aim of the present research is to respond to the main research question using quantitative methods by way of multivariate regression analysis of content analysis of the 2010 annual reports.

3.1 Target population and sampling method Target population consists of 26 publicly listed banks in the UAE as of 31 December 2010 (DFM, 2012; ADX, 2012). DFM consists of 12 banks, ADX consists of 14 banks. The present study examines 100% of the target population based on the following reasons:

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Muhieddine Ramadan and George Majdalany

Powerful statistical analysis is only effective when using larger, more representative sample size, which in this study is provided by 100% inspection (Hair et al., 2010);

Sample size affects the informativeness, reliability, and generalizability of the findings (Hair et al., 2010);

Sampling 100% of the target population eliminates the risks involved in the various types of sampling, such as sampling bias and sampling errors (Hair et al., 2010).

3.2 Annual reports and content analysis Several researchers used content analysis of corporate annual reports as the main source of data in the examination of IC reporting (Gray et al., 1995; Beattie and Thomson, 2007). Although it can be argued that all forms of external communication of an organization should be monitored if a researcher wants to capture all IC reporting, the difficulty is that it is impossible to determine with certainty that all communications are taken into consideration (Gray et al., 1995). Therefore, the present study examines annual reports for three reasons:

Annual reports are considered a valuable source of official information for internal and external stakeholders (April, 2003; Guthrie and Petty, 2000);

It has been established that disclosure levels in annual reports are significantly positively correlated with other forms of disclosure (using other media) of corporate information (April, 2003; Guthrie and Petty, 2000); and

Annual reports are produced on a regular basis, usually yearly, and as such, they provide an opportunity for meaningful comparisons and analysis (Niemark, 1995)

According to Beattie and Thomson (2007), content analysis is a widely used method to assess the frequency and type of ICD. Content analysis is used to analyze published information in a systematic, objective, and reliable manner (Krippendorff, 1980; Guthrie and Parker, 1990). Several researchers have pioneered the use of content analysis in IC research, such as Guthrie and Petty (2000) and Brennan (2001). This method of analysis is held to be empirically valid (Guthrie and Parker, 1990; Gray et al., 1995). In order to guarantee the effectiveness of content analysis, the present study ensured that the following criteria are met (Guthrie and Mathews, 1985):

The categories of classification were clearly and operationally defined;

Categorizations were objectively prepared in a way to ensure that there’s no overlap between categories;

Content analysis was carried out by reliable coders; and

Computer‐based content analysis tools were used to ensure stability and reproducibility.

3.3 Definition of variables This section lists the dependent, independent, and control variables and the proxies used to measure these variables. 3.3.1 Independent variables and control variables Table 2 includes the independent and control variables, their definitions, and the proxies used in measurement. Table 2: Independent and control variables Independent Variables

Code

Bank Size

BSize Bank size calculated by value of total assets in millions of USD

Definition

Leverage

Lev

Bank leverage calculated by total assets / total liabilities

Profitability

Prof

Bank profitability calculated by earnings before interest and tax (EBIT) in millions of USD

Board of Directors Size Ownership Structure Control Variables

BodSize Total number of members of the board of directors IIS

Shareholding of institutional investors

Code

Definition

Listing Age

LAge

Listing age of bank, measured in number of years since listing date

Bank Age

BAge

Age of bank, measured in number of years since incorporation

Source: Authors

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Muhieddine Ramadan and George Majdalany 3.3.2 Dependent variables The IC frameworks reported by Guthrie and Petty (2000) were adopted directly or indirectly by several studies. The IC proxies used in this study are derived from the frameworks of Guthrie and Petty (2000), Bozzolan et al., (2003), Guthrie et al. (2004), Abeysekera and Guthrie (2005), and Bruggen et al., (2009). However, according to Grasenick and Low (2004), determining the proxies for ICD measurement is complicated, and the outcome is usually controversial. Therefore, the present study utilized a combination of the proxies from the different frameworks to ensure full representation of all IC indicators. The present study employs the count of IC capital related terms as the unit of the content analysis because of better comparison of different annual reports (Gao et al., 2005). Further, disclosure frequencies were aggregated to determine the quantity of ICD. To lower subjectivity, which is usually associated with the allocation of different weights to various IC categories, the present study followed a 0 ‐ 1 coding scheme following the set of coding rules. Simply stated, the appearance of the terms, as per the content analysis software search engine, yields a score of 1, whereas the nonappearance yields a score of 0. Consistent with previous studies (Guthrie and Petty, 2000; Bozzolan et al., 2003), the categories and the number of terms used under each category are as follows: Table 3: Intellectual capital categories Category

Number of Terms

Human Capital

158

Relational Capital

133

Structural Capital

146

Source: Guthrie and Petty, 2000; Bozzolan et al., 2003; Guthrie et al. (2004); Abeysek era and Guthrie (2005); Abdolmohammadi (2005); Bruggen et al., (2009)

The definitions of these categories are as follows:

Human Capital: The tacit knowledge embedded in the minds of the employees (Edvinsson and Sullivan, 1996)

Relational Capital: The knowledge embedded in the relationships established with the outside environment (Edvinsson and Sullivan, 1996)

Structural Capital: The organizational routines of the business (Edvinsson and Sullivan, 1996)

3.4 Data collection The 2010 annual reports of the 26 publicly listed banks were downloaded in PDF format from the website of each bank, converted to Ms. Word format 2007 using “ABBY FineReader 10 Professional Edition”, uploaded to the content analysis software (QDAMINER 4 and WORDSTAT 6), coded, and then electronically analyzed to extract the count of the variables: Human Capital disclosure, Relational Capital disclosure, and Structural Capital disclosure. In addition, the 2010 annual reports were used to extract the following independent variables: Bank Size, Leverage, Profitability, Board Size, and Ownership Structure. Furthermore, the 2010 annual reports were examined in order extract the following control variables: Firm age and Listing age.

4. Results and discussions This section includes the statistical analysis of the study, including descriptive analysis and regression output.

4.1 Descriptive analysis Table 4 shows the descriptive statistic of independent, dependent, and control variables:

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Muhieddine Ramadan and George Majdalany Table 4: Descriptive statistics Variable

N Minimum Maximum

ICD

13.00

629.00

224.85

151.40

BSize

287.29

77,881.87

14,430.60

20,181.27

Lev

Prof

BoDSize

IIS

0.25

Mean

Std. Deviation

0.91

0.81

0.13

1,030.14

199.01

302.49

3.00

12.00

8.08

2.13

0.05

1.00

0.54

0.22

(349.00)

LAge

2.53

10.78

6.49

2.51

BAge

2.67

44.03

22.34

14.68

Source: Authors

Total ICD has a minimum frequency of 13, maximum of 629, mean of 224.85, and standard deviation of 151.40. In terms of bank size (BSize), the minimum amount of total assets is 287.29 millions of US Dollars (mUSD), maximum is 77,881.87 mUSD, mean is 14,430.60 mUSD, and standard deviation is 20,181.27 mUSD. Leverage (Lev) shows a degree of variance with a minimum of 25%, maximum of 91%, and mean of 81%. In terms of profitability (Prof), minimum is (349.00) mUSD, maximum is 1,030.14 mUSD, and the mean is 199.01 mUSD. Regarding board size (BoDSize), there is also a degree of variance; minimum of 3 members, maximum of 12 members, and the mean is 8.08 members. Percentage of institutional investors (IIS) shows a large variance, with a minimum of 5% and a maximum of 100%. As for market listing age (LAge), minimum is 2.53 years, maximum is 10.78 years, and the mean is 6.49 years. Finally, bank age (BAge) shows also a large variance, with a minimum of 2.67 years, a maximum of 44.03 years, and a mean of 22.34 years. Having analyzed the variables descriptively, Table 5 shows the correlation of coefficients between the dependent variable and the independent variables of banks for the year 2010 (n = 26). The correlation of Pearson coefficients indicates the statistical significance of positive association between ICD and the independent variables BSize, Lev, Prof, and BoDSize. Table 5: Correlation matrix ICD ICD

BSize

Lev

Prof

BoDSize

IIS

LAge

BAge

Pearson Correlation

BSize

Lev

Prof

BoDSize

IIS

LAge

BAge

Sig. Pearson Correlation Sig. Pearson Correlation Sig. Pearson Correlation Sig.

.755**

.000 .461**

.343*

.009

.043

.384*

.754**

.241

.026

.000

.118

.344*

.280

-.039

.184

.043

.083

.425

.184

-.002

.133

.374*

0.075

0.083

.496

.258

.030

.358

.344

Pearson Correlation

.324

.370*

.515**

.462**

0.131

0.286

Sig.

.053

.031

.004

.009

.262

.078

-.031

.187

.342*

0.323

0.027

.407*

.607**

.440

.180

.044

.054

.449

.019

.001

Pearson Correlation Sig. Pearson Correlation Sig.

Pearson Correlation Sig.

**. Correlation is significant at the 0.01 level. *. Correlation is significant at the 0.05 level. Source: Authors

4.2 Regression output The present study follows the four phases of data examination as suggested by Hair et al. (2009):

Graphical examination of the variables: all variables were examined graphically to ensure that they meet the requirements of the analysis;

Missing data analysis: no missing data was found in all the variables;

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Muhieddine Ramadan and George Majdalany

Identification of outliers: no univariate or multivariate outliers in any of the variable; and

Assessment of the ability of the data to meet the statistical assumptions specific to multivariate regression analysis, including: linearity, normality, homoscedasticity, multicollinearity, and uncorrelated error terms.

Multivariate regression technique will be used, which involves linear regression analysis. In this case, the model for regression is specified thus: ICD = β0 + β1 BSize + β2 Lev + β3 Prof + β4 BoDSize + β5 IIS + β6 LAge + β7 BAge + ε 4.2.1 Coefficient of determination (R2) The adjusted R2 in this model is 0.713. The interpretation of R2 is that 71.30% of the variation in ICD is justified by the variation in the independent variables, while 28.70% of the variation in ICD is explained by other factors not included in this model 4.2.2 F‐Test The regression model shows highly significant results, where the F value (9.872) shows a significant statistical (p = 0.000) relationship between the dependent and independent variables at the 95% confidence level (α = 5%). 4.2.3 RegressiontTests After performing all classic tests to conform to regression requirement, the regression analysis is performed to test all the hypotheses developed in this study is performed using SPSS software. The results are presented in Table 6 and the discussions are presented below. Table 6: Regression results

Model

Unstandardized Coefficients B -177.360

134.507

.007

.001

Lev

363.943

Prof

Sig.

Beta -1.319

.044

.905

5.100

.000

164.319

.304

2.215

.040

-.202

.089

-.403

-2.265

.036

12.337

8.144

.174

1.515

.147

-129.616

86.602

-.186

-1.497

.152

LAge

10.730

9.555

.178

1.123

.276

BAge

-2.180

1.492

-.211

-1.461

.161

(Constant) BSize

Std. Error

Standardized Coefficients

BoDSize IIS

Source: Authors

The intercept β0 has a value of ‐177.36 and a t‐value of ‐1.319, which is significant (p = 0.044) at the 95% confidence level (α = 5%). Table 6 reveals the significant regression coefficients, namely bank size (BSize) (β1) at p = 0.000, leverage (Lev) (β2) at p = 0.040, and profitability (Prof) (β3) at p = 0.036. BSize and Lev have positive coefficients which imply a positive relationship, while Prof has a negative coefficient, which implies a negative relationship. The variables board size (BoDSize) (β4) and ownership structure (IIS) (β5) are not statistically significant at the 95% confidence level. This shows that only BSize, Lev, and Prof contribute to the regression equation, thereby making a significant contribution to the prediction of ICD. The unstandardized coefficients indicate that for one unit increase in the independent variable, ICD will increase or decrease by that amount. Therefore, for one unit increase in BSize (in mUSD), ICD will increase by 363.943 frequencies, for one unit increase in Lev (in percentage), ICD will increase by 0.07 frequencies, and for one unit increase in Prof (in mUSD), ICD will decrease by 0.202 frequencies. From this information, we produce the regression equation as follows: ICD = ‐ 177.360 + 0.007 BSize + 363.943 Lev ‐ 0.202 Prof

4.3 Hypotheses verification

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Muhieddine Ramadan and George Majdalany Hypothesis 1 Table 6 shows that bank size (BSize) has a significant t‐value at α = 5%. Thus, the null hypothesis H10 is not accepted and H1 is accepted. BSize has a statistically positive significant effect on the ICD. This result is in line with the studies by Barako et al. (2006) and Falikhatun et al. (2010) that found positive relationship between firm size and the level of information disclosure. Hypothesis 2 Table 6 also shows that leverage (Lev) has a significant t‐value at α = 5%. Thus, the null hypothesis H20 is not accepted, and H2 is accepted. This result supports the findings of Barako et al. (2006) and Falikhatun et al. (2010) which found statistically significant positive relationship between leverage and ICD. However, it contradicts the findings of Cerbioni and Parbonetti (2007) who stated that there is no relationship between leverage and ICD. Hypothesis 3 The regression model shows that profitability (Prof) has a significant t‐value at α = 5%. Thus, the null hypothesis H30 is not accepted, and H3 is accepted. This finding contradicts the results of Falikhatun et al. (2010) who found no statistically significant relationship between profitability and ICD. In addition, since the coefficient of profitability is negative in the present study, this also contradicts the studies by Wallace and Nasser (1995), Barako et al. (2006), and Hossain (2008) that found that profitability has positive influence on company disclosure. Hypothesis 4 Based on the results in Table 6, the present study found that the ICD model does not show a significant t‐value for board size (BoDSize) at α = 5%. Thus, the null hypothesis H4 0 is accepted, and H4 is rejected. This result contradicts the findings of Jensen (1993) and Hidalgo et al. (2011) who claimed that as board size increases, ICD will decrease. However, it supports the findings of Mak and Li (2001), Lakhal (2005), and Falikhatun et al. (2010) who found no significant statistical relationship between board size and ICD. Hypothesis 5 The present study found that ownership structure (IIS) does not have a statistically significant relationship with ICD. Thus, the null hypothesis H50 is accepted, and H5 is rejected. This result supports the findings of Falikhatun et al. (2010) and contradicts the findings of Hossain et al. (1995), Barako et al. (2006), and Hidalgo et al. (2011). The higher the institution ownership is not enough to conduct better transparency in firms. Control Variable Tests The control variables, market listing age (LAge) and bank age (BAge), show t‐values of 1.123 and ‐1.461 which are not statistically significant at the level of α = 5%. Therefore, it can be concluded that market listing age (LAge) (β6) and bank age (BAge) (β7) do not have positive significant effects on the level of α = 5% on ICD. In summary of the hypotheses testing, the present study found that in the banking sector in the UAE, bank size and leverage affect positively, while profitability affects negatively the level of ICD. Board size, ownership structure, market listing age, and bank age do not have influence on the level of ICD.

4.4 Implications for research and practice The present study has both theoretical and practical implications. From a theoretical perspective, this study is expected to become a reference for further research on ICD and Corporate Governance in the UAE. The findings support some earlier studies and contradict others, which opens opportunities for academic debates and further research on the subject area. Regarding the practical implications, the findings of this study are expected to provide information for the Securities and Commodities Authority (SCA) to develop regulation to increase the implementation of Corporate Governance in the banking sector in the UAE. Furthermore, the

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Muhieddine Ramadan and George Majdalany present study provides valuable input for regulators who request continuous analytical work to know the implications of poor governance for firm transparency.

5. Conclusions, limitations, and future research The purpose of this study is to analyze Corporate Governance factors on voluntary ICD in the banking sector of the UAE for the fiscal year 2010. The independent variables used as proxies for Corporate Governance factors are bank size, leverage, profitability, board size, and ownership structure, while controlling for market listing age and bank age. ICD is measured by a disclosure index supported by word count of metrics using a combination of IC terms commonly used in earlier studies. Results of the analysis show that bank size and leverage have a statistically positive effect on the level of ICD, while profitability has a statistically negative effect. In addition, the analysis shows some statistically insignificant variables, which are board size, ownership structure, market listing age, and bank age. Therefore, in the absence of mandatory ICD regulations in the UAE, some Corporate Governance practices impact transparency levels in a rapidly developing banking sector. As with other empirical studies, the present study has some limitations. Apart from the limitations of the study, the present research also provides the opportunity for future research. The limitations and the opportunity for further research associated with this study are as follows:

The proxies of Corporate Governance used are only bank size, leverage, profitability, board size, and ownership structure. Further research can include other proxies, such as Corporate Governance index, board independence, ownership management, audit committee independence, frequency of audit committee meetings, chairman/CEO role duality, and ownership concentration;

The present study uses 2010 data; future research should use a longer research period in order to examine the relationship between Corporate Governance indicators and ICD over time; and

Since only the UAE banking sector is used in the present research, the generalization of the findings to other jurisdictions may be questioned. It is suggested for further research to study the banking sector of all the GCC countries, in order to compare and contrast between different jurisdictions and create a model that can be safely generalized.

Despite its limitations, the present study significantly contributes to the literature of Corporate Governance in several ways. First, it confirms as well as contradicts with findings of earlier studies. Second, and to the best knowledge of the researchers, this is the first study in the UAE that examines the impact of Corporate Governance indicators on ICD. The specific characteristics of banks in the UAE add different aspects to previous literature. In this sense, the findings offer new insights into these relationships in an institutional context that greatly differs from those of the countries considered in the previous literature on voluntary disclosure. Finally, the choice of a large sample, representing 100% of the population of banks in the UAE, contributed in overcoming the limitations of earlier studies that used a small sample relative to the population.

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Knowledge Management Practices as the Basis of Innovation: An Integrated Perspective Maria João Nicolau Santos and Raky Martins Wane School of Economics and Management (ISEG), Lisbon, Portugal mjsantos@iseg.utl.pt rakywane@socius.iseg.utl.pt Abstract: In recent years, there has been widespread debate about the relevance of intangible assets in general and knowledge in particular. Indeed, there is now a broad consensus that innovative capacities of companies to a great extent depend on their effectiveness in dealing with knowledge. Earlier research findings have already demonstrated that knowledge management (KM) practices contribute positively towards levels of innovative performance and that this input rises in accordance with organizational efforts to foster contexts favorable to KM. Our review of the literature identified three factors considered determinant to the success of a knowledge management strategy oriented to innovation: (1) enablers relating to a knowledge friendly organizational environment, (2) processes incorporating the appropriate KM tools and (3) innovation performance levels. Different analyses have been enforced to address the interrelationship between those three factors. However, very few research studies have adopted integrated models for the analysis of the interrelationships. Furthermore, a large majority of studies focus on the creation and sharing of knowledge, excluding the other knowledge cycle processes. There is a clear need to reach out to the other phases inherent to the KM cycle and integrate the findings into the overall variables making up KM. Leveraging KM practices to achieve innovation goals requires a deep understanding of the knowledge processes, what critical issues influence such implementation, and how all of these factors relate to each other. As a result, we posit that systems thinking provide a foundation that can facilitate such an integrative understanding and can enhance an effective KM practice. This study proposes a theoretical framework and outlines a series of research propositions that enables organizations to link knowledge enablers and practices with innovation performance. We argue that KM practices draw on the energy of the enablers and interact with them to generate new or significantly improved products. It seems to us that our framework developed the theoretical bases for understanding the specific relationships among the different core factors referred in the literature and therefore, it may be the starting point for further research aiming to understand how organizations can leverage KM for innovation. Keywords: innovation performance, knowledge context, knowledge life cycle, knowledge management practices, knowledge management tools

1. Introduction The relevance of intellectual capital (IC) and knowledge assets reflects the assumption that knowledge has become the most valuable economic resource. IC may be defined as knowledge that can be converted into value (Edvinsson and Sullivan, 1996). In this sense, leveraging value from IC requires effective management of knowledge processes. Although KM has became a central topic, in some cases the best efforts of organizations to manage knowledge have not achieved their objectives (e.g. De Long and Fahey; 2000; Lee and Choi, 2003). The question is no longer whether to manage organizational knowledge, but how to manage it to reach higher performances. In this paper we propose a theoretical framework to support the implementation of knowledge processes oriented to innovation, highlighting the key elements that should be included in it. This framework is the starting point for a set of propositions regarding how KM enablers and practices influence innovation performance levels. The main objective consists of portraying the effects of KM practices on the launch of new or significantly improved products. In the next section, we address the relationship between KM and innovation. Thereafter, we propose our theoretical model and develop some research propositions. We, then, close with a brief conclusion.

2. Knowledge management and innovation Innovative capacities make organizations more competitive as the new knowledge at the heart of the innovation is necessarily distinctive and difficult to imitate, and potentially the source of sustainable competitive advantages enabling organizations to turn in higher performance levels (Bogner and Bansal, 2007). Authors such as Nonaka, Toyama and Nagata (2000) deem the learning processes underlying creating knowledge to be the very foundation stone of innovation, which, in turn, reflects in higher levels of

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Maria João Nicolau Santos and Raky Martins Wane organizational performance (e.g. Organization for Economic Co‐operation and Development [OECD], 2005; Zack et al, 2009). Many authors have posited this correlation between KM and innovation and consider KM provides an important tool for enhancing innovation processes (e.g. Massey, Montoya‐Weiss and O'Driscoll, 2002; Darroch, 2005; Zack, Mckeen and Singh, 2009). The empirical results indicate that the implementation of KM practices, backed by a favorable organizational context, improves overall organization performance through higher profits, greater competitiveness and economic growth (e.g. Forcadell and Guadamillas, 2002; Choi and Lee, 2003; Zack et al., 2009). Furthermore, the creation (e.g. Calighirou, Kastelli and Tsakanikas, 2004; Jiang and Li, 2008), dissemination and usage of knowledge (e.g. McAdam, 2000; Birkinshaw and Sheehan, 2002) are sources of innovation and positively impact on company innovation performance levels (e.g. Massey et al., 2002; Du plessis, 2007). The identification of these key components – KM practices fostering innovation, facilitating organizational contexts and innovation performance – is neither new nor distinctive. However, there is a lack of study on the integrated interrelationship between these three factors (some exceptions are Forcadell and Guadamillas, 2002; Massey et al., 2002 and Lee and Choi, 2003). A better understanding of how KM initiatives can be turned into value creation with positive impacts on innovation performance is fundamental to support management decisions and to redirect efforts and investments towards those KM practices able to guarantee better results. This study therefore seeks to overcome these shortcomings through designing an integrated analytical model enabling research of the relationships between these factors. In the theoretical framework called ClicK.Innov ‐ Context (leadership, information technologies and culture), Knowledge cycle and Innovation performance – we do assume that KM practices are driven by enabling factors that mutually interact over the knowledge life cycle within the framework of producing new or significantly improved products.

3. Theoretical model: ClicK.Innov Leveraging KM practices to achieve innovation goals requires a deep understanding of the knowledge processes, what critical issues influence such implementation, and how all of these factors relate to each other. As a result, we posit that systems thinking provide a foundation that can facilitate such an integrative understanding and can enhance an effective KM practice. This approach is a conceptual framework for problem‐solving that considers problems in their entirety. Systems thinking theory is built on the premise that the set of dynamically interrelating subsystems creates a synergy effect that do not exist if we consider each subsystem separately (Rubenstein‐Montano, Liebowitz, Buchwalter, McCaw, Newman, and Rebeck, 2001). The same conceptual foundation has been adopted by other similar studies. Lee and Choi (2003) identify the approach as suitably able to capture the complex and dynamic relationships associated with KM processes as it encapsulates problems in their entirety from a holistic perspective. This facilitates a comprehensive approach that considers the necessary processes and tools for KM and the additional factors that impact KM activities, such as leadership, technology and culture. A visual representation of the model is set out in figure 1. Below, we develop a set of propositions regarding the relationship between these factors. For each one we identify theoretical relationships that might be addressed in future research.

3.1 Context The successful implementation of KM practices depends on contexts favorable to the creation and transmission of knowledge within the scope of which all actors actively participate (e.g. Nonaka, 1994; Comité Européen de Normalisation [CEN], 2004; Dalkir, 2005). The KM enablers incorporate the set of organizational mechanisms and initiatives that foster continuous Knowledge development (Lee and Choi, 2003). There are a range of findings referring to the importance of the organizational context and individual capacities. Authors such as Davenport and Prusak (1998), Allee (2003) and CEN (2004) clearly identity the factors determining KM success: culture, business models and strategy, leadership, technology and individual capacities.

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Figure 1: ClicK.Innov model The literature contains references to countless enabling factors within the scope of which leadership, IT and culture are incorporated into our theoretical model. 3.1.1 Leadership Leadership and management support should nurture a shared vision of knowledge and enhance its importance (e.g. Nonaka, 1994). Managers and team leaders play a critical role in KM, due to its influence on promoting new ideas, supply advice and mentoring to their teams (e.g. Nonaka, 1994; Forcadell and Guadamillas, 2002) and motivate their staff to actively participate in KM processes (e.g. CEN, 2004a). Leaders also encourage KM implementation by leading change processes (e.g. Sveiby 2007) and establishing autonomous working teams (e.g. McAdam, 2000). Those autonomous working teams are critical to KM initiatives given its role in fostering individual responsibility (e.g. Forcadell and Guadamillas, 2002), and in guiding action and deliberation (Nonaka, 1994) alongside with employee recognition (CEN, 2004a). Empirical research also suggested that management support is crucial for the success of KM practices (e.g. De Long and Fahey, 2000; Sveiby, 2007). On the basis of these observations, we propose the following: P1: There is a positive relationship between management support and practices designed to identify, create, store, share and apply knowledge. 3.1.2 Information technologies (IT) An equally important dimension is the technological infrastructure (e.g. Massey et al, 2002; Dalkir, 2005). IT is referred as a tool for supporting working in groups and for seeking out knowledge (e.g. Birkinshaw and Sheehan, 2002; Lee and Choi, 2003). Therefore, KM implementation may be backed up by technologies (e.g. CEN, 2004) as the infrastructural solutions necessary to bringing about not only the sharing of knowledge but also providing the stimuli required to ensure all individuals become active participants in KM processes (Dalkir, 2005). Technological infrastructures are analyzed here in terms of the extent to which they support and enable KM since it facilitates collaborative work, communication among departments and accelerates flows of knowledge (e.g. Alavi and Leidner, 2001; Du Plessis, 2007). Empirical studies have shown that KM practices, focused on people and based upon information technological resources, generate high performance levels (e.g. Choi and Lee, 2003). However, the literature also finds that such IT infrastructures only contribute towards practices involving the codification and/or storage of knowledge (e.g. Lee and Choi, 2003). In keeping with the aforementioned discussion and the arguments, we formulate the next proposition: P2: There is a positive relationship between technological infrastructures and practices designed to identify, create, store, share and apply knowledge.

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Maria João Nicolau Santos and Raky Martins Wane 3.1.3 Culture Many authors point to the organizational culture as playing a central role in KM for two main reasons. Firstly, given its role in defining just what is perceived as internally valid knowledge (Lee and Choi, 2003) and secondly due to the influence wielded over other components such as organizational structure and design of workplaces (Forcadell and Guadamillas, 2002). An organizational culture based on values such as transparency, trust, collaboration, openness to new ideas and tolerance of errors proves a central facet of many of these studies (e.g. Davenport and Prusak, 1998; Allee, 2003; CEN, 2004a). Correspondingly, core factors include the levels of trust and ongoing collaboration in effect at the company. Trust is built on maintaining mutual levels of conviction and commitment, reciprocity as well as the appropriate intentions, behaviors and competences for successful KM implementation (Lee and Choi, 2003). Trust relationships exist when individuals reciprocally believe in others behaviors, attitudes and skills (e.g. CEN, 2004a; Sveiby and Simons, 2002). The lack of trust has been suggested in several studies as one of the main barriers to create and share knowledge (e.g. Davenport and Prusak, 1998; De Long and Fahey, 2000). Researchers have also reported that high levels of trust and credibility among people contribute to accelerate knowledge flows (e.g. De Long and Fahey, 2000; CEN, 2004a). The positive effect of trust on KM implementation has been testified to by a series of empirical studies (e.g. Forcadell and Guadamillas, 2002, Lee and Choi, 2003). These arguments lead us onto our next proposition: P3: There is a positive relationship between trust and practices designed to identify, create, store, share and apply knowledge. Collaboration refers to the level of mutual support, help and cooperation present in the organization (Lee and Choi, 2003). Prior researches have acknowledged the critical importance of collaboration in promoting knowledge creation and sharing (e.g. Nonaka, 1994; CEN, 2004a). The presence of collaborative environments may increase knowledge exchange as it facilitates experimentation, help to create a shared understanding about an organization, and reduces functional silos (e.g. Fahey and Prusak, 1998, De Long and Fahey, 2000; Sveiby, 2007). Various empirical studies (e.g. McAdam, 2000; Sveiby and Simons, 2002; Choi and Lee, 2003) uncover that the collaboration between individuals have a positive influence on KM initiatives. Therefore, we see no reason a priori to expect a different relationship. P4: There is a positive relationship between collaboration and practices designed to identify, create, store, share and apply knowledge.

3.2 Knowledge cycle KM consists of a dynamic and continuous set of processes and practices related to each other (Alavi and Leidner, 2001). The set of activities making up the KM process is commonly known as the “knowledge life cycle” (e.g. McElroy, 2000; Birkinshaw and Sheehan, 2002). While the literature fails to attain a consensus, we may identify two key stages: the creation and the sharing of knowledge (e.g. McElroy, 2000; Dalkir, 2005). Beyond these, the literature mentions knowledge planning (e.g. Rollett, 2003), storage, utilization (e.g. CEN, 2004) and evaluation (e.g. Dalkir, 2005). The KM processes taken into consideration within the scope of this study incorporate the core phases detailed in the literature in order to establish a broad reaching vision. The challenge lies in understanding, and for each phase, just which tools and techniques are most suitable to leveraging value from knowledge (Birkinshaw and Sheehan, 2002). Below, we describe each core stage making up the KM cycle.

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Maria João Nicolau Santos and Raky Martins Wane 3.2.1 Identification Identifying knowledge represents a strategic phase and seeks above all to align the KM strategy with the objectives and strategic targets of the organization (Rollett, 2003; CEN, 2004). The main objective consists of identifying the knowledge needs based upon analysis of the organization’s strategic positioning. The KM practice of seeking to extract strategic value from knowledge is among the lesser mentioned by empirical studies. This strategic planning technique is often implemented through forms of KM strategic design processes (e.g. Forcadell and Guadamillas, 2002) or planning techniques (e.g. Zack et al., 2009). The literature also refers to the adoption of auditing practices, surveying the specific needs of users, and monitoring objectives (e.g. Rollett, 2003; CEN, 2004b). Zack and co‐authors (2009) concluded that companies implementing KM practices such as identifying knowledge sources, strategic planning and external benchmarking do tend to return better results in terms of product leadership. However, the authors also consider other practices fostering the knowledge sharing and therefore establish no direct relationship between knowledge identification and product leadership. While not encountering robust empirical evidence to the identification of knowledge impacting on innovation performance, the literature does concur that this phase endows organizational direction through the implementation and achievement of strategic targets (CEN, 2004) and thereby contributes to the success of the other phases. Identifying knowledge is fundamental for supporting and justifying decision making regarding facets related to personnel needs, the acquisition of KM support tools (CEN, 2004) and the definition of specific KM related objectives (Rollett, 2003). In full awareness that there is no robust empirical evidence confirming this relationship and, simultaneously, of the need to advance our understanding of the role that identification of knowledge plays in the theoretical framework, we put forward the following propositions: P5: There is a positive relationship between knowledge identification practices and other KM practices. P6: There is a positive relationship between knowledge identification practices and innovation performance. 3.2.2 Creation The creation of knowledge seeks to boost the amount of knowledge available to the organization (Dalkir, 2005). As such, an organization should simultaneously concentrate on capturing the existing knowledge (ibib.) and fostering the creation of new knowledge (e.g. McElroy, 2000). According several approaches learning, prior knowledge and creativity are crucial factors to the success of this phase. Learning deals with the capacity to absorb the knowledge of other persons and transform it into new useful knowledge (ibid.). Previous research pointed that learning and prior related knowledge enhances the ability to recognize the value of new information, assimilate it, and apply it to commercial ends (Cohen and Levinthal, 1990). Hence, much importance is attributed to establishing learning networks in organizations (McAdam, 2000). The literature refers to various tools driving organizational learning such as learning by doing (e.g. CEN, 2004), discussion forums, CoPs (McElroy, 2000; Birkinshaw and Sheehan, 2002), academic journals, conferences and “lessons learned” (e.g. Calighirou, et al., 2004; CEN, 2004b). Some authors see innovation as the successful implementation of creative ideas (see Hennessey and Amabile, 2010). Organizational creativity represents the means of transforming knowledge into value (Lee and Choi, 2003). Creativity can be enhanced by tools such as brainstorming, group problem solving, external benchmarks and CoPs (e.g. Birkinshaw and Sheehan, 2002; Rollett, 2003; CEN, 2004b). New knowledge creation, through learning and generation of new ideas and concepts, lies at the base of organizational innovation processes (e.g. Nonaka, 1994; Calighirou et al., 2004; CEN, 2004). There are countless studies demonstrating the relationship between knowledge creation and levels of innovation performance (e.g. McAdam, 2000; Massey et al., 2002; Jiang and Li, 2008). For example, according to the SECI theory on knowledge creation, adopted by various authors (e.g. Lee and Choi, 2003), the sources of innovation multiply when individuals share their tacit knowledge that is then rendered explicit (Nonaka, 1994).

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Maria João Nicolau Santos and Raky Martins Wane However, the impact of knowledge creation on innovation has turned up some odd results. In the model proposed by Lee and Choi (2003), the creation of knowledge positively contributed to creativity that in turn contributed towards organizational performance (including innovation capacities). The Nortel case study also assumed the creation of knowledge bears a positive effect on innovation performance levels while this relationship is not rendered explicit as the tool applied does not focus exclusively on knowledge creation (Massey et al., 2002). These results suggest that, despite having been one of the most highly researched facets, analysis of the direct effects of knowledge creation on innovation performance levels requires greater depth and justification. Correspondingly: P7: There is a positive relationship between knowledge creation practices and innovation performance 3.2.3 Storage When new knowledge is evaluated as valid and appropriate to the organization then it requires internal dissemination (e.g. McElroy, 2000; CEN, 2004) as a means of extracting value from that which has been produced (Birkinshaw and Sheehan, 2002). There is a corresponding need to store such knowledge in a way able to facilitate and foster searches for knowledge/learning as well as for problem solving (e.g. Rollett, 2003). New knowledge needs to be lodged in the organizational memory and institutionalized through the respective culture, processes, structure (CEN, 2004) and technological infrastructure (e.g. Birkinshaw and Sheehan, 2002). The storage practices analyzed in the literature’s empirical studies featured manuals, documents (e.g. Choi and Lee, 2003) and technological tools (e.g. Massey et al, 2002; CEN 2004). Furthermore, attention also needs paying to the contextual framework surrounding the storage of information and ensuring such is correctly learned by users (Rollett, 2003; Dalkir, 2005). In the knowledge storing process, competitive advantage derives from the effectiveness of means of accessing the information as well as the quality of the information given that such dimensions are difficult to copy (Birkinshaw and Sheehan, 2002). Lee and Choi (2003) concluded that information technologies positively contribute towards the combining of knowledge, that is, activities seeking to aggregate and synthesize new or already existing explicit knowledge. Taking into consideration our literature review, concluding in favor of the generation of new ideas and how the discovery of new usages for knowledge represents the launch pad for innovation (e.g. Cohen and Levinthal, 1990; OECD, 2005), we propose the following: P8: There is a positive relationship between storage practices and innovation performance 3.2.4 Sharing and application KM adds value to an organization through optimizing the knowledge using (Rollett, 2003). The main challenge facing the organization involves incorporating the knowledge produced into organizational practices inherently requiring the experimentation and sharing of knowledge between people (e.g. Birkinshaw and Sheehan, 2002; CEN, 2004). Two critical variables for knowledge sharing stand out from the literature: social interaction (e.g. Nonaka, 1994) and contact with the exterior (e.g. Birkinshaw and Sheehan, 2002). Social interactions may be established through mentoring programs, contacts with experts (e.g. Birkinshaw and Sheehan, 2002; Choi and Lee, 2003) or communities – of practice, interest or users (e.g. McElroy, 2000; CEN, 2004b). Regarding the interfirm cooperation it may take on various formats: strategic alliances and joint ventures, research consortia and taking out licenses (e.g. Tidd, Bessant and Pavitt, 2003). As knowledge is applied to organizational processes and/or incorporated into new products or services, the feedback generated encourages the emergence of new problems, new learning opportunities and nurturing individual inventive trends (e.g. McElroy, 2000, Birkinshaw and Sheehan, 2002). Furthermore, this also enables the identification of new and looming knowledge gaps (CEN, 2004), thus rebooting the knowledge cycle, a process undergoing continuous repetition. Many authors have posited that sharing and using of knowledge are key to leveraging the introduction of new products (e.g. Massey, et al., 2002; Lee and Choi, 2003; Darroch, 2005). Interfirm cooperation is also among the most commonly referenced KM practices in the studies carried out (e.g. Calighirou, et al, 2004; Jiang and Li, 2008). Contact with the external environment proves to be relevant to ascertaining the needs and

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Maria João Nicolau Santos and Raky Martins Wane expectation of clients, validating concepts/prototypes and running pilot projects (e.g. Booz & Company, 2010). In view of this previous research, we expect that the practices designed to share and use knowledge will have a positive impact on innovation performance. P9: There is a positive relationship between knowledge sharing and utilization practices and innovation performance.

3.3 Innovation performance The innovation performance concept is bound up with the measurement of the results stemming from innovation (e.g. COTEC, 2010). In practice, measuring innovation performance levels proves to be not only a complex exercise but also difficult to implement (OECD, 2005). The level of success achieved may be grasped through four different factors (ibid.): innovation inputs (e.g. innovation objectives), innovation activities (e.g. research and development), innovation outputs (e.g. patents) and/or innovation impacts (e.g. turnover, productivity). This study approaches innovation performance through two different output categories (new patents and new or improved products) and their respective impacts. As mentioned before several studies have demonstrated the relationship between KM practices and innovative performance. However, there are still facets requiring greater understanding such as which KM practices should be combined in order to increase innovation performance. This study seeks to analyze whether a combination of various KM practices generates interactive effects that enhance and boost innovation performance. Although, the effects of interaction between creating and sharing knowledge, based upon external alliances have already been empirically verified (Jiang and Li, 2008), the same does not occur with the remaining KM practices (identification and storage). In order to advance our knowledge of these interaction effects we propose the final proposition: P10: There is a positive relationship between KM practices and innovation performance

4. Conclusion In this paper we highlighted, among other things, the driving forces behind KM and innovation, the importance not only of KM processes but also of KM tools and practices, and the KM view as a system. The present study has a number of implications for both research and practice. This study clearly intends to contribute for understanding the impacts of KM practices on innovation performance. The proposed model supplies a broad reaching perspective of the KM cycle and enables the verification of the direct effects of the practices designed to identify, create, store and share and utilize knowledge for the purpose of innovation. We have built on current knowledge and developed some research propositions that can move us toward a more comprehensive understanding of the effects of knowledge enablers and practices on company innovation performance level. Another important contribution relates to IC management. According to the proposed model the company should promote knowledge friendly environments and mix internal and external knowledge to generate innovations. In this sense, the ClicK.Innov enables organizations to combine their human capital with relational and structural components to create value. For practitioners, our work may ensure organizations are able to fully grasp just which factors are critical to effective KM. Firstly, we need to perceive whether the prevailing organizational culture, managerial and technological support levels are factors encouraging KM implementation. Secondly, we should take into consideration that different practices deploy different tools. Additionally, the proposed framework may provide some guidance for organizations intending to implement KM processes from a broader and more holistic perspective. We are furthermore aware that there are other aspects susceptible to exploration. Our literature review identified that several studies are based on relatively small samples. While qualitative research is critical for

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Maria João Nicolau Santos and Raky Martins Wane theory development, it is insufficient to ascertain causal relations between constructs. Hence, we argue that it would be beneficial to validate the proposed framework in larger samples, through quantitative methods. It would also be desirable to assist companies in implementing the proposed model. To advance, we should develop a set of guidelines and directions for implementing a KM strategy oriented for innovation. It seems to us that the development of stronger theoretical and empirical foundations will help organizations on focus their KM efforts on those practices leading to the best results.

References Alavi, M. and Leidner, D. (2001) “Review: knowledge management and knowledge management systems: conceptual foundations and research issues”, MIS Quartely, Vol 25, No.1, pp.107‐136. Allee, V. (2003) The future of knowledge: increasing prosperity through value networks. Amsterdam: Butterworth‐ Heinemann. Birkinshaw, J. and Sheehan, T. (2002) “Managing the knowledge life cycle”, MIT Sloan Management Review, Vol. 44, No. 1, pp. 74‐84. Bogner, W. and Bansal, P. (2007) “Knowledge management as the basis of sustained high performance”, Journal of Management Studies, Vol. 44, No.1, pp. 165‐188. Booz & Company (2010) “The 2010 Innovation 1000: How the Top Innovators Keep Winning.” [online] www.booz.com/global/home/what_we_think/featured_content/innovation_1000_2010 Calighirou, Y., Kastelli, I. and Tsakanikas, A. (2004) “Internal capabilities and external knowledge sources: complements or substitutes for innovative performance?”, Technovation, Vol. 24, No. 1, pp. 29‐39. CEN Workshop Agreement 14924‐1 (2004) “European guide to good practice in knowledge management ‐ part 1: knowledge management framework.” [online] www.cen.eu/cen/Sectors/Sectors/ISSS/CEN%20Workshop%20Agreements/Pages/Knowledge%20Management.aspx CEN Workshop Agreement 14924‐2 (2004a) “European guide to good practice in knowledge management ‐ part 2: Organizational Culture.” [online] www.cen.eu/cen/Sectors/Sectors/ISSS/CEN%20Workshop%20Agreements/Pages/Knowledge%20Management.aspx CEN Workshop Agreement 14924‐3 (2004b) “European guide to good practice in knowledge management ‐ part 3: sme implementation.” [online] www.cen.eu/cen/Sectors/Sectors/ISSS/CEN%20Workshop%20Agreements/Pages/Knowledge%20Management.aspx Choi, B., and Lee, H. (2003) “An empirical investigation of KM styles and their effect on corporate performance”, Information & Management, Vol. 40, pp. 403‐417. Cohen, W. and Levinthal, D. (1990) “Absorptive Capacity: A New Perspective on Learning and Innovation”, Administrative Science Quarterly, Vol. 35, No. 1, pp. 128‐152. COTEC Portugal (2010) Guia de boas práticas de gestão da inovação (2nd ed.). Portugal: COTEC Portugal – Associação Empresarial para a Inovação. Dalkir, K. (2005) Knowledge management in theory and practice. Elsevier/Butterworth Heinemann, Amsterdam. Darroch, J. (2005) “Knowledge management, innovation and firm performance”, Journal of Knowledge Management, Vol. 9, No. 3, pp.101‐115. Davenport, T., and Prusak, L. (1998) Working knowledge: how organizations manage what they know. Mass.: Harvard Business School Press, Boston. De Long, D. and Fahey, L. (2000) “Diagnosing cultural barriers to knowledge management”, Academy of Management Executive, Vol. 14, No. 4, pp. 113‐127. Du Plessis, M. (2007) “The role of knowledge management in innovation”, Journal of Knowledge Management, Vol. 11, No. 4, pp. 20‐29. Edvinsson, L. and Sullivan, P. (1996) “Developing a model for managing intellectual capital” European Management Journal, Vol. 14, No. 4, pp. 356‐364. Fahey, L. and Prusak, L. (1998) “The eleven deadliest sins of knowledge management”, California Management Review, Vol. 40, No. 3, pp. 265‐276. Forcadell, F., and Guadamillas, F. (2002) “A case study on the implementation of a knowledge management strategy oriented to innovation”, Knowledge and Process Management, Vol. 9, No. 3, pp. 162‐71. Hennessey, B. and Amabile, T. (2011) “Creativity”, Annual Review of Psychology, Vol. 61, pp. 569–98. Jiang, X., and Li, Y. (2008) “An empirical investigation of knowledge management and innovative performance: The case of alliances”, Research Policy, Vol. 38, No. 2, pp. 358–368. Lee, H. And Choi, B. (2003) “Knowledge management enablers, processes, and organizational performance: An integrative view and empirical examination”, Journal of Management Information Systems, Vol. 20, No. 1, pp. 179‐228. Massey, A., Montoya‐Weiss, M. and O'Driscoll, T. (2002) “Knowledge management in pursuit of performance: Insights from Nortel networks”, MIS Quarterly, Vol. 26, No. 3, pp. 269‐289. McAdam, R. (2000) “Knowledge management as a catalyst for innovation within organizations: a qualitative study”, Knowledge and process management, Vol. 7, No. 4, pp. 233‐42. McElroy, M. (2000) “The new knowledge management”, Knowledge and Innovation: Journal of the KMCI, Vol. 1, No. 1, pp. 43‐67.

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Maria João Nicolau Santos and Raky Martins Wane Nonaka, I. (1994) “A dynamic theory of organisational knowledge creation”, Organization Science, Vol. 5, No. 1, pp. 14‐37. Nonaka, I., Toyama, R., and Nagata, A. (2000) “A firm as a knowledge‐creating entity: A new perspective on the theory of the firm”, Industrial and Corporate Change, Vol. 9, No.1, pp. 1‐20. Organisation for Economic Co‐operation and Development. (2005) Oslo Manual: Guidelines for collection and interpreting innovation data (3rd Portuguese edition). France: OECD. Rollet, H. (2003) Knowledge management: Processes and technologies. Kluwer Academic Publishers, Boston. Rubenstein‐Montano, B., Liebowitz, J., Buchwalter, J., McCaw, D., Newman, B. and Rebeck, K. (2001) “The knowledge management methodology team: A systems thinking framework for knowledge management” Decision Support Systems, Vol. 31, No. 1, pp. 5–16. Sveiby, K. (2007) “Disabling the context for knowledge work: the role of managers’ behaviours”, Management Decision, Vol. 45, No.10, pp. 1636‐1655. Sveiby, K. and Simons, R. (2002) “Collaborative climate and effectiveness of knowledge work – an empirical study”, Journal of Knowledge Management, Vol. 6, No. 5, pp. 420 ‐ 433. Tidd, J., Bessant, J. and Pavitt, K. (2003) Gestão da inovação: integração das mudanças tecnológicas, de mercado e organizações. Monitor, Lisboa. Zack, M., Mckeen, J. and Singh, S. (2009) “Knowledge management and organizational performance: an exploratory analysis” Journal of Knowledge Management, Vol. 13, No. 6, pp. 392‐409.

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Product Innovation Building, the Relevance of Human Capital: A Case Study Helena Santos‐Rodrigues1, Luis Lousinha2 and Desireé Cranfield 3 1 Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal and CIEO – Centre of Spatial Research and Organizations, Algarve University, Portugal 2 Master from Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal 3 University of Southampton, Southampton, UK hsantos@estg.ipvc.pt luisv22@portugalmail.com djcranfield@gmail.com Abstract: In a rapidly changing business world there is a greater demand for managers and researchers to better manage their intangible resources such as Human Capital. Increasingly important is the management of an organisations brand (image, brand philosophy, etc...), more specifically, its Own Brand, which has gained significance by obtaining an increasing role in various markets. This phenomenon also has a direct impact on an organisation’s competitiveness. The focus of this paper is placed on the relevance of Human Capital (as a dimension of Intellectual Capital) to ‘Own Brand’ Product Innovation development. The research methodology for this investigation incorporated a case study, using both formal and informal interviewing techniques, conducted on a firm situated in the Viana do Castelo district, Northern Portugal. Human Capital and Innovation was the focus of this research study, with Product Innovation being the focal emphasis. Data collection took place during September 2010, with reference made to the previous three years of activity and performance of companies. This research suggests that the different degrees of instability in the markets faced by companies has to do with the company's commitment to training and their ability to offer workshops to their employees on new challenges experienced, as well as their exposure to a more enterprising outlook. It also depends on the function for which the employee is employed and the attitude of the employee (positive, which achieved the maximum value in the questionnaire) to life and work. Formal education, together with the extra professional training, and attitude, is given more consideration and then easily recognised as added value. We verify that there is a very good understanding and appreciation of the kind of effort and sacrifice necessary by highly educated individuals. We found a higher value placed on the extra professional training (higher than that found for the formal education especially if it was based on the individuals own initiative). In present study we found that employee motivation and organization initiatives were important to, innovative initiatives, and also to ease of delivery and exchange of ideas and knowledge. Focusing on the designer professional, we established that the formal academic training of designers and their multidisciplinary training were drivers of innovativeness. Keywords: organizational management, intellectual capital, product innovation, own brand, design

1. Introduction In a business‐related and entrepreneurial world, where change is constant, there is a greater demand on managers and researchers to not only manage financial resources more efficiently, but also to manage tangible and intangible, direct and indirect resources in such a way so as to explore essential contributions that could enhance sustainable advantage. Innovation, and more importantly Product Innovation, is increasing in its significance and has been assuming an increasing protagonist role in various markets and segments, as well as in companies and products competitiveness. The actual economic activity is based significantly on innovation within a knowledge society (OCDE/UE, 2005), hence the importance of knowledge resources has been escalating as knowledge has become a critical ingredient towards competitive advantage (Hsu, 2007). One of the effects of this is that an organization may need to assume a proximity relation of an innovator behaviour, in a way to avoid taking the risk of lose market share to any competitor considered more innovative (OCDE/UE, 2005). Additionally, this action can be considered as a proactive attitude to acquire a strategic favourable position in the market (OCDE/UE, 2005). The Oslo Manual (2005) highlights that among the possible factors an organization may use to decide on innovative activity, are competiveness and entry opportunities in new markets, usually related with products, markets, efficiency, quality levels, or the capability to learn and implement change.

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The option to proceed along the path of Innovation is undertaken frequently, with a large level of incertitude, since the investment result from the Research & Development (R&D) in knowledge, technology, markets, products, processes, new marketing methods and possible technological applications are very unpredictable. A high level of uncertainty exists, as well as expressive economic and time costs, although it varies depending on the investment sector or activity, among other factors such as product lifecycle (OCDE/UE, 2005). The success and impact of Innovation clearly depends on several factors, for example, one being its quality, which may vary from region to region on the support for Innovation (e.g. marketing strategies) from the organization. The impact of Innovation is influenced by the company’s organizational methods, and the company’s ability to take advantage of the benefits of the new processes and technologies, together with the company’s ability to generate satisfactory profits from its innovative activity (OCDE/UE, 2005). Alternatively, the Innovative activity can face difficulties that may influence its inception, for example, certain economic factors such as high cost or the lack of research, the lack of staff with appropriate aptitudes, a shortage of sufficient numbers of staff in the labour market (OCDE/UE, 2005), absence of knowledge and legal factors like laws/ norms, taxes and government measures, and the possible incapacity of companies to defend against copy by their concurrence (OCDE/UE, 2005). Other reasons may include, the lack of suitable infrastructure, mainly outside large urban centres, the scantiness of technology knowledge or of the necessary markets for Innovation development, and the inability to find the adequate partners (OCDE/UE, 2005). The supply and demand of markets affects, in several ways, new Product Development and innovative activity, as it can compel companies to optimize its production and productive methods in order to control costs and prices (OCDE/UE, 2005). The markets can also affect Innovation at the Product Development and Product Design stages (OCDE/UE, 2005). 1 Design, as a profession, is relatively young; however, the influence of Design on the Management of a company, or groups of product lines and Own Brand products, is extremely important in the development of products. The concepts of Design and Management, from an academic point of view, have not been clearly related, constituting a gap that suggests that new evidence and information is needed in this area. The importance and relevance of Human Capital needs to be understood with a focus on the designers (and design) as active elements and as strategic tools within organizations, as well as the management service in relation to this that can be provided, and the influence on Innovative Product creations. At present, attention is given to modifications and the evolution of the designer’s vision, transmuting from a more object orientated perspective to a global panorama, being more interventionist, and contributing to the strategy, competitiveness, company productivity and organization. The designer, a qualified professional, may achieve significant importance at the launch of the organisations innovative ‘Own Brand’ products, with its own multidisciplinary composition, from his education, familiarity with methodologies, processes and proceedings optimization, as well as his ‘Product’ familiarity. Equally, the value of Human and Structural Capital, Intellectual Capital components, are recognized in the literature as strategic factors influencing a company’s ability to generate and manage value (Bontis, 1998; Bontis & Nikitopoulos, 2001; Costa, 2010; Santos Rodrigues, 2008; Santos Rodrigues, Figueroa Dorrego, & Fernández ‐ Jardón Fernández, 2010; Swart, 2006), within organizations, and there is a growing importance of ‘Own Brand’ development within diverse markets. After a substantial literature review, this research study was born, which provides useful information for managers on how to achieve competitiveness, increase and improve productivity. The objective of this research was to analyse the relationship between management and design, and the influence of these on Product Innovation using ‘Own Brand’ development. In relation to the area of management, the study focused on the influence that knowledge assets could have on developing Products using an innovative design, with application to the (under‐researched) brand, by carrying out two ‘case studies’. The analysis of this paper is structured as follows: firstly, the analysis focuses on Intellectual Capital, addressing Human Capital; secondly, focus is placed on Product Innovation, particularly addressing ‘Own Brand’ products. The proposed analysis model is applied to two case studies conducted on two companies considered to be innovative. The subsequent research findings are then presented. 1

This concept should be distinguished from “style”, “the style is superficial, while the design is intrinsic” (Murphy, 1998).

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2. Theory and literature review As integrant of Intellectual assets, the concept of Human Capital has evolved over time. It emanates from the assumption that human beings possess skills and abilities, and included in the skills is their knowledge and experience, which enables changes in equity and economic growth (Dakhli & Clercq, 2004); both personal and professional commitment (Hsu, 2007) can be shaped and improved, including how people react and interact. The value of knowledge is represented by the intangible (i.e. behaviours, abilities) and skills present in people who constitute the organization (I.A.D.E.‐C.I.C., 2003). The concept of Human Capital refers to elements within companies and individuals that can add value and considers the human factor as a generator of tangible and intangible wealth. It also represents the knowledge value (i.e. behaviours, capabilities) and aptitudes that is present in individuals who constitute an organization (Bontis, 1998; Bontis & Nikitopoulos, 2001; Dakhli & Clercq, 2004; I.A.D.E.‐C.I.C., 2003). The Knowledge value may vary depending on the degree of singularity (Swart, 2006) which allows changes to actions and economic growth as much as its compromise (personal and professional) and commitment (Hsu, 2007) that can be adjusted and improved, as well as the way in which individuals react and interact. This is important because it is a source of Innovation and strategic renewal (Bontis, 1998). Human Capital can be generic which means it can be developed outside the confines of a company, being the kind of capital that can easily move between companies (Swart, 2006). Collaborators, when appropriately incentivised, stimulated and motivated, contribute to company prosperity, also associated with this is that as employees generate more valour within their companies, the greater the return for the employees should be (Davenport, 2007). This means that, organizations with highly motivated collaborators (crucial aspect to Human Capital (Mouritsen, Larsen, & Bukh, 2001; Santos‐Rodrigues, Figueroa, & Jardon, 2011) satisfied with unique abilities, namely being qualified (or highly qualified), intelligent and well informed, possess high levels of Human Capital and consequently companies are able to obtain a competitive advantage and a higher degree of commitment and compromise from individuals (Hsu, 2007; Santos‐ Rodrigues, et al., 2011). We considered Product Innovation as: a) the introduction of a new product/ good (OCDE/UE, 2005) into the Market; b) the development of a new use for a product (OCDE/UE, 2005); c) the development of a new use for a product only suffering minor modifications to the technical specifications (OCDE/UE, 2005), and d) the development of small modifications to the technical specifications of a product (OCDE/UE, 2005). It is internationally accepted that the three main structural components of Intellectual Capital are Human Capital, Structural Capital and Relational Capital (Edvinsson & Malone, 1997; I.A.D.E.‐C.I.C., 2003; Roos & Roos, 1997; Saint‐Onge, 1996; Stewart, 1998). Accordingly, Human Capital, corresponds in summary form to the resulting value of knowledge (and implementation) of the individuals present and related with a organization (Bontis, 2001; I.A.D.E.‐C.I.C., 2003). Knowledge assets of enterprises are positively related to their level of innovation (Thornhill, 2006). To create new or better products, firms must reallocate resources, combine new ones or combine existing resources both inside and outside firms in new ways (Tsai & Ghoshal, 1998). Thus, we predict that Human Capital is positively related to Product Innovation when using an organisations ‘Own Brand’.

3. Methodology The methodology used within this investigation is the case study, embracing a more exploratory analysis as the information on which this study is based is under‐researched. Yin (1994) considers this method among the more difficult and complex to formulate, as it has not been sufficiently and fully researched as yet.

The data collection phase included semi structured formal interviews, addressing Intellectual Capital aspects, with the Human Capital component being considered. With regards to Innovation, focus was placed on Product Innovation. The results obtained were mirrored by formal interviews with a script designed and used in an informal setting during interviews with directors and authorities. The data collection tool contained questions in the form of statements, and was evaluated using, with agreement, a Likert scale, classified from level 1 – ‘don’t agree’, to level 5 ‐ ‘totally agree’. The interviews were conducted during September 2010, with reference made to the last three years of activity and performance of companies.

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4. Findings The companies invited to participate in this case study are, due to confidentiality issues, identified as ‘Company A’ and ‘Company B’, which having a symbiotic partnership with a new ‘Company C’, allowing it a usufruct of synergies, on advertising and by providing equipment and automation to this new company. The companies are of medium size, located in northern Portugal, with strong regional implementation, yet demonstrating an interesting influential level intervention in the domestic market and representing prospects in international markets. Company A, has experience of decades of market implementation, with its main market being in ‘construction’ retail. The main markets of intervention for it are: Portugal, Spain, France and Angola. Its annual turnover is around thirty million euro’s, where the values obtained from the ‘Own Brand’ products themselves are not very significant. Although it is a medium sized company, it enjoys high market power in the region, is heavily involved in the Portuguese market penetration, and has several international markets, usually driven by the incursion of a number of its customers in these markets. This company has approximately one hundred and forty (140) employees with higher qualifications and formal education. Its investment in innovation is around ten million euros; this investment corresponds to its facilities, provision of physical space, adoption of a new physical layout and organization and acquisition of new equipment, so far non‐existent in the company, and development of more profitability. It does not, however, have an annual budget aimed at Research and Development (R & D).

‘Company B’ has its target market within automation and control. Although it is a large company with international representation in the Portuguese market, it still has a small market share. The headquarters of ‘Company B’ is in northern Italy. Although it is a new company, it already has strong representation in international markets, directly or through partnerships, in more than 30 countries.

‘Company B’ has twelve employees (and an undetermined number of outsourcing) in its direct service in Italy, two direct employees and one indirect employee in Portugal, relying on their symbiotic partnership also created with ‘Company C’ to leverage resources and synergies. ‘Company C’ has a staff complement of approximately seven. This partnership allows ‘Company B’ the direct and indirect use of logistical resources and the use of their employees, since they share employees and its headquarters is in Portugal. The turnover of the Portugal headquarters is approximately five and a half million euro’s, 40% of this turnover comes from the introduction of Product Innovations, and together with a portion of the profits from the headquarters consorts, approximately 2.7% of the turnover, is intended for R & D performed in the Italian University of Udine, northern Italy.

5. Discussion and conclusion The Human Capital aspect suggests that it is of the utmost importance that staff motivation and innovation needs to be supported and encouraged by the organization. These factors are of great importance in order to obtain stable employment of the company since it was observed that the ‘psychological factor’ (optimism, attitude, initiative and entrepreneurship) and motivating employees, are the factors that have a direct and instantaneous impact on the present value of Human Capital, as stated by several authors (Bontis & Fitz‐enz, 2002; Dakhli & Clercq, 2004; Mouritsen, et al., 2001; Osterloh & Frey, 2000; Santos‐Rodrigues, et al., 2011). Also concerning with the high qualify professional, the designer, we established that the formal academic training of designers and their multidisciplinary training were drivers of innovativeness, reinforcing the role and significance of the Human Capital inside organizations and its reflections throw its results. It should be noted that the importance of Human Capital is repeatedly mentioned and supported by the literature (Bontis, 1998, 1999; Bontis & Nikitopoulos, 2001; Dakhli & Clercq, 2004; Santos‐Rodrigues, et al., 2011; Swart, 2006) and does at times appear in the literature in a more general way, with others having a specific focus on its value. The weight of Human Capital is based on the capacity and effectiveness of the firm to store value, transforming it into Structural Capital and to include it as the basis of profitability for the other capital constituents of Intellectual Capital (Bontis, 1998; Santos‐Rodrigues, et al., 2011).

Acknowledgements This paper is partially supported by the Portuguese Foundation for Science and Technology ‐ FCT.

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Intellectual Capital and Innovation: A Hospital Case Study Helena Santos‐Rodrigues1, João Faria2, Carminda Morais3 and Desireé Cranfield 4 1 Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal and CIEO – Centre of Spatial Research and Organizations, Universidade do Algarve, Portugal 2 Master from Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal 3 Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal 4 University of Southampton, Southampton, UK hsantos@estg.ipvc.pt jfariaenf@hotmail.com carmindamorais@ess.ipvc.pt djcranfield@gmail.com Abstract: This research aims to investigate the influence of intellectual capital and the capacity for innovation of a health care public institution. The focus of the research is centred on the human, structural, and relational components of intellectual capital and on innovation, in accordance with the research proposal of Santos‐Rodrigues (2011). The questionnaire was administered between July and August of 2011 to 68 managers / leaders of various service departments of a hospital. After analysis and validation of the questionnaires received, 65 of these questionnaires were used in the research. Using regression analysis, we found that incentives for the innovation dimension of human capital is related to the innovation created, trust is the only structural capital dimension related with innovation adopted and, finally, we found that networks and alliances, a dimension of the relational capital, is the only dimension simultaneously related with innovation created and innovation adopted. All the research hypotheses have therefore been validated, additionally the research suggests that human capital has a direct relation with innovativeness, but only with the innovation created. Structural capital was found to be partly related with innovation adoption. Finally, we found that relational capital is the only Intellectual Capital that is related simultaneously with innovation creation and innovation adoption. Keywords: intellectual capital, innovation capability, hospital, organizational performance

1. Introduction Carbone et al. (2005) contend that in an increasingly globalized world, the survival of companies depends on their capacity to innovate. A company’s ability to innovate depends on its organizational intelligence, and is represented by their information and knowledge systems, the competencies of their employees, the quality of their production processes and their customer service. Moreover, to succeed in this context, or simply remain viable, companies must be innovative (Govindarajan and Trimble, 2005). As such, this study aims to verify whether the different components of intellectual capital, i.e. Human Capital, Structural Capital, and Relational Capital, influence the innovative capacity of a hospital. The adoption and creation of a product, process and management innovation were considered as the dimensions of innovation. The hospital, as an organization, has several different departments and services, each having its own leadership and being quite differentiated. Hospitals are also very complex institutions, with a mixture of industrial, scientific and technological procedures conducted on humans, with a diverse set of cultural, educational and social components intertwined. As such, the influence of intellectual capital on the innovative capacity of a hospital was investigated. In order to meet our research objectives, we raised three hypotheses: H1: Human capital influences the innovative capacity of a hospital. H2: Relational capital influences the innovative capacity of a hospital. H3: Structural capital influences the innovative capacity of a hospital. To validate our research hypotheses, we considered the items proposed by Santos‐Rodrigues et al. (2011b).

1.1 Human capital In the '60s a very strong interest started to develop around the concept of human capital. Schultz (1961) and Becker (1962) pioneered the formalization of models centred on human capital. For these authors, the concept

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Helena Santos‐Rodrigues et al. is identified as an active set of skills, individual skills, and hence, human capital cannot be considered as the property of an organization. Human capital is extremely important to an organization as individual capacities will be reflected in the performance of an organization as a whole. Human capital represents the value of the knowledge and talent which is embodied in people who make up the organization, representing its know‐how, capacities, knowledge, talent, competence, attitude, intellectual agility, creativity, and others (I.A.D.E.‐C.I.C., 2003, Edvinsson and Malone, 1997, Bontis and Fitz‐enz, 2002, Edmonson, 1999, Roos et al., 1997, Davenport et al., 2003, Kaplan and Norton, 1996, Santos‐Rodrigues et al., 2011b). Currently, the knowledge and skills of employees is extremely important to any organization; however, a number of research studies have found that additional training does not necessarily lead to better performance (Santos‐Rodrigues et al., 2011b). Sanchez et al. (2000) refers to the employee's training as a springboard to raise the educational level of the company and consequently influence the innovation capacity. Mouritsen et al. (2001) contends that the company must also have an innovative attitude towards its employees and never expect that innovative behaviour is the result of an isolated employee initiative; therefore, the incentive of the company is also important (Osterloh and Frey, 2000). This innovative approach involves some freedom of action of the employees, so companies may consider promoting an innovative attitude of the employees, as it is a crucial aspect for innovation. Another important driver of an innovative employee, is the fairness and equity within the organization, which specifically includes a safe work environment and remuneration adjusted to provide compensation for each worker encouraged to participate in the process of knowledge creation, innovation and sharing (Santos‐Rodrigues et al., 2011b). Bontis and Fitz‐ enz (2002) claim that they find a strong relationship between the feeling of satisfaction and motivation, with organizational performance. Creativity is a way to combine knowledge to go beyond the original idea, and knowledge is the raw material of innovation. Creativity and innovation complement each other. The combination of technology and human capabilities assigns a value of creativity (Mouritsen et al., 2001). Shelton et al. (2005) assert that creativity must be exercised by all levels of the organization so that ideas turn into models. The cultural aspect of creativity is also linked to innovation; because there is respect for different cultures, this enables the openness to new ideas. Innovation is not guaranteed by creativity, however, it should be supplemented to lead to success (Shelton et al., 2005). Denisi et al. (2003) warn that to be creative, employees should feel safe and unafraid to take risks and make mistakes. This is supported by the study of Edmonson (1999) which highlights that, to enhance creativity and innovation, it is necessary to strengthen the climate of tolerance and security. Wan et al. (2005) reinforce the idea that managers should be tolerant of errors of innovation, and they also argue that these managers should gradually develop relationships within a multidisciplinary context. Fear of making mistakes is the end of the creative process (Farson and Keyes, 2002); these authors found that leaders must implement strategies and actions to encourage tolerance. Supervisors also have a great power to identify potential sources of innovation in the organization; this power was identified by Nonaka and Takeuchi (1995) who argued that middle managers identify and combine knowledge in order to make it explicit. This gives the managers/directors a commitment to the organization and employees. A number of research studies have concluded that a positive and direct relation between human capital and innovativeness exists (Santos‐Rodrigues et al., 2010a, Santos‐Rodrigues et al., 2012b) and that there is a positive and indirect relation (Santos‐Rodrigues et al., 2012a).

1.2 Structural capital When one starts to talk about structural capital, this leads one to think that this is part of the capital allocated to the structure of the organization. Putnam (1996) defines the concept as factors of social life, which may include internal networks and standards, as well as the confidence that reinforces the instinct to achieve the intended goal. That is, an inclusion of all processes and routines, as well as the organizational culture, systems, structures, brands and intellectual property, among others. It is also contemplated to include other intangible assets not having a measurable value, which can be conferred on the firm even after people have left the organisation.

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Helena Santos‐Rodrigues et al. As the name suggests, structural capital takes care of the infrastructure of the organizations non‐material assets. Edvinsson and Malone (1997) consider structural capital to be an outline, empowerment, providing infrastructural support for human capital. Structural capital is defined as knowledge, skills, experiences and information, institutionalized, codified, and used by databases, patents, manuals, structures, systems, routines and processes (Youndt et al., 2004). The culture can be developed within the organization to boost learning and innovation (Denisi et al., 2003). Jassawalla and Sashittal (2003) refer to the environment created among employees as the innovation culture that improves behaviour. These authors discuss three important factors for the innovative capacity: cognitive elements, behaviours and artefacts, and symbols. The culture which emphasizes knowledge and skills should be valued by the company. Culture is the essence for the development of skills and resources for innovation. Trust is a concept with some subjectivity. It cannot be imposed, only encouraged and maintained (Ford, 2001). For this author, the concept has undergone changes over time and has distinguished business confidence in three categories: strategic trust, personal trust and organizational trust. Despite the different backgrounds of the personal and organizational trust, both are infused by relative risk and interdependence. Rousseau et al. (1998) argue that trust is not a behaviour; rather, it represents a psychological condition. Santos‐Rodrigues et al. (2011) considers that the confidence associated with rewards at work adds a motivation for creativity. The attitude of workers is influenced by trust, motivating them to participate in activities that trigger innovation. The structure of organizations depends on the degree of bureaucracy and complexity of the structure. Nilakanta and Subramanian (1996), argue that formalization is related to the characterization and description of the duties of workers, a fact which is negatively related to innovation, according to Santos‐Rodrigues et al. (2011b). There are authors who argue that firm size has an influence on its ability to innovate, and there are several authors who found a positive relationship between firm size and the ability to innovate (Damanpour, 1992). Wan et al. (2005) found a positive relationship between decentralized organizations and innovative capacity. In general, hospitals are organizations with an inflexible hierarchy where creativity does not develop easily, however, there are groups who facilitate improving the innovative capacity; IADE (2003) reinforces the importance of this idea in the business world. The lack of a system for collecting and developing ideas of employees hinders innovation in the hospital. What is important in organizations is to remove the entire value of the innovation process (Shelton et al., 2005); structural capital seems to be related with the innovativeness (Santos‐Rodrigues et al., 2011b, Santos‐Rodrigues et al., 2012b, Santos‐Rodrigues et al., 2011a) and with cumulative growth rate (Santos‐Rodrigues et al., 2012a).

1.3 Relational capital Relational capital refers to the relationships the outside world has with the organization. A number of research studies refer to it as capital of the customer. However, it is worth noting that the name of the reducing client is only because, in the sphere of intellectual capital, all entities that relate to the organization are endowed with knowledge and capabilities that enhance all of their activities (Cabrita, 2009). Relational capital is the result of the value generated by the organisations relationships with the environment, including with suppliers, buyers, competitors, shareholders, stakeholders, and the society. In hospitals, as in all other organizations, all internal and external elements are important, such as training, experience, internal and external factors. It therefore becomes clear that the relational capital of an organization is an important trigger for innovation. The interactions with the outside world are also of relevance to innovation, although it is unusual that stakeholders contribute in a substantial way. Gordon (2007) warns that the company that is structured and centred only on internal interactions does not succeed; it is necessary to look outward and consider the wider market. Considering customers as a source for new ideas and innovation, in reference to the automotive world, especially producers of components, Santos‐Rodrigues et al. (2009) contend that this aspect influences the innovative capacity. The hospital as an organisation, is unique in that respect, as customers are sick and weak; however, they have opinions. Their feedback promotes the regeneration of knowledge, providing an

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Helena Santos‐Rodrigues et al. organization with the possibility of becoming more efficient and novel (Stewart, 1998). Shelton et al. (2005) highlights the role of information technology in the interaction between organizations and customers. Shelton et al. (2005) further reports that the existence of an external network of partners, which is consistent, allows the capture, balance and adjustment of creativity and value important for innovation. In healthcare institutions, there are networks created as regulators of health care, health inspection and specialized working groups in a given area. The existence of these networks is an important source of innovation, although it is not guaranteed that innovation happens as a result (Santos‐Rodrigues et al., 2010b). Alliances, mergers or business combination is a way of acquiring knowledge‐based resources (Denisi et al., 2003). The alliances come from the need for companies to complement each other in terms of skills, so that the major goal is reached.

2. Methods 2.1 Sample and data collection We tested the hypotheses using survey data collected in 2011. While obtaining a sample of significant linkage of intellectual capital as a strategic resource and its effect on innovativeness would allow a more comprehensive understanding of the phenomenon, we relied on service directors of a hospital from Northern Portugal as key experts ‐ an established practice in organizational research (Huber and Power, 1985) as they are aware of the strategic choices. We distributed the survey to 68 service directors. Each participation request included a description of the study and a statement of confidentiality. We received 65 responses, with a response rate of 95.4%.

2.2 Measures Both intellectual capital components and the capacity for innovation have been regarded as multidimensional constructs. This implies the need to establish a series of items to measure. We have used the questionnaire developed by Santos‐Rodrigues et al. (2011a) adapting the scales for human, structural and relational capital and innovativeness to the hospital context. Using the Cronbach Alpha, internal consistency of the constructs for each dimension was verified. Since each dimension is above 0.8, it can be stated that there is a good and very good internal consistency among the items. Table 1: Reliability analysis of the variables through Alpha Cronbach Variables Human Capital (CH) Structural Capital (CE) Relational Capital (CR) Innovative Capacity(CI) Source of Innovation(OI)

Items Nº 14 19 9 8 6

Alpha Cronbach 0,816 0,927 0,895 0,858 0,890

We considered that the main human capital dimensions relevant to an organisation’s innovativeness were:

Formation: as a representation of the knowledge of the employees due to the task development (Youndt and Snell, 2004, Youndt et al., 2004, I.A.D.E.‐C.I.C., 2003, Subramaniam and Youndt, 2005);

Innovative attitude: as the commitment and willingness of the employees and employers to innovate (Cabrita and Bontis, 2008, Mouritsen et al., 2001, Osterloh and Frey, 2000);

Creativity: representing the willingness, support and value of the creativity of the employees (Mouritsen et al., 2001, I.A.D.E.‐C.I.C., 2003, Youndt and Snell, 2004, Youndt et al., 2004, Davenport et al., 2003, Subramaniam and Youndt, 2005);

Incentive to innovativeness: as the personal and material incentives regarding the innovative behaviour of the employees (Shelton et al., 2005, I.A.D.E.‐C.I.C., 2003, Wan et al., 2005).

We considered that the main structural capital dimensions relevant to an organisation’s innovativeness were:

Culture: reflecting the existence of an innovation‐oriented department in the company, as well as processes designed to foster innovation or a collection system and implementing new ideas;

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Trust: between employees and the confidence they have in the company and its management. It also includes the environment of confidence in the company and the role played by the leader in the enterprise;

Creation and Knowledge Development: includes institutional support for the creation of knowledge through the existence of groups of valid improvements and use of employee suggestions, as well as the willingness to innovative in processes or suggest improvements;

Organizational structure: reflects the formalization and openness verified in the company.

We considered that the main relational capital dimensions relevant to an organisation’s innovativeness were:

Networks and alliances: represent the formal or informal input from customers, suppliers and competitors conducive to innovation in the enterprise. This also reflects the importance and structure of partnership agreements with competitors and partners.

Clients: particularly focused on the contributions and importance of customers for its innovative capacity. It also includes collaboration with knowledge institutions with a view towards innovation and growth of the importance and satisfaction of customers due to the innovative capacity of the company.

We relied on the adoption and creation of innovation measures and on the three performance measures of innovativeness: product, process and management innovation (Ahuja, 2000, Hii and Neely, 2000, Davenport et al., 2003, Ravichandran, 2000, Santos‐Rodrigues et al., 2011a). In the analysis, relative innovation was considered, meaning that an innovation is considered new if it is new to the firm, regardless of whether or not it is new to the world or industry.

2.3 Data analysis To evaluate the different constructs we used the principal components technique. This technique aims to reduce the size of the initial set of items that provides common information, seeking to illustrate them all, while creating some new variables which collect common information that keeps the residual and more specific information for each of the original items. The variables with communalities less than 0.4 were eliminated as they do not contain information common to the rest of the items. To select the number of factors, we took into account the Kaiser method, the scree plot and those that explain at least 50% of the total variance (Costelo and Osborne, 2005). Having reduced the information to better understand its meaning, we make use of a rotation process of adjusting to the different axes for the original items so no information is lost. Traditionally, it uses a technique that maintains a varimax orthogonal relationship between the components involved, ensuring they are uncorrelated. The degree of validity of this technique is given by two auxiliary instruments: the Bartlett test and the coefficient of Kaiser‐Meyer and Okin (KMO); the values that are usually considered acceptable are those greater than 0.6. Since the set of items was used for each aspect, trying to measure a single construct, to establish the reliability of the measuring instrument and data collection, the Cronbach alpha coefficient was calculated, through which the internal consistency of the questionnaire was determined. This method is based on the analysis of the average correlations among items related to one theme, from a single administration of the questionnaire. This ratio produces values ranging from zero (0) and one (1). The closer the value to one (1), the more reliable the instrument is. The criteria used for the interpretation of the Cronbach alpha coefficient values are given by Nunnelly (1978) as less than 0.6 (low), between 0.61 and 0.70 (right), ranging from 0.71 to 0.80 (good), and over 0.80 (high). To see the effect between constructs, we made use of linear regression techniques that allow us to evaluate and compare the direct effect of each independent variable on the dependent question (Jardón et al., 1997). For the analysis process, purification and processing of data, determining factors and impact assessment, we used the Statistical Package for Social Sciences (SPSS version 18).

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2.4 Analysis and results For Human Capital, factorial analysis of principal components showed that the 14 initial variables were explained in 70.54% for 4 common factors obtained from a Varimax rotation with Kaiser Normalization converged in 5 interactions. The KMO indicates a reasonable correlation between the items (KMO=0.729) and Bartlett's test has an associated level of significance of 0.000 which leads to the rejection of the hypothesis that the correlation matrix is the identity matrix (p <001), so there is a correlation between some variables. Both tests allow the continuation of factor analysis. Four indices were set. For Structural Capital, factorial analysis of principal components showed that the 19 initial variables were explained in 69.71% for 4 common factors obtained from a Varimax rotation with Kaiser Normalization converged in 6 interactions. The KMO indicates a reasonable correlation between the items (KMO=0.842) and Bartlett's test has an associated level of significance of 0.000 which leads to the rejection of the hypothesis that the correlation matrix is the identity matrix (p <0.01), so there is a correlation between some variables. Both tests allow the continuation of factor analysis. Three indices were set. For Relational Capital, the factorial analysis of principal components showed that the 9 initial variables were explained in 68.69% for 2 common factors obtained from a Varimax rotation with Kaiser Normalization converged in 3 interactions. The KMO indicates a reasonable correlation between the items (KMO=0.848) and Bartlett's test has an associated level of significance of 0.000 which leads to the rejection of the hypothesis that the correlation matrix is the identity matrix (p <0.01), so there is a correlation between some variables. Both tests allow the continuation of factor analysis. Two indices were set. Finally, we considered two factors as valid factors that represent the ability to innovate. The factor analysis indicates a reasonable correlation between the variables included (KMO=0.769). The test of Bartlett's sphericity is associated with a significance level of 0.000, from which it follows that there is a correlation between some variables. Both tests allow the continuation of factor analysis. The component matrix shows that the 14 initial items were explained in 69.44% for 3 common factors, obtained through a Varimax rotation with Kaiser Normalization converged in 5 interactions. We did a regression with all variables of Intellectual Capital, selecting the B's with values greater than 0.200 demonstrating the existence of robust relationships between the constructs. We verified different behaviours for Innovation creation (product / process / management) and Innovation adoption (product / process / management). Considering the results obtained with the Multiple Linear Regression analysis, we note that human capital (on the incentives to innovate dimension) and structural capital (on the trust dimension) are related only with the innovation creation (product / process / management). Furthermore, the relational capital (on the network and alliances dimension) is the only intellectual capital related with creation innovation and adoption innovation (product / process / management).

3. Conclusion As expected in our first hypothesis (H.1.), Human Capital is associated with the innovativeness of the company, in particular we conclude that Human Capital is related only with innovation creation and only with “the incentives to innovate” dimension. However, in this research study, the connection is weak. This is not new, as other research studies have not even found a direct connection between human capital and, for instance, cumulative growth rate (Santos‐Rodrigues et al., 2012a), or they have not found a direct relation between human capital and management innovativeness (Santos‐Rodrigues et al., 2011b). Stewart (1998) found that Human Capital has no significant direct impact on business performance because it needs the other intellectual components, such as the structural and relational capital to be processed. In addition, Bontis (1998) and Cabrita (2008) found no significant direct relationship between Human Capital and business performance. We also validated our second hypothesis, H.2. We observed that Structural Capital is directly related to innovation adoption, and these results were validated by theoretical arguments (Davenport et al., 2003) that consider that it is the company that turns knowledge into performance. Businesses should support the performance of employees through their infrastructure, information systems, routines, culture and trust, facilitating the dissemination of knowledge. The relationship between structural capital and innovativeness was also contrasted by Subramanian and Youndt (2005), Organizational Capital in their case, and they verify

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Helena Santos‐Rodrigues et al. the existence of a significant relationship with incremental innovation capacity (not all types of innovative capacity). On the other hand, we see that structural capital is not directly related with innovation creation; this result does not coincide with the argument of a number of authors who ascertain that trust is essential for innovation processes to be effective (Adler and Kwon, 2002, Ford, 2001). We also validated our hypothesis H.3., noting that Relational Capital is the only Capital directly related with both innovation creation and innovation adoption. The dimension of networks and alliances is directly and positively related to innovation creation and innovation adoption. In summary, the three research hypotheses were validated. Therefore, we can conclude that our study supports that Intellectual Capital influences the innovativeness of the company, although there are some nuances worth noting. An important result achieved is that we found a dichotomy within the Innovative Capacity. This dichotomy is very relevant to our findings and conclusions.

References Adler P. S. & Kwon, S. W. 2002. Social capital: Prospects for a new concept. Academy of Management Review, 27, 17‐40. Ahuja, G. 2000. Collaboration networks, structural holes, and innovation: A longitudinal study. Administrative Science Quarterly, 45, pg. 425‐455. Becker,B.E. (1962): "Investments in human capital: a theoretical analysis", Journal of Political Economy, n.70, pp.9‐44. Bontis, N. 1998. Intellectual capital: an exploratory study that develops measures and models. Management Decision, 36, 63‐76. Bontis, N. & Fitz‐Enz, J. 2002. Intellectual capital ROI: A casual map of human capital antecedents and consequents. Journal of Intellectual Capital, 3, 223‐247. Cabrita,M.R. (2009): Capital Intelectual e Desempenho Organizacional, Lisboa e Porto, Lidel. Cabrita, M. R. & Bontis, N. 2008. Intellectual capital and business performance in the Portuguese banking industry. International Journal of Technology Management, 43, 212‐237. Carbone, P. P., Brandão, H. P., Leite, J. B. D. & Vilhena, R. M. P. 2005. Gestão por Competências e Gestão do Conhecimento, Rio de Janeiro, FGV. Costelo, A. & Osborne, J. 2005. Best Practices in Exploratory Factor Analysis: Four Recommendations for Getting the Most From Your Analysis. Practical Assessment. Research & Evaluation [Online], 10. Damanpour, F. 1992. Organizational size and innovation. Organizational Studies, 13, 375‐402. Davenport, T. H., Prusak, L. & Wilson, H. J. 2003. Who´s bringing you hot ideas and are you responding? Harvard Business School Press, 81, 58‐64. Denisi, A. S., Hitt, M. A. & Jackson, S. E. 2003. The knowledge‐based approach to sustainable competitive advantage. In: Jackson, S., Hitt, M. A. & DenisI, A. S. (eds.) Managing knowledge for Sustained Competitive Advantage. San Francisco: Jossey‐Bass. Edmondson, A. 1999. Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44, 350‐ 383. Edmonson, A. 1999. Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44, 350‐ 383. Edvinsson, L. & Malone, M. S. 1997. El Capital Intellectual: Cómo Identificar y calcular el valor de los recursos intangibles de su empresa, Gestión 2000. Farson, R. & Keyes, R. 2002. The Failure‐Tolerant Leader. Harvard Business Review, 80, 64‐71. Ford, D. 2001. Trust and Knowledge Management: the seeds of sucess. Canada: Queens's University at Kingston. Govindarajan, V. & Trimble, C. 2005. Organizational DNA for Strategic Innovation. California Management Review 47, 47‐76 HII, J. & Neely, A. 2000. Innovative Capacity of Firms: on why some firms are more innovative than others. 7th International Annual EurOMA Conference 2000‐ Ghent. Ghent. Huber, G. & Power, D. 1985. Retrospective reports of strategic‐level managers: guidelines for increasing their accuracy. Strategic Management Journal, 6, 171‐180. I.A.D.E.‐C.I.C. 2003. Modelo Intellectus: medición y gestión del capital intelectual. Madrid. Jardón, C., Verdugo, M. & Cal, M. 1997. Econometría estática aplicada, Santiago de Compostela, Tórculo. Jassawalla, A. R. & Sashittal, H. C. 2003. The DNA of culture that promote product innovation. Ivey Business Journal Online [Online], 1. Kaplan, R. S. & Norton, D. 1996. The Balanced Scorecard: translating strategy into action, Boston, Harvard Business School Press Mouritsen, J., Larsen, H. T. & Bukh, P. N. 2001. Valuing the future: Intellectual capital supplements at Skandia. Accounting, Auditing & Accountability Journal, 14, 399‐422. Nonaka, I. & Takeuchi, H. 1995. The knowledge Creating Company. How Japanese Companies Create The Dynamics of Innovation, London, Oxford University Press. Nunnally, J. 1978. Psychometric Theory, New York, McGraw‐Hill. Osterloh, M. & Frey, B. S. 2000. Motivation, knowledge transfer, and organizational forms. Organization Science, 11, 538‐ 550.

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Helena Santos‐Rodrigues et al. Putnam,R. (1996): Who killed civic America, Prospect . Ravichandran, T. 2000. Redefining Organizational Innovation: Towards Theoretical Advancements. The Journal of High Technology Management Research., 10, 243‐274. Roos, J., Roos, G., Dragonetti, N. C. & Edvinsson, L. 1997. Intellectual capital: navigating in the new business landscape, London. Rousseau, D. M., Sitkin, S. B., Burt, R. S. & Camerer, C. 1998. Not so different after all: A cross‐discipline view of trust. Academy of Management, 23, 393‐404. Sanchez, P., Chaminade, C. & Olea, M. 2000. Management of intangibles: An attempt to build a theory. Journal of Intellectual Capital, 1, 312‐327. Santos‐Rodrigues, H. & Almeida, M. D. R. A. D. 2009. The Influence Of Clients, as a Dimension of the Relational Capital, on the Product‐Process Innovativeness. International Journal of Engineering and Industrial Management, Special issue on Knowledge Management, 183‐192. Santos‐Rodrigues, H., Figueroa Dorrego, P. & Jardon, C. 2010a. The Influence Of Human Capital On The Innovativeness Of Firms. International Business & Economics Research Journal, 9. Santos‐Rodrigues, H., Figueroa, P. & Jardon, C. 2010b. The relation between network of collaboration (as a relational capital dimension) and firm innovativeness. 2nd European Conference on Intellectual Capital. Lisbon, Portugal. Santos‐Rodrigues, H., Figueroa, P. & Jardon, C. 2011a. Intellectual Capital and Firm’s innovativeness. 3th European Conference on Intellectual Capital. Nicosia, Ciprus. Santos‐Rodrigues, H., Figueroa, P. & Jardon, C. 2011b. The main intellectual capital components that are relevant to the product, process and management firm Innovativeness. International Journal of Transitions and Innovation Systems, 1, 271‐301. Santos‐Rodrigues, H., González‐Loureiro, M. & Figueroa‐Dorrego, P. Year. System of Innovation and Innovative SMEs; a Model for Measuring the Intellectual Capital of SMEs. In: 4th European Conference on Intellectual Capital, 2012a Helsinquia, Finland. Santos‐Rodrigues, H., Lousinha, L. & Cranfield, D. Year. The Human and Structural Capital Influence on the Launch of Own Brand Product Innovation. In: 4th European Conference on Intellectual Capital, 2012b Helsinki, Finland. Schultz,T.W. (1961):” Investment in human capital” , American Economic Review, vol.51, n.1, pp:117. Shelton, R., Davila, T. & Brown, P. 2005. The Seven Rules of Innovation. Optimize, 4, 51‐56. Stewart, T. A. 1998. Intellectual Capital: The New Wealth of Organizations, New York, Doubleday. Subramaniam, M. & Youndt, M. A. 2005. The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal., 48, 450‐463. Wan, D., Ong, C. H. & Lee, F. 2005. Determinants of firm innovation in Singapore. Technovation, Vol. 25, 261‐268. Youndt, M. A. & Snell, S. A. 2004. Human Resource Configurations, Intellectual Capital, and Organizational Performance. Journal of Management Studies, XVI, 337‐360. Youndt, M. A., Subramaniam, M. & Snell, S. A. 2004. Intellectual Capital Profiles: An Examination of Investments and Returns. Journal of Management Studies, 41, 335‐361.

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Human Capital and Financial Results: A Case Study Helena Santos‐Rodrigues1, Guiomar Pereira‐Rodrigues2 and Desireé Cranfield 3 1 Dept. of Economics and Business Sciences, School of Technology and Management, Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal and CIEO – Centre of Spatial Research and Organizations, Universidade do Algarve, Portugal. 2 Dept. of Economics and Business Sciences, School of Technology and Management, Polytechnic Institute of Viana do Castelo, Viana do Castelo, Portugal 3 University of Southampton, Southampton, UK hsantos@estg.ipvc.pt guiomar@estg.ipvc.pt djcranfield@gmail.com Abstract: If a company aims to succeed at developing its competitive advantage, knowledge assets should be considered as an important resource as it is the raw material from which financial results are obtained. This Case Study aims to determine whether human Capital is presented and valuated in a small company working in the logistics sector, and if it has an impact on the financial performance. Considering this, we have developed a Case Study that utilises a pragmatic and unique, holistic and exploratory approach. Data collection was carried out mainly through interviews and observation centred on Human Capital and on the financial performance, conducted on two elements from different levels of authority and responsibility within the company, a director and an operation employee. A Likert scale of 5 points was used, and the study concluded that both participants interviewed, shared a similar point of view about Human Capital and the financial performance. It was also concluded that the company evaluated is human Capital, in particular, the follow elements: the employee’s formation and training, skills, teamwork, internal relations and knowledge share had impact in the financial performance of a firm, and the company had a positive result over the years, although yields have stagnated recently, and expenses have increased due to the current international crisis. Consequently, it was concluded that in those companies, Human Capital was valuated and the case study suggests that there is a relationship with financial performance. Keywords: human capital, enterprise results, financial results, financial performance, logistics

1. Introduction The social and business environment is becoming increasingly competitive, hence, if companies want to develop a sustainable competitive advantage, the key is to focus on knowledge based assets, such as those considered in Intellectual Capital. It is considered that the efforts of organizations must go through the incorporation of knowledge in its production and management strategy. Sullivan and Sullivan (2000) state that the number of companies whose value is focused largely on Intellectual Capital has increased dramatically in recent years. The new economy may or may not materialize, but there is no doubt that the next society will be with us soon (Drucker, 2001).Chen, Cheng, and Hwang (2005) suggest that Intellectual Capital not only has a positive impact on present financial performance, it also indicates future financial performance. Considering this we have developed a Case Study focused on whether the Human Capital was present and valuated within a small logistics firm located in Northern Portugal and if it was related with the financial performance of the firm. Several research papers and literature reviews focus on Intellectual Capital, with some focusing on the measurement perspective of Intellectual Capital such as the Chen, Zhaohui, and Xie (2004) research, with other studies focusing on the influence of Intellectual Capital on different aspects of the firm, such as the study of Human Capital as a key strategic asset of companies (Bontis and Fitz‐enz, 2002), the relation of Intellectual Capital with business performance (Bontis et al., 2000), and the relationship of Intellectual Capital with the innovative capacity(Santos‐Rodrigues et al., 2011d, Santos‐Rodrigues et al., 2011c).When we started this study, at 2010, no similar study was found that related the influence of Human Capital on financial performance, later, Murthy and Mourtisen (2011), relate Intellectual Capital with financial capital in the banking sector, and hence, their suggestion support our study. Furthermore, we follow the methodology suggested by Santos‐Rodrigues et.al (2011c, 2011d) to analyse the influence of Intellectual Capital on financial results.

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2. Human capital and finance results Currently, organizations are concerned with achieving excellence in their performance, and as Stewart (Stewart, 1998) states, Intellectual Capital is the raw material from which the financial results occur. Intellectual Capital management therefore, intends to extract value from the firm’s knowledge (Egbu, 2004).Murthy and Mouritsen (2011)contend that a relation between Intellectual Capital (which includes Human Capital) and the firm’s financial performance exist, hence, this research study aims to examine a logistic organization to find if there is any relation between Human Capital and financial performance. Intellectual Capital includes the strategic perspective of intellectual assets and knowledge (Santos‐Rodrigues et al., 2011d). The literature tends to explore the different sub‐components of Intellectual Capital in detail, and there are three attributes inherent in the Intellectual Capital present in most settings; the result of the collective processes (Mouritsen et al., 2002) has value and the potential to create value (Petrash, 1996, Stewart, 1998, Edvinsson and Sullivan, 1996). It is internationally accepted that the three main structural components of Intellectual Capital are Human Capital, Structural Capital and Relational Capital (Edvinsson and Malone, 1997, Roos et al., 1997, I.A.D.E., 2003, Stewart, 1998). Accordingly, Human Capital, corresponds in summary form to the resulting value of knowledge (and implementation) of the individuals present and related with the organization (Bontis, 2001, I.A.D.E., 2003).Structural Capital is the value of knowledge present on the organization by the structure of the organization, which includes: formal rules and informal norms (Bontis, 2001, I.A.D.E., 2003). Relational Capital represents the value knowledge generated by the relations of the organization with it environment, including trade relations, partnerships, affiliations and associations. Intellectual Capital is a process which extracts value from existing knowledge in an organization. The Human Capital, " is the basis of intellectual capital" according to Chen et al (Chen et al., 2004). human capital has been recognized as a vital and creator of value for companies. Cabrita (2008) stresses that human capital is identified as the engine of economic activity, competitiveness and economic prosperity. Bontis and Fitz‐Enz (2002) state that "the human capital embodied knowledge, talent and experience of employees". Refers to "the qualities that make people" says Brooking (1996). One cannot forget that human capital is one of the elements of the organization that deserves much attention because it can create value and competitive advantage for the organization compared to competing companies. For "is an irreplaceable resource and its imitation is imperfect" according to Bontis and Fitz‐Enz (2002). After cited no doubt that human capital is crucial for companies like Brooking says (1996, p. 15), which refers to its importance because "there is no business that can operate without at least one person ". As far as human capital has important implications in terms of the strategy of intellectual capital in the company it is a source of profit in the knowledge economy, "human capital is important because it is a source of innovation and strategic renewal" (Bontis and Fitz‐enz, 2002, Bontis, 1999). In today's business environment, human capital is considered as a major source of competitive advantage, Human capital is essential to the success of the organization because it affects their performance and gives the organization collective intelligence. Stewart (Stewart, 1998) says that "when people work together create something that is worth more than the sum of their individual efforts. The difference is profit, return on capital. "

3. Methodology The methodology used for this investigation was the Case Study, embracing a more exploratory analysis approach as the information on which this study is based is under‐researched. Yin (1994) considers this method among the more difficult and complex to formulate, as it has not been sufficiently and fully researched as yet, which could lead to the investigation being compromised. The study was guided to answer the research question and the structure suggested by Santos‐Rodrigues et al.(Santos‐Rodrigues et al., 2012, Santos‐Rodrigues et al., 2011a, Santos‐Rodrigues et al., 2011b, Santos‐ Rodrigues et al., 2010) was followed, i.e., the component of Intellectual Capital, namely Human Capital, was

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investigated separately, and a link with finance performance examined. Guided by the literature review, the study aimed to ascertain whether the Human Capital was considered important by the company, and whether a link of these element with financial performance, could be identified. To do so the following model was followed:

Figure 1: Model To guide the research, a research protocol was developed; a pragmatic or mixed approach was used, characterized by using some objectivity and subjectivity. A single, holistic and exploratory Case Study was used, including a Portuguese transport company XYZ (a fictitious name as a request for confidentiality), with eleven employees distributed by two hierarchical levels, the Directors level and the traffic department. This company has been providing transport services since 1948, both nationally and internationally, and is legally classified as a private limited company, has a family management style with an annual average turnover of € 900,000.00.Although it is a small company, it is committed to customer service excellence, social responsibility, and internationalization as some of its strategic priorities. For the data collection phase, a semi structured interview was designed, addressing Intellectual Capital, where the component of Human Capital was considered, and in terms of the financial performance, focus was placed on the results, and income and spending. The interviews followed a formal script (conducted in an informal setting), with the study questionnaire containing the questions in the form of statements, using a 5 point Likert scale classified by “don’t agree” to “ totally agree”. Additionally, observations were performed and the firm records studied. The interviews were conducted in August and September 2011.

4. Results In terms of Human Capital, the study findings suggest that employee training is considered an important element of the company.The combination and appropriate application of company resources depend on the existing knowledge, such as training and knowledge of employees as the knowledge‐based resources are usually difficult to emulate and can provide a sustainable competitive advantage for companies in the global era. Additionally, the training of the employees was not very specialized; however, the company supports their employees in updating their training, knowing the advantages that the company can attain.

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Similarly, the competence, performance and experience of employees are of central importance to the performance of the company. The company in this study confirmed this, and it isreiterated byAndriessen (2004) who contends that companies have realized that inner experience and human experience, exclusively individual, can indeed create milestones in business performance. In this study the perception was that employees were not deemed the best in the industry despite being very skilled, however, the organization utilises the skills of their employees appropriately and maximally, prefiguring that they hire the best professionals in the industry; they considered that the employees could do better, despite having positive results. The company considers their recruitment policy to be very effective (although not ideal) and that they do hire the best employees available .The point of disagreement is between the two hierarchical levels: the Director level suggests that it will be difficult to replace an employee (valuing the tacit knowledge of workers), and the traffic employee believes that no one is irreplaceable. Additionally, the internal relationships and teamwork elements are very important for the development of employees and the company, with no exception to the company in the study. Steward (1998) contends that when people work together, they create something that is worth more than the sum of their individual efforts .The difference is profit, and return on capital. The study highlighted that when there is teamwork and cooperation, the result is better. Both interviewees promoted the development of internal relationships within the company but also considered that this effort is not recognized. However, it is considered that knowledge transfer (tacit and explicit) is a reality in the company and that everyone values the work of each other. Finally, we must stress the importance of attitude, Santos‐Rodrigues, Lousinha, and Cranfield (2012) contend that a component of Human Capital is attitude, which translates into behaviour, motivation, performance and ethics of the staff, that lead to good performance of the company, confirmed in this study. In the Case Study, the interviewed considered that employees are motivated and feel satisfied; a situation that is reflected in the achievement of company objectives .In this case it seems that employees express their opinions in order to check the profitability of the company and are motivated and satisfied. As for the ability of directors to influence staff to commit themselves, it seems that the effort made in this respect, is not recognized or managed. Furthermore, there is no consensual opinion about the change attitude of the directors.

5. Conclusions It is reported in the literature that the goal of companies is to achieve their best result / performance, i.e. profit. Cabrita (2008) advocates that high performance is central to the concern of all organizations. As profit is the difference between income and expenditure, the yield should be higher than the expenses; this is the situation with the case company under review It has obtained positive results, hence achieving profit over time, even though their income has stagnated, and despite this, it continues to exhibit a profit, which the respondents contend is due to the different elements and components of Intellectual Capital. These elements include, among others, good and competent employees of the company, encouraging teamwork, ensuring that the fleet was in good working condition, and addressing the primary and on‐going concern of the company which was to satisfy the requirements of their customers, reflected in the longevity of relationships and repeat procurement. This case suggests that the Human Capital, is considered and valued, yet differently by two different hierarchical levels within the company, and, also suggest that the financial performance of the company studied is good. This case study suggests therefore, that there is a potential relationship between the Human Capital and the company's financial performance. In summary, one can conclude that the research complied with its aims and objectives, and found that Human Capital is important for the company within this case, and that a direct relationship with the financial performance of the logistics industry, particularly the company within the case, exists. Employees and their knowledge are the key ingredient for the company's development and subsequent financial performance. Therefore, the above suggests that Human Capital has a positive impact on the financial performance of the company studied. However, the research results suggests that the logistics industry, in particular this case, recognizes the importance of Human Capital to the success of the industry in relation to sustainability and competitiveness, but like most national and international companies, they are unaware of how to identify the element of Intellectual Capital, and how to exploit it and manage it. Intellectual Capital management aims to

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extract the value of knowledge (Egbu, 2004), which provides competitive advantage and "competitive advantage depends on the identification, pooling and management of knowledge assets, Intellectual Capital (Santos‐Rodrigues et al., 2011e).

Acknowledgements This paper is partially supported by the Portuguese Foundation for Science and Technology ‐ FCT.

References Andriessen, D. 2004. Making sense of intellectual capital, Elsevier Butterworth‐Heinemann. Bontis, N. 1999. Managing Organizational Knowledge by Diagnosing Intellectual Capital: Framing and advancing the state of the field. International Journal of Technology Management, 18, 433‐462. Bontis, N. 2001. Managing Organizational Knowledge By Diagnosing Intellectual Capital: Framing and Advancing the State of the Field. Managing Organizational Knowledge 271, Chapter XVI, 271 – 301. Bontis, N. & Fitz‐Enz, J. 2002. Intellectual capital ROI: A casual map of human capital antecedents and consequents. Journal of Intellectual Capital, 3, 223‐247. Bontis, N., Keow, W. C. C. & Richardson, S. 2000. Intellectual capital and business performance in Malaysian industries. Journal of intellectual capital, 1, 85‐100. Brooking, A. 1996. Intellectual capital. Core asset for the third millennium enterprise, London, International Thomson Business Press. Cabrita, M. R. & Bontis, N. 2008. Intellectual capital and business performance in the Portuguese banking industry. International Journal of Technology Management, 43, 212‐237. Chen, J., Zhaohui, Z. & Xie, H. Y. 2004. Measuring intellectual capital: a new model and empirical study. Journal of intellectual capital, 5(1), 195‐212. Chen, M.‐C., Cheng, S.‐J. & Hwang, Y. 2005. An empirical investigation of the relationship between intellectual capital and firms’ market value and financial performance. Journal of intellectual capital, 6, 159‐176. Drucker, P. 2001. The next society. The economist, 52. Edvinsson, L. & Malone, M. S. 1997. El Capital Intellectual: Cómo Identificar y calcular el valor de los recursos intangibles de su empresa, Gestión 2000. Edvinsson, L. & Sullivan, P. 1996. Developing a Model for Managing Intellectual Capital. European Management Journal, 14, 356‐364. Egbu, C. O. 2004. Managing knowledge and intellectual capital for improved organizational innovations in the construction industry: an examination of critical success factors. Engineering, Construction and Architectural Management, 11, 301‐315. I.A.D.E. 2003. Modelo Intellectus: Medición y gestión del Capital Intelectual. 1ª edición, Junio 2003 ed. Madrid: CIC. Mouritsen, J., Bukh, P. N., Larsen, H. T. & Johansen, M. R. 2002. Developing and managing knowledge through intellectual capital statements. Journal of Intellectual Capital, 3, 10‐29. Murthy, V. & Mouritsen, J. 2011. The performance of intellectual capital: Mobilising relationships between intellectual and financial capital in a bank. Accounting, Auditing & Accountability Journal, 24, 622‐646. Petrash, G. 1996. Dow's Journey to a knowledge Value Management Culture. European Management Journal, 14, 365‐373. Roos, J., Roos, G., Dragonetti, N. C. & Edvinsson, L. 1997. Intellectual capital: navigating in the new business landscape, London, Macmillan. Santos‐Rodrigues, H., Figueroa Dorrego, P. & Fernández‐Jardón, C. 2010. The Influence Of Human Capital On The Innovativeness Of Firms. International Business & Economics Research Journal, 9. Santos‐Rodrigues, H., Figueroa, P. & Feranández‐Jardón, C. 2011a. The main intellectual capital components that are relevant to the product, process and management firm Innovativeness. International Journal of Transitions and Innovation Systems, 1, 271‐301. Santos‐Rodrigues, H., Figueroa, P. & Fernández‐Jardón, C. 2011b. Intellectual Capital and Firm’s innovativeness. 3th European Conference on Intellectual Capital. Nicosia, Ciprus. Santos‐Rodrigues, H., Figueroa, P. & Jardon, C. 2011c. Intellectual Capital and Firm’s innovativeness. 3th European Conference on Intellectual Capital. Nicosia, Ciprus. Santos‐Rodrigues, H., Figueroa, P. & Jardon, C. 2011d. The main intellectual capital components that are relevant to the product, process and management firm Innovativeness. International Journal of Transitions and Innovation Systems, 1, 271‐301. Santos‐Rodrigues, H., Lousinha, L. & Cranfield, D. The Human and Structural Capital Influence on the Launch of Own Brand Product Innovation.4th European Conference on Intellectual Capital, 2012 Helsinki, Finland. Santos‐Rodrigues, H. M. S., Dorrego, P. F. F. & Fernández, C. M. F.‐J. 2011e. La influencia del capital intelectual en la capacidad de innovación de las empresas del sector de automoción de la eurorregión Galicia Norte de Portugal, Vigo, Universidade de Vigo. Stewart, T. A. 1998. Intellectual Capital: The New Wealth of Organizations, New York, Doubleday. Sullivan Jr, P. H. & Sullivan SR, P. H. 2000. Valuing intangibles companies–An intellectual capital approach. Journal of intellectual capital, 1, 328‐340. Yin, R. K. 1994. Case study research: design and methodology. California: SAGE Publications. Liite.

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Measurement of Intellectual Capital for Innovation Sabina Scarpellini1 Miguel Marco1, Alfonso Aranda2 and Estrella Bernal3 1 CIRCE – University of Zaragoza – Department of Management, Spain 2 CIRCE –Research Centre for Energy Resources and Consumption, Spain 3 University of Zaragoza – Department of Management, Spain Sabina@unizar.es Abstract: The increasingly competitive pressure on companies forces them to constantly improve their processes and products offered to the market. Therefore, innovation becomes a requirement for survival and business growth. The ability of firms to innovate depends not only on their exploitation of internal resources but it is also increasingly influenced by their ability to use knowledge from other organisations in their environment. For the latter, almost 100 Technology and Research Institutes (TRIs) are considered specific players in the science, technology and social system and have been selected as a case study. These Institutes contribute to the overall social benefit and to improving business competitiveness by providing research and development (R&D) and innovation. For this reason their human resources are considered a strategic resource for the promotion and implementation of R&D and innovation, with SMEs as their principal clients of innovation related services. A specific applied method for measuring their intellectual capital has been developed, which is illustrated in a case study. The methodological measurement approach and the different key actions are described in this paper in order to foment the exploitation of intellectual capital of TRIs in the management of product innovation. Keywords: intellectual capital, technology and research institutes, innovation, indicators, human resources, research and development

1. Introduction For the promotion and implementation of business innovation, Spain has centres devoted to R+D, and in particular to innovation, called “Technology and Research Institutes”, which are differentiated from other research institutes by the role they play as agents of the System of Science, Technology and Society (SSTS). The almost 100 registered TRIs are specifically regulated by the Spanish Royal Decree 2093/2008 that defines the principal conditions required for institutes to be recognised as “Centros Tecnológicos” 1 or “entities with legal personality created for the purpose (declared in its statutes) of contributing to overall social benefit and to improving business competitiveness by providing research and development (R&D) and innovation”. The sample studied corresponds to the 98 TRIs registered in the official register of the Spanish Ministry of Science and Innovation 2 in 2009 The TRIs analysed have common specific characteristics which can be summarised as: private or hybrid nature, non‐profit legal form, various categories of beneficiaries, uniqueness and diversity of purposes, sector‐specific features or characteristics, territorial implication of activity, origin and different characteristics of the activities, and a mission different from other public R&D Institutes. To analyse the Institutes of Technology in Spain there is an extensive bibliography including Barge, A. (2007); Barge‐Gil, A., Modrego‐Rico, A. (2009); Fernández, M. (2010); Fernández de Bobadilla S., (2009); Fundación Cotec (2004); Giner, J.M., Santa María, M.J. (2000); Gracia, R., Segura, I.; (2003); Heijs, J. (2008); Mas, F. (2003); Modrego, A., Barge, A., Núñez, R. (2003); Rico, P. (2007); Santamaría, L. Nieto, M.J., Barge‐Gil, A. (2008); Scarpellini (2012). Nevertheless, despite these entities having been studied by different authors, the specific focus on the management and measurement of the TRIs' intellectual capital is not common and this matter of analysis has been explored very little. It is for this reason that we decided on a specific study to analyse in detail the aspects related to the human resources of these Institutes, in terms of the classification of activities and the specific measurement of the activity of their workforce for the evaluation and management of their intellectual capital. 1

Public register of Technology Centers and Centers for Innovation regulated by Official State Bulletin (Boletín Official del Estado, BOE) of January 23, 2009 http / / sede.micinn.gob.es / inforct / (accessed on 09.21.2011) 2 Available at: https://sede.micinn.gob.es/inforct/ (consulted on 09/03/2012).

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1.1 Description of the sample and method For the study, a specially designed method based on a set of different variables and a regression model was used to the full sample of TRIs 3 registered in the abovementioned Register in order to select the indicators to apply to the whole sample about their activity. Most frequent activities carried out by Spanish TRIs were classified as a result of the characterisation, taking into account the innovation process scheme proposed by Fundación COTEC (2001) in turn based on the Oslo Manual (OECD 2005) and summarised as follows: Table 1: Classification of main TRIs activities Main Classification TRIs Activities GROUPS OF ACTIVITIES

R&D / Technology Innovation

Technology Consultancy / Laboratories

Generate Resources for innovation

MAIN ACTIVITIES 1‐ R&D for incremental innovation 2‐ R&D in Experimental Laboratories 3 ‐ R&D for disruptive innovation 4‐ Actions to promote Innovative Technology 5‐ Demonstration of advanced innovation Technology 6‐Support on innovation strategy and technology 7‐ Design and measurement products and processes 8‐ Technology Labs services 9‐ Fostering Collaborative working environment 10‐ Supporting innovation management 11‐ Technology Surveillance 12‐ Human Resources training in processes and innovation 13‐ Participation in investment (spin‐off) 14‐ Spread knowledge for innovation 15‐ Encourage creativity and entrepreneurial spirit

The analysis has shown that Spanish TRIs are mainly providers of technology and innovation services to the public and private sectors, being a catalyst in the innovation process. They have particular skills when interacting and collaborating with large and medium‐sized companies but especially with SMEs, to a greater degree than public research centres, universities and other agents, due to their direct involvement in the regional context in which they act. At present in Spain, TRIs have three main ways to get funds:

to present proposals to calls for public R&D and innovation funds;

to offer services for administration tenders

to supply knowledge and technological and advanced services to private firms.

To select the appropriate variables for the study phase, the principal aspects of the TRIs that are suitable for defining the behaviour and characteristics of their human resources were studied through an analysis of quantitative and qualitative activity. In the specific case of Intellectual Capital the selected indicators were 4 applied to the activity performed by the workforce of one of the Institutes as a Case Study . The main results obtained in terms of the human resources of the Institutes are described in the following sections.

2. Characteristics of the workforce in the TRIs The staff profiles at the TRIs show a high level of specialisation. The analysis of the staff at the Institutes reveals some common features in terms of specialisation and organisation, and in terms of the number of staff according to the legal form, although it does not provide evidence of unique behavioural parameters regarding the composition of the workforce, the profiles, the distribution of responsibilities, etc. Practically all the Institutes have their own contracted staff, both for R&D and innovation and technological consultancy, and for management work. The latter usually represents between 15% and 20% of the workforce in most cases. The most frequent qualifications among the staff of the TRIs correspond to engineering and scientific degrees, including among the directors, which is reflected in the management, the selection and management of the human resources and, in many cases, the orientation of the organisation and planning of activity towards organisational models similar to those of intensive service companies in technology. 3

Energy has been considered a “relevant” part of its activity in the cases where several of the following conditions arose: the majority of customers of the energy sector, the main activity stated to be the energy area; revenue coming from activities in this area of more than 25% approximately; the existence of a specific division/area/department for energy. 4 Fundación CIRCE ‐ Centre for Research into Energy Resources and Consumption. http://circe.cps.unizar.es

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Sabina Scarpellini et al. In many cases, as indicated by Fernández de Bobadilla (2009), a local focus predominates in the operations of the TRIs and is present in the selection of human resources, in addition to centralisation and specialisation being evident in the workforce. It is relevant that the Spanish TRIs have signed up to different collective bargaining agreements, in many cases dependent on the sector of the main activity of each Institute. For example, the Basque institutes analysed in this study are for the most part subject to the collective agreement for metal. The disparity of agreements increases the differences as regards working conditions, organisation, management and staffing costs among the various TRIs. This fact partly influences the size of the workforce (which is generally proportional to the revenue and other factors unrelated to these analyses) and its composition, marked by the occupational statuses set out in each collective agreement, which greatly hinders work to find standardised categories. Where a certain homogeneity was detected between TRIs was in the total number of people connected (except some anomalous observations described in the characterisation phase), calculating an average of 111 people in total 5 (data based on the total number of people in the TRIs in 2008). If the TRIs are grouped according to the number of people linked, you can see in the following graph how the vast majority of them have a staff of less than 200 people 6 , which denotes the tendency for TRIs to be medium‐sized entities, which allows flexibility in the management of the human resources, and a certain degree of sector‐based or territorial specialisation.

Figure 1: TRIs that have a total of employees in each of the predetermined intervals: Authors’ compilation If the total number of staff members is analysed according to the legal forms of the TRIs, it is important to note how the public law entities in 2008 had a higher number of employees than the rest, and the average number of staff members of the foundations was higher than that of the associations. The following table sets out the fundamental difference detected in terms of staff between the two most common legal forms of the TRIs. You can see how, like the private foundations that represent 49% of the TRIs analysed, in the year studied they had more than 6000 people connected (54% of the total), and an average workforce of 126 people. The associations, which are 41% of the TRIs analysed had, nevertheless, a workforce of around of 3400 people, that represents 31% of the total and an average of 86 employees, considerably less than private foundations. Private foundations Associations Public foundations Public institutes Cooperatives TOTALS

No. of TRIs 48 40 3 3 3 97

Average total of people per legal form 126 86 126 319 124 115

% of TRIs 49 41 3 3 3 100

% of the total workforce of the TRIs 54 31 3 9 3 100

Figure 2: Average workforce and total number of people connected for each of the legal forms of the TRIs. Authors’ compilation 5

One Catalan TRI was eliminated from the sample for calculating the average. In 2008 the Laboratori General D'Assaigs i Investigacions, which was then a public law entity, had a workforce of approximately 700 employees (estimated). It has since been acquired by a company and does not figure among the Institutes registered according to the new legal framework 6 This data includes the 8 Foundations that merged into a single Foundation in 2011, Tecnalia Research & Innovation, which currently has a workforce of around 2500 people, and is an exception to what has been stated

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Sabina Scarpellini et al. Private foundations employed the majority of the staff of the TRIs, followed by associations, public institutes, public foundations and cooperatives. If we look deeper into the distribution of staff in the Institutes that have detailed information by occupational status (according to information on 50 TRIs), we can see the following results in the table below.

539 1092 3884

10 37 262

0 42 160

0 54 116

153 400 1192

2154

559

/ Mgmt.

656 70 220

49 0 0

16 0 0

10 0 0

119 12 156

879 5002 6171 TOTALS

55 303 358 2 50 Cooperatives

27 191 218 50 Public institutes

22 158

123 1573 1864

180 2 50 Public foundations

18 45 Associations

breakdown

available

54 Private foundations

% TRIs

No. of TRIs available breakdown

Total employees TRIs breakdown

3551

No. contracted staff

2777

652

No. of research fellows

teachers

No. of

No. of other staff

Doctors

462

holders

Degree

Admin.

Other qualifications

376

Table 2: Details of the composition of the workforce by category and contractual relationship of the 50 TRIs for which we have the detailed data: Authors’ compilation

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Sabina Scarpellini et al. As the majority of these entities are private, the composition of the workforce consists of a high percentage of contract staff with a labour relationship 7 , that in the year studied represents 81% of the total, followed by the research fellows (14%) 8 and, to a lesser degree, university teachers that collaborate continually with the Institutes. Collaborating staff of different types make up 1%, for example volunteers, as the TRIs are not‐for‐ profit entities, or visitors, when the TRIs participate in exchange programs for research staff, etc. Analysing the information obtained through the field work, it is important to note how the category of research fellows 9 converges above all in the foundations, while the associations have a higher percentage of collaborators including teachers and staff from their partners, who work at the TRIs part time or sporadically. This is due to the underlying associative spirit of this legal form. Once we go deeper into the distribution of staff by qualification, you can see how the Institutes predominantly employ degree holders dedicated to the activity of R&D and innovation, and those with doctorates make up approximately 10% of the workforce, and administration staff 18%, which at the same time is composed of half (approx.) non‐research university degree‐holders and half professionals with other qualifications. In most cases the percentage of doctors is lower in the associations, and the average workforce devoted to non‐research tasks of administration and management increases in the case of public entities, as you can see in the graph below, which gives a breakdown of the qualifications that make up the workforces of the TRIs per legal form of the Institutes and main responsibilities. Based on the analysis we can state that there is no parameter common to all the TRIs in the composition of the workforce, and that to a certain extent the distribution between the categories and qualifications of the staff is marked by the legal form of the Institutes, where foundations are generally speaking differentiated from associations.

2.1 Intellectual capital for R+D and innovation activity The overall perception is that R&D and innovation work is performed in the TRIs in flexible teams made up of people with different levels of experience, directed by one project director with scientific and/or technical experience (principal researcher). The variety of profiles and the multidisciplinary nature of the group as a whole means the TRIs can create efficient teams with regard to the demand for services, and at the same time produce results in activities that require a high level of specialisation, which is demonstrated by the capacity of the Institutes to increasingly respond to the demand of both the Administration and the private sector. Regarding the human resources of the TRIs, it must be noted how they are involved in all stages of R&D and innovation, and are one of the fundamental factors for the competitiveness of the Institutes, as their intellectual capital is their best asset, and indicates the need to actively encourage the “engagement” of the researchers in the Institutes, as a key factor in the generation of knowledge and the transformation of new ideas into commercial results. If the activities are analysed according to the legal form and the average volume of revenue of the TRIs that offer this activity, it is obvious how non‐directed research and R&D and innovation activity in general generate a slightly lower revenue than the average derived from activities aimed at the application in the market of the Technology Institutes' services. The legal form is not especially significant when offering one activity or another although some differences can be detected between the activities “innovation” (offered by 75% of the foundations and 85% of the associations), “technical assistance/consultancy” (offered by 56.2% of the foundations and 60% of the associations), and “technological development” (offered by 20% of the foundations and 10% of the associations). The second most frequent activity offered by the TRIs is technology transfer, with 69 Institutes (70%) among the entities registered in the Register of the Research Results Transfer Office (Oficinas de Transferencia de los 7

In public law entities a minority of civil servants can be detected This data denotes the proximity of these entities to the area of research that considers the figure of research fellow, both with official grants linked to R&D projects funded by public administrations and grants of a shorter duration funded by the TRIs themselves 9 See the information related to this occupational status set out in Royal Decree 1493/2011 of 24 October and the current legislation on the subject. 8

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Sabina Scarpellini et al. Resultados de la Investigación or OTRI). In this regard, it must be indicated that the percentage of TRIs that are private foundations inscribed in OTRI (54%) is lower than that of associations recorded in the same Register (82%), which demonstrates the greater commitment of associations to transfer their research results to companies, in particular, to their partners. This percentage of inscribed entities is actually even lower for other Institutes (50%). Throughout the study we detected numerous TRIs that were especially active in other transfer activities, that frequently receive specific public grants, and/or are considered desirable for improving the competitiveness of companies, such as marketing of know‐how, the creation of spin‐off companies or similar, dissemination, investment and/or marketing of intellectual and industrial property, or the promotion and funding of research grant programmes. Another of the aspects appertaining to the activity of the TRIs analysed was the use of laboratory infrastructures, in particular for providing technological assistance services. The results can be summarised in the following graph.

Figure 3: Use of laboratory infrastructures to provide technological assistance services by the Institutes of Technology: Authors’ compilation Approximately half of the TRIs frequently use the laboratories to provide technological assistance services, while a minority of the entities analysed do not offer this type of service and do not have laboratories for this purpose. After analysing the main characteristics of the workforce of the TRIs in this section, an introduction is offered on the use of indicators as a measurement tool within the framework of the innovation process and the main systems currently used for R+D and innovation activity of the researchers as the necessary basis for the synthetic selection of the measurement indicators for the workforces of the TRIs is summarised. As mentioned above, the objective of the analysis was to then draw up a proposal of indicators for measuring the activity carried out by the staff connected to the TRIs, which is provided in the next section.

2.2 Measurement of the intellectual capital In the specific study of technology transfer, an activity considered primordial in the Institutes of Technology, an initial analysis of the indicators in use led us to the conclusion that the R&D and innovation indicators are not suitable for the transfer done by the TRIs as the majority have been designed for public research institutes and universities. Measurement of the transfer activity currently carried out is actually based above all on indicators of an academic nature, such as scientific publications, doctoral theses, R&D projects subsidised by the government, patents, etc. not properly reflecting all the aspects appertaining to the use of the results of the R+D in the private sector.

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Sabina Scarpellini et al. An approximation to what could be a classification of the indicators in use is offered below:

Direct output indicators: production of patents, creation of spin‐off companies, funds obtained from marketing licenses, venture capital obtained, invoicing for collaboration in research, creation of new instrumentation and development of new technological methods, new employment of staff dedicated to R+D.

Indirect impact indicators: they have a strategic value due to the economic and social implications (production of knowledge and scientific information, graduate education, creation of human capital, prospective technological studies, access to new technologies (indicators that are rarely used as they are difficult to quantify).

In general terms the indicators of activity or action (direct output) do not allow an exhaustive assessment of the efficiency of the transfer activity carried out by the staff at the Institutes. For example, the price of a technology transfer contract does not consider any of the activities carried out as a consequence of it, for example the activity of dissemination on the network, the knowledge disseminated in the area of influence such as social (or relational) marketing of the technology transfer (Alborse Hidalgo 2003). These authors add that, at the same time, the result or impact indicators (indirect) are complex and cannot be measured simply by the number of technology transfer contracts closed. The indicators are even more intangible, as the transfer function, in addition to facilitating agreements, also covers the task of “developing a culture and attitudes (for example, a more global and business‐oriented vision) through the promotion of external collaboration (that can lead to other agreements), the promotion of innovation between SMEs, etc.”. There is no doubt that, like in the transfer activity, measuring the activity carried out for innovation requires specific indicators (Bueno and Casani 2007) and systems capable of measuring the wide variety of activities and types of action taken in this field would entail overcoming the difficulties posed by the lack of a commonly accepted conceptual frame of reference in this matter. With this premise, if the activity and mission of the TRIs are considered entities that have to generate knowledge and technology, it is evident that specific instruments are required for continuous monitoring of their activities, to be able to quantify the results achieved and best direct their objectives.

2.3 Intellectual capital indicators From the perspective of this thesis, the definition of “intellectual capital” refers to knowledge as an expectation of value, which identifies the sources of future profit generated by innovation and includes unique organisational designs and optimum personal practices. The implementation of innovation in processes, products or services entails, on one hand, making the intellectual capital of the TRIs profitable and, on the other, contributing to expanding, replicating and implementing it in the production systems. In this regard the “knowledge” is an integral part of the resources of the Institutes and this term includes:

At individual level: people's skills and talent

At level organisational: the infrastructure, relationships, technology, routines, procedures, archives, documents, patents, and organisational culture.

For organisations that provide services generated through knowledge, like TRIs, it is strategic to learn what their competitive advantages are, what capabilities they are based on and, consequently, identify their knowledge assets. In this area we must mention the “SkandiaNavigator” models (Edvinsson, 1997), the model for monitoring intangible assets by Sveiby (1997), the map of knowledge assets (Schiuma and Lerro, 2008) and the EFQM model, among others. In this context, and given the transcendence intellectual capital has for all TRIs, it is considered opportune to propose a collection of particular indicators to measure the activity carried out by the different categories of staff of the TRIs that are listed in the following table, where activities carried out were associated with selected indicators for each as a basic proposal for evaluating staff performance at the TRIs to assess the evolution of their intellectual capital.

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Sabina Scarpellini et al. Based on the analysis of the existing indicators and the most common activities of the TRIs an exhaustive list of specific indicators has been drawn up that represents the activity of the workforce of these Institutes as a whole and is synthesised in table 3. Table 3: Proposal of particular groups of indicators for analysing and measuring the “intellectual capital” of the Technology Institutes depending on the main activities carried out by their staff: Authors’ compilation

Activity categories: SCIENTIFIC PRODUCTION Publications Participation as speaker

Attendance R&D and innovation projects with grants from public administrations European Union and International National Autonomous community and local ONGOING TRAINING AND COLLABORATIVE ENVIRONMENT Training activities completed Mobility and human resources Teamwork

Activity categories: TRAINING AND DISSEMINATION (15) Teaching Training Activities Coordination/management Management of: (activities of the year ‐ completed or not)

Projects with Private Entities and Intellectual Property

Intellectual property R&D and innovation activity with companies Technological consultancy work Charges and management

Charges Public office and university responsibilities Horizontal and management services

The main new items included in this list proposed with respect to the indicators commonly used for R+D activity can be summarised as follows:

The inclusion of specific indicators for the administration, services and management staff as it is considered a crossover activity that is essential for innovation and the achievement of results in the TRIs.

The inclusion of indicators that clearly reflect the dedication of the workforce to each and every different transfer activity, not only those traditionally considered to be markedly scientific.

The inclusion of indicators particularly designed for the activity of innovation carried out by the workforce of the TRIs for the private sector, especially SMEs.

The inclusion of indicators for on‐going training activity, not only university postgraduate education, considered relevant for the effective implementation of innovation in companies.

3. Conclusions The study revealed that the intellectual capital of TRIs is generally pro‐active, offering private clients R&D and innovation services in a mature stage of development. Human resources for innovation are continuously updating their knowledge and capability, and are developing technology transfer and performing technology consultancy services. When offering and conducting their activities for private companies, the TRIs' Intellectual Capital can play a leading role in fostering innovation between companies as they can act as a catalyst, accelerating the innovation process for companies, particularly SMEs. To improve the strategic management of the TRIs it is therefore essential have a clear vision of the main asset of these organisations: their “intellectual capital”. The indicators proposed allow improved management of the intellectual resources for the TRIs to pass from innovation defined as “occasional”, easier to execute in any environment, to innovation defined as “systematic” that requires a specific, complex organisation that is maintained over time, more and more frequently in international environments. The need to optimise the management of these assets requires two complementary stages that need specific measurement systems:

An initial stage that identifies the components of knowledge and that facilitate their management so they can become a source of continual improvement (internal perspective).

For this initial stage indicators have been selected and designed to measure the on‐going training activities of the staff and their performance in collaborative fields and those of responsibilities and management in the TRIs themselves

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A stage intended to assess an organisation 11 to communicate its value to the market (external perspective)

The indicators proposed, if they are measured periodically, provide valuable information to the management of the TRIs to assess the degree of compliance with the mission assigned to these organisations and their capacity to make their intellectual capital available to the industrial infrastructure. In this sense the TRIs have to consider an analysis of the results in terms of socio‐economic impact of their activities in their annual reports, with special emphasis on aspects of occupational and intellectual capital.

References Albors Garrigós J. y Hidalgo Nuchera A., (2003). “Las redes transnacionales de transferencia de tecnología. Un análisis del estado del arte y de la red europea de IRCs”. Revista Madri+D, Número 18, agosto ‐ septiembre 2003. Barge, A. (2007). “La utilización empresarial de fuentes externas de conocimiento: Análisis Teórico y Estudio Aplicado a los Centros Tecnológicos Españoles” Tesis Doctoral. Universidad Complutense de Madrid. 2007. Barge‐Gil, A., Modrego‐Rico, A. (2009). Ciencia y Economía. Rev. Arbor: Ciencia, Pensamiento y Cultura ‐ CLXXXV 738 julio‐ agosto (2009) 757‐766 ISSN: 0210‐1963 ‐ doi: 10.3989/arbor.2009.738n1050. Bueno E. y Casani F. (2007). La Tercera Misión de la Universidad. Enfoques e indicadores básicos para su evaluación en La transferencia de la I+D en España, principal reto para la innovación. Revista de Economía industrial, n.366. 2007. Edvinsson, L., (1997). Developing Intellectual Capital at Skandia. Long Range Planning, Vol. 30, No. 3, pp. 366 to 373,1997. 1997 Elsevier Fernández, M. (2010). “Modelo de desarrollo de Centros Tecnológicos Industriales orientados a proyectos en entornos no intensivos en innovación”. Tesis Doctoral. 2010. Universidad de Oviedo. Fernández de Bobadilla S., (2009). “Dinámicas de Crecimiento y Características del Modelo Centros Tecnológicos”. Serie Economía y Empresa. Editorial Universidad del País Vasco/ Euskal Herriko Unibersitatea. ISBN 978‐84‐9860‐195‐4. Bilbao 2009. Fundación Cotec (2001). "Indicadores de innovación. Situación en España". Ed. Cotec. Madrid. Fundación Cotec (2001) “Innovación Tecnológica. Ideas Básicas”. Colección: Innovación práctica. Cotec ISBN: 84‐95336‐17‐ 0 Depósito legal: M. 23.483‐2001. 12 Fundación Cotec (2004). “Nuevos papeles de los centros tecnológicos: empresas, redes y desarrollo Regional” . Serie Encuentros empresariales Cotec, 10. Fundación Cotec, Madrid 2004. Giner, J.M., Santa María, M.J. (2000) La política de centros tecnológicos y de servicios: la experiencia de las regiones valenciana y Emilia‐Romagna. Revista de Estudios Regionales Nº 57 (2000), Universidad de Alicante. BIBLID [0213‐ 7525 (2000); 57; 131‐149]. Gracia, R., Segura, I.; (2003) Los centros tecnológicos y su compromiso con la competitividad, una oportunidad para el sistema español de innovación" Economía Industrial, nº 354 pp. 71 – 84. Heijs, J. (2008). Justificación de la política tecnológica: un enfoque teórico ‐ Revista Madri+d – Revista de Investigación en Gestión de la Innovación y Tecnología ‐ Octubre de 2008 – nº 49 ISSN 1579‐9506 http://www.madrimasd.org/revista/revista10/aula/aulas2.asp. Mas, F. (2003): “Centros Tecnológicos y Sistemas Regionales de Innovación: Modelos Europeos”, en Investigaciones Regionales, nº3, otoño. Modrego, A., Barge, A., Núñez, R. (2003). Evaluación de los centros tecnológicos españoles. Instituto Flores de Lemus, Universidad Carlos III, Madrid. Rico, P. (2007). "La política tecnológica y sus efectos sobre el cambio de las organizaciones de I+D: El caso de los Centros Tecnológicos del País Vasco (1980‐1999) " Tesis Doctoral. Universidad Complutense de Madrid. Santamaría, L. Nieto, M.J., Barge‐Gil, A. (2008). Beyond formal R&D: taking advantage of other sources of innovation in los and medium‐technology industries. Research Policy. Doi: 10.1016, 2008. Scarpellini, S. (2012). “Eco‐innovación y eficiencia energética en centros tecnológicos: caracterización y sistemas de medición para un análisis cualitativo de la actividad” Tesis Doctoral. Universidad de Zaragoza. 2012. Schiuma G., Lerro A., (2008). Intellectual capital and company’s performance improvement. Rev. Measuring Business Excellence VOL. 12 NO. 2 2008, pp. 3‐9, Q Emerald Group Publishing Limited, ISSN 1368‐3047

For this more specific stage indicators have been selected or designed related to scientific production, R&D and innovation projects and intellectual property, and of training and dissemination performed by the Institutes 12 M.J. Montejo coordinadora.

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Intellectual Capital Formation in EU Cross Border Regions: Theory and Application Klaus Bruno Schebesch1 and Eduardo Tomé2 1 Vasile Goldiş Western University, Arad, Romania 2 Universidade Lusiada Famalicão, Portugal kbschebesch@uvvg.ro Eduardo.tome@clix.pt Abstract: In this paper we aim at analyzing how Intellectual Capital (IC) is formed in two sets of cross‐border regions located in the south (between Portugal and Spain) and in the East (between Hungary and Romania) of the European Union. The study is important because traditionally border regions have more difficulties achieving higher levels of sustained economic development, due among other factors to a bigger distance to the political powers of the countries involved. The st focus on IC was chosen because in the 21 century intangibles are considered to be the main driver of economic and social prosperity. Using publicly available data to roughly define the current macroeconomic and demographic situation in the two distant European cross‐border regions, we attempt to explain how IC formation may be enhanced by influencing the formation of coalitions or cooperation between cross‐border counties. The payoff matrices for the games which results in the coalitions are themselves a result of the influence of qualitatively different influence factors, which are discussed in detail. In order to understand the region and country specific differences within these factors historical and contextual explanations are given, which might also point to the probable future evolution. The attractive and repulsive forces in this coalition formation may be interpreted to act similarly on IC formation, namely the (data dependent) formation of many stable coalitions is a potential, which also fosters IC formation. Hence we propose this potential of stable cooperation to be a proxy or an index of IC formation in our context of study. The number and sizes of potential coalitions may give clues on applying IC fostering regional cross‐border developmental policies. Keywords: cross border regions, intellectual capital formation, historical factors, county capitals, stable coalition formation

1. Introduction Intellectual Capital (IC) came to be an important matter of scientific managerial and behavioral research because of the importance of attributing a value to organizations and to their knowledge (Edvinsson and Malone, 1997). However, following empirical studies made mainly in the last decade, determining the importance of regional IC formation is also in demand (Bonfour and Edvinsson, 2004). Particularly in Europe, owing to the dynamics of European Integration and its effects on effective exchange processes on several societal levels, regional clusters may come to be considered ever more important. especially as centers of long term prosperity. In this context we analyze the theory on regional clusters and that of intellectual capital in order to apply those theories to the cases of EU cross border regions. For empirical and comparative‐illustrative purposes, two rather different EU regions are considered, in this study, namely that between Portugal and Spain as well as that between West Romania and East Hungary. The conditions of IC formation in the two regions may be different and unrelated, given that today’s Portugal and Spain are deriving from influential colonial powers looking back to oversea trading related wealth accumulation in the past, and, subsequently, to transitory right‐wing dictatorships in the past WWII period ‐ before eventually joining the UE, while the Hungarian‐Romanian border region is historically part of Central‐ European, mercantilist, Austro‐Hungarian empire, which formed wealth owing to more conservative agro‐ industrial developments, and which transited a post WWII period of left‐wing dictatorships, which did in turn disrupt the traditional cooperation patterns within that region. The remaining paper will be divided into five sections. In the second one we outline the theoretical and conceptual ideas for the study, namely of IC and regional development. In the third section we present the Portuguese‐Spanish (PT‐SP) case and in the forth section we address the Hungarian‐Romanian (HU‐RO) border case. Section five discusses some similarities and differences between these two EU cross border regions. Finally in section six we develop a model which evaluates potential coalitions formed between the cross border counties in the two EU cross border regions. The potential of stable coalition formation is used as a proxy for enhanced IC formation. The paper concludes with a short discussion of the potential usefulness of the proposed approach.

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2. Concepts and theories 2.1 Intellectual capital In the history of economic thought IC is a considerably new concept (Edvinson and Malone 1997). It appeared to solve the increasingly in the accountancy arena to solve the increasingly complex problem of the definition of the value of companies and organizations in the Knowledge Era and in the Information Society. IC also appeared in an epoch in which Knowledge, and the Knowledge cycle became more and more important for organizations (Nonaka and Takeuchi, 1995). Although IC and Knowledge are not the same they are related: an organization which has more IC, should manage and create more knowledge. But IC is more easily defined as an asset (IC being divided in Human Capital, Organizational Capital and Customers Capital) whereas knowledge is distinguished from data, information, and wisdom (Tomé, 2012). Many measurement methods on IC were presented (Sveiby, 2012) among the most popular the Balanced Scorecard (Kaplan and Norton, 1994). And suddenly, the models were applied to countries (Bounfour and Edvinsson, 2005), countries (World Bank, 2012) and cities (Rodrigues and Tomé, 2010).

2.2 Regional development In Economics, Regional Development (DR) has been studied for long, as a cross road between micro‐economics and macro‐economics. The major studies on DR have emphasized the importance of space in the economic analysis. Seminal works have dealt with the importance of certain factors to define the location of economic activities (Von Thunen, 1826; Richards, 1962). The consideration of the State intervention lead to valuable studies on regional policy which the creation of “poles of development” was advocated (Hansen, 1967). Finally, in the last years of the last century, regional studies received increasingly more attention from scholars from the International economics fields, following the Krugman (1991) studies on economic geography.

2.3 IC and regional development The confluence of the previous two types of analysis implies that IC is nowadays viewed as one of the major factors of location of economic activities. The localization of successful businesses requires the local availability of IC assets, in its various forms. Positive, virtuous cycles of prosperity and vicious cycles of decay and poverty are generated by the existence or inexistence of IC in a given region. It is in this context that the cross‐border creation of IC looks to be decisive in economic and social terms. The creation of those positive cycles requires a change in the market for IC in the poor and lagged regions. This change requires not only an improvement in the stock of the regions’ IC but a complete change, for the better in the market of IC in those regions.

3. The case of the Portuguese‐Spanish border region 3.1 Macro evolution Since WWII, Portugal and Spain underwent a massive transformation in political, economic, social and financial terms. In short, both countries started as influential colonial powers looking back to overseas trading for wealth accumulation and governed by right wing dictators. Suddenly, in the seventies, democracy was installed and the adhesion to Europe became a major political goal, achieved in 1986. For Portugal the change, and shock was even greater because Spain had descolonized almost totally in the 19th century, only remaining with the Spanish Guinea (until 1967) and the Spanish Sahara (until 1975), Portugal only did it after the Revolution in 1974 and following 13 years of colonial war. Then, in 2002, both countries joined the Eurozone. The main data about Portugal and Spain are summarized in Table 1, just below: Table 1: The main socio economic data for Portugal and Spain

Portugal

GDP per head as % of “old” EU25 in 2004 + (PPP in 2012) (20K in $2005)

Education, mean years of schooling / R&D expenditure: EU25 spends 2.9% 7.7 / 1.5

Spain

(26K in $2005)

10.4 / 1.35

399

Health services; life expectancy / 7.3% of GDP /78.0/ 5.8% of GDP /80.0/

HDI rank

Information society, EU25 spends 2.9 % of GDP on IT&C

5.9

4.8

Klaus Bruno Schebesch and Eduardo Tomé Spain is traditionally more developed and Portugal, although the smaller is always trying to catch up.

3.2 The political question of the border For Portugal, the border with Spain has always been one of the most important elements of definition of the country. Indeed, the terrestrial border between the two countries in Iberia has been stable since 1297, and it is the oldest frontier in Europe. After that period, Portugal and the Kingdom of Castella and Leon / Spain fought many battles, in the Peninsula, and all over the world, Spain even took over the Portuguese government from 1580 to 1640, but the border was stable. However, all over the centuries, Portugal sought independence by assuming a divergence from Spain in Iberia. That struggle resulted in a small and centralized republic, independent from the big regionalized monarchy. The result is also two countries with similar cultures, similar languages, similar histories, who share the same territory if we located it in a world map; but in which the border has remained the same since the Middle Age.

3.3 The economic question of the border Even today the border with Spain has a considerable influence in the Portuguese economy. It is quite interesting to understand that the Portuguese regions near the border are much less developed than the Spanish regions of the other side. And it is also very curious to note that in Portugal the more developed areas are located in the seaside (from Porto to Setubal) and in the Algarve. This unbalance in development is also related with some mistrust. There is even a popular saying, in Portugal about the secular antagonism between the two countries: Of Spain neither good wind, nor good marriage. Therefore, traditionally, the Portuguese border regions with Spain have lived between two problems: the central government that neglects them and the Spanish neighbor they don’t rely on. The Portuguese migrated mainly to Brazil, and to France, and not to Spain. Finally, for many years, to the Portuguese, the border also meant the way to import goods; even today, it is worth buying oil in Spain, and some fortunate profit from it. The Spanish regions near the border solved much of their development problems by becoming “Autonomous Communities” (Comunidades Autonomas). That political achievement, which meant that there are 19 regional governments, parliaments and budgets in Spain, 4 of which in regions that border with Portugal: Galicia, Castela e Leon, Extremadura and Andaluzia). Those four ACs would seek to promote regional economic development and to protect the Spanish border regions from the suction power of Madrid, Barcelona, Valencia and the Basque Country. The data available on the border which illustrate what we just said are included in Table 2a, below. Table 2a: Balances and unbalances across the border between Portugal and Spain (2010) Portuguese Regions Minho Trás os Montes e Alto Douro Beira Alta Alto Alentejo Alentejo Central Algarve

GDP Education Health Spanish Regions GDP Education Health 16000 15 79 Galicia 21000 66 80 17500 35 79 Castilla e Leon 23000 77 83 17500 18100 17900 20000

45 24 38 45

79 78 79 80

Extremadura

16000

Andaluzia

18000

Source: Eurostat, Portuguese and Spanish National Institutes of Statistics. Note: GDP relates to Gross Domestic Product per capita. Education is enrollment in Higher Education in % and Health is Life expectancy at birth

3.4 Cooperation over the border Traditionally the border regions of the two countries lived with their backs turned to one another. The Spanish despised the Portuguese as inferiors, and to fight Madrid. The Portuguese mistrusted the Spaniards, while trying their best to fight Lisbon. Also, the lowering of the borders since 1992 meant that people in the Portuguese interior began to feel closer to their Spanish neighbors than to Lisbon. And in fact, it was in the scope of the European Union (EU), that the cross border cooperation between the two countries was officially

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Klaus Bruno Schebesch and Eduardo Tomé put forward. The EU understood well that the four Spanish regions were among the less developed in Spain, and that they would be better if they could cooperate with their Portuguese counterparts. As a consequence, an operational program was designed, in 2007 to enhance the cooperation between the two countries’ regions (EU, 2012).

3.5 Intellectual capital and the border The level of IC of the border Spanish regions is much higher than the level of the IC in the Portuguese border regions. This fact has important economic consequences. The gap is smaller in the South (Algarve/Andaluzia and Alentejo/Extremadura) than in the North (Minho /Galicia and Trás‐os‐Montes and Beira Alta vrs Castilla and Leon). Algarve is a fairly developed region, with an average level of education, an important University in Faro, a strong tourism industry and a population with an important number of foreigners, particularly English, a fact that somehow enriches the region because it contributes to its social capital. In a way, Algarve is comparable with Andaluzia, which has its main cities in Seville, Cordoba, Malaga and Granada, and also a very important tourism activity, lots of foreign expatriates and is trying to develop a dense network of Universities. The two following sets of pairs (Alentejo / Extremadura, and Trás‐os‐Montes and Beira Alta/ Castilla and Leon) relate more to the agricultural sector, and have even less IC. Finally, the pair Minho/Galicia is based in textile and fishing industries. Below we include two tables that describe the investment in IC in the border regions (Table 2b) and also the basic demographics in those regions (Table 2c). Those Tables relate to Tables 4 and 5 of the Hungarian and Romanian section and are the base for an analysis on the Portuguese regions in section 6, Table 2b: The county capitals of the PT‐SP cross‐border region and a proxy to their educational and research infrastructure (similar county data for e.g. knowledge intensive firms are harder to obtain) County population / local capital city population (including capital city growth tendency)

Higher education institutes: Types (foundation), name*, number of stu‐dents of the largest inst., specialty

450000 / Faro 65000 (+) 288000/ Évora 45000 (=) 520000 / Bragança 25000 (=) 1050000/ Braga 180000 (+)

College “UAlg” (8500) / broad College “UE” (8200) / broad College “UTAD” (6000) / broad College ”UM”(17000) / broad

8400000/ Sevilla /1200000 1100000/ Merida/ 60000 2550000 /Valladolid/ 415000 2800000/Santiago/ 150000

College “US” (65000) / broad College “UEx” (24000) / broad College “UdeS” (30000) /broad College “USC”(42000) / broad

Source: PT‐SP National Institutes of

Statistics and university sites, * if available

Portugal Algarve Alentejo Tras os Minho Spain Andalusia Extremadura Castilla Leon Galicia

Table 2c: Travel distance between major cities in the PT‐SP region Faro Faro Évora Braga

Evora

Braga

Bragança

226

600 415

725 461 222

Bragança Seville Merida

197 253

345 140

705 530

634 500

Valladolid Santiago de Compostela

773 784

512 591

422 188

199 266

Seville

Merida

Valladolid

Santiago

191

584 395

888 697 447

Compiled by using distance calculator at: www.wildtexas.com/travel-calculator.php

3.6 Cooperation on intellectual capital over the border The EU program for 2007‐13 stated as priority the reinforcement of the immaterial component of the interventions. That priority should be used when putting in operation the five parts of the program, each one linked to, respectively: 1) competitiveness and employment; 2) environment and culture; 3) territory and accessibility; 4) institutional and socio‐economic integration; 5) technical assistance. The program benefited

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Klaus Bruno Schebesch and Eduardo Tomé from a donation of 267 Million Euros from the European Fund for Economic Development (EFED) and was expected to cost 354 Million Euros. The non‐governmental sector rallied the public effort and in the last years some initiatives putting together universities, and other organisms began to be made in the border.

4. The case of the Hungarian‐Romanian border region 4.1 Historical and general remarks The Hungarian‐Romanian border region (HU‐RO cross‐border region) is a consequence of the Austro‐ Hungarian empire (the western part of today’s Romania was part of that empire), which was actively developing and expanding the commercial, industrial and intellectual as well as religious urban centers (mainly Debrecen, Nyireghaza, Bekescsaba and Szeged from contemporary Hungary and, respectively, Satu‐Mare, Oradea, Arad and Timişoara from contemporary Romania). The pre WWII years were generally tumultuous in the region, proliferating right‐wing nationalistic approaches, and with the eventual onset of socialist post WWII dictatorial political economies, to a large extend, some left‐wing nationalistic developments paths were pursued, by both countries, in isolation. The post‐revolutionary (i.e. post 1990) developments essentially freed both countries from dictatorship, although, on both sides of the border, certain nationalistic and xenophobic attitudes are again finding popular support. Both sides of today’s borderline are home to a mixture of language, religion and culture, and the general picture is still that of post‐socialist recovery. In the meantime, many EU funded projects treat a wide range of symptoms of economic and social malfunctioning but which, as yet, do not convince by any overarching strategy. The HU‐RO cross‐border region is a target of the EU 2007‐2013 FEDR program, totaling expected EU funding of 224 Million Euros, which was set up in order to promote cooperation between the two countries by means of common local projects.

4.2 What are the actual characteristics of this East‐European cross‐border region? As the labor market tightens in the HU‐RO cross border region, there are important tendencies of migration towards the national central urban areas (Budapest and Bucharest areas, respectively) and a drain of skilled labor force from the HU‐RO region towards well‐paying developed countries (in the

Source: HU‐RO cross‐border program 2007‐2013 of the European Union Figure 1: The four “mirror” counties of the HU‐RO cross‐border region EU25, overseas). Intellectual centers with substantial tradition like Szeged, Debercen and Timişoara can only partially halt or reverse theses tendencies, even in a declared and embraced “knowledge oriented” economy ‐

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Klaus Bruno Schebesch and Eduardo Tomé as both countries like to define the future role and orientation of their remaining industries. One of the key problems of the region is the failure of restoring or reinventing their industrial, agricultural and energetic potential. Infrastructure is improving, rail‐ and road links are superior in Hungary, communication links are competitive in both countries but efficient cross‐border links between urban centers are still rare. As depicted in figure 1 each of both countries has four counties (provinces) along the common border text which are governed at the regional level by eight major cities (county capitals) of different sizes, each having a spectrum of higher educational institutions being hence local educational centers. Two of the HU cities have universities with substantial academic tradition (Szeged and Debrecen) being followed by Timişoara (from RO) which more closely follows them. Table 3: Some economic / societal indicators of Hungary and Romania compared to EU25

Hungary Romania

GDP per head as % of “old” EU25 in 2004 + (PPP in 2012) 23% of EU25 (16K in $2005) 13% of EU25 (10K in $2005)

Education, mean years of schooling R&D expenditure: EU25 spends .9% 10.4 / 1.0% of GDP 11.1 / 0.4% of GDP

Health services; life expectancy / inf. death per mille 7.4% of GDP 71 / 79 / 4.9 5% of GDP 70 / 78 / 10.7

HDI* rank

Information society, EU25 Spends 2.9 % of GDP on IT&C 5.5% of GDP

38 6.0 % of GDP 50

Source: UNDP – International Human Development Indicators (*HDI, as of year 2012) At a general level Romania is a bigger and more populous country then Hungary but is lacking behind the latter in GDP per capita (as depicted in table 3). Still the cross‐border region is of comparable size on both sides, having each a series of important urban centers. These cities are home to diverse institutions of education (table 4) but they also used to be important industrial centers in the socialist period after the World War II. In post revolutionary Hungary the pace of adapting the university structures to international and especially West‐ European standards is faster than that in Romania. Table 4: The county capitals of the HU‐RO cross‐border region and a proxy to their educational and research infrastructure (similar county data for e.g. knowledge intensive firms are harder to obtain)

Hungary Szabolcs‐Szatmar‐ Bereg Hajdu‐Bihar Bekes Csongrad Romania Satu‐Mare Bihor Arad Timiş

County population / local capital city population (including capital city growth tendency)

Higher education institutes: Types (foundation), name*, number of faculties of the largest inst., specialty

555000 / Nyiregyhaza 117000 (+)

College (2000) 5 / appl. sciences broad

540000 / Debrecen 208000 (‐) 361000 / Bekescsaba 64000 (‐) 422000 / Szeged 170000 (+)

TradU** (1538) 13 / nat / med / math ModU branch of SZIU (2000) / econ TradU*** (1921) / 11 / math, biomed

329000 / Satu Mare 95000 (‐) 550000 / Oradea 183000 (‐) 409000 / Arad 148000 (‐) 650000 / Timişoara 334000 (‐)

College, 5 branches (1990+) / broad ModU (1990) U‐Oradea 17 / broad ModU (1990) UAV 9 / UVVG 6 / broad TradU** (1962) UVest 11 / TUT 10 / broad

Source: HU‐RO National Institutes of Statistics and university sites, * if available Table 4 is listing the respective four county capitals (2nd column) from the Hungarian and the Romanian side of the border showing an approximate nominal equality of size. However, reputation of the higher education centers differs significantly (marked by stars) within the countries and between the countries and research output is also not quite substitutive over the different higher education centers (i.e. number of faculties in universities, research institutes). A worthwhile approach is perhaps to attempt to value possible coalitions between higher education institutes in the HU‐RO cross‐border region and, implicitly, between their counties (see section 6, below) as a factor for cross border IC formation.

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Klaus Bruno Schebesch and Eduardo Tomé

4.3 Intellectual capital and the HU‐RO border As a symmetric counterpart to the case of the cross‐border region between Portugal and Spain as was exposed in previous sections, here too, there is a certain asymmetry, namely the level of IC of the Hungarian counties that border the Romanian ones, is higher than the level in those from Romania. The differences are pointed at indirectly, by Table 4. Hence, in the case of HU‐RO region there is a question of whether cultural and behavioral differences in the intellectual domains should be attributed to long standing historical or more to recent nation‐centric political divergent development. One may assume as a conservative working hypothesis a certain reluctance of forming deep cross‐border partnerships. In order to also cover some pair‐wise relations between regions, we decide to use as rough approximation of such pair‐wise relation the city distances (geographical, Table 5) which, upon data availability, may be modified using other cost‐based or investment based pair‐wise relations. Table 5: Travel distance between major cities in the HU‐RO region Nyiregyha za Nyiregyhaza Debrecen Bekescsaba Szeged Satu Mare Oradea Arad Timişoara

101 122 204 307

Deb‐ recen 49

Bekes‐ csaba 179 130

Szeged

106 72 190 259

220 89 90 159

314 182 108 116

Satu Mare

Oradea

Arad

Timi‐ şoara

132

249 117

319 187 58

310 261 97

Compiled by using distance calculator at: www.wildtexas.com/travel-calculator.php

5. Intra‐regional cultural differences and inter‐regional similarities Notable difference between Hungary and Romania are a) the way religion influence behavior, b) risk perception (considerable power distance), c) propensity to imitate foreign solutions. Both countries enjoy a rich heritage of artistic and intellectual talent which seems to be in contradiction with the countries endowment and effective power. However elite behavior and results where more successful in the past, substantially and often predominantly contributed by the Jewish urban communities of both countries. Corruption index (Corruption index (2012)) being 4.6 at rank 54 for Hungary (down from 5.9 in 2002) and 3.6 at rank 75 for Romania (up, or improved, from 2.6 in 2002) in a global corruption context of 9.5 for New Zeeland (the most favorable) and 1 for Somalia (presently the worst case). Portugal and Spain are in a better shape but with a weak tendency towards increasing corruption: Portugal being rated 6.1 at rank 32 (down from 6.3 in 2002) and Spain 6.2 at rank 31 (down from 7.0 in 2002). The two more corrupt neighbors Romania and Hungary, being also more different w.r.t. corruption, may make embarking on public projects or on other long duration, large scale projects unpopular. This is underscored by the relatively low (but otherwise similar) trust levels in both countries (Morrone et al. (2009)) of 0.21 (Hungary) and 0.2 (Romania). With regard to interpersonal trust all our four counties are situated well below the average of 0.36 reported in (Morrone et al. (2009), p12) with the two western neighbors scoring surprinsingly low, i.e. 0.2 for Spain and 0.1 for Portugal (in a trust context where the most favorable is Norway with 0.72 and one of the lowest scores of 0.05 is attained by Turkey). Moreover a dramatic decrease in trust over the last 20 years is observed in all our countries (more than 30% in Hungary, more than 40% in Spain and more than 50% in Portugal; Romanian data on this particular issue are not available). There are certainly some similarities owing to the relatively periferic location of both cross border regions but there are also some intricate differences.

6. Towards constructing an IC‐formation index using county interactions 6.1 IC formation enhanced by cross border coalitions: a modeling approach Is there a force acting on the readiness to cooperate within cross‐border regions, and, hence, potentially stimulating IC formation? Indeed, by means of similarities between different aspects of the cross‐border regions and especially of their county capitals, one may define a mechanism, which leads to stable coalition formation and which can be associated with enhanced IC formation.

404

Klaus Bruno Schebesch and Eduardo Tomé In order to identify possible cooperation networks, one would first attempt to record data about ease of communication (transportation, language barriers), flows of persons in exchange and cooperative efforts or numbers of patent applications resulting from cross‐border activities. However, as many of these data are hard to come by, for the present illustrative purpose, we propose a com‐ putational experiment using publicly accessible data based on pair‐wise comparisons between counties (their urban centers). Among these we will include “travel distances” as of Table 5, which can be replaced, updated or modified by a large variety of pair‐wise similarity measurements. Further‐more, some other similarities are calculated, i.e. by using Tables 3 and 4 (i.e. for the Hungarian‐Romanian border case). In doing so, for the HU‐ RO and the PT‐SP cases, respectively, we arrive at three distinct 8 × 8 ‐matrices: matrix D0 , which contains the distances from Tables 2c and 5, the matrix D1 , which contains the similarities between the features of the county capitals derived from Tables 2b and 4, and matrix D2 , which contains two country‐wise 4 × 4 − sub‐ matrices at their diagonals and which is zero otherwise. Each sub‐matrix is filled with a scalar coefficient obtained by row‐wise aggregating the entries of Tables 1 and 3. Then, e.g. for the PT‐SP case, the (1 : 4) × (1 : 4) entries refer to Portuguese counties and (5 : 8) × (5 : 8) entries refer to those of Spain. By doing so we arrive at two separate influence matrices, one for the PT‐SP and the other for the HU‐RO case. Each such influence matrix then reads M (α , β ) = − D0 + αD1 + β D2 , with parameters α , β ≥ 0 . As both cases happen to have 8 cross border counties, the total influences of a respective county i ∈ {1,...,8} being in coalition x ∈ {0,1} (i.e. a 0‐1 vector of length 8 with xi = 1 ) are then T ( x, i ) = 8

∑M

(α , β ) xk . A

coalition is said to be stable (attainable with high probability) if no other county from coalition x can improve its total effects (gains) by switching to the counter‐coalition 1 − x (e.g. x and 1 − x being something like 00110001 and 11001110, etc.), that is, for no such county i the inequality M ii + T (1 − x, i ) > T ( x, i ) should hold. These are the (potentially many) local optima of a quadratic integer programming problem (Axelrod et al. (1995), Schebesch and Someşan (2008)), which in our case reads: maximize payoff xM (α , β ) x over all

28 = 256 coalition vectors x. Hence, counties which are grouped into stable coalitions can be thought of as contributing more intensively to IC formation. Figure 2 depicts such a valuation of mutual regional influences. The 256 coalitions are sorted according to coalition size (line). A stable coalition which is shown by an impulse. The depicted runs all uses α = 0.02 and β = 0.035 (only ratios are important). The Do matrices of the PT‐SP and the HU‐RO region are weighted in order to scale their relative influence (for changing this very weight see also Table 6).

6.2 How sensitive is the cross‐border IC‐formation index based on coalitions? For a broad range of parameter values a relatively small number of local maxima as indicated by Figure 2 is quite typical for both, the PT‐SP and the HU‐RO case. However, as Table 6 indicates, many such stable coalitions are not cross border. However, increasing the influence of the distance matrix D0 would increase the number of small cross border Nash coalitions in the PT‐SP case. In the HU‐RO setting decreasing the influence of the distance matrix would have a similar effect, but is leading to large coalitions. Durable large coalitions and, indeed, large cross‐border coalitions may be much more difficult to keep alive. Such computations are preliminary and more informed schemes for weighting the contributions of the single matrices combined with more qualitative, human judgment are in order to better guide and support IC‐enhan‐ ced regional development.

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Figure 2: The size of all possible coalitions (sorted) formed within regions PT‐SP (left) and HU‐RO (right) with the resulting coalitions which are stable, here given by their payoffs (impulse lengths)

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Klaus Bruno Schebesch and Eduardo Tomé Table 6: Those relative maxima of Figure 2 (stable coalitions) which are also cross border coalitions are shown in ascending order of the binary number representation of their coalitions (i.e. they are not sorted like those in Figure 2). PT‐SP and HU‐RO member counties have the same order as those listed in Tables 2b and 2c and in Tables 4 and 5, respectively. The ratio of the two starting weights (*) and (**) accounts for the total distances which occur in matrix D0 of PT‐SP and HU‐RO respectively, which are roughly two times larger in the case of PT‐SP Current coalition

Value of Portuguese payoff members 127 1.813 0 1 1 1 1 1 1 0 205 1.274 1 1 0 0 1 1 0 0

Spanish members

Current coalition

Total of 21 (8.20 %) Nash coalitions, 2 of which are cross

Value of Hungarian Romanian payoff members members 127 2.295 0 1 1 1 1 1 1 0 232 2.333 1 1 1 0 0 1 1 1 240 2.949 1 1 1 0 1 1 1 1 Total of 16 (6.25 %) Nash coalitions, 3 of which are cross

border. Using: 0.000135 × D0 (*).

border. Using: 0.00035 × D0 (**).

If 0.00035 × D0 is used as in the HU‐RO case, then 58

By using 0.000135 × D0 as in the first PT‐SP ca‐se, 34

(22.6563 %) Nash coalitions result, 28 of which are cross border with maximum of 4 members (coalition 205 with 1 1 0 0 1 1 0 0 is retained).

(13.2813 %) Nash coalitions result, 24 of which are cross border, with a minimum of 6 members retaining all previous coalitions 127, 232 and 240.

7. Conclusions and outlook Anecdotic evidence from the two studied cross‐border EU regions seems to indicate very limited incentives to increase regional IC‐related effort. However, favorable conditions for IC formation in both regions may be residing in untapped human, developmental and natural resource potential. Utilizing these assets would result in a) bringing local talent to local use, b) implement otherwise obvious infrastructural projects by culturally reinforcing political support (i.e. willingness to express support for cross border action), and c) to increase the scope of medium to large scale cross‐border projects. In proposing a small number of stylized influence factors for influencing coalition formation and, as a probable consequence IC, formation in a cross‐border context, we use publicly available data form our two EU regions and we then introduce a way of utilizing similarities between different intra‐regional units (counties) in order to find all stable coalitions. Some of these coalitions are also cross border. The way these stable cross border coalitions change by number and structure upon varying certain influences (the role of pair‐wise distances, i.e. transport, communication, etc.) is markedly different for the PT‐SP and the HU‐RO regions, implying different recommendations about how to stimulate formation of regional IC. We note from the experiments that the payoffs for the PT‐SP coalitions appear to be somewhat weaker then those for HU‐RO, but also that many smaller coalitions, which are the rule for PT‐SP region, also indicates that more IC formation may be triggered there more easily. Finally, in both cases, we find a similar number of effective cross‐border coalitions.

References Axelrod, Robert, Will Mitchell, Robert E. Thomas, D. Scott Bennett, and Erhard Bruderer (1995). “Coalition Formation in Standard‐Setting Alliances.” Management Science 41:1493‐1508. Bounfour, A. and Edvinsson, L. (2005). Intellectual capital for communities – nations, regions, and cities, Butterworth‐. Heinemann, Oxford Corruption Index (2012). Accessed at http://en.wikipedia.org/wiki/Corruption_Perceptions_Index Edvinsson, L. and Malone, M. (1997). Intellectual Capital: Realizing your Company’s True Value by Finding Its Hidden Roots. New York: Harper Business. EU (2012). Programa Operacional de Cooperação Transfronteiriça: Espanha Portugal, 2007‐2013. Brussels, 2007 EU (2012). Programul Operational de Cooperare Transfrontaliera: Ungaria Romania, 2007‐2013. Brussels, 2007 Hansen N. (1967). Development Pole Theory in a Regional Context: Kyklos, International Review of Social Sciences ‐ Volume 20, Issue 4, pages 709–727, November 1967. Joia, L. A., and Malheiros, R. (2009). Strategic alliances and the intellectual capital of firms. Journal of Intellectual Capital, 10(4), 539–558. Kaplan R.; Norton D (1994): The Balanced Scorecard. Harvard Business School, Boston. Krugman, P. (1991). Increasing returns and economic geography'. Journal of Political Economy 99, pp. 483–99. Morrone, A., Tontoranelli, N., and Ranuzzi G. (2009), “How Good is Trust?: Measuring Trust and its Role for the Progress of Societies”, OECD Statistics Working Papers, 2009/03, OECD Publishing. http://dx.doi.org/10.1787/220633873086 Nonaka, I. and Takeuchi H. (1995). “The Knowledge‐Creating Company,” Oxford University Press, 1995.

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Klaus Bruno Schebesch and Eduardo Tomé Richards, H. A. (1962). Transportation Costs and Plant Location: A Review of Principal Theories. Transportation Journal, 2(2), 19‐24 Rodrigues K. and Tomé E. (2010). Knowledge Cities: A Portuguese Case – ECIC Conference. Proceedings. Cyprus, April pp. 343‐349. Sánchez, M. P., Elena, S., and Castrillo, R. (2009). Intellectual capital dynamics in universities: a reporting model. Journal of Intellectual Capital, 10(2), 307–324. Schebesch, K.B. and Someşan C. (2008). Activity Internationalization and Innovation in SME: Searching Building Blocks for Rating Models, ECEI 2008, Winchester Sveiby, K.E. (2010). Methods for Measuring Intangible Assets. As assessed on November 26 2012 ‐ http://www.sveiby.com/articles/IntangibleMethods.htm. Tomé, E. (2012). “Knowledge Management” in Human Resource Development: Learning, Education and Training 3rd Edition. Edited by JP Wilson. Kogan Page Editors UNDP (2012) Romania Country Profile: Human Development Indicators, accessed at http://hdrstats.undp.org/en/countries/profiles/ROU.html UNDP (2012) Hungary Country Profile: Human Development Indicators, accessed at http://hdrstats.undp.org/en/countries/profiles/HUN.html Von Thünen, J .H. (1826). Der isolierte Staat in Beziehung auf Landwirtschaft und Nationalökonomie, pp. 11‐12. Hamburg (1966 edition, Stuttgart : Gustav Fischer) World Bank, (2012) Measuring Knowledge in the World’s Economy: Knowledge Assessment Methodology and Knowledge Economy Index. Knowledge For Development Program, accessed at http://siteresources.worldbank.org/INTUNIKAM/Resources/KAM_v4.pdf

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Intellectual Capital Factors as the Basis for a Brazilian Competitive Intelligence System Camilo Augusto Sequeira1, Markus Will², Eloi Fernández y Fernández1, Holger Kohl2 and Adeline Du Toit3 1 Institute of Energy Catholic University Rio de Janeiro, IEPUC‐Rio, Rio de Janeiro, Brazil 2 Division Corporate Management, Fraunhofer‐IPK, Berlin, Germany 3 Centre for Information and Knowledge Management, University of Johannesburg, South Africa Camilo@esp.puc‐rio.br Markus.will@ipk.fraunhofer.de Eloi@puc‐rio.br holger.kohl@ipk.fraunhofer.de adutoit@uj.ac.za Abstract: Two fundamental and recently initiatives have shown that it is time to think about new ways of managing companies, particularly in emerging economies. The paper, “Intellectual Capital Statements in Brazilian SME” (Fernández, et al., 2012), points out that, in the rapidly emerging Brazilian economy, intangible assets become a key success factor for sustainable growth. As experiences in the fast moving city and state of Rio de Janeiro have shown, the development of systematic management procedures for these intangible assets is especially valuable for fast growing small and medium‐ sized enterprises (SMEs) in order to serve as the solid backbone for an increasingly knowledge‐based economy. In this context, it becomes an essential management goal to keep productivity at a constant high level, in a dynamic and fast growing business environment, and thus, at the same time, securing individual profits and national welfare. This management challenge has been the starting point for the first pilot‐project on implementing the management tool “Intellectual Capital Statement”, ICS, in ten pioneer SMEs from Rio de Janeiro. The second initiative described in the paper “Current State of Competitive Intelligence in Brazil” (Sequeira, et al., 2012) highlights that Brazil has been evolving into a knowledge society dealing with political changes, globalization, new technologies, and new global competitors, such as China. The need to enhance companies´ and, by extension, countries´ competitiveness has grown rapidly. The Brazilian government and companies have realized that competing in a global economy requires a strong vision of what exists outside the country. As a result, Competitive Intelligence is becoming more accepted as a fundamental business function. The paper concludes that organisations in Brazil should seek to engage proactively with the global environment by revising their strategic priorities. It is, therefore, evident that organisations and particularly government policies need to redress some critical competitiveness issues, most notably the establishment of the Competitive Intelligence System as a strategic tool. Without such tool, organisations and the country will find it difficult to position themselves in the global marketplace. Taking into account the main conclusions of the two initiatives described above, and the unique circumstances of organically grown organizations in the Brazilian business environment, this paper discusses the challenge of integrating the ICS into a comprehensive strategic change process. In order to promote sustainable business development in an emerging economy, the ICS has to be used to establish a continuous improvement cycle in the individual company, focusing on practical actions for maintaining and developing its intangible assets to ensure future competition capability. And, in parallel, there is the need for a National Innovator Monitor as a Competitive Intelligence System in order to fulfill the requirements of, at least, four main stakeholders’ perspectives: Companies (benchmarking), Policies (innovator monitor), Research (research agenda), and Financial Market (risk assessment). Keywords: intellectual capital, intangible assets, knowledge economy, competitive intelligence, Brazil, oil and gas

1. Introduction Abundant tangible (financial and physical) resources do not necessarily lead to prosperity. Knowledge, expressed by the intellectual capital of organizations, is the most valuable asset and creates wealth and social mobility. It is not expensive, considering its cost‐benefit ratio in the medium and long term, but many organizations still consider knowledge as a secondary strategy. Intellectual capital from investment in education shows the innovativeness of organizations, whether public or private. Consequently, innovation is strongly correlated with intellectual capital. South Korea’s example demonstrates that focused investments in education, aligned to modernize management, transformed it from an agrarian country, until the seventies, in a nation globally known for goods and services with high innovation content.

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Camilo Augusto Sequeira et al. Two recent studies show that it takes more than access to unlimited resources to progress. The "oil curse" has contaminated the 25 municipalities in the states of Rio de Janeiro, Espirito Santo and São Paulo that receive more resources from oil royalties. Quality of life in those municipalities as measured by safety, education, health and sanitation indicators, did not accompany the GDP growth rate. The Brazilian Index of Basic Education (IDEB) fell in those municipalities despite the improvement in the national sphere. None of the municipalities had the ability to draw up plans for structuring the use of these resources. According to the study, they lacked quality of management. That is the conclusion of a survey carried out by a consultancy company (Macroplan, 2012). Another study carried out by the Energy Institute of Catholic University, Rio de Janeiro, in a partnership with the Fraunnhofer IPK Institute, Berlin, and supported by SebraeRJ (Serviço Brasileiro de Apoio às Micro e Pequenas Empresas do Estado do Rio de Janeiro), showed that companies in the private oil and gas sector also require innovation in management. In this study, most companies indicated the need to improve the quality of management. This shows that Brazil needs more than the current “Local Content Policy” which, although necessary, is not sufficient to leverage the development of new technologies and competitiveness to domestic firms. Several programs of investment in innovation are continuing, but they still require integration and monitoring so that the results are evident in the medium and long term. The Institute of Energy study, besides emphasizing the management issue, also pointed to the need for a "National Innovation Monitor" as a “Competitive Intelligence System”, if Brazil wants to improve performance and competitiveness in a global scenario. This paper aims to illustrate and explain the imperative of these two issues: the application of a method in order to innovate the companies’ management and a monitor to track the companies’ capacity to innovate and create new technologies.

2. Oil and gas context “Tangible assets, financial and physical, are necessary but not long enough to create competitive advantage in a global world”. These are the words of a senior executive involved in the operation of this sector. According to him, the creation of value through intangible assets gained strategic importance in Brazil. The newly discovered enormous reserves of oil and gas, off the coast of Rio de Janeiro state, draws attention to the leading global operators in the industry. The most significant multinational corporations of this sector are operating in Brazil, besides Petrobras, the largest state‐owned company. This causes thousands of companies, potential suppliers of goods and services with high technological and original content to focus on Rio de Janeiro and neighboring states, such as São Paulo and Espirito Santo. The suppliers of the oil and gas production chain, especially small and medium enterprises, have strategic importance in Brazil’s economic context for its likely and necessary endogenous development of technology and innovation. If Brazil wants to play a relevant role on the world stage, the economic agents need to be capable of providing products and services on a high technological development and innovation level on a medium and long term basis. Thus, the oil and gas sector stands out as being a driver for this intensive technological development and innovation. In this context, the knowledge assets or intellectual capital may play a key role in the process of differentiation and competitiveness. As empirical studies confirm, productivity is a direct consequence of the level of technological development and innovation activities. Therefore, the amount of investments in technological innovations results in an increased value creation in companies and, consequently, in the whole country. Evaluating the content of intellectual capital is crucial for direct and well‐aimed investments in potentially productive sectors. As a consequence, we believe that, once identified and mapped, the content of intellectual capital can be an indicator of yield potential. We consider the content of intellectual capital directly related to the intangible factors of success as, for example, employee motivation, internal communication, knowledge transfer and cooperation, capacity management and leadership, as well as relationships with suppliers, customers and other stakeholders, including the impacts of corporate activities in the social and environmental field. All these factors, classified

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Camilo Augusto Sequeira et al. into three categories, make up the intellectual capital of a company: human capital, structural capital and relational capital.

3. Innovating management to add value Usually, managers consider and treat intangible resources, such as knowledge, in the background, or in a subjective manner without applying methods capable of identifying the intellectual capital factors within the potential value generator and aligning them with company’s goals systematically. Unlike conventional methods, “Intellectual Capital statement” (ICS) allows, through a structured and straightforward procedure, to represent and manage the intellectual capital of the enterprise in a highly efficient way. The external stakeholders also benefit from the application, including funding institutions, providing more transparency to their investments. Therefore, both companies and interested parties may have a better understanding and management of their investments in knowledge assets, minimizing risks on expectations of returns. A set of selected companies from the oil and gas sector participated in the first pilot project of this kind in Brazil. The main objectives to be achieved with this pilot application were:

Show the benefits to Brazilian companies through actual case studies;

Extract lessons learned from the implementation of the European method, and define the requirements for suitability of the Intellectual Capital Statement Brazil (ICS‐BR) method to the Brazilian reality;

Demonstrate that the method aims to formulate strategies from the perspective of intangible assets;

Prepare the team and tools to support the future implementation on a large scale;

If the application is viable on a large scale, verify the requirements and the possibility of developing a database for future benchmarking on the content of intellectual capital.

The “ICS Toolbox” software supports the method that provides different visual forms to illustrate the results. The summarizing visualization is a portfolio of Intellectual Capital Factors which displays the factors, having the greatest impact on the company’s results compared to their current assessment in a four quadrant matrix. The portfolio represents, on a consolidated basis, the results of the evaluation of each factor of intellectual capital. The Y axis displays the relative weight or impact of the factors on the results of the organization. The impact matrix, a tool for analyzing each factor compared to its significance in relation to the organizations results, generates this weighing measure called “relative influence”. The X axis represents the consolidation of the assessment of intellectual capital factors in three dimensions: Quantity, Quality and Systematic (QQS analysis), and the extent to which the company treats each of the factors. Thus, through easy and realistic illustrations, managers can manage their intangible assets and objectively assess the results over time as shown in Figure 1. Another extremely useful tool, derived from the Toolbox, is the cross‐impact matrix and its “loops”. The Impact Map represents the factors with their mutual influences and their delays. In order to develop a comprehensive understanding about the investment results in one of the factors of intellectual capital, for instance in product innovation, it is necessary to understand how long this factor takes to affect the financial results. This is a powerful tool to formulate strategies in the medium and long term. Managers assess future scenarios and prioritize their investments and actions to achieve clearly connected goals in each of the prioritized IC factors as shown in Figure 2. The ICS method can be considered an indicator to reveal critical factors and hence decide about the failure or the success of the company in an early stage of its life cycle. Companies often fail to focus on aspects of general business management to the point of diminishing growth and trigger financial strangulation. This explains, for example, the high mortality rate of startups. ICS helps companies to become aware that they do not have the necessary management skills or structure which allows organic growth. The companies also reported that the biggest gains of the method derives from the ICS evidence of possible failure mechanisms of coordination within the enterprise and internal communication, as well as some rigidity factors or counterproductive effects of corporate culture. The companies witnessed this evidence by themselves.

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Figure 1: Example of an IC management portfolio, impact analysis and QQS assessment

Figure 2: Example of an impact map with an IC loop and measurable actions In general, according to the results of the pilot project, the intellectual capital factor that needs to be developed the most is the human capital factor “Management Competence”. It appeared in most companies as the factor with the greatest relative impact on business results, but with low assessment. This means that by investing in the development of this factor with the highest intervention potential, the results arising from this investment are high.

4. The method in perspective In a questionnaire based survey, all ten companies replied that they would recommend the method to other companies. In general, benefit of the method comes in two main aspects: internal communication to increase

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Camilo Augusto Sequeira et al. transparency and monitor the strategic development. Another benefit lies in using the method for communicating the values of the company externally. The companies also stated that the method helps in the following aspects as shown in Figure 3.

Figure 3: Perceived management support of ICS Based on the feedback from the pilot‐companies, the method proved to be an effective and efficient way to manage and focus on intangible assets, with the greatest potential to add value. Likewise, it worked remarkably well as a consistency check of their business model, emphasizing the importance of systematic management. The companies were able to introduce a new language and attitude, and gains from the exchange of ideas within the team became apparent extremely fast. Commonly, companies undergo varying degrees of maturity over the course of their life cycle. First, companies begin their activities with a focus on the product and marketing, then seek innovation in internal processes necessary to the operation, and then prioritize the use of resources. In this case, the application of the method helps managers to conduct their business to a higher level of maturity and sustainability. The results of the pilot project indicate the need for post‐implementation monitoring, especially in the interpretation and implementation of actions in a systematic way. The companies mentioned that they need more time to conduct a deeper diagnosis in order to better analyze the results. They refer specifically to the phases of impact assessment and loops as well as the planning of actions. Thus, more time and specific supporting measures should be considered after the completion of the workshop. One of the important features of this process is the “Quality Assurance” policy. Only trained and certified moderators can apply the method in a future ICS‐BR brand. Therefore, leading trainers, responsible for training moderators and auditors, who monitor the implementation process, should follow international standards required by the method. The results of this pilot project also point to the need for promoting the application of the method in a larger number of companies. This approach should be an issue for development, following a strategy that makes it an available management tool for the vast majority of Brazilian companies. The method must be applied periodically to monitor the companies’ progress. So, we will receive reports with graphs that show the development of each factor of intellectual capital throughout the period. Collating this information in the database, we are creating a “benchmark” to generate trends that will be useful to define policies for the sector. Using a standard method, this “benchmark” can be compared to similar international applications creating a network of “best practices and lessons learned” for Brazilian companies.

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Camilo Augusto Sequeira et al. Taking into consideration the intangible resources, besides serving as a management tool, the ICS method also draws managers’ attention to the need for change in processes and practices using a structured communication procedure of the method itself. In this respect, it is particularly beneficial to follow the first applications from the companies, as well as raising the level of certification of moderators who will carry out this monitoring. Based on these considerations, it is necessary to understand the method from a broader perspective on the services, evolving toward a system of “Benchmark” that includes performance information, management processes, methods and tools focused on managing innovation, among others. Following this development, the enterprises and institutions responsible for developing policies for the sector can strategize more sustainably. In this sense, the adoption of the method should be treated in the medium and long term. In itself, the method is a paradigm shift in management, leading executives to adopt an innovation management process using the structure of internal and external communication inherent in the method. Based on these issues, and considering that the application of the method in a massive way will provide substantial cross information, it is extremely relevant to start developing a Competitive Intelligent System to help Brazilian companies achieving performance and competitiveness in a global scenario.

5. An overview of competitive intelligence in Brazil Substantial political changes in Brazil since 1990 have led to greater information exchange, and the Brazilian society has been evolving into a knowledge society, dealing with political changes, globalisation, new technologies, hyper competition and new global competitors, such as China. The Brazilian government and Brazilian companies have realized that competing in a global economy requires a strong vision of what exists outside the country’s borders. As a result, Competitive Intelligence (CI) is becoming more accepted both as a profession and as a fundamental business function. In spite of this, CI in Brazil remains fragmented for decision makers who need reliable information to deploy innovative policies for economic development. Over recent years, there has been much talk about the future world role to be played by a small group of previously subaltern or marginalised countries that have large territories and populations and considerable natural resources and will constitute not only large markets but will be important producer nations. Most frequently referred to as the BRICS (Brazil, Russia, India, China and South Africa), this loose and highly diverse group of countries play an increasing role on the world stage in cultural, economic, and political terms (Dwyer, 2009). With the increased volatility of the business environment, countries and companies rely on early detection of environmental changes so that they may respond with appropriate counter measures. Since they require time to adapt to the changing environment, they should have the ability to anticipate changes, and imagine the consequences of alternative responses to those changes, and they use CI to facilitate the identification of potential opportunities and threats. Because CI improves decision‐making, it helps a company or a country to take better decisions and understand the relationships between partners, competitors, laws, regulations and social behavior. According to the Global Competitiveness Report 2011‐2012 (GCR) (Schwab, 2011), Brazil has improved its rd competitive position by five places, ranked 53 out of 142 countries, as illustrated in Figure 4. Brazil has also benefited from several competitive strengths as noticed in Figure 04. These strengths include internal market size (10th), a sophisticated business environment (31st) and innovation (44th). The country also has an efficient financial market, ranked 40th, and the rate of technology adoption is relatively high at 47th compared to other countries in its region. However, there are several problematic areas that hinder countries from doing business with Brazil. According to the GCR, factors such as tax rates, tax regulations, inadequate supply of infrastructure and restrictive labour regulations rank high as problem areas for doing business in Brazil and these factors also impact Brazil’s capacity to fulfill and sustain its competitive potential.

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Figure 4: Global Competitiveness Index Concerning the CI implementation in Brazil, a study conducted by Libis (Libis 2005) points out some important issues: CI is not widely accepted in business. Brazilians decision makers do not seem motivated to establish CI capabilities in their companies. However, they do have CI departments in international companies based in Brazil. Usually, CI is in marketing departments, restricted only to market research and detached from decision makers. Only larger companies contemplate CI in strategic departments. Another recent study conducted by Sequeira (Sequeira, et al. 2012) as a survey mainly exploratory in nature, found the following results: 23% of the respondents indicated that competition is unusually intense in their country while 46.1% of the organisations indicated that they cope above average with changes in the external environment. This is an indication that currently CI practitioners in Brazil do not realize the importance of scanning the environment as an early‐warning tool to adapt strategies. A formal CI function exists at only 15.4% of the organisations, and no company has had a CI function for more than five years. With regard to the five main CI activities implemented by organisations, 61.5% of the respondents strongly agreed that the CI function assists to quantify/qualify strategic choices. The majority of the organisations (84.6%) agreed that their staff members always report back on competitor actions and that they evaluate the reliability and accuracy of the information. The most significant primary sources used by organisations in Brazil are direct customer feedback, customers/suppliers and analysis of competitor’s feedback. This finding correlates with the finding of Libis (Libis 2005) that reports there is abundant access to primary research but that sources credibility is questionable. Organisations, therefore, prefer to collect their own information directly from customers. Globalisation as a primary economic phenomenon compels a country to be competitive and the CI practice can be used to improve the country’s competitiveness as a whole. Only a limited number of organisations in Brazil recognize the importance of a CI unit and did not indicate the use of CI to support decision making. CI in Brazil should thus evolve from providing just the facts (reactive) to being a key component of strategy (proactive). Considering this scenario, Brazil should seek to engage proactively with the global environment by revising strategic priorities, and implementing a monitor to track both performance and competitiveness improvement. Otherwise, Brazilian companies will find it difficult to position themselves in the global marketplace.

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6. The need of a competitive intelligence system The National Innovation Monitor, as a Competitive Intelligence System, aims at fulfilling the needs and expectations of four main stakeholder perspectives: Companies, Policies Makers, Financial Market and Research Organisations. A Central Database will provide indicators for economic and innovation performance, and the company’s content of intellectual capital. The development of the database will connect existing monitor systems such as tax and education systems with companies´ performance data at regional, sectorial and national level. Database Implementation will comply with international standards to allow comparison and benchmarking at a national level with other countries, as a basis for transferring the best practices for successful development of the national innovation system. Massive application of ICS method, as described before, will collect and gather substantial information from companies that must be structured in a database system, as illustrated in Figure 05. By mining the database, one can answer the following questions from the perspective of:

Companies: How reliable is performance compared to others?

Research: Which solutions, knowledge and methods does the industry need from applied research to promote innovation, improve performance and competitiveness?

Financial Market: How can we assess the future potential and differentiate the risks of investments and how can we guarantee?

Politics: Which are the industry‘s most critical challenges to ensure high productivity and sustainable innovation. To attend the strategic demands of the economy, which new technologies must be developed? Figu

Figure 5: Four stakeholder perspectives The National Innovation Monitor must be developed in a step‐by‐step approach and considering the intellectual capital factors as the resource base for innovation at company level. Therefore, the entire system must be constructed based on a bottom up procedure from the results of the ICS application in each company, considered as the base step, according to Figure 6. The next step to be implemented, the IC Monitor level as shown in Figure 06, relies on a “quick‐check” tool prepared as a qualitative Intellectual Capital Factors monitoring. Standardized measurement of innovation and

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Camilo Augusto Sequeira et al. overall economic performance of companies are compared at national and international level through Benchmark Index in the 2nd step. As a final stage, one can analyze causes and effects to focus programs in different parts of the national innovation system, aligning industry initiatives with programs for R&D system, matching the maturity of industry sectors with applied research agenda, among others.

Figure 6: Competitive intelligence system Step 1 Objectives and Benefits

Sensitize a large number of companies for the importance of IC management

Assess own IC and to get first recommendations for IC management

Compare own IC with a reference group and initiate best practice transfer on IC management

Gather data on a large scale for regional and national analysis

Step 2 Objectives and Benefits

Implement international standard for performance measurement of industries and be the first country in Latin America to join the Global Benchmarking Network (GBN)

Provide a well‐structured monitoring system for Brazilian companies to assess their business and innovation performance

Support companies’ improvements to increase the national degree of value adding activites and national content

Step 3 Objectives and Benefits

Implement an integrated monitoring system to analyze the performance of the national innovation system, including industry, R&D system and framework conditions

Align the industry’s demands with performance and focus of R&D system

Provide a systematic decision basis for policy makers and other stakeholders to improve the national innovation performance and competitiveness

Take into account existing monitoring systems in Brazil and international standards

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7. Conclusions Two studies here described converged for the necessity of developing a National Innovation Monitor. The massively application of ICS method will provide the required information to create a dynamic and integrated database, considering Intellectual Capital Factors as a proxy for the companies’ capacity to innovate. The current context of Competitive Intelligence in Brazil demonstrates that developing a national Competitive Intelligence System is vital if Brazil wants to become a global competitive country. It is clear that CI practices exist mainly in large companies. Small and medium ones do not have conditions to support such activity. Therefore, the main beneficiaries of National Innovation Monitor will be Small and Medium Enterprises (SMEs). The governmental policies can be articulated, based on an integrated and dynamic system. The Brazilian companies will change from reactive state into a strategically proactive one. Two main issues justify a prudent approach during the implementation of the National Innovation Monitor: The confidentiality about the business information gathering from the companies, and the roles of each stakeholder. The system needs a quality assurance policy establishing a clear workflow with the responsibilities of each person involved: training leaders, moderators, auditors and defining the organization in charge of the database. Performance and competitiveness of the Brazilian companies, supplying goods and services with high content of innovation, are achieved with the implementation of the following strategy: paving the infrastructure for all the economy, as a whole, and not focusing only on a limited number of sectors. In this sense, the National Innovation Monitor will be an extremely useful tool to support this strategy.

References Dwyer, T. (2009). “On the internalization of Brazilian academic Sociology”, ISA E‐Bulletin, 13: 20‐47. Fernández Y Fernández, E., Mertins, K., Sequeira, C.A. and Will, M. (2012), “Intellectual Capital Statements in Brazilian SME, lessons Learned from the first Pilot‐Implementations”, 13th European Conference on Knowledge Management, Conference Proceedings, 6‐7 September, Cartagena, Spain. Libis, J. (2005). “Competitive intelligence in Brazil” In: Competitive intelligence and global business. Edited by D.L.Blenkhorn & C.S. Fleisher. 2005. Westpoint, Connecticut: Praeger. pp 237‐251. Macroplan, (2012), “Royalties do Petróleo e Desenvolvimento Municipal”, Agosto de 2012, http://www.macroplan.com.br/MonCenarios_Item.aspx?Id=34. Mertins, K., Will, M. and Meyer, C. (2009). InCaS: Intellectual Capital Statement. Measuring Intellectual Capital in European small and medium sized enterprises. ECKM 2009, Conference Proceedings. Schwab, K. (2011), “Global competitiveness report 2011‐2012”. World Economic Forum, Geneva. th Sequeira, C.A., Du Toit, A.S.A. and Sewdass, N. (2012), “Current State of Competitive Intelligence In Brazil”, The 8 International Conference on Knowledge Management, Conference Proceedings, 4‐6 September, University of Johannesburg, South Africa.

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Disclosing Intellectual Capital in Tertiary Education: From Necessity to Reality Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă Academy of Economic Studies, Bucharest, Romania Christina. suciu@economie.ase.ro lusianapiciorus@yahoo.co.uk imbrisca_c@yahoo.com Abstract: Intellectual capital is one of the key elements of economies all over the world. Under these circumstances, the paper aims at continuing and expanding the research carried in the last two years. Therefore, we intent to develop a comparative analysis of the 2012 Romanian educational system to the results of the study performed in 2011, but focusing on those changes that took place in the state of the art and evaluation models and frameworks applied in tertiary economic education. The main argument for selecting this area of interest is the impact of the prolonged economic downturn which transformed radically the educational system. The research methodology includes three different phases, with unique research instruments: two questionnaires dedicated to beneficiaries and academic staff in higher education. The first stage is focusing on a theoretical underpinning of the latest literature in the area of research. The next action is to create a questionnaire, considering both the literature review results and other studies from European countries where the tertiary educational system is similar to the Romanian one. Finally, the last part is dedicated to analyze and validate econometrically by using inferential statistical analysis for evaluating the initial research hypothesis. The results are expected to be of relevance as the educational environment in our country does need for intellectual capital evaluation and disclosure of the connected information and procedures, whereas the case. If in the last two years our research efforts indicated that though the oldest Romanian universities now are facing fierce competition as both students and professors have worldwide options. Unfortunately, many superior education institutions are still far from valuating intellectual capital as a success factor in establishing a medium and long term growth strategies. Keywords: intellectual capital, knowledge‐based society, human capital, disclosing of intangibles

1. Brief literature review Intellectual capital has gained permanently in terms of importance and relevance not only for individual entities, but also for nations (Yeh‐Yun Lin, C., Edvinsson‚ L., 2010). Accordingly, measurement models have been designed, though yet there is lacking an international agreed framework. But what it is relevant is that models comprise indicators connected to human, relational and structural components. Therefore, we find the classic structure of intellectual capital in the static approach (Chaminade, C., Catasús, B., 2007). Since the first generation of concepts things have evolved: going from private entities to public sector and even nations, intellectual capital is presently evaluated using a dynamic approach, combining intangible assets and activities, characterized by interactions and strategy (Veltri,S., Bronzetti, G, Sicoli, G., 2011).

What about intellectual capital in higher education institutions? Universities are continuously transforming, “virtual classrooms”, “online educations” are just few of the novelty elements. And certainly they must adhere to new requirements – acknowledging their role and contributing to the economic development of a nation. So, after learning how to manage intellectual capital and intangibles, the next logical step is for them to learn how to disclose information on this topic.

There are several significant initiatives addressing intellectual capital that can be also applied to universities ‐ “Guidelines for Managing and Reporting on Intangibles (Intellectual Capital Report)”, that involves a new classification of intangible assets, 70 case studies in terms of management and control of intangibles in companies, role of intangibles for the equity market and guidelines for measuring and disclosure of intangible assets (European Commission, Research and Innovation), the Austrian Research Centers ARC released the “Intellectual Capital Report 1999‐2004” in 2005, the future basis for Austrian universities reports on intellectual capital and, in 2006, “RICARDIS” (Reporting Intellectual Capital to Augment Research, Development and Innovation in SMEs) belonging to the European Commission (Sánchez, P., Castrillo, R., Elena, S., 2009).

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2. Is it really a necessity to report intellectual capital in tertiary education? For decades now higher education institutions were faced with massive changes that affected also their image in the eyes of the society, both in terms of responsibilities, organization and procedures. Romania was also part of the process, sometimes characterized as “ineffective, irrelevant, and low in quality” as qualified by the Presidential Commission in 2007 (Andreescu et al., 2010). Therefore, why should intellectual capital be evaluated?

2.1 Reasons behind reporting and disclosing For answering this question let us make reference to diagnosis reflecting potential successful long run scenarios for the Romanian higher education (The Quality and Leadership for The Romanian Higher Education Project, 2008‐2011). Firstly, intellectual capital in higher education is about human capital, so about skills, competencies, qualifications, mostly obtained within an institutional environment as the one of universities. Therefore, for matching as precisely as possible the demands of the labour market (well trained employees contributing significantly to increasing productivity levels, new jobs) investing in education and human capital is essential. But this cannot happen unless the needs are correctly evaluated. Secondly, organizational (structural) capital, represented by “structured knowledge” (Veltri, S., Bronzetti, G, Sicoli, G., 2011) such as databases, protocols and codes, plays a strategic role for higher education. Naturally this is connected with the ability of the institution to meet the external demands, both those coming from the main stakeholders and beneficiaries – the students, of other stakeholders and of the labour market. Lastly, the relational capital connects and integrates higher education. Here are included the partnerships that universities create with the civil, research and business sectors, as well as with other universities, naming here bilateral agreements (in Romania many have been enforced under the Erasmus partnership and Bologna process) and interdisciplinary projects. Another approach (Fazlagic, 2005) connects reporting intellectual capital to the need for transparency specific to the public sector, contributing to a just ranking of universities and supporting the decision process for beneficiaries, and also inter‐relating researchers and the rest of the society as common ground can exist. Further, the paper is going to distinguish between best practices models in terms of management and disclosure, but also to compare European reality to the Romanian one. Though not fully aligned to the latest trends and suffering from a lack of systematic and unified approach, it is necessary to identify the positive aspects as well. The research methodology uses a quantitative approach by collecting data using a questionnaire; another reason is for being able to make comparisons to the previous results registered in 2011. The findings could contribute to expanding the research area, offer guidelines and working more on the concrete aspects by finally implementing an intellectual capital evaluation framework.

2.2 Best practice examples in Europe Austrian Research Centre (ARC) The idea of reporting on intellectual capital can trace its beginning to the early nineties when Scandia published an IC report along with its annual report. Afterwards, the initiative started to gain ground in the industry, however, not so much in the research sector. The Austrian Research Centres Seibersdorf was the first European organization to publish an Intellectual Capital Report in 1999. The various advantages of such a report were easily recognised afterwards and soon implemented by other institutes. In 2002 the reorganisation of the Austrian education system introduced as mandatory an IC report to be published. There are two objectives that need to be fulfilled by the report:

To provide adequate information to management so that the progress of different programs can be easily monitored;

To disclose information in an appropriate manner to external stakeholders.

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Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă The ARC model framework is structured around the idea that the reporting should be based around the objectives, which can be either organizational goals, of interest to those within the organization, or political goals, of interest to different outside stakeholders. These are then connected to the elements of IC contained within the organization and they function as inputs for the activity. Furthermore, six performance processes are identified and they can be measured as required. Finally, the achievements are assessed in the final phase when the report shows how they impact the different stakeholders (Leitner, 2002). The Poznan University of Economics Intellectual Capital Report (2005) The initiative was carried by Professor Amir Fazlagic at the Polish university of Poznan. According to this view, intellectual capital should be reported in an inclusive manner, therefore being concentrated on human and structural capital, and evaluated through almost 30 indicators. The structure of the IC Report consists of several areas of interest ‐ strategic management, knowledge goals, employees’ satisfaction, student satisfaction, the graduates from university, organisational structure and finally the IC indicators. A special point is represented by enumerating possible barriers in pursuing the IC evaluation, such as cultural barriers and issues to be managed when designing the evaluation instrument itself (Fazlagic, 2005). RICARDIS ‐ Reporting Intellectual Capital to augment research, development and innovation in SMEs (2006) The Directorate General for Research of the European Commission (EC) formed an expert group for supporting intellectual capital reporting in SMEs, considering both the significance of the public and private stakeholders, underlining the link between intellectual capital and research and development activities, including general guidelines and policy recommendations (Encourage corporate measuring and reporting on research and other forms of intellectual capital. RICARDIS: Reporting Intellectual Capital to Augment Research, Development and Innovation in SMEs, 2006). However, universities are also analyzed, including also an IC (Intellectual Capital) Reporting Award that could be attributed to universities as they are sometimes taking the first place in terms of technological advance, influencing also the speed of innovation. Guidelines for Managing and Reporting on Intangibles (Meritum Project) The MERITUM Guidelines is the result of the Meritum Project which was a joint research program that brought together researchers from the Copenhagen Business School, the Research Institute of the Finnish Economy, the Swedish School of Economics and Business Administration, Groupe HEC, Norwegian School of Management, IADE‐Autonomous University of Madrid, the University of Seville and Stockholm University. The project, which was carried out between 1998 and 2001, was funded by the EU through the framework of the TSER program. The main purpose was to serve as a basic framework for companies that are interested in measuring and management of their intangible resources. As such, they can be used either by companies that do not yet have a measurement method or by companies that already have developed one but are now interested in harmonising their methods for disclosure purposes. The proposed guideline advises companies to do split the measurement and management process into three phases (MERITUM Project):

Identification of intangibles: during this phase the company identifies those intangibles which are the key drivers of its activity and, if possible, to assign them weights.

Measurement: the organization must identify indicators to serve as proxies for the before mentioned intangibles; these must be comparable, reliable, objective, truthful, verifiable and feasible.

Action: this stage has two intertwined objectives because its first purpose is to use the knowledge gained from the first two phases and integrate that in the normal processes of the company and at the same time to improve the measurement process by refining the application of the guideline for that company.

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2.3 The Romanian superior education and intellectual capital According to the objectives set by the European Union through the Treaty of Lisbon which entered into force in 2009, Europe has to become the most powerful knowledge based economy. Under these premises, all European countries made continuous efforts, using as corner stone innovation and intellectual capital. Yet, the intellectual capital reporting and evaluation is sometimes focused on the profit sector and less on non‐profit and education institutions. In Romania it is a special situation as up to now there is no intellectual capital evaluation framework enforced nationally or even regionally. However, we have to mention several initiatives which represent the foundation of a positive transformation. Starting 2005, the Executive Unit for Financing Higher Education, Research Development and Innovation launched Foresight in S&I (2005‐2006). This was the first national foresight exercise carried between September 2005‐May 2006, and which led to developing and fostering the largest program which aimed to increase collaboration between different research and development units, economic agents and/or public administration units in Romania, as it is mentioned in the Government Decision no. 474/2007 concerning the approval of the National Plan for Research and Development and Innovation II, for the period 2007‐2013. The second step was represented by the 1st Cycle of strategic projects for the Romanian Higher Education system (2008‐2011). The main programs build up under this structure were ‘Quality and Leadership for the Romanian Higher Education’, ‘PhD in Excellence Schools’, ‘Doctoral Studies in Romania. Organisation of the Doctoral Schools’, ‘Improving Universities Management’, ‘National Student Enrolment Registry and University Graduates’ and ‘Labour Market’. The most recent programs are united under the 2nd Cycle of Strategic Projects for the Romanian Higher Education System developed for 2011‐2014:‘Quality and Diversity of the Romanian Universities’, ‘Quality Assurance in Higher Education by Developing and Piloting the Methodologies for Habilitation and Auditing’ and ‘Performance in Higher Education’. Under the umbrella of the last program, the efforts are concentrated on training both members of management structures and students who will then contribute to the methodology and audit procedure of intellectual capital. The results are going to be publicly disclosed and transferred by incorporating online platforms designed for this purpose. Also, several Mutual Learning Workshops have taken place since 2009. The most recent was in October 2012, in Bucharest, the ‘Mutual Learning Workshops. Intellectual Capital Reporting – International Practice. Universities, Regions, Nations’. This project aims at creating five reports resulting from the Mutual Learning Workshops (MLW), including best practices for human capital, methodological framework in elaborating a national report for human capital in universities, as well as the methodology required for Romanian universities (‘Mutual Learning Workshops. Intellectual Capital Reporting – International Practice. Universities, th Regions, Nations’, 23‐24 October 2012). Except these programs specially tailored to suit the current needs of higher education, there has been created a Scientometrics Office within the Executive Unit for Financing Higher Education, Research Development and Innovation, that has as a priority also to follow and analyze studies related to key areas of science such as intellectual capital and knowledge management. For a five year period, starting 2003, the department also published the "Journal of Political Science and Scientometrics" as a quarterly publication. On the other hand, there is no evaluation or report structure for intellectual capital dedicated to universities individually or grouped. Probably one of the most significant causes is related to the financing system of higher education. Taking as example the human capital, it is well known that results of investments in this component of intellectual capital require time. But the financing of higher education is mainly from public funds, allocated to three main directions: covering the costs due to carrying the educational process, especially of those areas that contribute significantly to economic and sustainable development of the society; complementary financing for accommodation, investments and capital refurbishing, scientific research funds; supplementary financing that

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Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă is offered based on excellence criteria achieved by universities, both public and private ones (UEFISCDI, Higher Education Financing).

3. Research methodology 3.1 Starting point This paper continues to find new insights and mostly to underline the changes that took place in the Romanian higher education system. Almost two years ago, our research team carried an analysis of the Romanian education system. The aim was to underline the close connection between intellectual capital and higher education, all under the conditions determined by the economic crisis, uncertainty and the lack of instruments for evaluating intellectual capital within Romanian education (Suciu et al, 2011). Now we are focusing on the progress in the state of the art and reporting and disclosure of intellectual capital within Romanian universities. The first study was based on the data collected starting November 2010; the research instrument used then was a questionnaire. The statistic sample was significantly, and the respondents randomly selected, 25% men and 75% women, with ages between 20 and 60 years old (Suciu et al, 2011). The findings identified the success and failure critical factors of an efficient intellectual capital evaluation framework offering the proper weight to the particularities imposed by the Romanian higher education system. According to the methodological path we decided by starting with a literature review on this research topic, both at national and international level. Also, this contributed to answering to questions related to whether intellectual capital reporting, evaluation and disclosure are relevant actions to be taken by universities and other higher education institutions, and to define the present context of intellectual capital within the Romanian higher education system. Next, it is our intention to refine the initial questionnaire, use the expertise acquired through other researches carried since 2010, and integrate the experience of other European educational systems. All these have as final goal to identify several possibilities for reporting, evaluating and disclosing intellectual capital in Romanian universities. The last stage of the research is represented by collecting, analysing and validate the findings from statistic and econometrical perspective. Then, by using inferential statistics tools and procedure (assume a normal distribution of the data, conduct several experiments, check the validity of the hypothesis and finally make an inference) to make predictions regarding the evolution of the intellectual capital evaluation process.

3.2 Research stages Pilot study The analysis is going to be carried in two of the faculties of the Bucharest Academy of Economic Studies: Economics Faculty and Business Administration in Foreign Languages Faculty. The respondents are both students and academic staff because a need to expand the research beyond the direct beneficiaries of education and to determine the level of acknowledgment for professors and administrative structures in higher education. The instrument we propose for data collection is a questionnaire. The first step was the survey design. This was done in two stages (Levy and Lemeshow , 1999). First, it was designed the sampling plan for determining the required sample from the population – size and methods to administrate the questionnaire. Next, we have to establish procedures for deciding on the response rate and accurateness. Also, it was preserved the pilot study for improving the quality and efficiency of the larger study that follows. Hence, an initial survey took place in January 2013, its structure was based on the one used in the previous study (Suciu et al, 2011). This questionnaire had an introductory section for familiarising respondents with the research topic, three sections ‐ human capital, organizational capital and relational capital. But the most important is the part related to

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Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă intellectual capital reporting which missed in our previous study. The aim was to determine the direction towards which such higher education reports should focus. Hence the items included were: Table 1: Reporting on intellectual capital 1. Financial information (revenues and expenses, synthetic indicators) 2. Organizational structure 3. Technology and other technical and material equipments 4. Information on courses and study programs

5. Institutional management (efficiency indicators)

6. Structural Capital elements 7. Human Capital elements 8. Relational Capital elements

Following the initial questionnaire applied in January 2013, the following results were obtained:

Figure 1: Intellectual capital reporting indicators. Source: Authors’ pilot survey The interesting aspect that resulted after the pilot test is connected to the financial elements. Though the general interest lays in budgetary and economic‐financial elements, the direct beneficiaries of services provided by the higher education institutions are primary interested in human capital elements and information concerning the courses and programs offered by the university, while the financial data is placed last of all. Under these circumstances, for the main study there are going to be developed sets of questions for each of the category of items so that it results a clear image of what is really relevant for the interviewed categories to be found in a intellectual capital report. Sampling and data collection The sample size was of 60 respondents, 25 men and 35 women, with ages ranging from 22 to 37 years old, with a mean of 24.8 years and a median of 24, with diverse educational backgrounds. Though it only offers limited information, it was very useful because the information allows us to develop the intellectual capital reporting section, the priority of the main study. Also, it provided data for evaluating the research technique and protocol, as well as for statistical purposes. Finally, we could verify if the sample is or not random and representative, connected to the population and sampling error, the last depending on the sample variance. To ensure that the sample fulfils the required conditions, we also made a probability histogram, by considering more than only one sample, of various dimensions and plot on the same graph their means, looking for a smaller standard deviation. In addition, relevant data connected to higher and tertiary education was selected from data basis like Eurostat, World Bank, the National Institute of Statistics of Romania for creating our own data basis in accordance with our research goals. Coding system The information was collected with the help of a written survey, multiplied and distributed to students for the pilot study. The questions are mainly closed and dichotomous yes/no questions, excepting for the

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Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă demographic aspects and introductory section. For his part of the research, the coding system was simple so that the information was conveyed into useful data. Hence, each question thick box had a number so the results were introduced directly to our databases. Statistical validation and analysis The data collected is going to be structured so that it focuses on non‐financial indicators (enrolment for tertiary education – enrolment and graduating rates, teaching staff evolution), then on financial indicators (total expenditure on education as per cent of GDP, funding of education), and on reporting intellectual capital. Under this title the items will be grouped according to the most common reasons for reporting as identified in the specific literature – matching human capital with the labour market’ demands, the ability of higher education institutions to meet external requirements, need of transparency (use of public funds, financial decentralization, competition among universities) (Córcoles, 2012). For ensuring the accuracy of the analysis reliability and validity are going to be evaluated. Firstly, reliability is important because the results include also an error and bias. This issue has to be eliminated by test/re‐test method: test twice the elements belonging to the statistic sample so that there are two sets of values (X1 and X2); afterwards, is performed a correlation analysis between the two sets of values. Higher the correlation, then more reliable our measurement instrument is. Secondly, to ensure validity of measurement instruments and construct, this aspect has to be analyzed from several perspectives: content, convergence, divergence and nomological validity (Conways, 2012).

3.3 Results and interpretation In order to have a better understanding of the organization so that the adequate structure of the research instruments was to be determined, the study initially focused on an analysis of the Bucharest Academy of Economic Studies. Except for the pilot study, a part of the data and information was collected on‐line, from the website of the ASE (Academy of Economic Studies) as presented within the Annual Activity Reports starting 2007 until 31st of December 2011. This included the structure of revenues (both from the public budget and private sources, research activities, donations or sponsorship, etc.) and expenditures of the institution (capital expenditures, investments, personnel, credit lines, etc.), separated according to the most important categories for a public higher education organization. The purpose of this information is two‐fold; first, there must be a thorough understanding of the manner in which the institution has directed its financial resources in order to have a basic understanding of its current priorities. Second, it should be noted that the manner in which the current accounting system is structured is biased towards tangible assets; as such it can be difficult to observe the annual financial data connected with Intellectual Capital and its components. From here it is simple to see that the revenues as well as the expenses have been relatively stable for the last 5 years. It is fairly noticeable that the revenues and the expenses took a dip in 2009. However, this can easily be explained due to the fact that 2009 was the year when a series of projects were completed. Table 2 Distribution of revenues 2007‐2011 (thousand RON)

2007

2008

2009

2010

2011

Total Revenues

203,946 256,027 208,758 185,313

186,848

Operational Revenues

122,144 131,629 132,424 124,075

111,692

Other Revenues

59,696

31,569

21,789

Total Expenses

183,354 252,234 199,258 186,477

190,917

Operational Expenses

121,670 150,398 148,115 133,791

110,494

Source: Adapted from ASE Annual Activity Report 2011

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46,347

Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă

Figure 2: Evolution of revenues (2007‐2011). Source: Adapted from ASE Annual Activity Report 2011, [online], http://www.ase.ro/ase/management/pdf/Planuri_rapoarte/2011_an/raport%20BVC.pdf The main reason to include these aspects is to show that financial data as reported so far in the financial statements is insufficient, especially for the present interest of different stakeholders in more then figures. An interpretation of the economic, budgetary and financial results could make a difference, especially combined with an analysis of the role of the elements intellectual capital that makes a difference for a university. Though over 80% of the total respondents of the pilot survey – students were against including financial data in a periodical intellectual report, there are strong demands coming from other type of stakeholders (teaching and administrative staff, business sector, etc.) transforming this in a must.

4. Conclusions and recommendations Integrating intellectual capital in higher education is a key element for increasing the performance level, transparency and accountability of the institutions towards the beneficiaries, students, MA and PhD students, and their academic and administrative staff. This would also impact the medium and long run evolution of the educational institutions; reporting, evaluating and disclosing intellectual capital represents reporting, evaluating and disclosing valuable knowledge and intellectual assets. Hence, it influences the performance of the universities. In Romania, the number of articles and studies focusing on intellectual capital is constantly increasing, underlying the interest of the scientific community for this topic. Also the existence of the Executive Unit for Financing Higher Education, Research Development and Innovation contributes to this change, many initiatives on intellectual capital reporting, evaluation and reporting, are financed through European funds. The results are even more important as they build up on the achievement of the objectives settled in the Treaty of Lisbon. However, the past of higher education in Romania and the lack of coherent measures and strategies related to intellectual capital, keep our educational system behind other European countries where there are already implemented the instruments, reporting and evaluating methodologies tailored according to the characteristics of the national education, as well as disclosing the findings. The current study is still in its pilot phase; this is because the available data is incomplete due to accounting regulations, the annual report for 2012 are not yet available, furthermore this data needs to be contrasted with data from other similar institutions in order to see how they fit together. Due to the high volatility of the current economic conditions adequate data is required before being able to move forward with a more in‐ depth questionnaire.

References Bucharest Academy of Economic Studies, Annual Activity Report 2011, [online], http://www.ase.ro/ase/management/pdf/Planuri_rapoarte/2011_an/raport%20BVC.pdf Chaminade, C., Catasús, B. (2007). Intellectual Capital Revisited: Paradoxes in the Knowledge Intensive Organization, UK:Edward Elgar Publishing Limited Conways, A. (2012). ‘Statistics One’, ‘Descriptive statistics. Measurement’, course syllabus, [online], https://www.coursera.org/course/stats1

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Marta‐Christina Suciu, Luciana Picioruş and Cosmin Ionuț Imbrişcă Curaj, A. (2012). ‘Introductory session’, presentation delivered at the Mutual Learning Workshop. Intellectual Capital Reporting – International Practice. Universities, Regions, Nations, 24th‐26th October 2012, [online], http://aer.forhe.ro/sites/default/files/context_‐_presentation_adrian_curaj.pdf Curaj, A., Scott, P., Vlasceanu, L., Wilson, L. (2010). European Higher Education at the Crossroads. Between the Bologna Process and National Reforms, Springer, Dordrecht, pp.995‐996 Encourage corporate measuring and reporting on research and other forms of intellectual capital. RICARDIS: Reporting Intellectual Capital to Augment Research, Development and Innovation in SMEs. Report to the Commission of the High Level Expert Group on RICARDIS (2006), [online], http://ec.europa.eu/invest‐in‐ research/pdf/download_en/2006‐2977_web1.pdf European Commission, Investing in European Research, Encourage corporate measuring and reporting on research and other forms of intellectual capital. RICARDIS: Reporting Intellectual Capital to Augment Research, Development and Innovation in SMEs, [online], http://ec.europa.eu/invest‐in‐research/pdf/download_en/2006‐2977_web1.pdf European Commission, Research and Innovation, MERITUM ‐ Intellectual capital guidelines for firms, [online], http://ec.europa.eu/research/social‐sciences/projects/073_en.html Executive Unit for Financing Higher Education, Research Development and Innovation, ‘Higher Education Funding’, [online], http://uefiscdi.gov.ro/Public/cat/569/Finantarea‐Invatamantului‐Superior.html Fazlagic, A. (2005). “Measuring the intellectual capital of a university”, Proceedings of the Conference on Trends in the management of human resources in higher education, OECD, [online], http://www.oecd.org/edu/imhe/35322785.pdf Government Decision no. 474/2007 concerning the approval of the National Plan for Research and Development and Innovation II, for the period 2007‐2013, [online], http://www.microsoft.com/isapi/redir.dll?prd=ie&ar=windows Leitner, K. H. (2002). ‘Intellectual Capital Reporting for Universities: Conceptual background and application within the reorganisation of Austrian universities’, Paper prepared for the Conference ”The Transparent Enterprise. The Value of Intangibles.”, Autonomous University of Madrid, Ministry of Economy, November 25‐26, 2002, Madrid, Spain, [online], http://systemforschung.arcs.ac.at/Publikationen/11.pdf rd Levy, P. S., & Lemeshow, S. (1999). ‘Sampling of populations: Methods and applications’, (3 edition), John Wiley and Sons, USA. MERITUM Project, “Guidelines for Managing and Reporting on Intangibles (Intellectual Capital Report)”, [online], http://www.pnbukh.com/files/pdf_filer/MERITUM_Guidelines.pdf OEU – Observatory of the European University (2006). ‘Methodological guide, Observatory of the European University’, PRIME Project, [online], http://www.prime‐noe.org. Ramirez Córcoles, Y. (2012). ‘Towards Improved Information Disclosure on Intellectual Capital in Spanish Universities’, Global Journal of Human Social Science, Volume 12, Issue 5, Version 1.0, March 2012, [online], https://globaljournals.org/GJHSS_Volume12/1‐Towards‐Improved‐Information.pdf Sánchez, M. P., Elena, S., Castrillo, R. (2009). Intellectual capital dynamics in universities: a reporting model, Journal of Intellectual Capital, Vol. 10 Iss.: 2, pp.307 – 324 Suciu, M., Picioruş, L., Imbrişcă, C., Bratescu, A. (2011) Intellectual Capital and the Romanian Education System, Proceedings of the 3rd European Conference on Intellectual Capital (ECIC 2011), University of Nicosia, Cyprus, 18‐19 April 2011 The Quality and Leadership for the Romanian Higher Education Project, 2008‐2011, [online], http://www.edu2025.ro/UserFiles/File/LivrabileR1/diagnostic_panel1.pdf Veltri,S., Bronzetti, G, Sicoli, G. (2011). Reporting Intellectual Capital in Health Care Organizations: Specifics, Lessons Learned, and Future Research Perspectives, Journal of Health Care Finance, Volume: 38, No. 2, pp. 79‐98 Yeh‐Yun Lin,C., Edvinsson‚ L. (2010). ‘National Intellectual Capital: A Comparison of 40 Countries’, Springer, USA; Abeysekera, I. (2008). Intellectual capital accounting: practices in a developing country, Routledge, USA

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Specificity of Corporate Value Creation in Different Types of Companies Grigorii Teplykh National Research University of Higher School of Economics, Perm, Russia teplykhgv@gmail.com Abstract: Intellectual capital is very heterogeneous so it’s usual practice to divide it into some groups of more similar and homogeneous intellectual assets. It’s widespread to distinguish human capital (knowledge, skills of employees etc.), structural capital (business‐processes, innovations, corporate culture etc.) and relational capital (brand, reputation, relationships with customers etc.). The literature supports the significance of intellectual capital influence on company’s value creation. Researchers find a strong dependence of corporate performance on intellectual assets in different countries and economy branches. But their findings about a character of intellectual capital transformation in corporate value are ambiguous. Importance of human, structural and relational capital and interrelationships between them vary highly across papers. It may be explained by high firm specificity of corporate value creation. It doesn’t mean impossibility of intercompany research but requires a comparability of analyzed firms. Empirical researches on the theme of intellectual capital are often limited to particular country and industry. This restriction makes investigated companies more comparable. But we suppose there is a lot of other significant aspects of firm specificity that may impact on transformation of intellectual assets into corporate value such as firm size, amount of intangible assets, total firm efficiency etc. These variables are sometimes considered as additional factors of corporate value. But we suppose these criteria may define the model of corporate value creation in principle. This study is targeted to reveal some main types of companies and investigate a specificity of corporate value creation model for each of them. We expect to discover significant differences in models mostly related to importance and significance of particular intellectual assets. This paper is empirical and quantitative. Our sample embraces about 200 large public European industrial companies from 7 countries (Denmark, Germany, Great Britain, Finland, Netherlands, Portugal and Spain) for 2005‐2009 years. The database includes: 1. Information from financial statement. The source is Amadeus database (Bureau Van Dijk). 2. A set of nonfinancial proxy indicators (quantitative and qualitative) displaying a state of human, structural and relational capital. This data has been collected from open Internet sources such as companies’ sites. Methodology of the research combines statistic methods (cluster analysis and factor analysis) and econometrics (regression analysis). Clustering distinguishes some main types of companies. Factor analysis constructs integral indices for human, structural and relational capital on the base of initial proxy set. Regression is an instrument of modeling the corporate value creation. We found significant differences between models of corporate value creation. Human, structural and relational capitals differently transform into firm value in each type of companies. Our findings have some practical implications. For example prioritizing investments in intellectual assets should take into account a firm’s specificity more deeply. This study comprises research findings from the ‘Intellectual Capital Evaluation” Project carried out within The Higher School of Economics’ 2011 Academic Fund Program. Keywords: intellectual assets, value creation, clusters

1. Empirical researches of intellectual capital Concept of intellectual capital (IC) is very popular in today's corporate management. IC is information and knowledge applied to create value (Edvinsson, Malone, 1997). IC combines a variety of new type resources that are usually not reflected in traditional financial statements. It’s recognized that in postindustrial knowledge economy, increasingly important role of corporate success is played by intellectual assets such as knowledge and experience of personnel, technology, innovations, intellectual property, relationships with the environment etc. – by the intellectual capital. Intellectual capital is very heterogeneous so it’s usual practice to divide it into some groups of more similar and homogeneous knowledge‐based assets. Most of researchers keep up tri‐partial structure of IC (Bontis et al, 2000; Dumay, 2009). It’s widespread to distinguish:

Human capital (HC) – knowledge, skills of employees etc.,

Structural capital (SC) – business‐processes, innovations, corporate culture etc.,

Relational capital (RC) – brand, reputation, relationships with customers etc.

th th IC is practice‐oriented conception, stemming from the experience of business consultants in 1980 ‐1990 (Tseng, Goo, 2005; Dumay, 2009). Practitioners are interested in effective management a new factor of corporate performance. By thinking in framework of value‐based management, it may be resumed that understanding of intellectual capital allows find new opportunities to maximize corporate value. So, the key

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Grigorii Teplykh objectives of researches on this topic should be a measurement of intellectual capital that is mostly intangible and revelation a mechanism of its impact on corporate value. For the last decade a lot of empirical researches on the theme of IC were published. Most of them may be reduced to the solution of two consecutive tasks: identification of a method of measuring IC and assess its impact on the corporate performance (Oskolkova, Teplykh, 2012). The literature supports the significance of intellectual capital influence on company’s value. Researchers find a strong dependence of corporate performance on intellectual assets in different countries and economy branches. Also they often find that HC is most important kind of IC. But on the whole their findings about a character of intellectual capital transformation in corporate value are ambiguous. Some papers reveal that in the main HC effects indirectly through other kind of IC so total influence of HC may be more or less important than SC and RC (Bontis et al, 2000; Moon, Kym, 2006; Huang, Hsueh, 2007). Other researches discover that only human capital is vital for companies and structural capital have no impact on financial performance (Shiu, 2006; Komnenic, Pokrajcic, 2012). Also, authors may reveal no strong influence of IC on corporate performance especially in the developing countries (Firer, Williams, 2003; Volkov, Garanina, 2006; Chan, 2009; Mehralian et al., 2012; Oskolkova, Teplykh, 2012). Importance of intellectual assets and interactions between them vary highly across papers. It may be explained by high firm specificity of corporate value creation.

2. Specificity of corporate value creation Every well developed company is unique and has own specificity. Tangible and intangible recourses for each company transform into products and services by own idiosyncratic manner. Practitioners are mostly interested in discovery drivers of value growth in concrete situation. Dumay notices a practical importance of understanding how IC is constructed within the company in particular organisational setting (Dumay, 2009). Well‐known knowledge‐based management systems like Balanced Scorecard are just common framework for owners and directors and need further adaptation and completion in accordance with particular organizational context. However empirical studies on the intellectual capital theme analyze a range of companies trying to identify common patterns in the impact of the IC on the financial results. Presence of differences does not mean impossibility of intercompany research but requires a comparability of analyzed firms. So it’s important to comprehend what determines a high specificity and to take it into account. There is a variety of factors which have an impact on value such country, industry, firm size, structure of ownership, corporate strategy etc. All these variables underlie specific of corporate value creation process. So, it’s necessary to take them into consideration. We discern three types of treatment with them that take place in empirical papers:

Imposing restrictions on the sample for ensure homogeneity of firms.

Consideration of these factors as control variables.

Separation of the sample into some groups and comparison of models for each one.

A simple method to ensure homogeneity of analyzed firms is imposing restrictions on variables and consequent data collection. Empirical papers on the IC topic are usually limited to particular country and industry. Researches may also investigate most successful public companies, firms of some size etc. These limitations make analyzed companies more comparable. Objective selection the criteria for restrictions is an important question. Next drawback of this approach is tied with the possible lack of a large number of comparable companies. Finally findings obtained in the course of its application are not useful for firms beyond limitations. However, some conclusions about companies' specificity could be made when comparing results obtained from studies based on different samples. Bontis et al. compare relationships of human, structural and relational capital in service and non‐service industries (Bontis et al., 2000). Some papers reveal a great difference between small and large companies in functioning of IC (St‐Pierre, Audet, 2011). A higher dependence of corporate performance on IC is found in high‐tech companies than in other industries (Tseng, Goo, 2005; Zeghal, Maaloul, 2010) and in developed countries than in developing ones (Volkov, Garanina, 2006).

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Grigorii Teplykh Another very popular way to consider influence of different attributes on corporate specificity is to include them in value creation model as control variables in addition to tangible and intellectual assets. Researches include such factors as market capitalization (Chen et al., 2005; Firer, Williams, 2003; Shiu, 2006; Chan, 2009), total assets (Liang et al., 2010; Orens et al., 2009; Zeghal, Maaloul, 2010), number of employee (St‐Pierre, Audet, 2011; Dıez at al., 2010), sales (Pal, Soriy, 2012), financial leverage (Chen et al., 2005; Firer, Williams, 2003; Shiu, 2006; Riahi‐Belkaoui, 2003), ownership structure (Orens et al., 2009) and many others. Including control variables in model of corporate performance is easy and convenient. But it’s fully justified if there are not relationships between them and independent factors in value creation model (tangible and intellectual assets). It’s possible that such relationships take place and these factors may affect efficiency of assets and completely change the model of corporate value creation. So, consideration of them as control variables distorts the understanding of corporate growth drivers. Third way to analyze specificity is to divide the sample of companies into some more homogeneous groups and compare models of value creation for each one. Criteria for separation should be factors that may specify relationships between tangible assets, intellectual capital and firm value. These factors may be additionally included as control variables to study nonlinearity of their influence. Third method is more flexible than the first two allowing their parallel application. It gives more comprehensive and deep knowledge about corporate success’ drivers. One important difficulty with this approach is due to the need to justify economically and/or statistically a selection of criteria for distinguishing firms. Also total sample of companies should be enough large. There are a very few empirical studies on the IC theme applying this path to account a specificity of companies. For example Youndt et al. distinguish clusters of companies according to amount of intellectual assets (Youndt et al., 2004). Cheng discerns some types of firms, varying in efficiency of IC and change of this efficiency in time (Cheng K.Y., 2004). But there is still a big gap in revelation the causes influencing a specificity of value creation in companies. Until the gap is filled, researchers will be regularly faced with great discrepancy of conclusions about relationships between intellectual assets and corporate value. This study is targeted to reveal some main types of companies and investigate a specificity of value creation for each of them. We suppose that some significant aspects of firm such as firm and activity in usage of IC may have an impact on transformation of intellectual assets into firm value. These variables are usually considered as additional factors of value but we suppose these criteria may define the model of corporate value creation in principle. We expect to discover essential differences in models mostly related to importance and significance of particular intellectual assets.

3. Database for the research A sample forming was dictated by the requirement that we tried to get a large sample of relatively comparable companies. It should be quite large firms actively employing intellectual assets. In addition, information about activity of these companies must be open. Our sample embraces large public industrial companies from 7 countries (Denmark, Germany, Great Britain, Finland, Netherlands, Portugal and Spain). All countries represent Western Europe and European Union. They have close economic ties and high mobility of resources. We chose large economies with a great number of well‐developed companies with high levels of IC. The selected countries are in the top quintile in regional ranking of Knowledge Economy Index (KEI). So we may assume relative homogeneity of selected economies. We gathered information about some hundred large manufacturing companies shares of which are traded on stock exchange. Manufacturing is the largest and most representative industry. Public nature of companies ensures availability of information about them. Firms were limited in size. Number of employees varies from 500 to 20 000. Hereby we attempt except smallest or largest companies because of high‐specific features of their activity. The analyzed period is from 2005 to 2009. This time window provides comparability of financial data that is exposed to inflation. So finally we have a panel data including 969 observations of 216 companies. The database includes:

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Information from financial statement: The source is Amadeus database (Bureau Van Dijk).

A set of nonfinancial proxy indicators (quantitative and qualitative) displaying a state of human, structural and relational capital: This data has been collected from open Internet sources such as companies’ sites, patent’s database and ratings.

4. Research methodology Methodology of the research includes statistic methods (cluster and factor analysis) and econometrics (regression analysis). At the first stage we reveal some main types of companies. We are limited in the depth of classification. So we confine ourselves to the analysis of only two important dimensions of corporate specificity:

Corporate size

Activity of intellectual capital’ involvement

These variables are sometimes considered in empirical researches as control variables like factors of corporate value in addition to tangible and intangible capital. But unlike previous papers we suppose these aspects may determine the model of corporate value creation in principle. We want to examine whether a scale effect and a law of diminishing marginal returns take place in respect to intellectual assets. It is possible that large companies with high levels of IC have fewer opportunities for further growth. On the other hand, there may be inverse relationship. Large companies have sufficient resources to make breakthrough in research process. Tseng and Goo suggest that an increasing marginal return is one of notable features of intellectual capital (Tseng and Goo, 2005). Corporate size is measured by two variables: total asset value and number of employee. Because of their significant variation we switch over to logarithms of variables. Activity of IC involvement is also measured by two indicators: intangible assets to total assets ratio and R&D expenditures to total assets ratio. We account average for the five years of these four variables for each company in order to eliminate random fluctuations in time. We carry out cluster analyses on the base of average values of variables. By the k‐means method we distinguish 4 firms’ types. Number of clusters is related with our expectation to get at least two poles in both distinguishing dimensions. Also greater number of clusters leads to relatively small quantity of companies in each of them that makes results of further analysis less reliable. Next stage of research is factor analysis. Table 1 represents the set of initial indicators for each kind of IC. By principal components analysis we construct integral indices for human, structural and relational capital on the base of initial proxy set. Factor analysis provides a transition from a large set of promiscuous proxies to a small number of more reliable underlying measures. Table 1: Proxy indicators of intellectual capital Variable name Description Type Source IC kind HC_BOARD_Q Board of directors’ qualification Ordinal Site HC HC_OWN_DIR Share of directors with ownership Numerical Statement HC HC_TC_PERS Personnel cost per employee Numerical Statement HC HC_TR_RAVE Productivity (revenue per employee) Numerical Statement HC SC_ERP Presence of ERP system Dummy Site SC SC_IA R&D costs to fixed assets Numerical Statement SC SC_PATENTS Logarithm of the number of patents Numerical QPAT SC SC_RD Intangible assets to fixed assets Numerical Statement SC SC_STRATEGY Presence of open corporate strategy Dummy Site SC RC_AGE Company age Numerical Public data RC RC_BRAND Presence of well‐known brand Dummy Global 1000 RC RC_CITATIONS Frequency of citations in Internet Ordinal Google rating RC RC_LOC_CAP Location in a capital Dummy Public data RC RC_LOC_POP Location in a millionaire city Dummy Public data RC RC_SITE Quality of corporate site Ordinal Site RC

Further, we model influence of intellectual assets on the corporate value for each cluster by the regression analysis. We use a modified Cobb‐Douglas model of next form:

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MCap = A × BV a 1 × NE a 2 × exp a 3 × HC + a 4 ×SC + a 5 × RC , that is equivalent to log(MCap) = a 0 + a1 × log(BV) + a 2 × log( NE) + a 3 × HC + a 4 × SC + a 5 × RC MCap – market capitalization BV – book value (proxy for capital) NE – number of employee (proxy for labour) HC – Human capital index SC – Structural capital index RC – Relational capital index Note, that HC, SC and RC are standardized variables because of principal components’ nature. So, we may compare an influence power of different intellectual assets just by looking at nominal value of empirical coefficients a3, a4 and a5. We do a panel least squares estimation with fixed effects for periods. We suppose that time factor is significant because two periods are related to financial crisis. But we ignore possible cross‐section effects because our sample does not allow get quality and reliable estimations of firms’ effects. At last stage of empirical research we compare obtained models. We expect to confirm hypothesis about high specificity of value creation process in different types of companies.

5. Empirical results Implementation of k‐mean’s method has given four different types of companies. Results of analysis in term of clusters’ centers are presented in table 2. Table 2: Final centers of clusters Variable Cluster 1 Cluster 2 Cluster 3 Cluster 4 Logarithm of average book value 12.935 14.361 11.595 15.469 Logarithm of average number of employee 7.885 9.097 6.748 6.945 Intangible assets to fixed assets, average ratio 0.177 0.199 0.120 0.115 R&D costs to fixed assets, average ratio 0.01047 0.00580 0.00342 0.00004 Number of companies in cluster 79 62 62 13

It’s possible to give economical interpretation to all clusters according to value of their centers. We have done this by such way:

Cluster 1 – middle‐size companies with greater involvement of IC

Cluster 2 – large‐size companies with greater involvement of IC

Cluster 3 – middle‐size companies with less involvement of IC

Cluster 4 – large‐size companies with less involvement of IC

First three clusters are comparable in number of companies but the fourth one stands out. Cluster 4 is represented only by 13 companies. It’s rare occasion when large‐size companies have low activity in involvement and management of intellectual resources. First components resulting from principal component analysis for human, structural and relational capital are represented in table 3. Note that signs of all component loadings have a clear logical explanation. First components are used as integral indices for HC, SC and RC. Table 3: Loadings of first principal components for three kind of IC HC Index SC Index RC Index Variable Loadings Variable Loadings Variable Loadings HC_BOARD_Q 0.295 SC_ERP 0.573 RC_AGE 0.187 HC_OWN_DIR 0.266 SC_IA 0.278 RC_BRAND 0.271 HC_TC_PERS 0.655 SC_PATENTS 0.533 RC_CITATIONS 0.591 HC_TR_RAVE 0.643 SC_RD 0.440 RC_LOC_CAP 0.308 SC_STRATEGY 0.342 RC_LOC_POP 0.401 RC_SITE 0.536

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Grigorii Teplykh Table 4 represents outcomes of regression analysis for all companies in whole and for each cluster separately. We analyze a logarithmic form of Cobb‐Douglas model so the dependent variable in regression equations is log of market capitalization. Table 4: Regression models of value creation Variable All companies Cluster 1 Cluster 2 Cluster 3 Cluster 4 C 1.683 *** 2.122 * 5.053 *** 3.705 *** 6.173 *** Log(BV) 0.770 *** 0.670 *** 0.833 *** 0.863 *** 0.629 *** Log(NE) 0.083 * 0.195 * ‐0.351 *** ‐0.393 *** ‐0.293 HC Index 0.276 *** 0.238 *** ‐0.036 0.427 *** 0.761 *** SC Index 0.097 *** 0.102 *** 0.032 0.027 0.989 *** RC Index 0.099 *** 0.122 *** 0.105 ** 0.217 *** ‐0.348 *** Cross‐sections included 216 79 62 62 13 Total panel observations 969 364 280 266 59 Adjusted R‐squared 68.05% 37.89% 39.33% 38.21% 63.96%

Symbols *, **, *** denote significance by t‐statistics at the 10, 5, 1% percents accordingly. According to the general model for all companies, corporate value is directly and positively depends on labor and capital, level of HC, SC and RC. The value noticeably more dependent on attracted capital than on labor. The most powerful kind of IC is human capital. Analysis in the section of individual clusters shows high specificity of the value creation process for various types of companies. Model for first cluster is close to the general model for all companies. The value of medium‐sized companies with a high level of involvement of the IC directly and significantly depends on labor, capital and quality of the human, structural and relational capital. Value of firms from second cluster significantly and negatively depends on number of employees and has non‐ significant relationships with quality of HC and SC. We can assume that here a law of diminishing marginal returns takes place. Large companies that actively use intellectual assets are near to maximal efficiency of HC and SC, so appropriate coefficients are close to zero. However, such firms have a potential to increase value through development of RC. Corporate value of companies from third cluster has significant negative relationship with number of employees and non‐significant link with SC. Medium‐sized companies with lower stock of IC could be close to maximally efficient management of SC. So, a marginal effect of this kind of IC is low. These firms however can increase their value through development of HC and RC. The model for fourth cluster is the most outstanding. Value of firms is positively associated with HC and SC and negatively linked with RC. All coefficients for IC are the largest compared to other clusters. So, fourth cluster is most sensitive to IC. We give a next interpretation of the model. Large companies with low level of IC have the huge potential to engage knowledge‐based resources, but do not use their capabilities. Therefore, the marginal effects for IC are particularly high. These effects are positive for HC and SC. Negative effect of RC may be explained by inefficient management. Note, however, that these outcomes are not reliable enough because of small cluster’s size. In general, we found some evidences of the law of diminishing returns with regard to IC. However, this dependence is not so univocal. Marginal effect of SC is larger for cluster №1 than for №3. We note that activity in IC distinguishing clusters is measured in variables, which are also considered in a level of SC. So, medium‐ sized companies that use structural capital less actively have no significant incentive to develop it. But a significant increase in a stock of structural capital may transfer company to another cluster and makes improvement of SC more gainful. So there could be a well complicated nonlinearity in the relationships between IC and corporate value. At last, we refer to goodness of a models’ fit. Regression equation for all companies has a higher explanatory power than equations for separate clusters, excluding fourth one. This can be explained by large between‐

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Grigorii Teplykh group variation of the data. Models obtained for each cluster should be applied only if the company does not go beyond the cluster. With strong changes that may lead to the withdrawal out of the cluster, it is more correct to use the common model. Herewith significant efforts of firms to develop will give more predictable effect in change of their market value.

6. Conclusion Empirical researches find a significant influence of intellectual capital on corporate value. However their findings about relationships between human, structural and relational capital and value are very dissimilar. We explain that fact by high firm specificity of corporate value creation. We suppose various factors may determine firm specificity that means unique scheme of assets’ transformation into corporate value. In this study we investigate influence of firm size and activity in involvement of intellectual assets. Our study is one of first empirical work on the theme that directly identifies and endeavors to solve the problem of corporate specificity in value creation. We analyzed large public companies from manufacturing sector in European Union. Four clusters of companies were distinguished. We revealed significant differences in the models of corporate value creation. Human, structural and relational capitals transform into value in each type of companies by different ways. We found some evidences of the law of diminishing returns with respect to IC. Larger and more active in involvement of IC firms have less marginal effect of intellectual assets on their value. However there may be much more complicated links between IC and corporate value. We hope that our work will stimulate researchers to analyze models of corporate value creation more carefully. They should consider different factors of corporate specificity which may significantly distort results of their empirical studies. Also our findings have some practical implications. Prioritizing investments in intellectual assets of concrete company should take into account factors that may affect its specificity such as size and activity of intellectual capital usage.

Acknowledgements This study comprises research findings from the ‘Intellectual Capital Evaluation” Project carried out within The Higher School of Economics’ 2011 Academic Fund Program.

References Bontis, N., Keow, W.C.C. and Richardson, S. (2000) “Intellectual Capital and Business Performance in Malaysian Industries”, Journal of intellectual Capital, 2000, Vol 1, No. 1, pp 85‐100. Chan, K.H. (2009) “Impact of Intellectual Capital on Organisational Performance. An Empirical Study of Companies in the Hang Seng Index (Part 1)”, The Learning Organisation, №16 (1), pp 4‐21. Chen, M.‐C., Cheng, S.‐J. and Hwang, Y. (2005). “An empirical investigation of the relationship between intellectual capital and firms’ market value and financial performance”, Journal of Intellectual Capital, No. 6, Iss: 2, pp 159‐176. Cheng K.Y. (2004) Intellectual Capital and Firm Performance of IC Design Companies in Taiwan, Master's Thesis, National Cheng Kung University, Institute of Business Administration. Diez, J.M., Ochoa, M.L., Prieto, M.B. and Santidrian, A. (2010) “Intellectual capital and value creation in Spanish firms”, Journal of Intellectual Capital, Vol 11. No. 3, pp 348‐367. Dumay J.C. (2009) “Intellectual capital measurement: a critical approach”. Journal of Intellectual Capital, Vol 10, No. 2, pp 190‐210. Edvinsson, L. and Malone, M. (1997) Intellectual Capital: Realising Your Company’s True Value by Finding its Hidden Brainpower, Harper Collins, New York, NY. Firer, S. and Williams, S.M. (2003). “Intellectual capital and traditional measures of corporate performance”, Journal of Intellectual Capital, Vol 4. No. 3, pp 348‐ 360. Huang, C‐F. and Hsueh, S‐L. (2007) “A Study on the Relationship between Intellectual Capital and Business Performance in the Engineering Consulting Industry: A Path Analysis”, Journal of Civil Engineering and Management, Vol XIII, No. 4, pp 265–271. Komnenic, B. and Pokrajcic, D. (2012) “Intellectual capital and corporate performance of MNCs in Serbia”, Journal of Intellectual Capital, Vol 13. Iss: 1. pp 106‐119. Laing, G., Dunn, J. and Hughes‐Lucas, S. (2010) “Applying the VAIC model to Australian hotels”, Journal of Intellectual Capital, Vol 11, No. 3, pp 269‐283. Mehralian, G., Rajabzadeh, A., Sadeh, M.R. and Rasekh, H.R. (2012) “Intellectual capital and corporate performance in Iranian pharmaceutical industry”, Journal of Intellectual Capital, Vol 13, Iss: 1, pp 138‐158.

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Grigorii Teplykh Moon, Y.J. and Kym, H.G. (2006) “A Model for the Value of Intellectual Capital”, Canadian Journal of Administrative Sciences, Vol 23, No. 3, pp 253‐269. Orens, R., Aerts, W. and Lybaert, N. (2009) “Intellectual capital disclosure, cost of finance and firm value”, Management Decision, Vol 47, No. 10, pp 1536‐1554. Oskolkova, M.A. and Teplykh, G.V. (2012) “Intellectual capital performance evaluation: a review of empirical research”, Financial analytics: problems and solutions, No. 24, pp 41‐49. Pal, K. and Soriya, S. (2012) “Emerald Article: IC performance of Indian pharmaceutical and textile industry”, Journal of Intellectual Capital, Vol 13, Iss: 1, pp 120‐137. Riahi‐Belkaoui, A. (2003) “Intellectual capital and firm performance of US multinational firms: a study of the resource‐ based and stakeholder views”, Journal of Intellectual Capital, Vol 4, No. 2, pp 215‐226. Shiu, H.J. (2006) “The Application of the Value Added Intellectual Coefficient to Measure Corporate Performance: Evidence from Technological Firms”, International Journal of Management, Vol 23, No. 2. Shiu, H.‐J. (2006) “The Application of the Value Added Intellectual Coefficient to Measure Corporate Performance: Evidence from Technological Firms”, International Journal of Management, Vol 23, No. 2, pp 356‐365. St‐Pierre, J. and Audet, J. (2011) “Intangible assets and performance: Analysis on manufacturing SMEs”, Journal of Intellectual Capital, Vol 12, Iss: 2, pp 202‐223. Youndt, M.A., Subramaniam, M. and Snell, S.A. (2004) “Intellectual capital profiles: an examination of investments and returns”, Journal of Management Studies, Vol 41, No. 2, pp 335‐361. Tseng, C.‐Y. and Goo, Y.‐J.J. (2005) “Intellectual capital and corporate value in an emerging economy: empirical study of Taiwanese manufacturers”, R&D Management, Vol 35, No. 2, pp 187‐199. Volkov, D.L. and Garanina, T.A. (2006) “Evaluation of Russian companies intellectual capital”, Scientific reports, № 22(R)– 2006, NRI of management SPbSU. Saint Petersburg. Zeghal, D. and Maaloul, A. (2010) “Analysing value added as an indicator of intellectual capital and its consequences on company performance”, Journal of Intellectual Capital, Vol 11. No. 1, pp 39‐60.

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Millionaires and Intellectual Capital: An Empirical Study Eduardo Tomé1, Luliia Naidenova2 and Marina Oskolkova3 1 Department of Economics, Centro Lusíada de Engenharia e Gestão Industrial (CLEGI), Universidade Lusiada de Famalicão, Portugal 2 Laboratory of Investment Analysis and Department of Financial management, Faculty of Economics, Higher School of Economics University, Perm, Russia 3 Department of Financial Management, Faculty of Economics, Higher School of Economics University, Perm, Russia eduardo.tome@clix.pt oskolkovama@gmail.com naidenovayn@gmail.com Abstract: In this paper we present an application of the model of Intellectual Capital to the world of the very rich and millionaires. It Is, we believe an important research topic, because in the last decade inequality grew, and Intellectual Capital became the most important economic asset. But no empirical studies exist to link the two phenomena. We applied our model to a set of football coaches, football being an industry that produces outlying incomes. We estimated the relation between a set of intellectual capital characteristics of those coaches and their incomes. We found that indeed, IC explains almost two thirds (63%) of the evolution of the very big salaries of those very rich people. Even if those results are interesting, and give an indication of the influence of IC in the success of rich people, they are only limited to a small sample of persons. Anyway, from our research we may infer that IC (social capital, human capital, and structural capital) plays a major role in defining the wealth of the top earners in the world. From this we may conclude that a policy of inequality reduction should take into account that intangible assets are at the base of those persons wealth. The study is original, because at least for our knowledge, It is the first in which the relation between IC and the wealth of millionaires has been tested. We hope to enlarge the study in the future in order to include the phenomenon of billionaires, as well. Keywords: millionaires, intellectual capital, impact, empirical study

1. Introduction In 2012, few would doubt about the socio‐economic importance of Intellectual Capital (IC): It is well known that IC is extremely important in the success of organizations (Stewart, 1997); there is also evidence that countries with higher levels of IC constituents are more developed (Bonfour and Edvinsson, 2005); poverty may also be explained by the lack of IC (Sachs, 2006; Tomé, 2004). However, we do not know about any empirical work made on the impact of IC on millionaires. What is the influence of IC in the existence of very rich people? It is the gap we will try to begin to fill in this paper. While there are a wide range of industries that could be analyzed in the world, we have chosen a small set of very well know people: football coaches. Indeed there is plenty research of football clubs, their performance and incomes (Barajas, Rodriguez, 2010; Szymanski, 2001). Others studies investigate intellectual capital of football clubs (Shareef, Davey, 2005). But there is a lack of researches that combine the IC and ability to become a millionaire trough football. And we all know that football coaches, not to name football players are very wealthy people. Therefore our research aims at investigating the dependency between income and some special kind of intellectual capital (that usually may be called "talent") of top football coaches that helped them to become famous and highly paid people. Because we cannot measure this talent directly, we use proxies of different kinds of intellectual capital: such as change in championships ranking, image in media, licenses, awards in World Cup and Euro Championship (performance of the club during the leadership dealt with the coach) to explain the evolution of the coaches’ salaries. The results are interesting and impressive. The paper is divided in three parts. In the first part we define the main concepts (IC, millionaires, and billionaires) and we expose briefly the main economic theories on those concepts an on their relation; we also describe some studies we know that are somehow related to our demarche and that helped us defining our model. In the second part we use regression analysis to assess the relationships among intellectual capital and income of football coaches. In the third part we present our conclusion, discuss the limitations of the study, propose policy guidelines and suggest further studies.

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2. Concepts, theories, related studies 2.1 Concepts Intellectual Capital (IC) is defined as a multidimensional concept with roots in accountancy theory and that encompasses Human Capital (competences), Social Capital (brands) and Structural Capital (routines) (Edvinsson and Malone, 1997). IC is strongly related with Knowledge, even if it defers from it. Knowledge is “understood information” (Maurer, 1998) and a Knowledge worker or a Knowledge company are the ones who possess intensively Knowledge (Nonaka and Takeuchi, 1995). Knowledge is in general analyzed in a management perspective, the Cycle of Knowledge transformation (Nonaka and Takeuchi, 1995) and the creation and renewal of Knowledge (Kianto, 2007) being two fundamental parts of that analysis. Knowledge Management (KM) is the activity and science of managing knowledge. Interestingly though IC analysis has its roots on accounting problems and KM analysis has its roots on management problems. A millionaire is someone whose wealth is of more than 1 million dollars per year. A billionaire would someone who has a wealth of more than one thousand million dollars per year. As we will see in the next section, millionaires and billionaires are explained by the economic theory.

2.2 Theories The existence of very rich people may be explained by several factors (Tomé, 2012). Those factors relate to microeconomics or to macroeconomics. In relation to microeconomics, the type of market (Frank, 2005), the political power (BBC, 2011), crime activities (Barry, 200, Le Grand and al, 2008), the perceived uniqueness linked to brands and marketing (Goal, 2012), technology (Rosen 1981), globalization (Community Banker) and luck (Daily Mirror, 2012) are all characteristics of market or of economic agents that may favor the existence of billionaires or millionaires. In relation to macroeconomics, we know that different ideologies, view the phenomenon of the very rich very differently: from encouraging Liberalism (Smith, 1977, Mill, 1848 Marshall, 1890) to forbidding Socialsm (Marx, 2008) passing by understandable Conservadorism (Pope Leo XIII, 1891) and taxing Social Democracy (Keynes, 1936). We also should add that Intellectual Capital explains the wealth and prosperity of people and organizations. In the case of people wealth accumulation may be related to Human Capital and Social Capital. People with more education, experience or a special talent – all forms of Human Capital – may become millionaires or billionaires by accumulation of wages and other forms of income. But, also, in the business world contacts matter, and the image the individual has or its image as a brand may and can increase decisively the income he receives. A high income may of course be translated in millionaire or billionaire wealth. In the case of organizations IC may influence the stock market, by increasing the market value of companies. Indeed the most basic definition of IC is to compare it with the difference between market value (defined as shares) and book value (defined as assets minus liabilities) (Edvinsson and Malone, 1997). But IC can also increase the value of company because it increases the organizational knowledge, which in turn increase the value of companies regardless of them having shares of know (Bontis, 1999, Youndt and Scott, 2004). Tome (2012) concluded that, on one hand, billionaires owe their fortunes to the fact that they use the knowledge and IC of others because they own companies like Microsoft, WallMart, HLMV, Google, or Facebook. But, on the other hand, megastars or millionaires have smaller fortunes than billionaires and derive their wealth from the global exploitation of some specific skill in the domains of music, sport, or literature. Finally, both kinds of persons are helped by the existence of mechanisms of knowledge sharing, creation, storage and transfer that are characteristic of the Information Age and Knowledge Era. Therefore, the next years will probably witness an increase the millionaires and billionaires phenomenon (Commmunity Banker, 2008).

2.3 Related studies However, very few empirical studies have been made on the relation between intangibles and rich people, especially in football sphere. Most of the analysis on rich people relate to definition of the volume of wealth of those individuals in ranking (Forbes, 2012). Those rankings are accompanied with a brief corporate analysis of the billionaires’ companies and main investment interests; in fact what is done is a business description in

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova the name of several dozens of extremely wealthy individuals. One of the interesting phenomena about those billionaires is that sometimes they even don’t know how much they are worth, as Atkinson described in an old book – “if they were to be giants, their high would be in the clouds and they would not know their precise dimension themselves” (Atkinson, 1984). Some much bigger rich lists (Sunday Times, 2012) also describe the wealth of millionaires, like sport celebrities, and musicians etc. In both those types of analysis elements of IC are mentioned, but not scientifically. While intellectual capital and wealth have become favorite and popular topics of discussion, their interdependence in case of individuals is still an unexplored question. After the literature review we found out that there are plenty researches about the influence of football clubs performance on their incomes. Thus, the paper of Barajas and Rodriguez in International Journal of Sport Finance describes a study of salaries in Spanish football clubs in crises (Barajas, Rodriguez, 2010), while Szymanski dedicated his paper to income inequality of team sports, in particular football (Szymanski, 2001). However, all those papers remain unclear on whether the players’ and coaches’ intellectual capital influence club incomes or if we can explain those incomes using only some tangible factors. One of the reasons because a study on intangibles in difficult to make on football, it is because we have to take into consideration the football clubs, the people wealth (generically ignored) and the intellectual capital (which is also difficult to define). Although there are a lot of papers dedicated to intellectual capital of countries and companies, intellectual capital of football clubs rarely becomes the object of study. We would like to underline the paper of Shareef and Davey that discusses the IC disclosure by football clubs (Shareef, Davey, 2005). Also, Gurel and Ekmekci measure the IC of Turkish football clubs as a whole, regarding football club as a company. But there is the absence of researches connected with intellectual capital of key football club stakeholders. Nobody tried to decompose, classify and measure the individual intellectual capital of players or coaches. However, given the nature of high salaries that are paid in football, the investigation of the connection between special intellectual capital component such as talent and the wealth of football coaches becomes to be an extremely important and practice‐oriented task.

2.4 Justification The literature review just presented gave us the understanding that we know no micro‐econometric study relating IC with the wealth of billionaires or millionaires. The omission is almost intriguing because it is very well known that the elements that constitute IC and knowledge are decisive to the efficiency of the companies that the billionaires possess; and also, as we already said, it is known that specific IC is the root of the wealth of millionaires. In our opinion the omission might be explained by three main reasons. First, it is very difficult to find reliable data on billionaires and millionaires. Second, the phenomenon of IC and billionaires is recent. Studies on IC and knowledge are usually made with the support of entities (private or public); but regarding billionaires no company would command the study, and even in the academic world it would seem to be the work of outsiders; only if Forbes Magazine would decide to fund the study, it would be made. In fact, the study of the wealth of millionaires and billionaires would be an inquiry at the heart of the winning capitalism of the st global 21 century. And as all the studies that are socially challenging, in any epoch, is hard to do. However given the actual economic trends: globalization, dominance of the economy by knowledge driven services, networks and social networks, BRICs, the study has all the logic. So we decided to make a first step in the correct direction.

3. Variables and model 3.1 Modeling IC and wealth The analysis of existent theoretical and empirical studies dedicated to wealth, intellectual capital and sport economics allows us to determine the unexplored area. Therefore the main purpose of this paper is to determine how the talent of football coaches’ (which we consider an intangible asset and a proxy of the coaches’ intellectual capital) is transformed into wealth. According to the purpose of the research we want to test the following hypothesis: Is the talent of football coaches transformed into wealth? For the measure of wealth we use the annual salary, measured in millions of euro.

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova On IC, all the existent definitions and decompositions underline its heterogeneity in one hand, and the lack of a generally accepted measurement method in the other hand. Accordingly, the type of individual intellectual capital named “talent” also cannot be measured primarily by generally accepted integral indicator. So its quantity and quality can be expressed only by approximate indicators. In our study, the choice of indicators was based on the review of sport cites, expert interviews and the review of empirical studies dedicated to financing of football clubs (e.g. Barajas, Rodriguez, 2010). After, all the selected variables were divided into proxy indicators of coach’ talent and control variables. Next we excluded those proxies that couldn’t be found in publicly available sources. Table 1 includes the final set of proxies we end up using. Table 1: Chosen indicators determining the wealth of football coach Proxy indicators of talent Difference of team places in national league during the year Leading places in national championships during the year Image in media

Control variables Wins in championships in previous years Former football player Played for the same team Age Place of birth Team players’ quality

3.2 Chosen indicators The chosen indicators are described in more detail below. Proxy variables:

Difference of team places in national league during the year. If coach has talent, his team will succeed in different championships during the period of his working. We could take into account national league or different international championships such as the UEFA cup, the Europa League, etc. But we have set of reasons to exclude them:

First of all we wanted to create a homogeneous sample, so we took the same number of clubs in each country. As for international championships, counties have different quotas, so the number of chosen clubs could differ from country to country and we couldn’t took great number of clubs from the same country.

Secondly, international ratings, such as UEFA ranking, include club results for the previous years (for example, UEFA includes results for the previous five year and 20% of country coefficient). It means that a current low international rating may be the result of previous coach work. But national league represent results of only one year.

Another one reason is for some clubs the national championships is more important than international competitions. Some English and Spanish clubs use the reserve team for international games in order to save the energy of first team for national cups.

International cups have fewer games during the year in comparison with national ones. So the coach’ talent can be better seen in national league results.

In order to use the variable in regression, we have made a dummy variable with the meaning “1” if club place became higher after the year of coach work and the meaning “0” otherwise.

Leading places in national championships during the year. The reasons to take into account national league were described below. We created dummy variable that equals “1” if the team took places from first to third and equals “0” otherwise.

Image in media. Talented coaches are famous and charismatic persons that are often discussed in media resources by pundits and fans. We took into account the recognition of their professional football and management skills (measured by the number and quality of trophies won in his career), the fans opinion, the presence of club scandals, rumors and image as a whole. So we measured the frequency of coach name mention in media and give the value from “1” to “10” for each coach. “1” means that coach is unpopular in media sphere while “10” indicates his extreme popularity. Then we transformed these categorical variables into a dummy variable: if the value of image exceeds the median value then dummy variable has value “1”, otherwise it has value “0”.

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova Control variables:

Wins in championships in previous years. The current big salary of a coach may be determined by his success in previous years. But that result depended on a big variety of factors, not only on talent. That is why we should exclude previous results. We created a dummy variable that equals “1” if the coach won any championships and equals “0” otherwise.

Former football player. The talent of a football coach doesn’t depend on the fact that he was a professional player earlier (the most striking example is José Mourinho, who is one of the best and high‐ paid coaches). But if the coach was the high‐paid player, he has a positive image in football sphere, and he may expect a higher starting salary. We used a dummy variable that equals “1” if the coach was a professional player in the past and equals “0” otherwise.

Played for the same team. The reputation and image of a football player can increase his future salary as a coach in the same club. But, if the player became a coach and was demanded outside his team, this fact also shows his quality. So this factor can influence the salary but not necessarily connected with talent. We created dummy variable that equals “1” if the coach played for the same team during his career as a player and equals “0” otherwise.

Age. Age has strong correlation with experience and therefore influences the salary positively.

Place of birth. The place of birth to some extent determines education, culture and therefore the ability to earn money.

Team players’ quality. This It is the main control variable because the team results that we used as a proxy for coaches’ talent depended also on the players of the team. The proxy of players quality is their value on the transfer market. So we have measured the mean value of players transfer costs. We

3.3 Sample and data The hypothesis was analyzed on the sample of European top clubs. We have selected clubs that meet the following requirements:

The clubs operate in Russia, England, Germany, Spain, Italy, France. The choice of countries was based on football development and popularity.

The clubs achieved places in national championships from the 1st to the 10th. This choice was made in order to analyze the most talented coaches.

The date relate to 2011, because of data availability.

The final sample that met all requirements consists of 60 coaches. We used information from official clubs websites and the following websites: http://www.uefa.com/, http://www.fifa.com/, http://www.francefootball.fr, http://www.guardian.co.uk/, htt p://www.gazzetta.it/, http://www.kicker.de/,. For transfer cost We used the data from www.transfermarkt.de website.

3.4 Specification Thus, our model has the following specification: SALARY = c + α1∙PLACE + α2∙IMAGE+ α2∙DOWN + α3∙UP +β1∙PLAYERS + β2∙ AGE + β3∙BIRTH + β4∙FPLAYER + β5∙SAMETEAM + β6∙WINS + ∑ γi∙Di where SALARY is coach’s salary in 2011 year, million euros; PLACE equals 1 if the club has one of 3 top places in national league in 2010/11 season and 0 otherwise; IMAGE equals 1 if the coach is popular in media and 0 otherwise; DOWN equals 1 if the club’s position in national league lowered and 0 otherwise; UP equals 1 if the club’s position in national league improved and 0 otherwise; PLAYERS represents the average value of the club’s players, million euros; AGE is the coach’s age;

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova BIRTH equals 1 if the coach was born in one of 6 countries with the highest UEFA country coefficient rankings and 0 otherwise; FPLAYER equals 1 if the coach was a professional football player and 0 otherwise; SAMETEAM equals 1 if the coach played for this club when he was a football player and 0 otherwise; WINS equals 1 if the coach has won national championship ever before and 0 otherwise; Di dummy variables for countries where the clubs plays.

4. Results 4.1 Descriptive statistics In Table 2 we present the descriptive statistics for chosen indicators. They show that in 2011 the considered top coaches received a salary from 0.4 to 14.8 million euros. On average, the top coaches were 50 years old and in received 3 million euros. Most football top coaches were born in European countries with high UEFA country coefficient rankings, had been football players and had the experience of winning the championships. Only a quarter of coaches worked with a team in which they played in the past, but almost all (93%) had been professional footballers. One third of the coaches had a good media image. As far as we consider the clubs in which the top coaches worked, 27% of them had one of 3 top places in national championship in 2011 year. You can also see that the championship 2011/12 season was competitive for the clubs and only 11% of the teams have not changed their positions. The number of teams in the championship table rose approximately equal to the number of teams that worsened their position. The average value of the players varies considerably. On the one hand it shows how different the potential of the clubs is (regardless of coach’s talent), and on the other hand it evidences about diverse financial capacities of considered clubs. Table 2: Descriptive statistics for variables used in the model Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

SALARY (a) 2.97 2.10 14.80 0.40 2.81 2.53 9.85

Mean Median Maximum Minimum Std. Dev. Skewness Kurtosis

IMAGE (c) 0.32 0.00 1.00 0.00 0.47 0.79 1.62

AGE (b) 50.67 49.00 70.00 39.00 7.82 0.63 2.53

BIRTH(c) 0.77 1.00 1.00 0.00 0.43 ‐1.26 2.59

PLACE (c) 0.27 0.00 1.00 0.00 0.45 1.06 2.11

DOWN (c) 0.42 0.00 1.00 0.00 0.50 0.34 1.11

WINS (c) 0.42 0.00 1.00 0.00 0.50 0.34 1.11

UP (c) 0.47 0.00 1.00 0.00 0.50 0.13 1.02

SAMETEAM(c) 0.25 0.00 1.00 0.00 0.44 1.15 2.33

FPLAYER (c) 0.93 1.00 1.00 0.00 0.25 ‐3.47 13.07

PLAYERS (a) 5.59 3.64 26.04 0.40 5.43 2.23 7.93

Note: (a) in million euros. (b) in years (c) dummy variable

4.2 Correlation and regression Correlation analysis (Table 3) shows that there is no high correlation between independent variables (all coefficients are lower than 0.6), therefore they all could be included into the model.

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova Table 3: Correlation analysis of variables SALARY PLAYERS PLACE IMAGE AGE BIRTH DOWN FPLAYER SAMETEAM UP WINS SALARY PLAYERS PLACE1011 IMAGE AGE BIRTH DOWN FPLAYER SAMETEAM UP WINS

AGE 0.21 0.13 0.08 0.03 1.00 ‐0.05 ‐0.12 ‐0.06 ‐0.41 0.20 0.22

SALARY 1.00 0.75 0.28 0.59 0.21 0.02 ‐0.23 ‐0.35 ‐0.07 0.28 0.46 BIRTH 0.02 0.05 0.07 0.04 ‐0.05 1.00 ‐0.01 0.17 0.05 ‐0.12 0.07

PLAYERS 0.75 1.00 0.59 0.59 0.13 0.05 ‐0.03 ‐0.26 0.00 0.03 0.51

DOWN ‐0.23 ‐0.03 0.18 ‐0.21 ‐0.12 ‐0.01 1.00 ‐0.05 0.21 ‐0.79 ‐0.03

FPLAYER ‐0.35 ‐0.26 ‐0.14 ‐0.25 ‐0.06 0.17 ‐0.05 1.00 0.15 ‐0.02 ‐0.32

PLACE 0.28 0.59 1.00 0.32 0.08 0.07 0.18 ‐0.14 ‐0.09 ‐0.26 0.48 SAMETEAM ‐0.07 0.00 ‐0.09 0.10 ‐0.41 0.05 0.21 0.15 1.00 ‐0.08 ‐0.02

IMAGE 0.59 0.59 0.32 1.00 0.03 0.04 ‐0.21 ‐0.25 0.10 0.23 0.59 UP 0.28 0.03 ‐0.26 0.23 0.20 ‐0.12 ‐0.79 ‐0.02 ‐0.08 1.00 0.09

WINS 0.46 0.51 0.48 0.59 0.22 0.07 ‐0.03 ‐0.32 ‐0.02 0.09 1.00

The model was tested using heteroscedasticity robust ordinary least squares method. Table 4 shows the results (proxy indicators of talent are given in bold). Adjusted R‐squared of the model is 0.64. Two of four variables of interest (an improvement in the championship table and coach’s image in media) have a significant and positive influence on coach’s salary. Whereas lowering the position of the club does not considerably affect the coach’s wealth. Also the absolute measure of club’s position is of no importance to assess the success of the coach’s work. One of the control variables ‐ average value of club’s players ‐ is of the utmost importance and has significant positive impact on coach’s salary. This variable enables us to control the difference in clubs’ financial capacities. In addition, we found the country‐specific feature: salary of football coaches working with the Italian clubs is lower than in other considered countries. Table 4: Regression results Variable Coefficient C ‐10.20 PLACE ‐0.69 UP 1.34* DOWN 0.32 IMAGE 0.98* PLAYERS 0.36** AGE 0.45 BIRTH 0.01 FPLAYER ‐1.19 SAMETEAM ‐0.45 WINS ‐0.12

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Std. Error 10.21 0.99 0.81 0.66 0.57 0.08 0.41 0.74 1.53 0.68 0.75

Eduardo Tomé, Luliia Naidenova and Marina Oskolkova Variable RUS FRA GERM ITALY SPAIN

Coefficient ‐0.93 0.31 ‐0.59 ‐1.39* ‐0.15

Std. Error 1.02 1.10 0.77 0.80 0.87

** indicates significant at the 1% level; * indicates significant at the 10% level

5. Concluding comments 5.1 Conclusions The importance of IC has a cause of wellbeing and economic prosperity is undisputed nowadays. However empirical studies are lacking to illustrate the reality, In particular, empirical studies on the top end of the wealth spectrum are inexistent. This reality fact is amazing because globalization creates the conditions to the increase in the number of very rich people and because inequality is becoming a more serious problem every day. In consequence we made a study on football coaches and concluded that a set of intangible variables explains almost two thirds of the coaches salary. Given the very high value of the salary we believe it will be transformed in wealth and that those coaches are potential millionaires. In the specific case, the value of the clubs players was found to have a positive and very significant effect on the coach’s wealth; other important explanatory factors whereas the coach’s public image, the fact that the club went up in the classification in the league and the fact that he worked in Italy have also significant positive effects.

5.2 Social interest and suggestions for further research We find very interesting that variables linked to the professional activity of millionaires may explain so well the fortunes of these people. We would like to continue the study by enlarging the analysis to other types of people, namely football players, tennis players, fashion designers, fashion models, artists, Formula 1 drivers, singers, politicians or business men. We would be able then to explain the social and economic rise of those persons: a fact that usually can be attributed to luck and that may generate social envy.

5.3 Limitations This study was only limited to a small sector of activity (football), in an economic year (2011), using data on 60 persons (coaches). We expect similar patterns to exists over the 10 to 25 million billionaires that are said to exist.

5.4 Policy guidelines We believe that in the next few years the very rich phenomenon will become more and important. Governments should make a policy on those cases. That policy should relate to attractiveness, investment and tax. If intangible are said to be the core of the cause of wealth, they should be the basis of those policies. In our case, the football coaches should not be analyzed on their income, but in relation to the variables that explain their income: player’s value, image, upward mobility of club, and place of work (namely Italy).

References Barajas, A. Rodriguez, P. (2010) Spanish Football Clubs’ Finances: Crisis and Player Salaries, International Journal of Sport Finance, 2010, 5, 52‐66, West Virginia University, Barry H. (2007) Wealth Concentration Associated with Frequent Violent Crime in Diverse Communities, Social Evolution & History. Volume 6, Number 2, BBC (2011) France investigates Tunisia's Zine al‐Abidine Ben Ali http://www.bbc.co.uk/news/world‐africa‐12270294 As assessed in May 15, 2011. Bonfour A Edvinsson L (2005) Intellectual Capital for CommunitiesButterwurht‐Heineman Elsevier, Oxford UK. Bontis, N (1999) Managing organizational knowledge by diagnosing intellectual capital: framing and advancing the state of the field Int. J. Technology Management, Vol. 18, Nos. 5/6/7/8, 1999 433 Community Banker (2008) Top 10 forescats,Feb2008, Vol. 17 Issue 2, p15

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Eduardo Tomé, Luliia Naidenova and Marina Oskolkova Daily Mirror (2012) Gold medal: Special Olympics National Lottery draw smashes millionaire records http://www.mirror.co.uk/news/latest‐news/national‐lottery‐olympics‐euromillions‐draw‐1185554 Gurel P. Ekmekci Y. (2011) Measuring Intellectual Capital For Football Clubs: Evidence From Turkish First Division Football League – Conference on Sports Economics, Prague. Edvinsson L. and Malone M. (1997) Intellectual Capital Harper Business. Forbes (2012) The world’s billionaires http://www.forbes.com/billionaires/. Frank, R (2005) Microeconomics and Behavior. 6th ed. New York: McGraw‐Hill 2005. Goal (2012) Special One Mourinho wants to be known as the "Only One http://www.goal.com/en‐ us/news/88/spain/2012/08/13/3305392/special‐one‐mourinho‐wants‐to‐be‐known‐as‐the‐only‐one Keynes, J. M. (1936) The General Theory of Employment, Interest and Money, London: Macmillan (reprinted 2007. Le Grand J.; Propper C. Smith S. (2008) The Economics of Social Problems,Palvgrave. Marshall A. (1890) Principles of Economics. London: Macmillan and Co., Ltd. Mill J (1848) Principles of Political Economy with some of their Applications to Social Philosophy (Ashley ed.). Pope Leo XIII (1891) RerumNovarum, Papal Letter to Christianity, Vatican. Sachs J. (2006) The End of Poverty: Economic Possibilities for Our Time. Penguin Books. Shareef, F. Davey, H. (2005) "Accounting for intellectual capital: Evidence from listed English football clubs", Journal of Applied Accounting Research, Vol. 7 Issue: 3, pp.78 ‐ 116 Smith, Adam (1977) An Inquiry into the Nature and Causes of the Wealth of Nations. University Stewart, T. (1997).Intellectual capital: the new wealth of organizations. New York, NY: Doubleday. Of Chicago Press. ISBN 0226763749 Sunday Times (2012) Rich List http://www.thesundaytimes.co.uk/sto/public/richlist/ Szymanski, S. (2001). Income Inequality, Competitive Balance and the Attractiveness of Team Sports: Some Evidence and a Natural Experiment from English Soccer. The Economic Journal. 111(469), 69 ‐ 84. Tomé, E (2004) “Intellectual capital, social policy, economic development, and the world evolution” Journal of Intellectual Capital, volume 5, number 4, pgs. 648‐665 Tomé E. (2012) “Intellectual Capital and the Very Rich” ECIC 2012 Conference Proceedings, Helsinki. Youndt, M.; Snell, S (2004) .Human Resource Configurations, Intellectual Capital, and Organizational Performance. Journal of Managerial Issues, Vol 16(3), 2004, 337‐360

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ICBS Intellectual Capital Benchmarking System: A Practical Methodology for Successful Strategy Formulation in the Knowledge Economy José Viedma Marti1 and Maria do Rosário Cabrita2 1 Department of Business Administration, Polytechnic University of Catalonia, Spain 2 UNIDEMI, Department of Mechanical and Industrial Engineering,Faculty of Science and Technology, FCT, Universidade Nova de Lisboa, Portugal jose.m.viedma@upc.edu icms.viedma@telefonica.net m.cabrita@fct.unl.pt rosariocabrita@gmail.com Abstract: The advent of the knowledge economy fundamentally changes the way to create wealth. According to new theoretical foundations (Resource Based View, Dynamic Capabilities and Knowledge Based View) key strategic knowledge or Intellectual Capital has become the fundamental driver of wealth creation. A revision of the literature concludes that business excellence has always been due to good strategy formulation and superior strategy implementation. In order to achieve business excellence in the knowledge economy context substantial efforts have been made to improve the process of strategy implementation and some of them have produced relevant frameworks and methodologies, such as Balanced Scorecard and InCaS (Intellectual Capital Statement. Made in Europe). Nevertheless, fewer efforts have been made in the process of strategy formulation and, in practice, the SWOT analysis still is the most well known existing framework. However, in a world where customer preferences are volatile and the identity of customers and the technologies for serving them are changing, a market‐focused strategy may not provide the stability and constancy of direction needed as a foundation for long term strategy. When the external environment is in a state of flux, the firm itself, in terms of its bundle of resources and capabilities, may be a much more stable basis on which to define its identity. Hence, a definition of the firm in terms of what it is capable of doing may offer a more durable basis for strategy than a definition based upon the needs the business seeks to satisfy. Consequently, the SWOT analysis methodology can’t cope with the new external environment requirements and a kind of improved or extended SWOT analysis is needed. ICBS (Intellectual Capital Benchmarking System) is the output of a practical research on extended or improved SWOT analysis, a framework that knowledge economy requires for successful strategy formulation. ICBS is a new management method that allows companies to perform a competitiveness strategy check‐up of their business models. For that purpose, ICBS benchmarks their core innovation and operations intellectual capital against the world class competitors in their sector. Keywords: strategic management, core competencies, core capabilities, intellectual capital, extended SWOT analysis

1. Introduction We live in a time of great opportunities where creativity and innovation has led to competences and technologies that have allowed many great advances in almost every aspect of our lives. The opportunities arise in a new economic landscape where change and uncertainty is constant, and the firm’s focus should be on identifying and exploring these opportunities. Organisations facing uncertain, changing, or ambiguous market conditions need to be able to learn and make effective use of intellectual capital factors. The main features of this new economy involve major systemic changes: new forms of competition between global competitors; temporary rather than continuous competitive advantages; vertiginous pace of change; and ever‐shorter life‐cycles for products and services (Hitt et al., 2002). Those trends are changing the competitive structure of markets in such a way that the effectiveness of traditional sources of advantage is blurred. A new paradigm emerged in which knowledge, itself, became a critical factor of production (Adams and Oleksak, 2010), specifically, knowledge related to identifying and exploiting new ways to establish sustainable competitive advantages. In response, new models of business are emerging where the value chain have their hard nucleus in the creation, dissemination, application and leverage of intellectual resources. Structural changes transform the traditional business frameworks into insufficient and incomplete tools for developing a strategy. Traditional frameworks such as the BCG matrix, the Porter’s Five Forces and the SWOT analysis have had a lasting influence on strategic management and have been especially valuable for managers to develop and implement long‐term strategy for organizations so as to build and sustain competitive advantage. However, those frameworks are becoming insufficient because they do not take into account the

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José Viedma Marti and Maria do Rosário Cabrita dynamics of global markets. As most of models were developed in an era of stable markets, they also lack the perspective of intangibles. To be able to create value within this new economic landscape, we need to rethink our established notions regarding value creation process and strategy formulation ‐ in short we need to change our recipes for success. The value creation process is now based on the ability of firms to generate and exploit new forms of knowledge, and the most important contribution management needs to make is similarly to increase the productivity of knowledge work and the knowledge worker (Drucker, 1999). It is imperative for firms to focus on strategic management processes concerned with creating long‐term value from intellectual capital. One of the main challenges for the knowledge economy is how to use SWOT analysis efficiently and effectively in a context of permanent changes. Extended SWOT analysis is seen as a framework for formulating strategies at business level in an efficient and effective way to achieve success in the new context in which the main features are: (i) the importance of knowledge as the main source of sustainable competitive advantage; and (ii) the world‐wide hyper‐competition. The challenge is to move SWOT analysis away from the generalities of “strengths”, “weaknesses”, “opportunities”, and “threats” to more concrete factors and characteristics appropriate to the new reality. A specific methodology and information system framework – Intellectual Capital Benchmarking System (ICBS)–, focused on the value chain activities of both the operations and innovation processes, is developed. Deploying scarce resources to create superior value when dealing with the innovation process is a very different task from that involved when dealing with the operations process. To create value the two processes require particular resources and different core knowledge. For this reason, the ICBS has a specific methodology and information system framework for each of the processes (Viedma and Cabrita, 2012). The first is the Innovation Intellectual Capital Benchmarking System (IICBS) which is mainly focused on the value chain activities of the innovation process. The second is the Operations Intellectual Capital Benchmarking System (OICBS) which refers to the value chain activities of the operations process. This paper explores the theoretical foundations behind the process of strategy formulation in the context of knowledge economy. It starts by addressing the value creation process as a function of intangibles. Drawing on the activity‐based view and the resource‐based view, we discuss the theories and concepts that support the application of the Extended SWOT analysis as a framework designed to accomplish the dynamics of the knowledge economy. The concepts of business intelligence and strategic competitive benchmarking are also discussed as key components of the ICBS model. It is concluded that: (i) in order to achieve entrepreneurial excellence the process of strategy formulation is the key one, because it is closely related with effectiveness; (ii) among different intellectual capital methodologies and tools, ICBS is the only relevant for successful strategy formulation, for gaining and sustaining competitive advantages.

2. Theoretical foundation In the context of global economy, entrepreneurial excellence is related to the ability to achieve and sustain competitive advantages by building long‐term value from intellectual capital identified as a set of intangibles with potential to create value. Business excellence depends on soundly formulated strategy (business formula) and effectively implemented strategy (business recipe) based on core competencies, core capabilities and intellectual capital, as illustrated in Figure 1.

Figure 1: Entrepreneurial excellence in the knowledge economy In order to create value, the ingredients (resources, competencies and capabilities) in the business formula must be transformed into products and/or services that deliver business recipe.

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José Viedma Marti and Maria do Rosário Cabrita This set of intangibles or intellectual capital creates value when its components are combined and put into action and degrades when they remain unused (Roos, 2005). These value drivers are bundled together, and the interactions between them are varied, complex and dynamic making difficult to demonstrate the cause and effects relationships and its linkage to value outcomes. This perspective goes beyond the traditional value chain to other more complex ways of creating value mainly based on intangibles. Value creation as a function of intangibles. Value creation process is always linked to the capacity to build sustainable competitive advantages. In order to achieve sustainable success, which is the primary goal of strategic management, companies should build up a competitive advantage vis‐a‐vis its rival companies. Competitive advantage comes from the company’s ability to create value for its customers and to capture part of this value in form of profits. At the micro level, discussions seeking to explain sustainable competitive advantages have focused on the industrial organization theory (Porter, 1985), the resource‐based view (Wernerfelt, 1984), dynamic capabilities (Teece et al. 1997), core competencies (Prahalad and Hamel, 1990), and knowledge‐based view (Sveiby, 2001). Value creation process in the context of knowledge economy is directly linked to the intelligence, the speed, and the agility that comes from a host of latent intangibles which represent a reservoir of potential talent and innovation that provides a source of competitive advantage. This suggests that the value generated is a function of the way in which resources are managed. This means that having a resource is not enough to create value. In order to create or leverage value, the resources have to be deployed effectively and efficiently. Sveiby (2001) argues that the key to value creation lies with the effectiveness of knowledge transfers and conversions. Carlucci et al., (2004) state that the generated value is the result of an organization’s ability to manage its business process and the effectiveness and efficiency of performing organizational processes are based on organizational competencies. Knowledge assets interact with each other to create competencies and capabilities, and it is often these interactions that provide a competitive advantage because they make these assets difficult for competitor to replicate (Barney, 1991; Teece et al., 1997; Marr, 2005). Value is then created through complex dynamic exchanges between tangibles (goods and money) and intangibles (cognition processes, intelligence and emotions) where individuals, groups or organisations engage in a value network by converting what they know, both individually and collectively, into tangible and intangible value. Formulating business strategies The purpose of strategy is to ensure the achievement of competitive advantage by defining the direction and scope of an organization. Strategy formulation process mainly deals with effectiveness, or choosing the right things to do. Drucker (1977) adverts that the pertinent question is not how to do things right but how to find the right things to do, and then concentrate resources and efforts on them. Formulating the right questions demands that organizations understand which resources, capabilities and competencies they need in order to gain and sustain the competitive advantage. At the same time, to be successful or to be excellent, organizations need to know what their competitive advantage is. Making good decisions are based on strategies well formulated. The crux of strategy formulation is to define a strategy that makes the best use of the organization’s resources, competencies and capabilities. Resources, competencies and capabilities. Resources are inputs into the production process and they can be tangible or intangible assets (Itami, 1987) that a firm controls and can use to conceive of or implement strategies (Barney and Hesterly, 2006). The resource‐based view (RBV) of the firm argues that sustainable competitive advantage requires unique and inimitable resources (Barney, 1991). Intangible resources can include skills, human assets, information and organizational assets, and relational and reputational assets. These all represent what a firm has. Another class of intangible resource is capabilities or competences that represent what a firm does (Hill et al., 2007). Capabilities may be understood as the way resources, talents and processes are combined and used (Teece et al., 1997). Prahalad and Hamel (1990) defined competencies as the collective learning that gives firms the ability to deploy their resources productively. Competencies are the means by which a firm deploys resources

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José Viedma Marti and Maria do Rosário Cabrita in a characteristic manner in order to compete (Haanes, 2000). Thus, professional competencies integrate professional skills and knowledge, and organizational competencies include a firm’s knowledge, routines, and culture. Prahalad and Hamel (1990), have distinguished particular competencies, which they call “core competencies”, as being fundamental to the firm’s performance and strategy. “Core competencies”, according to these authors, are those that make a disproportionate contribution to ultimate customer value, or to the efficiency with which that value is delivered. Core competencies thus provide a basis for entering new markets (Prahalad and Hamel, 1990:81). The authors put the cumulative development of specific competencies at the centre of the agenda of corporate strategy because “the real sources of advantage are to be found in management’s ability to consolidate corporate‐wide technologies and production skills into competencies that empower individual businesses to adapt quickly to changing opportunities”. Hence, the sustainable competitive advantage of firms resides not in their products, but in their core competencies. Furthermore, those core competencies feed into more than one product, which, in turn, feed into more than one business unit. Teece et al. (1997) defined dynamic capability as a firm’s ability to integrate, build, and reconfigure competence. It is the heterogeneity of skills and capabilities available from its resources that gives each firm its uniqueness (Penrose, 1959). In describing how organizations create and leverage competitive advantage, the literature focuses on what the firm has, but not less important is what the firm does with what it has. Collis and Montgomery (2008, p. 142) note that “the RBV inextricably links a company’s internal capabilities (what it does well) and its external environment (what the market demands and what competitors offer). In strategy management, two relevant perspectives still coexist in understanding how firms deploy scarce resources to create superior value (Haanes, 2000). These two perspectives are the resource‐based view and the activity‐based view (Porter, 1985, 1996). The two are complementary. The resource‐based view focuses on what the firm has, whereas the activity‐ based view focuses on what the firm does.

Figure 2: The basis of competitive advantage: complementary perspectives The resource‐based view (RBV) The focus of resource‐based view is on the relationship between firm resources and firm performance. Following the seminal work of Penrose (1959), the RBV of the firm proposes that firms consist of bundles of productive resources and that different firms possess different bundles of these resources in competitive environments. Distinct types of resources including tangible assets, intangible assets and skills have been identified as underlying the distinctive or core competences of a firm (Prahalad and Hamel, 1990). These core competences can only achieve sustainable competitive advantage when underlying resources are valuable, rare, cannot be imitated, and have no substitutes (Barney, 1991). In accordance with Grant (1998), a key common ingredient in all business success stories is the presence of a soundly formulated and effectively implemented strategy. Grant (1998) has stated that the starting point for the formulation of strategy must be some statement of the firm’s identity and purpose. This generally takes the form of a mission statement that answers the question: ‘What is our business?’. Traditionally, firms have defined their business in terms of the market they serve by asking: ‘Who are our customers?’ and ‘Which of their needs are we seeking to serve?’ Nevertheless, in a volatile world in which the identity of customers, their preferences, and the technologies for serving them are all changing, a market‐focused strategy might not provide the stability and constancy of direction required as a foundation for long‐term strategy. When the external environment is in state of flux, the firm itself, in terms of its bundle of resources and capabilities, might be a much more stable basis upon which to define a sense of identity. Hence, a definition of the firm in terms of what it is capable of doing might offer a more durable strategic basis than a definition based upon the needs which the business seeks to satisfy (Quinn, 1992).

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José Viedma Marti and Maria do Rosário Cabrita The above discussion points to the fundamental role of resources, capabilities and competencies in strategy formulation for entrepreneurial success in an environment of rapid change in technology and in the needs of customers and industry. Figure 3 summarizes the above discussion on resources, capabilities and core competencies.

Figure 3: Resources and capabilities of a firm The activity‐based view (ABV) The activity‐based view has mainly been concerned with seeing firms as value chains that create value by transforming a set of inputs into more refined output (Porter 1985, 1996). Nevertheless, to be more specific, we need to consider how value is created in the internal business process value chain. The business process value chain can be divided into major processes: (i) the innovation process; and (ii) the operations process. The innovation process is made up of product design and product development, whereas the operations process is made up of manufacturing, marketing, and post‐sale service. Figure 4 illustrates the business process value chain.

Source: Adapted from Kaplan and Norton (1996) Figure 4: Business process value chain The traditional perspective has focused on the operations process. According to the short‐term view, value creation begins with the receipt of an order from an existing customer for an existing product or service, and ends with the delivery of the product to the customer (Kaplan and Norton, 1996). In this case, value is created through operations core competencies. However, viewed from the perspective of the innovation process, value creation is a long‐term process which, for many companies, is a more powerful driver of future financial performance than the short‐term operations process. This view requires an organisation to create entirely new products and services that will meet the emerging needs of current and future customers. For many companies, their ability to manage successfully a multi‐year product‐development process, or to develop a capability to reach entirely new categories of customers, can be more critical for future economic success than managing existing operations efficiently, consistently, and responsively. Value is thus created through innovation core capabilities. Specifically,

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José Viedma Marti and Maria do Rosário Cabrita innovation value chain is about to translate competencies into new processes, products and services, and, where necessary, develop new competencies. Then, building core competencies is not done in a vacuum, but is done in the business process value chain in which resources are deployed in a characteristic manner in order to compete. The RBV and the ABV are therefore complementary. Taken together, they explain the process of creating value and securing a sustainable competitive advantage.

3. Building the intellectual capital benchmarking system (ICBS) As previously noted, in our times the RBV and the ABV are the fundamental cornerstones that determine company competitiveness. The RBV stresses that, in turbulent times sustainable competitive advantages are mainly due to the intangible resources of a company or, more specifically, to core competencies (which are, in practice, equivalent to core knowledge). However, resources per se do not create value, and because the RBV focuses only on what the firm has, this view does not, in isolation, adequately explain how to deploy scarce resources to create superior value. In this sense, the ABV is a necessary complementary perspective which focuses on what the firm does, and takes into account that value creation results from the activities to which the resources are applied. If core knowledge is the key strategic asset, improving existing core knowledge and building new core knowledge are fundamental tasks. Building and improving core knowledge require organizational learning capabilities, including the appropriate learning structures and information systems. World‐wide industry hyper‐competition has ensured that, in order to remain competitive, organizations need not only to protect their interests but also to expand their interests. They need to out‐innovate their competitors. For doing this, business intelligence and strategic competitive benchmarking have become essential learning tools. That valuable knowledge can be obtained only from: (i) a business intelligent process that gathers, processes, interprets and communicates the economic, social, technical and political information needed in the decision‐making process; and (ii) a strategic benchmarking process that provides a systematic and frequent comparison with the world‐class processes and core competencies of competitors in the same business segments. Organisations are now competing on the basis of core knowledge and core competencies. Opportunities and threats come mainly from competitors who offer the best in the same industry segment. Business intelligence and strategic competitive benchmarking. Competitive intelligence helps organization to identify threats in the external environments capable of impacting negatively on the future of the company, and identify new opportunities for the organization, leading to innovation and ultimately benefiting the competitive status of the organization. The objective of competitive benchmarking is to identify specific information about the competitor’s products, processes and business results and then make comparisons with those of the own organisation. Competitive benchmarking is also useful in positioning the organisation’s products, services and processes relative to the marketplace. When we move from competitive benchmarking, to strategic competitive benchmarking (Watson, 1993) we mainly focus on core activities, core competences and specially core knowledge. This suggests that the SWOT analysis should move away from the generalities of “strengths”, “weaknesses”, “opportunities”, and “threats” to more concrete factors and characteristics appropriate to the new reality. The Extended SWOT Analysis Fahy and Smithee (1999) agree the RBV of the firm helps to overcome some of the frequently cited problems of the SWOT framework. Amit and Schoemaker (1993:35) state that “the resource‐based perspective complements the industry analysis framework”. Roos (2005) presents a theoretical approach that seeks to integrate the competitive forces and the resource‐based paradigms of competitive advantage. Strategic development process based on the competitive forces paradigm starts by looking at the relative position of a firm in a specific industry, i.e. we first consider the firm’s environment, and then we try to assess what strategy is the one that maximize the firm’s performance. By contrast, the RBV can be seen as an “inside‐out” process of strategy formulation. We start by looking at what resources the firm possesses, and then we assess their potential for value generation and end up by defining a strategy. In short, the RBV of the firm provides a conceptually grounded framework for assessing strengths and weaknesses and enables strengths or weaknesses to be examined in terms of the criteria for establishing sustainable competitive advantage.

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José Viedma Marti and Maria do Rosário Cabrita Further to the discussion above, the SWOT analysis framework moves from A to B as shown in Figure 5. In effect, there is a change from simple SWOT analysis to an extended SWOT analysis. A: Swot analysis B: Extended Swot analysis

Figure 5: Evolution of SWOT analysis The Extended SWOT analysis gives us the main factors to consider when seeking strategies that leading to entrepreneurial excellence. The main factors of the extended SWOT analysis also determine the information system required to measure and manage those factors. In other words, the main factors produce the Intellectual Capital Benchmarking System (ICBS), an intellectual capital strategic management information system framework developed by Viedma (2004). Nevertheless, as previously noted, strategy formulation in dynamic environments, even those mainly based on core capabilities, has different features when dealing with the innovation process than when dealing with the operations process. Core capabilities can be very different in the two processes. The innovation process points to new products and services through the innovation value chain in which innovation capabilities are basic and fundamental. Core capabilities represent a potential and, therefore, cannot contribute to competitiveness unless they are successfully translated into new processes, products and services. This is the role of innovation management. The Innovation Intellectual Capital Benchmarking System (IICBS) has a specific system for the innovation process. The operations process, which produces ordinary products and services through the systematic and repetitive operations value chain, also requires core competencies and core capabilities to be competitive. However, these competencies and capabilities will probably be of a different nature from the ones mentioned above in the discussion of the innovation process. ICBS also has a specific process for the operations value – the Operations Intellectual Capital Benchmarking System (OICBS). Figure 6 illustrates the business process broken down into two constituent parts, and the specific methodologies and information systems that correspond to each of the constituent parts. C u sto m e r n eed

IN N O V A T IO N D e s ig n

D e v e lo p

O P E R A T IO N S M a k e

M a rk et

C u sto m e r

S e r v ic e

id e n tifie d

n eed s a tis fie d

C o r e a c tiv itie s

C o r e c o m p e te n c ie s

I n n o v a tio n c o r e k n o w le d g e

O p e r a tio n s c o r e k n o w le d g e

IIC B S

O IC B S

I n n o v a tio n I n te lle c tu a l C a p ita l B e n c h m a r k in g S y ste m

O p e r a tio n s I n te lle c tu a l C a p ita l B e n c h m a r k in g S y ste m

Figure 6: Business process value chain

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José Viedma Marti and Maria do Rosário Cabrita In summary, the general model of the ICBS can be divided into two partial models. The first, the IICBS, refers to innovation core activities and core knowledge, whereas the second, the OICBS, refers to operations core activities and core knowledge. The two models have a similar structure and they work in a similar way, but there is a fundamental difference. The IICBS model refers to the core activities and core knowledge of the different projects that make up the innovation process. In contrast, the OICBS model refers to the core activities and core knowledge of the different business units that make up the operations process. This paper describes only the IICBS. However, the structure and function of the OICBS can be easily deduced because the systems are very similar and work in an analogous fashion.

4. (IICBS) Innovation intellectual capital benchmarking system general framework Using the metaphor of a tree, we can consider the company that performs innovation activities as a new tree in which the visible part (that is to say, the trunk, the branches, and the fruits) corresponds to the tangible assets of the innovative company (see Figure 7). The invisible part of the tree (the roots of the tree below ground) corresponds to the intangible assets of the innovative company. The two parts – tangible and intangible – are inseparable. The roots of the tree send the sap through the trunk and the branches to the fruits. In a similar way, knowledge and its aggregates – competencies, capabilities, and intellectual capital – make up that flows from the roots to the new processes, and thus to the new products and services.

Figure 7: Innovation tree and innovation infrastructure In addition, the company has at its disposal a common intangible innovation infrastructure that is shared by all the project units. This infrastructure corresponds to the fertile soil in which all the company trees are planted. This fertile soil nourishes the roots (core knowledge) of each individual innovation company tree. The assessment process is carried out in a two‐fold fashion as depicted in the flowchart of Figure 8. On one side, we take as reference benchmarks the innovative project objectives and goals (Company A); on the other side, we take as a reference benchmark the equivalent innovative project of the best world competitor (Company B). The flowchart shows that, within each company innovation tree (project unit), an analysis can be made, successively, on the fruits (new products and services), the branches (new processes), and the roots (new core competencies and professional core competencies). In addition, the overall soil fertility (innovation infrastructure) can be analysed. In analysing each particular tree (i.e. each individual project unit), we use the innovation value chain as an analysis tool. We argue that it is a useful approach because it helps to identify the interrelationships between innovative products and innovation capabilities. If products with a closer fit to firm competencies tend to be more successful, in turn, the effect that new product projects have on the firm’s competencies is a crucial issue to be observed in the trajectory of firm’s renewal and development.

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José Viedma Marti and Maria do Rosário Cabrita All of the above mentioned analyses have the ultimate purpose of discovering, in each of the flowchart steps or phrases, the new core knowledge and new core technologies that are the prime reason for sustainable competitive advantages. Company A Project 1 Objectives

New Products and Services

New Processes

New core capabilities

New professional Core capabilities

Innovation Infrastructure

Customer emerging needs

Company B Project (h) Objectives

Benchmarking GAP

New Products and Services (h)

Benchmarking GAP

New Processes (h)

New core Capabilities (h)

New professional Core capabilities (h)

Innovation Infrastructure

(h) = Homologous

Figure 8: Innovation intellectual capital benchmarking system In the same way, the methodology makes it possible to compare each specific tree (project unit) with the homologous tree of the best of the competition, thus facilitating the benchmarking of fruits (new products and services), branches (new processes), roots (new core competencies and professional core competencies), and soil fertility (innovation structure). Implications for Managers Senior managers effectively integrate the ICBS into the overall business strategy in a similar way they integrate other strategy‐focused models. Nevertheless, in the particular case of the ICBS two new functions have to be performed: business intelligence and competitive benchmarking. The main benefits from using ICBS are the following:

Learning from one’s betters to surpass one’s own competitive position.

Identifying the specific competitiveness factors that are relevant I a given business activity.

Through the ICBS factors framework, enabling the identification, auditing and benchmarking of the core competencies or core knowledge that are the main sources of long term sustainable competitive advantages.

When using ICBS in an orderly systematic and repetitive way we obtain competencies statements that complete financial balance sheets and lead companies to leverage core knowledge.

Selecting in a systematic and organised way the necessary information for evaluating relevant factors, core knowledge, core competencies and key intellectual capital.

Identifying the key areas in which in‐depth benchmarking can be carried out in the future.

Promoting organizational learning through assessment teams, benchmarking teams, and strategic teams

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Introducing a common language for company managers when dealing with intellectual capital

Facilitating the work of the benchmarking and competitive intelligence team.

5. Conclusion In the knowledge economy, soundly formulated and effectively implemented strategies are still the main drivers of company success, and SWOT analysis still remains the most common approach for analysing business strategy. However, in the new context, classical SWOT analysis does not provide suitable guidance for building an effective strategic management information system. An extended SWOT analysis which takes into consideration the two main streams of modern strategic thought ‐ the resource‐based view and the activity‐ based view ‐ is a more reliable foundation. ICBS draws inspiration from the extended SWOT analysis and builds a strategic management information system in which core knowledge is the key issue.

References Adams, M. and Oleksak, M. (2010). Intangible capital. Putting knowledge to work in the 21st‐century organization. Santa Barbara. California: Praeger. Amit, R. and Schoemaker, P. (1993). Strategic assets and organizational rent. Strategic Management Journal, 4, 1, 33‐46. Barney, J.B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 1, 99‐120. Barney, J.B. and Hesterly, W.S. (2006). Strategic Management and Competitive Advantage: Concepts and Cases. Upper Saddle River, NJ: Pearson Education. Carlucci, D., Marr, B. and Schiuma, G. (2004). The knowledge value chain: How intellectual capital impacts on business performance. International Journal of Technology Management, 27, 6/7, 575‐90. Collis, D.J. and Montgomery, C.A. (2008). Competing on resources. Harvard Business Review, 86, 7/8, pp. 140‐50. Drucker, P.F. (1977). An abridged and revised version of management: Tasks, responsibilities, practices. Pan Books‐ Heinemann. Drucker, P.F. (1999). Management challenges for the 21st century. Oxford: Elsevier Butterworth‐Heinemann. Fahy, J. and Smithee, A. (1999). Strategic marketing and the resource based view of the firm. Academy of Marketing Science Review, 10, 1‐19. Grant, R.M. (1998). Contemporary strategy analysis. Oxford: Blackwell Publishers Ltd. Haanes, K. (2000). Linking Intangible Resources and Competition. European Management Journal, 18, 1, 52‐62. Hill, W.L., Jones, G.R., Galvin, P. and Haidar, A. (2007). Strategic Management: An Integrated Approach. Sydney: John Wiley and Sons. Hitt, M.A., Ireland, R.D., Camp, S.M. and Sexton, D.L. (2002). Strategic entrepreneurship: Integrating entrepreneurial and strategic management perspectives. In M.A. Hitt, R.D. Ireland, M.S. Camp, and D.L. Sexton (Eds.), Strategic entrepreneurship: Creating a new mindset. UK: Blackwell Publishers Ltd. Itami, H. (1987). Mobilizing Invisible Assets. Cambridge, MA: Harvard University Press. Kaplan, R.S. and Norton, D.P. (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74, 1, 75‐85. Marr, B. (2005). Perspectives on intellectual capital – multidisciplinary insights into management, measurement, and reporting. Oxford: Butterworth‐Heinemann. Penrose, E.T. (1959). The theory of the growth of the firm. New York, NY: Oxford University Press. Porter, M.E. (1996). What is strategy? Harvard Business Review, 7, 6, 61‐78. Porter, M.E. (1985). Competitive Advantage. New York: Free Press. Prahalad, C.K. and Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, May‐June, 79‐91. Quinn, J. B. (1992). Intelligent Enterprise. New York: The Free Press. Roos, G. (2005). Intellectual capital and strategy: A primer for today’s manager. Handbook of Business Strategy, 123‐32. Sveiby, K.E. (2001). A knowledge‐based theory of the firm to guide strategy formulation. Journal of Intellectual Capital, 2, 4, 344‐58. Teece, D.J., Pisano, G. and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18, 7, 509‐33. Viedma, J.M. (2004). Strategic knowledge benchmarking system (SKBS): A knowledge‐based strategic management information system for firms. Journal of Knowledge Management, 8, 6, 31‐49. Viedma, J.M. and Cabrita, M.R. (2012). Entrepreneurial excellence in the knowledge economy.Intellectual Capital Benchmarking System. London: Palgrave Macmillan. Watson, G. (1993). Strategic Benchmarking. John Wiley & Sons. Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5, 2, 171‐80.

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Intellectual Capital (IC) in Social Media Companies: Its Positive and Negative Outcomes Piotr Wiśniewski Department of Corporate Finance, Warsaw School of Economics, Warsaw, Poland piotr.wisniewski@sgh.waw.pl Abstract: Social media are becoming a vital element of intense Intellectual Capital (IC) growth. Their ultimate shape is being determined by dynamic technical innovation (involving hybrid products and services), merger and acquisition (M&A) activity among product and service innovators, as well as user behaviorisms (embodying the very social dimension of these media). Despite obvious constraints (novelty, limited research coverage), it is evident that two IC segments have come to the fore of social media expansion: Customer Capital (CC) and Structural Capital (SC). It is premature to produce a comprehensive assessment of social media sustainability and utilitarianism; however, key positives and negatives of online interconnectedness can now be outlined. Their impact analysis and interdependence should be explored in further empirically based research for which this paper might serve as a useful starting point. Keywords: intellectual capital, social media, social outcomes, social responsibility

1. The origins, definition and significance of social media Social media are a fairly recent phenomenon; although initial signs of their activity can be traced to the late 1960s (see Appendix 1). In earnest, their rapid ascent occurred in the late 2000s when the social media paradigm began to eclipse what had thereto been referred to as “mass media” (Appendices 1 and 2). “Social media are media for social interaction, using highly accessible and scalable publishing techniques” (Social Media Guys, 2010). This definition resonates with a notion formalized by Kaplan & Haenlein (2010) whereby social media are “a group of Internet‐based applications that build on the ideological and technological foundations of Web 2.0 [i.e. online interactivity], and [in fact it should be “i.e.”] that allow the creation and exchange of user generated content”. The classification of social media is in a constant state of flux, yet the following key categories of Web based interconnectedness are thus far distinguishable and reasonably established (cf. taxonomy proposed by Kaplan & Haenlein, 2012). Table 1: Social media classification, characteristics, examples and commercial aspects #

Name

Subsets, characteristics

Examples

Collaborative projects

wikis (websites allowing users to add, remove or alter web‐based content), 2) social bookmarking (group‐based collection and rating of Internet resources)

1) Wikipedia, 2) Reddit

Blogs

Websites portraying the life experiences of individuals or groups and presented in textual, pictorial or audiovisual forms

Huffington, TMZ

Content communities

Platforms for sharing media content (audiovisual, photographs or other formats) among users

Youtube, Flickr

Social networking

Applications enabling users to connect via personal profiles comprising diverse personal information (photographs, audiovisual files and blogs) and featuring instant messaging and email

Facebook, Twitter

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Commercial relevance Providing free access to information, enhancing socioeconomic efficiencies, improving resource transparency, challenging copyrighted content Keeping in touch with consumers, keeping employees informed, enhancing website visibility (traffic) Cross‐selling potential (relating to pay versions) from distributing free content, marketing Networking with consumers and employees, enhancing brand development,

Piotr Wiśniewski #

Name

Virtual worlds

Subsets, characteristics Computer‐based environments allowing users to create their virtual identities (avatars) and interact online: 1) virtual game worlds: Massively Multiplayer Online Role Playing Games (MMORPGs), 2) three‐dimensional platforms allowing users to interact in a way similar to real (offline) life

Examples

Commercial relevance

World of Warcraft, Second Life

Promoting brands, goods and services in contexts unavailable to mainstream media

Source: based on Miller (2011). Social media share a number of characteristics will mass (traditional) media. Certain features of social media are nevertheless unique and reflect the unprecedented character of this media resource. Among them are (cf. Social Media Guys, 2010):

popularity: social media are increasingly emulating the outreach of their (by far more established) predecessors – this trend is best illustrated by the dwindling circulation of newspapers vs. booming number of social media’s daily active users;

democracy: social media are – in essence – a grassroots movement (natural, spontaneous and driven by human individualism – opposed to the ineludible corporationism of traditional media sources);

credibility: on the one hand social media are relatively uncensored, outspoken and non‐partisan, on the other hand the lack of scrutiny prior to publication might result in errors, omissions, misinformation (largely unintended) or disinformation (downright deliberate);

accessibility: traditional media employ professionally trained staff and sophisticated equipment (whose costs ultimately have to be borne by end users), whereas the lion’s share of social media initiatives are usually amateur and free of charge (the chief limitation of their creators and users is Internet connectivity and hosting capacity);

timeliness: the very process of news gathering, verification, processing and dissemination by conventional media is time consuming, while social media are able to react instantaneously and without significant formalism;

permanence: in general industrial media cannot be altered following their dissemination, whereas social media are continuously and promptly editable (by their author or other online contributors), while their Internet traces are usually indelible (they can be retrieved by a skilled user).

2. Social media relevance to intellectual capital Intellectual capital (IC) has to date been defined in multiple ways. The following examples illustrate IC’s nomenclature in international literature at the turn of the millennium:

“non‐monetary and non‐physical resources that are fully or partly controlled by the organization and that contribute to the value creation of the organization” (Roos et al., 2005);

“knowledge that transforms raw materials and makes them more valuable” (Stewart, 2001);

“the brainpower assets of the organization, recognizing them as having a degree of importance comparable to the traditional land, labor, and tangible assets” (Sullivan, 2000);

“the hidden roots of value” (Edvinson & Malone, 1997);

“the sum of everything everybody in a company knows that gives it a competitive edge” (Stewart, 1997);

“intellect in action” (Hudson, 1993).

Despite these conceptual variations, the aforementioned definitions tend to be uniform in highlighting IC’s:

intangible form (IC ): in most in‐depth references to IC, it is portrayed as a fairly abstract notion and its character is usually nonmaterial/nonphysical;

socioeconomic impact: even avowed critics of IC oriented research begrudgingly admit that IC’s consequence for socioeconomic growth – although problematic in clear‐cut appellation, taxonomy and measurement – is undeniable and substantial;

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cross‐asset synergies: the most challenging aspect of IC (besides its inherent intangibility and measurement complexity) is functional overlap in IC’s segmentation and multidimensional interaction among individual IC components.

Table 2 demonstrates a frequently applied and reasonably coherent segmentation model for IC, with its key drivers of socioeconomic utility and value as well as examples existing in practical circumstances: Table 2: IC subsets: definitions, key drivers and examples IC Subset Customer Capital: relationships with customers and suppliers Human Capital: the skills and knowledge of the company’s people

Key drivers of utility and value

Disseminating creations of the human mind

Structural Capital: Intellectual Property

Extracting value from IC

Interacting among users

Examples Relationships with customers and suppliers Employees’ knowledge, practical skills and competences Patents, Processes, Databases, Networks etc.

Source: based on Stewart (2001). IC subsets listed in alphabetical order. The established record of traditional media has resulted in numerous scientific publications focused on how IC is created, enabled or facilitated by them. This contrasts with a rather scarce body of knowledge developed thus far with specific regard to social media. In consequence, it is problematic reapplying the IC segmentation philosophy to social online connectivity, yet an attempt to this effect is indispensable for any further analysis. Figure 1 demonstrates social media concepts associated with individual IC segments as well as the reasoning behind such linkage: Blogs are de facto one-directional platforms for communicating novel ideas

blogs

social networking, virtual worlds

content communities, collaborative projects

Admittedly, both content communities and collaborative projects involve human interaction, yet their defining feature is disclosing and sharing information content

Although the “customer” aspect is far from instinctive, these initiatives are primarily based on deep virtual interconnectedness

Source: own elaboration. Figure 1: IC subsets (Customer Capital: CC, Human Capital: HC, Structural Capital: SC and) in the social media context Evidently, HC is a prerequisite for the existence and spread of the two other subsets of IC (CC and SC), as social media cannot operate without human creativity and its transmission. However, it is CC and SC that underlie the commercial viability of IC embedded in social media. This happens for the following two reasons:

social leverage: the aggregate value represented by social media outnumbers the simple sum of their components (in other words – it is social media interconnectedness that defines the bulk of their commercial value);

value extraction: whereas innovation is a starting point of the social media value chain, its ultimate success is driven by effective commercialization.

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3. Are social media an IC asset or a liability? To begin with, IC interpretation is gradually evolving from a notion whose associations used to be universally positive to that whose social outcomes are by far more nuanced (Cf. Dumay, 2012). The socioeconomic perception of social media tends to be even more volatile and controversial. Despite the intense use of social media globally, relatively few of their social impacts have been proved empirically on the basis of statistically representative data. Table 3 encapsulates the most significant public outcomes relating to social media use along with their description and accompanying effects:

Negatives

Positives

Table 3: The positives and negatives of social media activity: the practices, their character and social impacts Practice

Description

Globalization

“Globalization is a process that encompasses the causes, course, and consequences of transnational and transcultural integration of human and non‐ human activities” (Al‐Rodhan et al., 2006)

Democratization

“The transition to a more democratic political regime. It could refer to the transition from an authoritarian regime to a full democracy, a transition from an authoritarian political system to a semi‐democracy or transition from a semi‐ authoritarian political system to a democratic political system” (Przeworski et al., 2000, Wikipedia, 2012)

Networking

Socioeconomic activity by which groups of like‐ minded people recognize, create, or act upon opportunities (cf. Wikipedia, 2012)

Scale benefits

Adding impetus to (online or offline) scale‐related business models facilitating the use of worldwide economic resources and enabling penetration of new markets and client segments

Functional/secondary illiteracy

“Inability to manage daily living and employment tasks that require reading skills beyond a basic level” (Schlechty, 2004)

Intellectual Property (IP) infringement

“An intellectual property infringement is the infringement or violation of an intellectual property right. There are several types of intellectual property rights, such as copyrights, patents, and trademarks. Therefore, an intellectual property infringement may for instance be a copyright infringement, patent infringement or trademark infringement” (Wikipedia, 2012)

Theft, lower propensity to innovate by legitimate IP developers, inefficient allocation of IC

Behavioral addiction

“Syndromes analogous to substance addiction, but with a behavioral focus other than ingestion of a psychoactive substance” (Grant et al., 2010)

Socioeconomic exclusion, lower micro/ macroeconomic, competitiveness,

Misinformation/ Disinformation

““While ‘misinformation’ can be simply defined as false, mistaken, or misleading information, ‘disinformation’ entails the distribution, assertion, or dissemination of false, mistaken, or misleading information in an intentional, deliberate, or purposeful effort to mislead, deceive, or confuse” (Fetzer, 2003)

Cybercrime, distrust in online activity, reputational damage

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Social impacts “World shrinkage”: reducing distances among individuals and groups, leveraging information and promoting interpersonal activity Overcoming information asymmetries, widening access to information, reducing the cost of information gathering and processing Synergies from online interaction among individuals and groups, developing and maintaining interpersonal ties Innovation in products and services, providing access to affordable good and services Socioeconomic exclusion, lower micro/ macroeconomic, competitiveness, inefficient socioeconomic choices

Piotr Wiśniewski

Cybercrime

“Crimes committed on the Internet using the computer as either a tool or a targeted victim” (Computer Crime Research Center, 2012)

Malware, viruses, hacking, scams, fraud and theft, distrust in online activity, reputational damage, stress

Privacy breaches

“A privacy breach is the result of an unauthorized access to, or collection, use or disclosure of personal information. Such activity is ‘unauthorized’ if it occurs in contravention of applicable privacy legislation. Some of the most common privacy breaches happen when personal information is stolen, lost or mistakenly disclosed. A privacy breach may also be a consequence of faulty business procedure or operational breakdown” (OPC, 2012)

Reputational damage, stress, cybercrime, distrust in online activity

Source: own elaboration based on the sources referenced. Although the positives appear to outweigh the negatives in social impact, both categories are interdependent (a great deal of positive outcomes can turn negative if abused). Such an observation might suggest the need for more scrupulous (albeit highly selective and sophisticated) regulation, and measures (e.g. in education) that would promote online accountability. Another way of examining the public impact of social media is reviewing its performance from the global investment perspective. Given the rising trend toward passive investment and fund indexation (Cf. EFAMA, 2012), it would be ideal to use a global proxy for the entire industry. Fortunately, such a proxy has existed since late 2011 as the “Solactive Social Media Index (SOCL)” and has been tracked by the Global X Social Media Index ETF (its composition is summarized in Appendix 3). In spite of limited history, tentative observations can be made as to the SOCL’s performance vs. the widely used benchmark for the U.S. equity universe (the Standard and Poor’s 500 Index, the SPX). They are indicative of social media’s two major investment features (Appendix 4):

relatively high correlation with the broad U.S. equity market returns, limited speculative characteristics: despite exposure to advanced technologies the SOCL’s beta (β) of 1.15 appears exceptionally close to the SPX (the scope for autocorrelation is limited by virtue of solely one stock, Google, being shared by both benchmarks) – this underscores ongoing convergence between social media and the general economy (interestingly, this convergence defies international borders: while the SPX is primarily focused on the U.S., the SOCL’s makeup is truly global);

inferior performance (in absolute and relative terms): the SOCL in the surveyed period posted a negative rate of return, whereas the SPX gained substantially – the SOCL’s risk‐adjusted efficiency has been further downgraded by other (than the β) measures of volatility (high standard deviation, semi‐variance) – this is only partially explainable by the inopportune course of Facebook’s Initial Public Offering (IPO) and a wave of mistrust in Web based business models.

Evidently, the popularity of social media has yet to be matched by solid business models that would captivate the interest of worldwide asset managers. Addressing negative social outcomes would help lure those institutions that are particularly sensitive to socially responsible and impact investment strategies (Cf. Falkowski & Wiśniewski).

4. Conclusion Social media have grown to be a powerful public media genre (whose global reach has begun to eclipse traditional mass media) thanks to unparalleled mobility, accessibility, interactivity, flexibility and scalability. Taking into account the character of currently dominant social media concepts, whereas the precondition of their growth is attributable to Human Capital resources, their commercial viability is primarily being driven by virtual interconnectedness (Customer Capital) and information disclosure and sharing (Structural Capital). Social media commercial relevance will therefore profit mostly from a greater degree of transparency with regard to their business models as well as more emphasis on efficient and legally compliant networking and content dissemination.

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Piotr Wiśniewski As with any globally potent force, social media can be both socially productive and disruptive. The future challenges to a more responsible use of social medial lie in raising public awareness of their public benefits as well as implementing highly selective and sophisticated regulation to curb practices deemed socially onerous. Any successful initiatives of this sort will have to be coordinated globally, mirroring the very essence of social media (based on globalization).

Appendix 1: The “social media” Google 2‐gram and timeline in 1969‐2008

First email sent

Bulletin Board System (BBS): 1st virtual community

Works on the WWW begin at CERN Prodigy: 1st dialup ISP

CERN completes the WWW

D F

B A Compuserve: 1st major Internet provider in U.S.

Usenet: bulletin board linking two U.S. universities

America OnLine (AOL) started

Tripod: online community for students

J H

Source: Google Ngram Viewer [accessed: December 31, 2012]. Events from “The Brief History of Social Media”: http://www.uncp.edu/home/acurtis/NewMedia/SocialMedia/SocialMediaHistory.html [accessed: December 31, 2012]. Notes: A: Beverly Hills Internet (BHI) starts Geocities, B: Newsweek features article “The Internet? Bah! Hype alert: Why cyberspace isn’t and will never be nirvana”, C: The Web has 1m sites, blogging begins, SixDegrees enables profile creation and friend listing, AOL Instant Messenger develops chatting, Blackboard – online education system for teachers and students, D: Google opens up as search engine, E: Friends Reunited – first online social network founded in U.K., F: dot.com bursts, 70 m computers connected to Internet, G: Wikipedia opens up, Apple starts selling iPods, H: Friendster (a social networking site open to public and grows to 3m users in 3 months), AOL has 34 m members, I: MySpace launched (clone of Friendster), Linden Lab opens Second Life online, LinkedIn started, 3bn Web pages reached, Apple introduces iTunes, J: Facebook started by Harvard College students, MySpace outpaces Friendster in page views, online podcasting begins, Flickr image hosting website opens, Digg set up as story sharing social news website, K: Blog Early, Blog Often (BEBO) social networking site started, News Corporation (global media giant) buys MySpace, Facebook launches version for high school students, Friends Reunited (15 m member strong) sold to British ITV, YouTube begins storing and retrieving videos, more than 8bn Web pages in operation, L: MySpace most popular social networking site in U.S. (based on unique visitors), Twitter launched, Facebook made available to anyone over age 13, Google indexing more than 25bn pages, 400 queries daily, 1.3bn images and more than 1bn Usenet messages, M: Microsoft buys stake in Facebook, Facebook initiates Facebook Platform enabling third‐party developers to create applications (“apps”) online, Facebook launches Beacon (targeted advertising system), Apple releases iPhone multimedia and Internet smartphone, N: Facebook surpassed MySpace in monthly unique visitors, fails to buy Twitter, AOL buys Bebo (subsequently to be resold as relatively unsuccessful social media site)…

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Appendix 2: Trends in Google searches of “mass media” (blue line) and “social media” (red line) in English‐language online resources in 2004‐2013* Forecast beyond 2012 using Google Trends

At this point “social media” outnumbered “mass media”

Source: Google Trends [accessed: December 31, 2012]. Note: examples of Google search results: A: Montreal Gazette (“Greek parties jump on social media bandwagon”), B: MarketWatch (“China Mass Media Reports)…(*) Forecasts using Google Trends.

Appendix 3: Top fund holdings for the SOCL as of December 30, 2012 Issuer name

Position

Value

Share of Total

Facebook Inc.

66,578

1,864,184

14.296%

LinkedIn Corp.

12,096

1,308,061

10.032%

Tencent Holdings Ltd.

38,914

1,271,325

9.750%

Dena Co Ltd.

32,464

1,191,285

9.136%

SINA Corp/China

22,610

1,029,207

7.893%

Mail.ru Group Ltd.

19,270

635,910

4.877%

Yandex NV

27,418

598,261

4.588%

Gree Inc.

33,889

589,106

4.518%

Google Inc.

832

581,044

4.456%

Nexon Co. Ltd

48,159

539,806

4.140%

Source: http://www.bloomberg.com/quote/SOCL:US [accessed: December 30, 2012]. Highlighted in gray is the only common issuer for both indices (Google, Inc.).

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Appendix 4: Performance analysis of the Solactive Social Media Index (SOCL) vs. the Standard and Poor's 500 Index (SPX) in the period November 30, 2011‐ December 31, 2012

Start Date

Summary “Global X Social Media Index ETF is an exchange‐traded fund incorporated in the USA. The Fund seeks to track the performance of the Solactive Social Media Index (SOCL).” (Bloomberg, 2012). “Standard and Poor's 500 Index (SPX) is a capitalization‐weighted index of 500 stocks. The index is designed to measure performance of the broad domestic economy through changes in the aggregate market value of 500 stocks representing all major industries. The index was developed with a base level of 10 for the 1941‐ 43 base period.” (Bloomberg, 2012). November 30, 2011

End Date

December 31, 2012

Currency

US$

Frequency

Daily

Index categories

Total Return

Portfolio description Benchmark description

Total Return: ‐2.240 Benchmark: 17.189 Performance Analysis Performance: Daily Total Return 1 Month(s)

Portfolio (SOCL)

Benchmark (SPX)

1.01

0.91

Total Return MTD

1.01

0.91

Total Return QTD

‐5.36

‐0.38

Total Return YTD Total Return 3 Month(s) Total Return 6 Month(s) Total Return 1 Year(s) Total Return 2 Year(s) Total Return 3 Year(s)

‐0.37

16.00

‐5.36

‐0.38

‐4.75

5.95

‐0.37

16.00

n/a

18.45

n/a

36.30

Risk: Weekly Standard Deviation 1 Year(s) Semivariance 1 Year(s)

Portfolio (SOCL)

Benchmark (SPX)

25.02

11.79

23.41

12.42

Beta 1 Year(s) Correlation 1 Year(s) R‐Squared 1 Year(s) Information Ratio 1 Year(s) Sharpe Ratio vs Risk Free 1 Year(s) Tracking Error 1 Year(s)

1.15

n/a

0.54

n/a

0.30

n/a

‐0.56

n/a

0.01

1.17

20.87

n/a

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Piotr Wiśniewski Source: calculations based on data downloaded from the Bloomberg Professional service, index definitions rom: http://www.bloomberg.com/markets/ [accessed: January 4, 2013].

References Al‐Rodhan, N.R.F. et al. (2006), Definitions of Globalization: A Comprehensive Overview and a Proposed Definition, Geneva Centre for Security Policy, Program on the Geopolitical Implications of Globalization and Transnational Security, Geneva, Switzerland, pp. 1‐21. Bloomberg (2012): Computer Crime Research Center (2012), definition of “cybercrime”: http://www.crime‐research.org/articles/joseph06/ [accessed: December 31, 2012]. Dumay, J. (2012), IC is Alive and Well Yet Still Seeking Relevance, Editorial for the ECIC Special Issue of the Electronic Journal of Knowledge Management (EJKM), Academic Publishing International Ltd., Volume 10, Issue 3, Reading, United Kingdom, pp. 1‐4. Edvinsson, L., Malone, M.S. (1997), Intellectual Capital. The Proven Way to Establish Your Company’s Real Value by Measuring its Hidden Brainpower, HarperBusiness (HarperCollins Publishers, Inc.), London, United Kingdom. EFAMA – European Fund and Asset Management Association (2012), Factbook, Trends in European Investment Funds, 10th Edition, Brussels, Belgium, pp. 1‐324. Falkowski, M., Wiśniewski, P. (2013), Impact Investment as a New Investment Class, Contemporary Economics (forthcoming), Warsaw, Poland, pp. 1‐25. Fetzer, J.H. (2003), Information: Does it Have To Be True?, Minds and Machines, Volume 14, Issue 2, Lisbon, Portugal, pp. 223‐229. Google Ngram Viewer (2012): http://books.google.com/ngrams [accessed: December, 30, 2012]. Google Trends (2012): http://www.google.pl/trends/ [accessed: December 30, 2012]. Grant, J.E. et al. (2004), Introduction to Behavioral Addictions, The American Journal of Drug and Alcohol Abuse, Vol. 36, No. 5, US National Library of Medicine, London, United Kingdom, pp. 233‐241. Hudson, W.J. (1993), Intellectual Capital. How to Build It, Enhance It, Use It, John Wiley & Sons, Inc., New York, United States of America, pp. 1‐231. Kaplan, A.M., Haenlein, M (2010) Users of the World, Unite! The Challenges and Opportunities of Social Media, Kelley School of Business, Indiana University/Business Horizons, Elsevier, No. 52, Amsterdam, The Netherlands, pp. 59‐68. Kaplan, A.M., Haenlein, M (2012) Social Media: Back to the Roots and Back to the Future (invited comment on the theme of the special issue); Social Media: Back to the Roots (Special Issue), Journal of Systems and Information Technology, Emerald Group Publishing Limited, Vol. 15, No. 2, Bingley, United Kingdom, pp. 101‐104. Miller, A (2011) 6 Classifications of Social Media (Blog) http://www.prmarketing.com/blog/6‐classifications‐of‐social‐ media/ [accessed: December 31, 2012]. OPC, Office of the Privace Commissioner of Canada (2012): http://www.priv.gc.ca/resource/pb‐avp/pb_hb_e.asp [accessed: December 31, 2012]. Przeworski, A. et al. (2000), Democracy and Development: Political Institutions and Well‐Being in the World, 1950‐1990, Cambridge University Press, Cambridge, United Kingdom, pp. 1‐336. Roos, G. et al. (2005), Managing Intellectual Capital in Practice, Butterworth‐Heinemann/Elsevier, Inc., Burlington, MA, United States of America, pp. 1‐258. Schlechty, P.C. (2004) Shaking Up the Schoolhouse: How to Support and Sustain Educational Innovation (Jossey‐Bass st Education, Imprint of John Wiley & Sons, Inc.), 1 Edition, New York, United States of America; samples available online at: http://catdir.loc.gov/catdir/samples/wiley031/00009570.pdf [accessed: December 31, 2012]. Stewart, T.A. (1997), Intellectual Capital. The New Wealth of Organizations, Doubleday/Currency, New York, United States of America, pp. 1‐246. Stewart, T.A. (2001), The Wealth of Knowledge. Intellectual Capital and the Twenty‐First Century Organization, Nicholas Brealey Publishing/Utopia Limited, London, United Kingdom, pp. 1‐336. Sullivan, P.H. (2000), Value‐Driven Intellectual Capital. How to Convert Intangible Corporate Assets into Market Value, John Wiley & Sons, Inc., New York, United States of America, pp. 4‐7. The Social Media Guys (2010), online research reports available on the The Social Media Guys website (http://www.thesocialmediaguys.co.uk/resources/:) http://www.thesocialmediaguys.co.uk/wp‐ content/uploads/downloads/2011/03/CompleteGuidetoSocialMedia.pdf [accessed: December 31, 2012].

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Revived Brands as Intangible Assets: Two Qualitative Case Studies Aleksandra Zaleśna Bogdan Janski School of Management and Entrepreneurship, Lomza, Poland aleksandrazalesna@wp.pl Abstract: The purpose of this paper is to shed light on a dormant brand as an intangible asset and on factors which distinguish successful and unsuccessful brand revival. Brands are identified as market assets and as a part of relational capital. However, is it the same for dormant brands? Are they forgotten intangible assets? Dormant brands as well as brand awareness can be seen as intangible assets because they are immaterial and invisible. However, this issue is little researched, especially from the perspective of intellectual capital. The revival of such a brand is sometimes successful, sometimes not. The paper investigates what factors influence the success of brand revival. It also explores how to discover the potential (attractiveness) of a brand which had been unused for a long time. There is the need to broaden the definition of relational capital. It is often associated with knowledge embedded in relationships with customers (and other stakeholders). However, when it comes to dormant brands this knowledge about customers (values, purchase intentions) is uncertain. Over years they have changed. It is hard to say anything about stable relationships with customers. Data about market share, brand awareness, customer loyalty are all past history. On the other hand, it is still possible to gain ‘old’ and new customers which in consequence will generate future value for a company. The methods to measure relational (customer) capital are not sufficient when it comes to dormant brands. Literature and research concerning this issue are very scarce. Moreover, in practice, opinions about brand revival are contrary. Thus, the research question becomes: how to measure the value of a dormant brand? The next research question is: when is brand revival successful? In exploring when brand revival is successful or not, two qualitative case studies are being conducted. They concern two Polish brands in the fast moving consumer goods (FMCG) market which were dormant for some years. An exploratory case study method was used to gain an understanding of which factors determine the value of such a brand and a successful reintroduction to the market. The data collection procedures employed were documentation and archival records. The findings might be interesting for companies which consider reviving a dormant brand. By defining critical factors which distinguish successful and unsuccessful brand revivals it is possible to give guidance on how to measure the value of a dormant brand and create new relational capital. Keywords: brand revival, relational (customer) capital

1. Definition of a brand What is a brand? There are numerous definitions of the brand and therefore its meanings are variable (Stern, 2006). Moreover, the meaning of ‘brand’ varies between managers in the same organization (de Chernatony, 2009, p. 101). Brand is one of the most valuable assets that companies have (Keller and Lehman, 2006, p. 740). Brand can be defined as a promise of benefits to the consumer (Raggio and Leone 2007, p. 390). De Chernatory and Dall’Olmo Riley identified twelve categorizations for brand definitions. The brand can be seen as: legal instrument, logo, company, shorthand, risk reducer, identity system, image in consumers’ mind, value system, personality, relationship, adding value, evolving entity (de Chernatory, Dall’Olmo Riley, 1999, p. 418). According to these authors, the brand is “a complex multidimensional construct whereby managers augment products and services with values and this facilitates the process by which consumers confidently recognize and appreciate these values” (de Chernatory, Dall’Olmo Riley, 1998, p. 436). Kapferer points out that consumers now have a wide choice and at the same time they have no time to compare the products or services before they make a choice. Brands are then a time and risk reducer. Thus, brands must convey certitude and trust (Kapferer, 2008, p.11). A brand is a consumer’s idea of a product. The name itself is not as important as the image that the name conveys to consumers (Rotfeld, 2008). Some authors use metaphors to describe what a brand is. Davies and Chun (2003) proposed three main root metaphors: brand as differentiating mark, brand as person, and brand as asset (p. 49). Brand as a differentiating mark stems from the idea that a mark should be unique and a brand name should both identify and distinguish something. The idea of having a relationship with a brand which can be described as trust and friendship leads to the use of the brand as person metaphor. Brand as an intangible financial asset is valuable and is seen as investment for the future. Its valuation might be included within the balance sheet. Lev (2004) suggests separating a company’s expenditures in brand enhancement, among others, from general costs (p.114). This would let managers see how these investments change over time and what benefits they bring in the future.

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2. Brand construct: Brand equity and brand value According to de Chernatory and Dall’Olmo Riley “the firm’s activities (input) and consumers’ perception (output) emerge as the two main boundaries of the brand construct, setting the condition (…) for the very existence of the brand itself” (1999, p. 428). It should be noted that brand exists to serve customers, not the other way around (Rust, Zeithaml and Lemon, 2004, p.110). It should also be noted that brand equity and brand value are not the same constructs. Brand equity is what the brand means to the consumer whereas brand value is what the brand means to the company. Brand equity is an individual‐level construct and neither the brand nor the firm ‘owns’ a brand’s equity (Raggio and Leone, 2007, p. 386). Brand equity may exist among consumers. It is the heart and mind of the consumers that determine brand equity. Brand equity contributes to particular outcomes and to some extent it makes marketing activities effective (see Raggio and Leone, 2007, p. 385). Brand equity must be actively managed over time by reinforcing the brand meaning and by revitalizing the brand (Keller, 1999, p. 103). The sources of brand equity are: brand awareness and brand image. Without these sources of brand equity, the brand itself may not continue to yield valuable benefits (Keller, 1999, p. 107). Similar to Keller’s view is the concept of brand equity proposed by Rust, Zeithaml and Lemon (2004). Brand equity is driven by three components: brand awareness, attitude toward the brand, and brand ethics. However, in contrast to Keller’s view, brand equity is not the point. Customer equity is the point. The goal of management is to grow customer equity which means maximizing customer lifetime value. Brand equity is a means to this end. Furthermore, brands may come and go. Thus, companies should focus on customer equity rather than brand equity (Rust, Zeithaml, Lemon, 2004, pp. 112‐114).

3. Relationships and brands as IC components Intellectual capital is the sum of ‘hidden’ assets in the company as they do not appear on its balance sheet. These assets are considered to support company success. From a strategic standpoint, intellectual capital is used to enhance company value. Various classifications of intellectual capital are presented in the literature (Andriessen, 2004). However, a convergent taxonomy emerged. Intellectual capital is divided into three categories: human, relational and structural capital. For the purpose of this article, relational capital is the topic of interest. For Roos, relationships are part of structural capital (1997). For others, relational capital is considered independently. Relational capital includes customer relationships, supplier relationships and relationships with other stakeholders (investors, public, partners etc.). These relationships are needed for building, maintaining and renewing a company’s resources (Cabrita and Vaz, 2006, p.12). Companies depend greatly on the relationships they build up in their environment (Hormiga et al, 2011, p. 620). Intangible assets include among others strong customer relationships and brands (Lev 2004; Teece, 2000; Roos et al. 1997). Brand is one of the most valuable assets that companies have (Keller and Lehman, 2006, p. 740). Brand is one of the components of relational capital (Carrington and Tayles, 2011, p. 141). For Brooking, brand is one of the market assets (Brooking, 2010, p. 137). Sveiby mentions brand names as an element of external structure of IC (Sveiby, 1998b). Petty and Guthrie include brands as an element of external (relational, customer) capital in their modified intangible assets monitor (2000, p. 166).

4. Dormant brands: Dormant brands as intangible assets Some brands may become passé and disappear. Dormant brands are unused for a long time and are eliminated from the marketplace. Yet still they can be in consumers’ minds. Consumers can still recognize the brands. Based on this belief, companies reintroduce products into the market (see Henning, 2004, p. 20). It is not possible for a brand to have no brand equity (Raggio and Leone 2007, p. 381). Because of the associations consumers make, some level of brand equity always exists. It must be emphasized that this brand equity is established by the existence of associations in the memory, not by outcomes such as purchase (Raggio and Leone, 2007, p. 382). In other words, it means that dormant brands might still have some level of brand equity. Raggio and Leone (2007, p. 385) define “brand equity as the perception or desire that a brand will meet a promise of benefits”. This could also be the case for nostalgia brands.

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Aleksandra Zaleśna Dormant brands are intangible assets, too. It must be emphasized that they are forgotten intangible assets. Actually, there is no definition of intellectual capital (or relational capital) that would include them. Intangible assets are invisible and untouchable. However, they can make the difference when it comes to market value. They create future benefits. The same is for dormant brands. They are still in consumers’ minds. In addition, similar to human capital, they are not ‘owned’ by a company (as a brand ceases to exist). However, when successfully revived, it is possible that dormant brands can bring fortune.

5. Brand revival Positive customer‐based brand equity is essential for a company considering reviving a no longer marketed brand (Henning, 2004, p. 18). Nowadays, through social networking sites such as Facebook consumers have the power to influence the return of a dormant brand. This was the case for the Wispa brand (McDermott, 2008). According to Keller (1999, p. 103) consumer brand knowledge has an indirect impact on the success of future marketing activities. This is true. However, it concerns existing brands. When it comes to dormant brands the knowledge about consumers is uncertain. Over years they have changed. Consumers are losing interest in many brands (Gerzema, 2009, p. 8). Not so many people are loyal to one brand. Brand awareness falls, perception of brand quality declines, and trust in brands erodes by almost 50% (Gerzema, 2009, p. 8). Furthermore, the marketing environment evolves and changes. In this regard the question is: what strong and favorable brand associations exist in the minds of consumers? Data about market share, brand awareness, customer loyalty are all past history. On the other hand, it is still possible to gain ‘old’ and new customers which in consequence will generate a future value for a company. The research question becomes: how to measure the value (attractiveness) of a dormant brand? The next question is: when is brand revival successful?

6. Methodology A case study method was used to gain an understanding of what factors determine the value (attractiveness) of such a brand and a successful reintroduction to the market. The data collection procedures consisted of documentation, archival records (newspaper articles, marketing brochures) as well as ‘netnography’ (Brown, Kozinets and Sherry, 2008, p. 22). The internet is a place where information is publicly available in online forums. ‘Netnography’, or ethnography on the Internet, can be a useful and unobtrusive method for studying the language and motivations of online consumers (Kozinets, 2002, p.68). The topic of interest was two polish brands: the Frugo (a fruit drink) and the Polo Cockta (a Coca‐Cola‐like drink). These brands were dormant for a couple of years, and then they were revived. The cases were selected because of ease of access to data and information and because of the similarity of the products. The topics of interest were the opinions of customers about these brands expressed at particular online forums (forum.wirtualnemedia.pl). Data were copied. First, observation of textual discourse took place, and then content analysis was used for analysing the content of conversational acts. There is limited generalization in the study.

7. Two qualitative case studies Case study: A fruit drink Frugo Frugo – a fruit drink – was introduced first in 1996. Brand consistency is critical in maintaining the strength of brand associations (Keller, 1999, p. 103). Meanwhile the company introduced Frugo Ego which diminished its consistency. Market share fell to about 2%. After six years the producer sold the brand as it no longer fitted with the strategic direction. The company which bought the Frugo faced bankruptcy and the brand ceased to exist. Meanwhile, the customers created fan‐pages and through online sites they expressed their nostalgia for the drink. The brand was later bought by FoodCare Group. After six years of dormancy the brand was reintroduced in 2011. New ad campaigns were launched only on the Web sites such as Facebook. Within six months the sales were 80 million bottles of this drink. The market share was 15%. In just one week of August more than 2 600 online customers made comments on Frugo, whereas about 300 customers expressed their opinions on the Coca‐Cola brand. The brand revival seems to be successful.

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Aleksandra Zaleśna Customers are in their twenties or thirties. They remember the brand from childhood. When it comes to attitudes, the consumers enjoy Frugo; they are even curious about the taste of the blue Frugo (actually, it never appeared on retailers’ shelves). Nowadays, the brand is being extended to other new products (jellies) and new versions (new tastes). Customers may not think about the company that provides a product. In a small sample of students at a university in Lomza (Bogdan Janski University of Management and Entrepreneurship) all remembered Frugo. But when asked who the producer was, not one student answered the question. This is consistent with the study carried out by Holehonnur et al (2009). Case study: A drink Polo Cockta (Polo Cola) The Polo Cockta was introduced in the 1970s and it was a Coca‐Cola‐like drink. In the beginning of the 1980s the brand ceased to exist. The company Zbyszko acquired the rights to the brand and tried to revive it in the 2000s. Despite heavy investments in advertising campaigns, the return was unsuccessful. Nostalgia was not enough to gain ‘old’ customers or attract new customers. One of the reasons of the failure was that the brand had been dormant for more than 20 years. The other reason was that the young generation of customers (16‐22 year‐olds) did not have positive associations with the brand. They could not remember it from childhood. Moreover, the product quality was perceived as poor. Customers had a wide choice of drinks. As a result, the level of brand equity was very low. The efforts for the brand revival were futile. The management decided to change the name (to Polo Cola), the logo and price strategy. A new ad campaign was launched. As a result, the sales increased. Despite the economic crisis, the sales are still growing which brings the company to the fourth position in the marketplace (data for 2012).

8. Attractiveness of a dormant brand The research question is: how to measure the value of a dormant brand? Here the ‘value’ is a synonym of attractiveness. To manage something, you need to be able to measure it. However, the methods to measure relational (customer) capital are not sufficient when it comes to dormant brands. For example, Skandia Navigator (Edvinsson and Malone, 1997) and Intangible Assets Monitor measure brands that exist, not dormant brands. The literature and research concerning this issue is very scarce. Moreover, in practice opinions about brand revival are contrary. Some authors emphasize that dead brands should lie (Edwards, 2011). Others give examples of successful brand revivals (McDermott, 2008). On the one hand, the combination of fame, heritage and affection does not automatically translate into sales (Edwards 2011, p.21). On the other hand, a well‐known brand reduces risk. Dormant brands, when successfully relaunched, may bring more benefits than a completely new brand. Moreover, strong brands contribute to reduced marketing costs (Raggio and Leone, 2007, p. 385). What is essential is that the revived brands must be repositioned to satisfy today’s customers’ values (Bellman, 2005). To better understand factors influencing the attractiveness (potential) of dormant brands, one needs to pay attention to brand equity, which was discussed earlier. Brand awareness and brand attitudes are factors that drive perceptions of brand equity, with attitudes being the strongest (Holehonnur et al, 2009, p. 174). Personal experiences as well as the experience of others determine what a customer thinks of a brand (Keller and Lehmann, 2006, p. 754). McKenna points out that a successful brand is characterized as having a special relationship between the customer and the company (McKenna, 1991, p.). This is only partly true. When it comes to dormant brands, though, it is difficult to talk about a firm’s activities as well as the relationship. A brand is a consumer’s idea of a product. In other words, a brand is an image in consumers’ minds. People have memories of a product. They do not care about which firm manufactured the product. They do not have to associate a brand name with the producer. As stated by Holehonnur et al (2009), consumers may be so familiar with the brand that they do not think about the company that provides the product (p. 176).

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Aleksandra Zaleśna It should be noted that there are some difficulties “in assessing whether or when internal measurement of intangible assets improves economic performance” (Ittner, 2008, pp. 269‐270). Research on the links between the measurement of intangible assets and economic outcomes is still needed. In the attempt to answer the above research question I suggest five factors to be essential for determining the attractiveness of dormant brands. These are: brand awareness, time of dormancy (brands disappeared not so long ago), distance in time (brands that are not so old), positive associations (brand image), willingness to buy and try. See Figure 1 for a conceptualization of the model. Willingness to try

Brand awareness

Attractiveness of a dormant brand Brand image

Time of dormancy

Distance in time

Figure 1: The conceptualization of a model for assessing the attractiveness of dormant brands The next research question is: when is brand revival successful? Case examples demonstrate that some potential of a dormant brand is needed. Not only is brand equity important, but also such factors as time of dormancy and distance in time (brands not old enough to be associated with an older generation). When time of dormancy is long (more than 20 years as it was in the case of the Polo Cockta), then the attractiveness of such a brand is low. The same is for distance in time. Since the brand disappeared, customers have become older. If the younger generation still remembers the brand, it is possible for the brand to be successfully revived. If, however, distance in time means that the brand is associated with the older generation (parents, grandparents) and it does not appeal to young people, then the attractiveness of such a dormant brand is low. In the case of the Frugo drink the time of dormancy and the distance in time were quite short (and the young generation as well as customers in their thirties still express purchase intentions). The next important factor is willingness to try. It opens up opportunities for innovation. For brands whose core associations are primarily product‐related attributes, innovation in product design, manufacturing and merchandising is critical to enhancing brand equity (Keller, 1999, p.107). In addition to successful brand revival, marketing and logistic support are needed. Otherwise, efforts would be futile and the brand loses ground instead of being successfully revived.

9. Extended definition of relational capital Relational capital along with structural capital and human capital constitutes most notions of intellectual capital. Relational capital includes relationships with customers, suppliers, investors, public and other stakeholders. However, these relationships concern current customers, not customers who had been left when a company decided to stop offering specific brands. Thus, I suggest when a brand ceases to exist, customers become ‘castaway’. Brands can disappear for many reasons. However, they are still in the mind of consumers and therefore they have some level of brand equity. If associations are positive, the brands might still have some potential for revival. Those customers might be powerful in creating online communities which campaign for specific products. In the case of dormant brands, there are no relationships between a company and customers. There are just relationships between customers and the specific brand. It is consistent with the metaphor of a brand as a person. When a brand exists, then it is possible to speak about relational capital, in particular about relationships between the manufacturer and its customers. If the company eliminates the brand from the marketplace, then

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Aleksandra Zaleśna the company breaks off these relationships. However, those customers may still have a liking for that brand. Taking into consideration a metaphor of a brand as a person (Davies and Chun, 2003), it is possible to speak about relationships between customers and the brand. But can this kind of relationship still be attributed to the relational capital? Describing the relationship that customers have with product brands using a relationship capital construct might be problematic. It refers to the relationships with stakeholders, organizations, groups of interest (Hormiga et al, 2011) etc. Relationship capital does not adequately describe the nature of relationships that people have with intangible, inanimate objects (brands). Therefore, on the one hand, it is problematic whether to speak of customers’ relationships with brands under relational capital theory. On the other hand, however, it is possible to include this type of relationship in relational capital. Some authors include brands among relational capital (Carrington and Tayles, 2011; Petty and Guthrie, 2000). The reason is, the brand is still in the heart and mind of customers. Moreover, these customers create groups using the Web sites (online communities). They are active and express their opinions. For this reason it is possible to state that relationships exist and so does relational capital. Actually, there is no definition of relational capital which includes relationships between customers and dormant brands. This is because intellectual capital is seen from the angle of a company. Like human capital, ‘castaway’ customers are not owned by a company. However, this group is a source of information for a company considering the revival of a dormant brand. Furthermore, this group might be the source of value. It makes it easy for a company to create and develop its relational capital by finding its hidden customer power. Sveiby argues that most customers are sources of value because they “provide training for employees, they can act as references, they talk to each other and so spread the word and the image, and their demands encourage the development of new products” (Sveiby, 1998 b). In this regard I suggest that castaway customers are still the source of value. Here ‘netnography, might be helpful. Through online communities customers provide insights into brand meanings. As discussed earlier, customers have some knowledge about a brand and it is characterized in terms of brand awareness and brand image (Keller, 1999, p. 102). This knowledge might be useful in formulating branding strategies (Kozinets, 2002, p.68). In other words, the knowledge from ‘castaway’ customers can be converted into profits. Therefore, active ‘castaway’ customers should be regarded as part of relational capital, provided that brand equity has not deteriorated. In general, the concept of intangibles is young, with only three decades of research (Kristandl and Bontis, 2007, p.1521). Examining the intangibles from the resource‐based view (RBV) of a firm is not sufficient, when it comes to ‘castaway’ customers. In this regard, social identity theory would be appropriate. This theory is “appropriate for examining customer‐brand relationships because identification has important implications for maintaining relationships despite relationship disruptions” (Lam, Ahearne, Hu and Schillewaert, 2010, p. 129). Disruptions threaten customer‐brand relationships. The brand ceases to exist. However, customers still remain and so does their remembering and nostalgia for dormant brands. If the time of dormancy is not so long and if customers are active through online communities, then it is still possible to revive a brand successfully. A company which succeeds in that will develop its customer (relational) capital. A revived brand becomes a company’s intangible asset.

10. Conclusions Consistent with Raggio and Leone, I suggest that brand equity is what the brand means to the consumers. Even if brands were eliminated from the marketplace, they are still in the consumers’ mind. Dormant brands might have some potential. That is why some entrepreneurs (companies) reintroduce these brands to the market. Brand awareness is important; however, more important is the issue concerning attitudes (Holehonnur et al, 2009, p. 174). The time of dormancy and the distance in time also play a role in determining the value of a dormant brand. The case studies provide insights for managers considering a brand revival and creating relational (customer) capital. Further research is needed to explore relational (customer) capital in the case of a market disruption such as a brand elimination from the marketplace and a brand revival.

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References Andriessen, D. (2004) Making sense of intellectual capital: designing a method for the valuation of intangibles, Elsevier Butterworth‐Heinemann, Oxford. Bellman, L. (2005) “Entrepreneurs: invent a brand name or revive an old one?”, Business Horizons, Vol. 48, Issue 3, May‐ June, pp. 215‐222. Brooking, A. (2010) “On the Importance of Managing Intangible Assets as Part of Corporate Strategy”, Proceedings of the European Conference on Intellectual Capital, pp. 137‐151. Brown, S., Kozinets, R.V. and Sherry, J.F. Jr (2003) “Teaching Old Brands New Tricks: Retro Branding and the Revival of Brand Meaning”, Journal of Marketing, July, Vol. 67, Issue 3, pp. 19‐33. Cabrita, M. and Vaz, J. (2006) “Intellectual Capital and Value Creation: Evidence from the Portuguese Banking Industry”, The Electronic Journal of Knowledge Management, Vol. 4, Issue 1, pp. 11‐20. Carrington, D. and Tayles, M. (2011) “Exploring IC in the Caribbean Hospitality Industry: Two Qualitative Case Studies”, Proceedings of the 4th European Conference on Intellectual Capital, pp. 136‐146. Davies, G. and Chun, R. (2003) “The Use of Metaphor in the Exploration of the Brand Concept”, Journal of Marketing Management, February, Vol. 19, Issue 1‐2, pp. 45‐71. De Chernatony, L. (2009) “Towards the holy grail of defining ‘brand’”, Marketing Theory, Vol. 9, No. 1, pp. 101‐105. De Chernatory, L. and Dall’Olmo Riley, F. (1998) “Defining a “Brand”: Beyond the Literature with Experts’ Interpretations”, Journal of Marketing Management, Vol. 14, Issue 4‐5, pp. 417‐443. Edvinsson, L. and Malone, M.S. (1997) Intellectual capital. Realizing your company’s true value by finding its hidden brain power, Harper Business, New York. Edwards H. (2011) “Let dormant brands lie”, Marketing, 10 August, pp. 21. Gerzema J. (2009) “The Brand Bubble”, Marketing Research, Spring, Vol. 21, Issue 1, pp. 6‐11. Henning, N. (2004) Brands in the Retrospective – A consumer motivation study, Master’s Thesis, GRIN Publishing, Munich. Holehonnur, A., Raymond, M.A., Hopkins, C.D. and Fine, A.C. (2009) “Examining the customer equity framework from a consumer perspective”, Journal of Brand Management, Vol. 17, No. 3, pp. 165‐180. Hormiga, E., Batista‐Canino, R. and Sanchez‐Medina, A. (2011) “The Impact of Relational Capital on the Success of New Business Start‐Ups”, Journal of Small Business Management, Vol. 49, No. 4, pp. 617‐638. Ittner, Ch.D. (2008) “Does measuring intangibles for management purposes improve performance? A review of the evidence”, Accounting and Business Research, Vol. 38, No. 3, pp. 261‐272. Kapferer, J.‐N. (2008) The New Strategic Brand Management: Creating and Sustaining Brand Equity Long Term, Kogan Page, London and Philadelphia. Keller K.L. (1999) “Managing Brands for the Long Run: Brand Reinforcement and Revitalization Strategies”, California Management Review, Vol. 41, No. 3, pp. 102‐124. Keller, K.L. and Lehmann, D.R. (2006) „Brands and Branding: Research Findings and Future Priorities”, Marketing Science, Vol. 25, No. 6, November‐December, pp. 740‐759. Kozinets R.V. (2002) “The Field Behind the Screen: Using Netnography for Marketing Research in Online Communities”, Journal of Marketing Research, Vol. 39, Issue 1, February, pp. 61‐72. Kristandl, G. and Bontis, N. (2007) “Constructing a definition for intangibles using the resource based view of the firm”, Management Decision, Vol. 45, No. 9, pp. 1510‐1524. Lam, S.K., Ahearne, M., Hu, Y. and Shillewaert, N. (2010), “Resistance to Brand Switching When a Radically New Brand is Introduced: A Social Identity Theory Perspective”, Journal of Marketing, Vol. 74, November, pp. 128‐146. Lev, B. (2004) “Sharpening the Intangible Edge”, Harvard Business Review, Vol. 82, Issue 6, June, pp. 109‐116. McDermott, P. (2008) “Coming back from the dead”, Brand Strategy, March, Issue 220, pp. 38‐39. McKenna, R. (1991) “Marketing is Everything”, Harvard Business Review, Vol. 69, Issue 1, January‐February, pp. 65‐79. Petty, R. and Guthrie, J. (2000) “Intellectual capital literature review. Measurement, reporting and management”, Journal of Intellectual Capital, Vol. 1, No. 2, pp. 155‐176. Raggio, R.D. and Leone, R.P. (2007) “The theoretical separation of brand equity and brand value: Managerial implications for strategic planning”, Journal of Brand Management, Vol. 14, No. 5, May, pp. 380‐395. Roos, G. and Roos, J. (1997) “Measuring your Company’s Intellectual Performance”, Long Range Planning, Vol. 30, No. 3, pp. 413‐426. Roos, G., Roos, J., Edvinsson, L. and Dragonetti N.C. (1997) Intellectual Capital – Navigating in the new business landscape, New York University Press, New York. Rotfeld, H.J. (2008) “Brand image of company names matters in ways that can’t be ignored”, Journal of Product and Brand Management, Vol. 17, No. 2, pp. 121‐122. Rust, R.T., Zeithaml, V.A. and Lemon, K.N. (2004) “Customer‐Centered Brand Management”, Harvard Business Review, Vol. 82, Issue 9, September, pp. 110‐118. Stern, B.B. (2006) “What Does Brand Mean? Historical‐Analysis Method and Construct Definition”, Journal of the Academy of Marketing Science, Spring, Vol. 34, No. 2, pp. 216‐223. Sveiby, K.‐E. (1998a) “Intangible revenues”, [online], www.sveiby.com/articles/IntangibleRevenues.html. Sveiby, K.‐E. (1998b) “Measuring Intangibles and Intellectual Capital – An Emerging First Standard”, [online], www.sveiby.com/articles/EmergingStandard.html. Teece, D.J. (2000) Managing intellectual capital, Oxford University Press, Oxford.

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Building Intellectual Capital by Using Computer Technology for Ver‐ nacular Creativity and Well Being in Nursing Home Residents: An Action Learning Approach John Zanetich Berkeley College, New York, USA jtz@berkeleycollege.edu Abstract: This presentation will provide participants with an understanding of the historical context and positive effects on intellectual capital of a technology based service‐learning project for both students and residents of a long term residential care facility. While intellectual capital (IC) and emerging technologies are linked in the working population, this connection has not been widely used with the elderly. The goal of creating this connection in the frail elderly is to create means for meaningful actions and possibilities to act as equal citizens. It is important that the resources and independent initiative of older people are stressed. If the functional capacity of older people is supported at the right time and in the right place, it is preventive, cost‐effective and productive. Finding ways of using digital media to build intellectual capital in the elderly in nursing homes becomes the challenge. A grounded theory linking vernacular creativity, folk art and well being using an iPad was developed during a college supported 3 year educational action learning project at a large, metropolitan nursing home. The project determined usability of an iPad and investigated preferences of over 135 residents for content collec‐ tions of photographs, music playlists, e‐books, as well as use of e‐mail, search engines, video sharing websites (Youtube) and video and voice‐over‐Internet software (Skype). Approximated 60 college students in 5 different courses participated in some segment of this iterative project. Project start‐end dates coincided with those of the college level service learning course and learning outcomes were defined in the syllabus. The touch pad features of an iPad present an opportunity to provide previously unavailable resources to frail residents in a nursing home. Computer technology can be a cost‐effective way to engage individuals in self‐selected creative activities that, when viewed as folk art, support feelings of wellbeing and build intellectual capital. Examples of vernacular creativity and folk art include decorated eggs, road side memorials to car victims, homemade shrines to Elvis and Di, photos and photo albums. Folk art is a matter of communication of creativity, not an abstract aesthetic value. Computer technology is a new artistic, creative tool much like the Kodak camera was at its inception. In 2006 Apple marketed the iPad and promised users access to creativity through software and effortless usabil‐ ity in hardware. Apple forged a campaign to blend ordinariness, creativity and technology in the iPad. The iPad’s light‐ weight, touch screen technology and graphic user interface provides long‐term care residents with an opportunity to be creative and share that creativity. The use of technology in problem based learning in a college academic service learning course enables the community to become co‐educators and supports students by providing them with professional skills. It also recognizes community voices in defining needs, faculty expertise in developing projects to address defined needs, uses students' voices in implementing community learning projects, and builds intellectual capacity by introducing technology as a creative tool that produces a feeling of well‐being to physically infirm residents in long term care and builds intellec‐ tual capital. Keywords: intellectual capital, vernacular creativity, technology, well‐being, educational action strategy

1. Introduction Managers at all levels in residential health care facilities are charged with increasing value by maximizing the monetary, relational, organizational, physical and competence resources of the organization (Roos, 2009; Aaronson 1994). The traditional resources of money, buildings, employees, and management teams are typi‐ cally viewed as areas for maximizing outcomes and as adding value to the organization. Recent advances in the study of knowledge management have pointed to the ways in which competence adds value (Ammann 2009). Until recently, building competence in an organization has been concentrated in human resources and in per‐ sonnel practices that include credentialing, training, record keeping and productivity in terms of performance reviews (Marr 2008). However, recipients of service have only recently received attention in terms of cus‐ tomer satisfaction, social media, marketing and brand loyalty. This initial focus on user competence has re‐ sulted in the recognition that, for patients, treatment results and feelings of well‐being improve when patients participate in the management of their illnesses. Self‐management of chronic conditions such as diabetes, obesity, blood pressure and mental health using customized protocols has produced many cost saving benefits and, as such, clinical self‐ management contributes to both the value of the firm and the intellectual capital of the healthcare service provider.

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John Zanetich In turn, the technology used by patients to enhance feelings of well‐being structure the organization, facilitate communication among members as well as store and make accessible artifacts of their creative endeavors (Stinchcombe 1990). By participating in activities designed to foster creativity and the communication of their creative products, patients and residents join workers and managers in the structuring of the organization, engineering organizational processes as well as defining ways to create social and intellectual capital. Building capital is a way for all organizational members to gain recognition of their efforts and, through the process of making a contribution, gain a sense of well‐ being. Finding ways to provide efficient and clinically effective, personalized care designed to enhance well‐being for the institutionalized and homebound individual is becoming daunting in this age of revenue reduction and tight budgeting. Digital technology can be a cost‐effective way to engage these individuals in self‐ selected creative activities that support feelings of creativity and wellbeing. Computer skill building in healthcare resi‐ dential communities, not only increases organizational competence but also permits access to the popular culture and prompts a new form of cultural citizenship. As computers become available to the chronically ill in residential facilities, digital equipment will emerge as assistive devices and will be viewed as essential equip‐ ment in the provision of therapeutic recreation and art activities (Marr 2008). Technology will become the means to express creativity as well as communicate and store the products of creativity in the form of content collections. But how is technology assisted activities of the chronically ill linked to creativity? Tom Lubbock (2005) in his review of Folk Archive: Contemporary Popular Art from the UK refers to ‘folk art’ as every day or vernacular cultural production. Burgess (2007) has identified ‘vernacular creativity’ as every day and mundane and places it in the context of contemporary cultural transformations and new media technolo‐ gies. Vernacular creativity and folk art include decorated eggs, road side memorials to car victims, homemade shrines to Elvis and Di, photos and photo albums. Vernacular is distinguished by its commonness. Not all creativity is elite or extraordinary or spectacular. In a similar simplistic manner, creativity describes the processes by which cultural objects, texts and perform‐ ances are made (Burgess, 2007). Folk art is a matter of communication of creativity, not an abstract aesthetic value. Popular media production can be considered a primary form of everyday cultural production (Atton, 2001). Vernacular creativity and the use of the digital media gives the common person the opportunity to participate more meaningfully in cultural citizenship and, in an individual and organizational way, build intel‐ lectual and social capital (Hemmingway, 1999). Vernacular creativity stands for a wide range of everyday crea‐ tive practices (from scrapbooks, to family photography to unique collections). The everyday practice of vernacular creativity has always been linked to availability of tools and the resources. Media literacy can be viewed as the cultural, social and technological competencies of individual users and is related to creative literacy that includes technology. Creative literacy draws attention to technology, designers of software and hardware and the market place in teaching new users how to use new tools, as well as sug‐ gests what they are for. They are designed to be usable by giving easy access to a pre‐determined set of sim‐ ple operations. Computer technology is a new artistic, creative tool much like the Kodak camera was at its inception. In 1988, the Kodak camera and new film technologies for capturing and sharing photographs made the prac‐ tice of photography accessible to a huge market that was created by George Eastman (Jenkins, 1975). The ‘Kodak moment’ changed the social, technological and aesthetics of photography. The turn of the century Kodak marketing slogan was ‘You press the button, we do the rest’ (McQuire, 1998). Photography was trans‐ formed from a specialist to a mass popular, everyday leisure activity. By selling the activity of photography to the public, vernacular photography became an aid to family memory (Walton, 2002) and travel enthusiasts on the basis of usability and portability (Nead, 2004). In a similar way, computer technology has shifted from scientific and military use to an everyday relationship with the general public and consumers. Social media is a powerful learning tool and technology allows us to share, find new resources and access knowledge. The revolution in personal computing in the 1970’s and 1980’s was a period of diversity and instability. Early personal computing was a mix of hacker ideology and playing games with an eventual convergence of play and fun with technological mastery and knowledge. The Amiga 1000, the market was told, was the first computer to give a creative edge. In advertisements, business and military success as well as productivity was expressed in terms of personal creativity (Commodore International, 1985). One of the most significant advances at this

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John Zanetich time was the Graphic User Interface (GUI) which created user friendly interface design principles and made it so the technology did not stand in the way the user’s ability to use the computer as he/she wished. In 2004 and 2005, Apple bundled iLife with new Apple computers. The suite contained software for imaging (iPhoto), video production and editing (iMovie), DVD creation (iDVD), music production (GarageBand) and web publishing (iWeb) with an emphasis on software for creative production. Apple focused on their user base and branding strategy and identified the computer and software as being effortlessly creative rather than techno‐ logically extraordinary. The Apple computer was marketed as a way to participate in creative practice that was within the competencies of the ordinary consumer (Kahney, 2004). The link between usability and creative th expression was made. Like Kodak in the 20 Century, Apple has become a leader in everyday digital content st creation in the 21 Century. Computers have also become sites of social connection and cultural citizenship. In 2006 Apple marketed the iPad and promised users access to creativity through software and effortless us‐ ability in hardware for the ordinary consumer. Apple forged a campaign to blend ordinariness, creativity and technology in the iPad. The iPad’s light‐weight, touch screen technology and graphic user interface provides long‐term care residents with an opportunity to be creative and share that creativity. It is the communication of creativity that defines art. Taking part in creative activities has been linked to health and wellbeing. People voluntarily engage in a spec‐ trum of creative arts on a variety of levels. Digital activities, such as listening to music and using content col‐ lections for photographs and other visual arts, are recognized as playing an important part in people’s daily lives and as having health and wellbeing dimensions (deNora, 2008; Saarikallio, 2010). In a report on The Arts and Humanities in Health Care and Education (1999), a set of general principles were produced. These princi‐ ples include – every person has a unique sense of aesthetics and a creative dimension; being open or closed to one’s creative energies will influence one’s mental, emotional, spiritual and physical responses to living and dying; and, individuals have creative needs. There is a long list of benefits to creative activities identified by Anita Holford (2011) including feeling happier and more positive about themselves; feeling less isolated and more connected with other people; gaining a sense of control over their lives; and, improving their self‐ confidence and self‐esteem. Creative activities for people with chronic conditions requiring long term care are important not only for self‐management of conditions and quality of life, but for building social connections and a sense of well‐being.

2. Educational action learning An educational action‐learning model was used to plan, implement, evaluate and reflect on activities intended to improve the quality of life of residents of a nursing home. This model starts with negotiating an agreement about activities with the staff of the nursing home. The interests of the nursing home become the project goal and objectives and students learn by following the action‐learning format of ‐ plan, implement, evaluate and reflect on their experiences to learn academic course content. Each succeeding class benefited from the prior class’s outcomes and reflections through the formal transfer of knowledge using artifacts produced during the course of the project including use of written material as well as the experiences and learning of the instructor. The educational action strategy developed into a 3‐year series of college level academic service learning courses in which students learned about project management in a health facility. The projects were iterative with each class learning about the requirements of action learning in order to plan activities, implement an intervention, evaluate the intervention in terms of measureable outcomes, and reflect on what was learned through their project experiences. Three (3) of the 12 projects conducted over the 3 year period are reported here. These three projects inform the development of a grounded theory involving technology, creativity and well‐being in the care of the long‐ term frail elderly in a nursing home. The goal of the first project was to improve the quality of life at a large, urban nursing home through the use of computer technology. This proposal was to provide a group of residents with access to an iPad along with the assistance of a volunteer/student so they can access internet resources of interest to them. The facility is in the process of digitalizing all medical records, so the entire facility was equipped with Wi‐Fi access.

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John Zanetich As a result of ongoing budget issues, including the periodic reductions in the government funded Medicaid and Medicare payments, the programs provided by ancillary services such as trained resident activities staff and access to the facility’s in‐house library were curtailed. More than 50% of nursing home residents have no liv‐ ing close relative, which may be related to the estimate that 60% of nursing home residents have no visitors. By giving access to iPads to residents with the assistance of a volunteer, residents would benefit from the edu‐ cational, social and technology based activities. Video visitors or virtual friendly visitors using applications such as Skype are an eventual intended use of computer technology. Touch screens and graphic user‐interfaces have made computer technologies accessible to staff as well as residents, who may be less comfortable working with a mouse and/or keyboard. These interfaces also enable a number of social connectedness and entertainment applications for long term, elderly residents that in‐ cluded email, social networking, internet browsing as well as brain and physical fitness software and technolo‐ gies. A feasibility study regarding the use of an iPad in a nursing home was conducted intended to familiarizing the residents with an iPad. The iPads were assigned by the college to the project. Overall, ninety‐one (91) ses‐ sions were conducted with 35 residents over a one‐month period. Most residents had restricted ambulation and used walkers or wheel chairs and some were confined to the bed. However, the convenience and port‐ ability of the iPad permitted interactions in the resident’s room, in the community’s common areas (day rooms and hallways) and in other locations facility wide (library, garden, visitor areas). As anticipated, most residents needed some assistance for sign‐ins and accessing the internet, mp3 player or special software (i.e., text read‐ ing options). Once set up, the resident was able to manipulate the equipment and enjoy personalized activi‐ ties. A favorite use was Google maps and images which were used to reminisce by returning the resident to old neighborhoods and prior vacation sites. Another favorite was using Youtube for music and videos of events and activities reflective of their unique cultural background, such as public celebrations in home. Typi‐ cally contacts between volunteers/students using the iPad lasted about 35 minutes. Even though residents felt they benefited from the iPad use as shown in a ‘customer’ satisfaction survey taken after each session, residents were not familiar with social media (email, Facebook, Twitter, etc.) and expressed little interest in opening accounts. One of the learning outcomes for this project was the finding that hand held, touch screen computer devices are usable with minimal instruction and, by bringing hither to fore unavailable personal resources, can en‐ hance the quality of life of nursing home residents. Simply put, they enjoyed the experience. With assistance, residents could reduce feelings of isolation and alienation by maintaining contact with family and friends as well as their broader communities of interest. They could re‐connect with society and reaffirm cultural citizen‐ ship. Reflecting on the results of the iPad usability and preference survey or Project 1, we concluded that reading material was more important than social networking for the current cohort of residents whose average age was 80 years old. Pervasive use of technology in today’s consumer market and the workplace will result in future nursing home residents arriving with basic computer skills and knowledge of the internet. However for current residents, preferences clearly lie in books, newspapers and special interest publications. The usability of the iPad and its ease in accessing content collections and e‐books as well as iPad features such as increasing print size, integrated audio book features, applications for creating a ‘bookshelf’ and accessing playlists would make technology of immediate use to current long term care residents. The goal of the second project was to identify reading preferences and digital public library resources which could be downloaded to the iPad on demand and therefore be accessible to residents. By searching for view‐ able material accessible with the iPad, the Andrew Heiskell Library in New York City, funded by the U.S. Library of Congress was identified. This special library has as over 20,000 downloadable books and provides special format audio books and magazines for people who have difficulty reading regular print, holding a book, or turning pages because of a physical disability. Many people in nursing homes qualify under these criteria as reading impaired and therefore are eligible for membership in this library. Also committed to providing access to the physically handicapped and/or homebound (residing in an institution is considered homebound) the New York City Public Library provides an institutional library card and access to downloadable up to date best‐ selling audio books and other digital materials. A prototype iPad resource template, including a wellness ‘book

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John Zanetich shelf’, was created resident users could have on going access to these materials. The iPad was configured with the intent of making this template transferrable to other iPad’s in use at the facility. During this second project, a survey of the reading preferences of 39 residents revealed a distinct interest in mystery stories, romance novels and stories of animals and pets. Although residents prefer reading material in English, clearly the cultural diversity of residents is reflected in use of a second language by a large percentage, especially Hebrew and Spanish. In a separate project (one of the 9 other action learning projects not reported here), nighttime rituals at the nursing home revealed patient preferences for reading, audio and visual mate‐ rial before going to sleep. The ability to customize the resources using the touch screen of an iPad makes these resources individually available to residents in their rooms and in bed after minimal volunteer or staff set up time. The individual use of the iPad enables night rituals to be accomplished with minimal staff disruption to the unit’s organizational routines. Having gained valuable information about usability and preferences in long term residents, a third project has been implemented with the goal of identifying rate of learning, and changes in software preferences and well‐ being over time. In this project residents are receiving individual assistance in accessing preferred resources and in using the hardware and software for creative activities. Ten residents with an expressed interest in improving their computer skills have been identified and received a total of 20 tutorial sessions on using the iPad over a 5 week period. A pre and post evaluation of skill levels and wellbeing were made. Field notes and participant observations were collected and used for analysis and reflection.

3. Summary and conclusion Educational Action Learning is a qualitative method that helps in the understanding of the cultural and social context in which residents of long term facilities live. By using the content and time frame of a college course in health management, students become participants in an action strategy and an intervention designed to foster vernacular creativity in long term residents and enhance feelings of wellbeing using computer technol‐ ogy. This paper presented a grounded theory of the relationship between vernacular creativity, well‐being and the use of the iPad by systematically gathering information using the action learning framework of planning, implementing, evaluating and reflecting. By providing an education action learning consultation to a nursing home over a 3 year period, iterative projects were able to build upon the reflections of previous projects to build skills and increase access to computer software and internet resources. Skill building, identification of individual preferences and freedom of choice using an iPad provided the ground work for vernacular creativity. An inductive, theory discovery approach allowed the development of a grounded theory. Based in qualitative information and observation, the usability, preferences and opportunities for vernacular creativity in a long term residential population were identified.

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Human Capital Intangibles in Family Firms: Identification and Measurement Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón University of Alicante, Alicante, Spain Patrocinio.zaragoza@ua.es Enrique.claver@ua.es Hipolito.molina@ua.es Abstract: Intangible assets are considered to have a high strategic value and have become very relevant factors in the creation of value for a firm. Together with intangibles, family firms are the most important wealth‐creation agents. Their resources and capabilities can make a considerable difference between family and non‐family organisations. These firms possess idiosyncratic resources of an intangible and tacit nature that are inherent to them because they have been generated throughout the firms’ history. Precisely for their condition as ‘family’ firms, these firms are a source of intangible assets which can provide the basis for their later achievement of competitive advantages. Based on the literature devoted to family firms, the human capital theory and the intellectual capital‐based view of the firm, the present paper has as its aim not only to identify the most important human capital intangibles owned by family firms but also to show a series of indicators that can help measure them. For this purpose, the paper firstly refers to the most important human resources practices that permit the maximum capitalisation of human resources available to the firm; it secondly identifies 12 intangibles which characterise the human capital of family firms; and finally, 32 indicators have been created to measure all human capital intangibles identified in family firms. Our main motivation stems from the fact that individuals represent the most important input for knowledge work, which is structured around people’s skills and competences rather than around the execution of programmed tasks and work routines. The human capital theory states that individuals own skills, experience and knowledge which provide economic value to firms. Therefore, knowing the human capital intangibles of family firms –as well as the indicators which can be used to measure them– will surely help improve the management of those intangibles, thus making the most of intellectual capital. Keywords: intellectual capital, human capital, family firms, indicators

1. Introduction Firms can only compete effectively if they learn new skills which allow them to find, manage, share and use information as well as knowledge (Abell and Oxbrow 1999). Competitive advantage consequently relies more and more on strategic assets, such as knowledge, and on a set of dynamic capabilities which mainly materialise in innovations. Knowledge‐based intangibles are now extremely relevant factors in the creation of value for the firm (Lev and Daum 2004), which is why intellectual capital has acquired such an essential significance within business organisations. Family firms are the most important wealth‐creation agents, together with intangibles. Their activities cause a considerable impact on society and contribute to the creation of value chains for products and services that represent the largest part of the demand in the market. Several theoretical and empirical works in the literature have referred to intellectual capital but practically none of them link intellectual capital to family firms. It can be due to different reasons. Firstly, the study of family firms only emerged as a differentiated research line a relatively short time ago; and, secondly, research on family firms has often been constrained by problems such as the lack of secondary data sources and the variety of theoretical approaches adopted by researchers (Ibrahim et al. 2004). Furthermore, most of the literature on intellectual capital focuses on describing, classifying and measuring intangibles, as well as on stressing the importance of intellectual capital reports (Sudarsanam, Sorwar and Marr 2006; Pike, Fernström and Roos 2005) without making any special reference to family firms. Seeking to fill this gap and considering how important individuals are for a business organisation, the present paper written from the point of view of family firms has three main aims: (a) to highlight those human resources practices which permit the maximum capitalisation of the human resources available to a firm; (b) to identify the most important human capital intangibles owned by family firms; and (c) to show several indicators that can help measure them.

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Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón Our essential motivation stems from the fact that individuals represent the most important input for knowledge work, which revolves around people’s skills and competences rather than around the execution of programmed tasks and work routines. According to the human capital theory, individuals own skills, experience and knowledge which provide economic value to firms. Therefore, being informed about the best human resources practices and the human capital intangibles of family firms –as well as the indicators which can be used to measure them– will surely help improve the management of those intangibles, thus making the most of intellectual capital. The paper is structured in four sections. The introductory section precedes a review of the literature devoted to the concepts of family firm and intellectual capital. The following section identifies the main human resources practices, it describes the main human capital intangibles of family firms along with the indicators which make it possible to measure them. The paper finishes with the conclusions, highlighting its contributions and limitations, along with the future research lines which can derive from it.

2. Literature review: Family firm and intellectual capital Since our paper focuses on a specific type of firm, it becomes essential to clarify the meaning of the expression ‘family firm.’ Despite the absence of a unanimously accepted criterion which can be applied to define this type of business organisation (Lansberg et al. 1988), Tagiuri and Davis (1996) say that it is a complex system resulting from the interaction of three subsystems: firm, family and ownership (‘The three‐circle model’). Among the criteria used to identify family firms stand out: the concepts of family, ownership and control (Gallo and Sveen 1991; Donckles and Fröhlich 1991); family management (Daily and Dollinger 1993); family employment (Astrachan and Kolenko 1994), the involvement of several generations (Shanker and Astrachan 1996); and the intention to transfer the firm to the next generations (Ward 1987; Churchill and Hatten 1997). Among the features which characterise family firms stands out their vocation for continuity; that is, the desire of founders and their descendants to keep the ownership and management of their firm permanently in the family’s hands. According to the resource‐based view of the firm, endogenous factors represent a more solid basis for firms to maintain their competitive advantages due to the dynamism inherent to the business environment (Amit and Shoemaker 1993; Peteraf 1993; Barney 1991; Grant 1991; Wernerfelt 1984). Resources and capabilities often mean substantial differences in terms of competitiveness between family firms and non‐family firms. Habbershon and Williams (1999) explain that family firms have been described as unusually complex, dynamic and rich in intangible resources; to which they add that the advantages of family firms usually appear as something specifically linked to a particular firm owned by a particular family. The convergence between family‐system and firm‐system thus generates some hard‐to‐imitate capabilities –or ‘familiness’– which make the family firm especially apt to survive and grow (Habbershon and Williams 1999; Chrisman, Chua and Sharma 2003). Habbershon and Williams (2000) also point out that family control creates the family‐related conditions which generate idiosyncratic resources at the firm level; and these idiosyncratic resources of an intangible and tacit nature are inherent to the firm because they have been generated throughout its years of operation. It highlights that, precisely for their ‘family’ condition, family firms are a source of intangible assets which can represent the basis for their achievement of competitive advantages. In this context, the intellectual capital‐based view of the firm exclusively focuses on the analysis of intangible resources and capabilities, paying special attention to the stocks and knowledge flows incorporated into the firm (Reed, Lubatkin and Srinivasan 2006). Intellectual capital can be defined as the sum of the knowledge and knowledge capabilities which the firm can use to obtain competitive advantages (Youndt, Subramaniam and Snell 2004; Stewart 1997). Intellectual capital offers a quantitative perspective and is more closely linked to the measurement and identification of the existing intangible assets developed by the firm. A number of intellectual capital classification and measurement models have appeared over time (Edvinson and Malone 1997; Sveiby 1997; CIC 2003, 2012) and it is widely accepted that intellectual capital groups intangibles together into three main blocks, namely: human capital; structural capital; and relational capital.

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3. Identification and measurement of human capital in family firms 3.1 Human resources practices Exactly the same as non‐family firms, a family firm needs to implement a series of human resource practices that facilitate both the creation of knowledge and its later transfer among all firm members. According to the human capital theory, individuals have skills, experience and knowledge which provide firms with an economic value. In this respect, Lee (1999) and Galunic and Anderson (2000) state that investments made in specific human capital for the firm are likely to generate revenues and sustained competitive advantages because those human resources become harder‐to‐imitate assets. Hence the pressing need for firms to place the emphasis on investments in human capital as well as on the motivation and development of workers’ capabilities. Human capital investments Investments in human capital usually materialise in the adoption of either a make or a buy system (Miles and Snow 1984; Snell et al., 2000; Lepak and Snell 2002). The former supports the internal development of human resources, mainly through training and learning by doing, whereas the latter implies the acquisition of human capital from the external market, essentially through recruitment and selection. These systems determine the type of competences and skills to be acquired, the buy system being more linked to generic, easily transferable competences, unlike the make system, which is associated with firm‐specific, context‐dependent competences. Individuals’ skills and attitudes emerge as very valuable intangibles; hence the need for the firm to make its selection taking into account certain emotional factors (Goleman 1998) as a way to avoid jeopardising creativity and organisational knowledge generation. Human capital encouragement Individuals can only put their competences into practice if they are given freedom of action, avoiding pressures from upper levels and allowing the expansion of their ideas as well as their creativity. Employees need jobs which represent a challenge for them, as they need to feel that they really form part of the firm. In this sense, employee involvement in the decision‐making processes combined with the implementation of mechanisms through which their ideas can come to the surface become a powerful stimulus for the creation and transfer of knowledge within the organisation. Human capital development Once a talented professional has been attracted, the firm must keep and reinforce his commitment through an ongoing development process meant to maintain that professional’s competitiveness and to provide him with the value required to stop him leaving the enterprise. The talent of individuals develops through experience, training and interaction within the work team.

3.2 Identification and measurement of human capital in family firms Human capital is made up not only of the knowledge, skills and capabilities that individuals own and use but also of their capacity to generate them. Human capital is made up of everything that people and groups know and by the capacity to learn and share this knowledge with others for the benefit of the organisation (CIC 2012). Human capital becomes an important area insofar it is closely related to the success and survival of a family firm (Astrachan and Kolenko 1994). The study of family firms makes it necessary to consider intangibles linked to: the founder‐entrepreneur’s personality, the values shared by family members, the knowledge acquired from ancestors, the commitment of employees regardless of whether they belong to the family or not, the relationships between successors, the meaning of the firm to family members and the professionalisation of management, amongst others. Measuring these intangibles is essential for their proper management. A set of indicators designed by us taking CIC (2012) as a reference will permit to measure the human capital intangibles of family firms (see Table 1).

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Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón Table 1: Human capital intangibles and indicators of family firms HUMAN CAPITAL INTANGIBLES IN FAMILY FIRMS Motivation Leadership Entrepreneurial spirit Shared identity

Emotional family component

Creativity Skills Capabilities and knowledge acquired from family members Commitment, feeling of membership and dedication Simultaneity of roles Parent‐child relationships & relationships between successors

Knowledge of non‐family professional

INDICATORS Number of goals achieved/number of targets Number of problems solved/number of problems identified Number of people who positively value the work environment/total staff Percentage of labour absenteeism Percentage of people involved in corporate improvement activities Percentage of people who know the firm strategy Existence of a Family Protocol Number of existing family governance structures Percentage of people who share family values Number of hours dedicated to the integration of new employees (family or non‐family members) Percentage of people who has been involved in the development of the organisation mission Number of verbalised conduct rules which are unconsciously maintained Number of restrictive behaviour patterns which are unconsciously maintained Number of ideas suggested by the employees Percentage of people dedicated to activities of R&D+I Average length of service in post Average length of service in the sector Average length of service in the firm Number of years working with family members Number of projects developed with family members Years of service in the firm Number of employees with shareholdings in the firm Percentage of people involved in corporate improvement activities Number of roles held by one family member Number of activities involving the founder’s children Number of activities involving successors Number of suggested and accepted contributions by the founder’s children Number of suggested and accepted contributions by successors Number of relatives involved in corporate projects Number of suggested contributions to business projects by non‐family professionals Number of suggested and put into practice ideas by non‐family professionals Number of corporate activities in which non‐family professionals are involved

Source: self‐elaboration Based on motivations, the founder of a family firm will most probably exert a considerable influence on the definition of business goals and objectives, especially during the firm’s embryonic stage (Ward 1987). Family firm entrepreneurs are characterised by their capacity to: identify problems and solve them; set objectives; control their fate; and seek prestige as well as recognition, although they may not always have as their ultimate aim to achieve a profit. Family firms need a leader who can contribute to business change through the generation of an innovative capacity within the firm and who can also surround himself with a team formed by able individuals –from both inside and outside the family– combine them and coordinate them properly, granting them decision power according to their skills and knowledge. Both ‘make’ and ‘buy’ systems are consequently used in family firms, as the leader will detect business opportunities that, to achieve them, can need external knowledge to complement the knowledge existing inside the family. ‘Empowerment’ –along with experience and training– are elements that can help motivate and develop the firm’s human resources, whether they belong to the family or not. The indicators that can measure these intangibles could be represented by:

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Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón Motivation’s indicators:

Number of goals achieved/number of targets

Number of problems solved/number of problems identified

Number of people who positively value the work environment/total staff

Percentage of labour absenteeism

Leadership’s indicators:

Percentage of people involved in corporate improvement activities

Percentage of people who know the firm strategy

Closely linked to the figure of the founder is the entrepreneurial spirit. One of the main problems which usually affects the family firm is the accommodation within a specific situation and the loss of the entrepreneurial spirit. Coping with this problem would require the adoption of family governance mechanisms which can transfer this entrepreneurial spirit to future generations. Among those mechanisms stands out succession planning and the firm professionalisation process. The ‘make’ and ‘buy’ systems will combine with them, and the owning family will engage relatives with management training together with professional executives alien to the family who can contribute to update the leadership style and orient it towards the one which facilitates the development of innovation processes to a greater extent. Closely linked to the succession and professionalisation processes is the implementation of a Family Protocol, by virtue of which governance structures such as the family Assembly, the family Holding Council and the family Councils of group firms are established. The existence of a Family Protocol can act as a source of motivation and development for future generations, who will see how their process of learning and adaptation to the family firm business is carried out in a proactive and controlled way and being planned over time. Some indicators of this asset could be: Entrepreneurial spirit’s indicators:

Existence of a Family Protocol

Number of existing family governance structures

The values expressed by family members, their commitment level, their feeling of membership and dedication –all of which can also be considered highly valuable intangibles– create a common purpose among the employees and help them consolidate a feeling of identification and commitment. The meaning of the firm to family members allows the development of a strong mission feeling among employees. This shared identity among family members permits to increase family and business loyalty, thanks to which a strong feeling of mission is obtained and more objective decisions are adopted. Sharing these values, a common commitment, and taking part in the firm’s decisions become highly motivating factors for family firm employees, particularly for those who do not belong to the family, because they highly appreciate being so well received and integrated into the family. Some indicators could be represented by: Shared identity’s indicators:

Percentage of people who share family values

Number of hours dedicated to the integration of new employees (family or non‐family members)

Percentage of people who has been involved in the development of the organisation mission

Family members have a strong emotional component reflected on the fact that families protect all their members and admit their unconditional acceptance, which is a powerful motivating element. The family system organisation can keep the family united (Davis 1983) as it regulates the behaviour of family members through verbalised conduct rules and restrictive behaviour patterns which are unconsciously maintained. The indicators that can measure this intangible can be:

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Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón Emotional family component’s indicators:

Number of verbalised conduct rules whish are unconsciously maintained

Number of restrictive behaviour patterns which are unconsciously maintained

For Sirmon and Hitt (2003) the creativity, skills, capabilities and acquired knowledge of family members characteristically allow family firms to accumulate a great potential to generate a deep tacit knowledge specific to the firm and hard to imitate. The origin of a family firm lies in some knowledge or core competences (a privative know‐how exclusive to the family) which have been tacitly transmitted from parents to children and which have been gradually enriched with new knowledge provided by well‐trained descendants and employees who are additionally well connected with certain agents in the environment. That initial knowledge has been continuously updated in order to cope with the new demands imposed by the changing business environment. Therefore, a combination of the ‘make’ and ‘buy’ systems will allow employees not only to acquire the most tacit knowledge existing in the firm but also to complement it with knowledge coming from outside. The indicators that can measure these intangibles could be represented by: Creativity’s indicators:

Number of ideas suggested by the employees

Percentage of people dedicated to activities of R&D+I

Skills’ indicators:

Average length of service in post

Average length of service in the sector

Average length of service in the firm

Capabilities and knowledge acquired from family members’ indicators:

Number of years working with family members

Number of projects developed with family members

The family’s level of commitment, feeling of membership and dedication to the firm are highly motivating and valuable intangibles, since the degree of cohesion within the family firm as well as the availability of certain resources and capabilities on which strategy development can be supported depend on those intangibles. According to Tagiuri and Davis (1996), other intangible assets coming from human capital can be observed in the capacity for the coexistence of simultaneous roles among family members, which makes possible rapid and effective decision‐making. Some indicators of these intangibles could be: Commitment, feeling of membership and dedication’s indicators:

Years of service in the firm

Number of employees with shareholding in the firm

Percentage of people involved in corporate improvement activities

Simultaneity of role’s indicator: Number of roles held by one family member A family firm must pay special attention to relationships between parents and children when the latter join the family firm with managerial responsibilities, or between successors belonging to the family, when they share firm management. Intergenerational conflicts may appear but new generations usually provide the family firm with a number of advantages such as the diversity of opinions and perspectives for problem analysis, teamwork and higher objectivity in evaluation and decision‐making processes. The founder must be willing to share firm management –and successors must have acquired the interpersonal skills required for shared decision‐making– in order to achieve success. It helps keep the company’s strength and maintain the energy that feeds the enthusiasm for firm growth, thus becoming a powerful motivating asset. Some indicators to measure these intangibles could be:

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Patrocinio Zaragoza‐Sáez, Enrique Claver‐Cortés and Hipólito Molina‐Manchón Parent‐child relationships & relationships between successors’ indicators:

Number of activities involving the founder’s children

Number of activities involving successors

Number suggested and accepted contributions by the founder’s children

Number suggested and accepted contributions by successors

Number of relatives involved in corporate projects

Non‐family professional executives are attracted from outside because they own some knowledge that the firm does not have and that it cannot internally generate either. They usually import new ideas and working methods –together with a more objective vision of business– into the family firm. Furthermore, since they are not biased by the “recipes followed by the family firm,” they can also provide more innovative and creative behaviours. The indicators that can measure these intangibles could be represented by: Knowledge of non‐family professional’s indicators:

Number of suggested contributions to business projects by non‐family professionals

Number of suggested and put into practice ideas by non‐family professionals

Number of corporate activities in which non‐family professionals are involved

4. Conclusions Because family firms have a set of intangibles which distinguish them from non‐family firms and considering that individuals represent the most important input for firms, the purpose of this work was to identify a set of human capital intangibles in family firms as well as a series of indicators that can be used to measure them. Therefore, based on the literature devoted to family firms, the human capital theory and the intellectual capital‐based view of the firm, our paper firstly refers to the most important human resources practices that permit the maximum capitalisation of human resources available to the firm; it secondly identifies 12 intangibles which characterise the human capital of family firms; and finally, 32 indicators have been created to measure all human capital intangibles identified in family firms. Several contributions result from this paper. From a theoretical point of view, the intellectual capital‐based view is linked to the literature about family firms, identifying a pool of human capital intangibles which are inherent to this type of firms along with indicators that can be used to quantify them. No publications offering a similar approach were available in the literature so far. From a managerial point of view, identifying the human capital intangibles of family firms and their indicators can help managers become aware of their actual importance and it will surely help them improve their management of the said intangibles, thus making the most of intellectual capital. This study faced certain limitations, mainly derived from: its theoretical nature, the difficulty in collecting all the human capital intangibles which characterise family firms and the problems associated with the creation of precise indicators for their measurement. However, these limitations encourage us to keep on working in this field, continuing the research initiated with this paper for the purpose of developing it and enlarging it, reaching a second level which not only offers human capital intangibles but also intangibles from structural and relational capital –along with the possibility to provide indicators which allow us to quantify all those intangibles. This will hopefully provide a more faithful picture of this type of firms than the one usually provided by the traditional assessment methods.

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Does National Culture Affect Intercultural Knowledge Transfer? Dolores Bengoa International Business School at Vilnius University, Lithuania sanchezl@cytanet.com.cy Abstract: From international construction projects to multicultural research networks or foreign manufacturing plants more than ever, international co‐operations are the pillars for many economies. Due to these co‐operations, the constant flow of employees and their intellectual capital require specific intercultural skills to successfully manage the transfer of knowledge across different cultures. The unlimited potential for innovation derived from this new intercultural knowledge based economic culture, should be carefully treated because is the key to economic progress. This knowledge’s value is identified by many companies and, therefore, treasured and protected to a great extent. This protective attitude represents a considerable obstacle for international business co‐operations. The paper explores how elements of culture e.g. values, attitudes, ways of communication, learning or even leadership styles amongst others, influence positively or negatively the transfer of knowledge between Eastern and Western European co‐operations. Additionally, the research highlights how manager’s intellectual capital sharing and employees’ absorptive capacity and willingness to learn are impacted by culture. The qualitative research applies a phenomenological approach because it tries to understand social and cultural realities, which are based on people’s experiences and the meanings attached to them. The data collection was conducted by in‐depth interviews, (23) needed to reach theoretical saturation, non‐participant and participant observation (7), focus groups (4) and fieldtrips notes in Russia and Austria. During the data collection, the grounded theory method of constant comparative analysis was used for the analysis. The researcher applied a fundamental shift from a mere comparative study of cross‐cultural differences (nodal level) to the study of intercultural interactions (dyadic level). The research findings provide an awareness for academics (due to the lack of existing literature in the field at a dyadic level) about how own self‐reference criteria, ethnocentric behaviours, competitiveness, hierarchies, knowledge alienation, cognitive understanding, risk taking or learning culture could limit or encourage knowledge transfer and its acceptance. For practitioners, understanding and integrating cultural diversity exponentially enlarge managers’ intellectual capital and facilitate its transfer. It provides higher levels of competitive advantage by utilizing diversity, sharing knowledge and reciprocal learning, e.g. for innovation (product, process or social) and for the choice of standardization and/or adaptation strategies in international markets (degree of localization of product and communication strategies) and finally quicker and more successful market entry. Keywords: knowledge transfer, culture, international co‐operation, Eastern/Western Europe Introduction

1. Introduction From international construction projects to multicultural research networks or foreign manufacturing plants more than ever are international co‐operations the pillars for many economies. Due to these international co‐ operations, the constant flow of employees and their intellectual capital require specific intercultural skills to successfully manage the transfer of knowledge across different cultures. The paper draws on an Eastern and Western European empirical exploration of how to improve the transferability of knowledge between co‐ operation members using qualitative data. The main objective of the paper is to provide practitioners with a close look to some of the main obstacles which bloc the successful transfer of knowledge. Additionally, the paper contributes to enlarge the limited body of available literature related to intercultural learning and knowledge transfer.

2. Lack of intercultural KT research The constant flow of knowledge offers an unlimited potential for innovation derived from this new intercultural knowledge based economic culture. This potential should be carefully treated because is the key to economic progress (Holden and Tansley, 2007). Having made explicitly this value, it is surprising to observe how limited research has been conducted in the field. This lack of research is what Holden (2002, p.51) called “the literature’s grand lacunae”. Additional researchers like (Cyr & Schneider, 1996; Bartholomew and Adler 1996; Gill & Butler, 1996; Szulansky in Odell 1998; Davenport & Prusak 1998; Woodrow’s & Tamulionyte‐Lentz, 2000; Shaw, 2001; Cornuel and Kletz, 2001,; Clark & Geppert, 2002; Lang & Steger, 2002) criticized that academia has not provide satisfactory solutions for the current inaccurate and inefficient transfer of knowledge across cultures in order to fully exploit opportunities offered by diversity. Further criticism is expressed by Andriessen and Vand den Boom (2007) explaining that almost all exiting literature has been developed in the West based on Western values, assumption, concepts and models.

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Dolores Bengoa Following the research of Serenko and Bontis (2004) on the exploration of 63 top knowledge management and intellectual capital researchers, they found out that only 6 researchers were coming from non‐Western countries. This Western unilateral knowledge creation leads in some occasions to the sociological theory of structuralism. Scholars like (Meyer and Rowan, 1977; DiMaggio and Powell, 1983; Mendoca and Kanungo, 1996; Lang and Steger, 2002; Clark and Geppert, 2002; Tsang, 2004) explain that the main idea behind structuralism is that the process of KT flows from the West to the East and this transfer occurs on a linear or one‐way direction. Further criticism towards this over domination of the West is expressed by (Ford and Chan, 2003; Hutchings and Michailova, 2004; Chen, 2005; Michailova and Sidorova, 2010) criticizing the lack of research on reciprocal learning and reciprocal exchange of knowledge, arguing that knowledge can also flow from Eastern partners to Western partners. Nevertheless, this criticism rapidly could reach an end. Times are st moving fast in the 21 knowledge based economy especially in Asian countries, where national policies are changing from manufacturing and processes mindset to knowledge base leading economies as it is the case for China. Qing, (2008, p.109) explains “the society we live in has been gradually turning into a knowledge society and knowledge has become argued to be one of the principal resources of lasting competitive advantage”. This change on the thinking and working way are calling for new knowledge alliances co‐operation between Western and Eastern Universities and companies.

3. Knowledge transfer and the influence of national culture In order to understand how national culture influences on the transfer of knowledge some definitions should be addressed. For Boone & Kurtz (1988), culture was defined as the combination of values, ideas, attitudes and other meaningful symbols that serve humans to communicate, interpret, and evaluate as members of society, or the “sum total of learned behaviour patterns which are characteristics of the members of a society” (Aceves, 1974, p. 60). Some years have passed since these definitions were created. The world has drastically changed in the last almost 40 years, from the crumble of the communist blocks, passing through the revolution of the web digital world, to the more current economic crisis situation. In view of these and other events, Holden (2002, p.226) challenged the traditional view on culture holding that “the modern business world can no longer be seen as comprising national cultures, perhaps it was the view 20 years ago but, the new millennium is mixing up people from all manner of linguistic, national cultural, educational and professional backgrounds on a scale and with intensity unprecedented in human history”. His conviction is that implicitly, due to this cross‐border interaction a new definition of culture should arise which “combats the restrictive, anthropologically derived culture concepts and acknowledges the shaping forces and influences on management thinking, attitudes and behaviour in the global connected economy” (p.59). Therefore, the richness of cultures also offer the chance to gain additional, often complementary, knowledge, experience, and opportunities. The latter are often not exploited to their full extent. For this reason, people involved in international business must develop more transnational and intercultural skills, ranging from flexible thinking, integration in planning, to broad cultural awareness to cope with this cultural diversity. Continuing with knowledge and its transfer, for Davenport and Prusak (1998) and Raich (2000) what constitutes knowledge is a combination of experiences, values, assumptions, opinions and even prejudice, contextual information, expert insight, and intuition that provides an environment and framework for evaluating and incorporating new experiences and information. This set of elements is originated in every individual’s mindset, being influenced by the individual’s national culture. The later author criticizes that many authors writing about knowledge do not take into account defining the meaning of knowledge and assume that other people will understand this widely Western used term in the same way. Helping to clarify further this criticism, the different Japanese perception of knowledge as thoughts and feelings as stressed by Nonaka and Takeuchi (1995) could serve as a good example. For the authors knowledge creation is perceived as a constant self‐transcending process based on Japanese philosophers. Nonaka et al (2001) transcend the materialistic view of knowledge as a thing for knowledge as a living process. It becomes apparent that the definition of knowledge in itself is very complex being influenced by a myriad of issues from materialism to philosophical constellations. The main idea of knowledge transfer is according to Leyland (2006, p.3) “to ensure that efforts provide the desired results (effectiveness) and ensuring that the new knowledge becomes embedded within the organization’s fabric (institutionalization)”. It is nicely said, but more complex to achieve, especially when the transfer occurs between individuals or organization’s members from different cultural background as it has been discussed above.

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Dolores Bengoa The cultural framework of Hofstede’s and his initial four dimensions of power distance, individualism/collectivism, feminity/masculinity and uncertainty avoidance are dicussed in this research by Ford and Chan (2003), Leyland (2006), Dignum and Van Eijk (2007), Ming‐Fong and Gwo‐Guang (2007) as a tool for illustrating more evidently and practically the implication about the intercultural complexity of transferring knowledge between Eastern and Western business co‐operations: Individualism, self‐interest predominates over group interest in cultures ranking high in Individualism e.g. Germany, France or USA. Individuals carefully observe where the knowledge is transferred to and who will acquire it. Additionally, these cultures are more interested in knowing which personal benefits the transfer of knowledge brings for them, rather than, caring for the overall company benefit. If this benefit is not lucrative or satisfactory enough, the individual or the company/ subsidiaries will place a great deal of roadblocks on the efforts and willingness to share and transfer the knowledge. It can be concluded that individualistic societies are more reluctant to share knowledge, since this is regarded as a powerful tool and guaranteed success for the individual. This protective attitude represents a considerable obstacle for international business co‐ operations. Opposed perceptions are presented by countries like Russia, Croatia, Bulgaria or Japan being more group orientated. This is reflected in the view that knowledge belongs to the company and is, therefore, for the benefit for the overall organization. Explicitly, Quing, (2008, p.110) explained that “individuals in a collective society are incline to scarify their personal interest for the goals of these collectives and are most motivated by norms, duties, and obligations imposed by the collectives”. Conclusively, when KT is taking place among members of these two opposed poles, a more equal balance of interests and expectations from sides knowledge provider and acquirer, has to come to the fore. Masculinity, being characterised by competitiveness as one of the most salient features, also faces difficulties in knowledge sharing. This is due to the factor that is mainly driven by individual performance, autonomy and independence, rather than by organizational performance. Related to knowledge’s possession and self value Dignum and Eijk (2007, p.4) explained that “knowledge creation is often considered more valuable than working with acquired knowledge. This explains the reluctance of users to make their knowledge and expertise available through a knowledge repository where knowledge is decoupled from the knowledge owner”. On the other hand, the flow of knowledge in high femininity societies occurs easily because both parts with their win‐ win policy in mind are interested in a bilateral successful outcome, and are more willing to find ways to bridge differences and reach a common benefit. Power distance, related to hierarchy and status also influences KT in masculine societies. For Leyland (2006) and Dignum and Eijk (2007) became clearer that individuals are more in favour to share their knowledge and engaging in action when this is done with their peers rather than with their employees. The later clarifies that this might be done because the knowledge shared can be somehow controllable within a trusted group, where conditions have been negotiated. Companies ranking high in power distance interfere with the knowledge flows between their hierarchical structures, and the knowledge flows mainly top down. Taking this stance, they will underestimate the knowledge value from the lower levels of the organisation, missing probably first hand information and making the upward flow of it difficult. The bases of these cultures are control and power, and therefore, they try to avoid any knowledge sharing facility or activities leading to treat knowledge as a private property. In higher power distance societies learning and knowledge transfer is conducted in a very hierarchical (imposing) way where the only option is the immediate compliance of unquestioned orders. This behaviour leads to question if real cognitive understanding and integration of knowledge as a way of personal growth and contribution to create knowledge can occur. A final observation form Maletzky (2008) relates to the innovation’s capacity or limitation of the employees if they cannot express freely due to this constrains in companies/countries with high hierarchies like Russia or Slovakia. On the other hand, societies ranking low in power distance, the relation between top, middle and lower level employees is open. Communication and knowledge flows in all directions leading to advantages in terms of company growth, innovation and personnel development. Conclusively, the interaction between low and high power distance cultures imply a challenge for overcoming old patterns of high control and knowledge hoarding, requiring a great deal of common efforts to balance these opposite perspectives and ingrained behaviour. Uncertainty avoidance or fear of the unknown represents a major barrier in KT. Leyland (2006, p.7) indicated that “change involves taking a leap of faith because the future is unpredictable, leading to a general feeling of

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Dolores Bengoa being careful towards new things or new ways of acting”. Furthermore, he underlined that “adopting something new is seen as risky and having the potential to create significant problems. Instead of accepting change, there is a strong preference for dealing with – what we are already good at – and avoiding new techniques even if these offer the potential for increased efficiency”. In other words, the potential to improve and to grow is inhibited leaving people behaving within the old patterns. For this reason, a trustful atmosphere where both partners are committed to developing such a supportive and low risk surrounding is regarded as vital to reduce fear and uncertainty behaviours focusing more on an increase of willingness to change and accepting new ways of working and thinking. In synthesis, these observations lead to an awareness of the complexity for transferring knowledge across cultures but, also for the absorptive capacity of the knowledge receiver. Being this complexity based on rooted cultural behaviours and being of intangible nature. The following methodology tries to explore the way this complexity can be handled or at least to smooth intercultural knowledge transfer process.

4. Methodology The paper aims to present part of the empirical research findings focusing on culture as a key issue influencing the knowledge transfer between Eastern and Western European co‐operation partners. For this purpose, a qualitative research has been conducted using a phenomenological approach to better understand social realities. The researcher has used the grounded theory method of constant comparative analysis based on Glasser and Strauss (1967) and Strauss and Corbin (1998) for analyzing the gathered data and for the generation of theory. The research was designed in three stages. In the first stage, prior to the data collection, secondary research was conducted by an extensive literature review. This research was intended to increase the researchers’ familiarity with the research setting rather than to develop any theoretical framework. The second stage was dedicated to the empirical research and the third part, was dedicated to the findings’ analysis and conclusions. The empirical data was conducted in Russia and in German speaking countries, using focus groups, 23 in‐depth interviews and participant observation for data gathering. The sample’s backgrounds refer to international companies and universities. The findings contributed to elicit the positive and negative attitudes and barriers influencing the transfer of knowledge.

5. Findings’ discussion The purpose of this section is to describe and clarify to the reader what, why and how actors feel when interacting with their foreign partners, and to show the influence and implications that culture has on KT. Those influences and implications relate to the individual in terms of attitudes, behaviour and values, as well as, company actions when transferring knowledge. Reflecting on the finding’s discussion, direct quotes from the participants are provided written in italic, followed by an R, meaning respondent, and the respondent’s number to care for anonymity. The research was conducted at a dyadic level, meaning that the respondents are already working with members of the other culture. During the literature review some meanings of knowledge were explored by Davenport and Prusak (1998), Raich (2000) and Nonaka et al (2001) as knowledge being something very close to the individual, although having different constituent elements. In this research a new term has developed, not in relation to knowledge clones to the individual but the opposite direction. The new terms refers to knowledge alienation, so far not identified in literature. The term knowledge alienation, as named by the researcher, refers to the distance between the personal identification with this knowledge and a lack of connection with it. In this context, the feeling experienced by Eastern European respondents in terms of knowledge alienation relates to Western knowledge being totally meaningless for them. During the interviews the sentence “relate knowledge to Russian reality” was repeatedly expressed. The respondents stressed that just getting Western examples was not very motivating for them because it didn’t fit with the Russian reality. (R2) tried to explain this reaction by commenting “if they think this concept doesn’t fit for Russians, you immediately lose them”. The researcher’s personal observation is that Russians are very practice orientated. With a sense of humour (R6) explained this behaviour occurring on a daily life situations “when we buy an appliance for example a hover, we don’t read the instructions, it should work immediately”. Similarly, (R5) criticised Western lectures for lacking knowledge

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Dolores Bengoa about their Russian culture and he commented, “if the knowledge is not adapted to Russian culture for us it is just useless”. A second example, a personal view point from a Russian student participating on a Western Master Programme tried to clarify why sometimes Western knowledge is not applicable for them, and therefore their interest and commitment for learning is low. (R36) “in double accounting and gray schemes, it was pointless to try to introduce Western standards. Also, the programme is too focused on global companies and multinationals, while most of the students come from small and medium sized firms”. It becomes clear the need to take deeply into account some of the cultural element for example attitudes, meaningful symbols and learn behaviours indicated by Boone & Kurtz (1988) and Holden (2002) in order to tailor the knowledge which is going to be transferred to the learner’s environment. Some Russian educational institutions are dealing with Western educational institutions in order to develop new programs, course content and business literature. They identified problems in terms of extreme Western nationalism by treating Russian students as part of their own culture. Although France was not researched in this study, the researcher took the French example given by the Russian respondent, in order to underpin the lack of cultural sensitivity of some Western institutions. Special problems were mentioned when dealing with French institutions, being nationally‐focused and ignoring the Russian partner and their culture. (R3) explained “they think the French culture is the best, they are not interested in Russian cases”. Once more, this Western behaviour ignoring the Russian interest produced knowledge alienation as to the program’s content and certain rejection in the partnership’s co‐operation. At a later stage, she indicated a positive acceptance in the case of co‐operation with German institutions, as they understand the need for this adaptation and integration of the Russian environment. Accordingly, (R1) clarified “German approaches are more practical and more useful for marketing”. Although, knowledge alienation was one of the most criticised and discussed category by Eastern respondents, for Western respondents was hardly acknowledged. They never thought of this, as being a potential barrier for transferring knowledge and learning. Here, it can be seen a very important imbalance of concerns and priorities regarded as the root of the problem: the lack of awareness as to what worries or troubles the business partner. In order that Leyland’s idea of knowledge transfer effectiveness and knowledge’s institutionalization come to the fore, a reflection on past learning pattern and existence of knowledge should be conducted. The following statement can be used as an awareness and reflection for understanding the Russian learning environment. (R1) explained that in 1980 management literature written in Russian was rare, and nowadays, specific examples to fit this Russian reality can be seen on bookshelves of Russian libraries where journals and magazines contain more live and real examples. This lack of Russian literature was explained by (R34) who compared it with Western literature “our books are mostly theoretical and of descriptive character. This is the result of a lack of practical experience”. The Hofstede’s power distance dimension explained above by Chan (2003), Leyland (2006), Dignum and Van Eijk (2007), Ming‐Fong and Gwo‐Guang (2007) can be very well illustrated by the following explanation. Due to their political past, where authoritarian commands were automatically obeyed the Eastern European population grew and lived in an environment of blind obedience where space for contradiction or criticism was unimaginable. The impact on attitudes toward criticism is also perceived in the learning environment. (R3) explained that Russians are not used to being criticised, they follow the instructions and it is difficult for them to understand that they can contradict somebody. This uncritical behaviour affects the absorptive capacity of the knowledge receiver by being only a mere listener without any self critical reflection. Therefore, a real internalised knowledge cannot take place leaving the learning process on a very superficial level. (R1) confirmed this statement by adding that “criticism is the weakness of the Russians”. One of the Russian and Eastern European national characteristics is having a hierarchical mind set. Pointing to a leadership gap in terms of motivating behaviour in stimulating critical thinking (R8, R9) explained that management lack patience in teaching. They explained that by using an authoritarian behaviour they discourage employees from having any kind of thoughts or asking questions leading to automatic task compliance and consequently, it is easy to guide them. These hierarchical minds are found at all levels in an organization. As soon as somebody has the chance to hold a slightly higher position over the rest, an

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Dolores Bengoa authoritarian, even depreciative behaviour, can be clearly perceived as explained in the following statement “a sales assistant will not even look at you or say hello, because you are a client just like another thousand more” (R8). She further explained that the need to have these hierarchies and control is also expected, and needed for many employees, as a way to get guidelines in the work place and to fulfil the job according to the boss’ demands. (R2) further indicated that Russians working for Western companies somehow feel lost about their performance if this daily control is not in place. This hierarchical mindset and inflexibility was experience by a Western respondent (R16), who explained the struggle of a Swiss company when trying to improve working procedures. After having tried in several occasions and forms, unfortunately, he stressed that it was impossible due to a lack of flexibility, strictly commanded rules together with blind unquestioning obedience. Similar situation, but in this case related to communication (R26) experienced this inflexibility when asking for further information and clarification of certain issues without any success. More implications from high power distance societies are perceived in the tandem of hierarchy and learning. They go hand in hand, Eastern educational traditions based more on a hierarchical level as it was in Communist societies, left a deep impact on the learning approach. This high respect for academics and the authority they represent, creates a big distance between children/students and their professors. Due to this high respect (R3, R1, R4) stressed that is almost impossible to have a confrontation between a student and a professor. A final remark as to the overall Hofstede’s cultural concept: It was a unanimous comment from the individual interviewee to the conference’s participants about the changes already Russia is experiencing. It can be seen form daily newspapers, constant articles related to economic development, international projects, tourism or in many other aspects shown that Russia is changing towards a more liberalised country. Compared with some Western scholars (R1) underlined the need for them to be up‐dated and to get to know better about how Russia is really changing. She suggested that Hofstede’s dimensions are changing in the Russian mentality and regards the scholar “old, but is interesting to compare”. Additionally, in relation to the above discussed issue of hierarchies and power distance, she indicated that the power structures are changing and there are no so extreme as before. Furthermore, she explained that the traditional group orientated behaviour characteristic from of the Soviet time is changing toward a more individualistic society. Eastern respondents continually expressed their disappointment towards Western knowledge transmitters related to their lack of cultural awareness, alienation of knowledge, arrogant behaviour and imperialistic attitudes all issues which compound the origins of the theory of structuralism criticised by (Meyer and Rowan, 1977; DiMaggio and Powell, 1983; Mendoca and Kanungo, 1996; Lang and Steger, 2002; Clark and Geppert, 2002; Tsang, 2004). These can be clearly underpinned by the following two examples. (R17) addressed the negative performance of a Swiss company and its fatal consequences of leading the business partner into bankruptcy by utilising a totalitarian ethnocentric attitude. Time has passed and reflection about their behaviour took place. He concluded explaining that “this is also our learning process, now we give them space”. In the same direction, (R18) referred to the rejection of this ethnocentric behaviour used by his company with their business’s partners and their reaction was “people didn’t like when we said to them how they have to do the things”. The issue of sharing knowledge and its connexion with power and individualism was acknowledged from both parts. Probably, more accentuated on the Eastern part as hierarchies are stronger and the need to show such levels are crucial. On the other hand, the West was more relax in the equation knowledge and hierarchy. They provided some reasons explaining why knowledge has not such importance and people should lose the strong feeling of property. They underlined that knowledge gets obsolete relative quick and the more the knowledge is shared the more up‐dated become and increases its potential. Nevertheless, some indications related to Westerners having troubles in sharing knowledge were provided. This happen only on very high company levels and due to inside political games (R24,R25). Communication and language are very important elements of culture as stressed in the literature by Boone & Kurtz (1988) and Holden (2002), and one of the most important barriers in KT identified by the respondents (R6, R7, R10, R11, R12,R15,R16,R17, R25). The communication process can be affected by issues related to semantic as (R5) explained “some words can have different meanings and originate a kind of cross‐cultural misunderstanding”. Moreover, this communications’ barriers can also be affected by the alienation of the

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Dolores Bengoa knowledge transmitter culture and the effort to integrate new knowledge together with a new knowledge receiver’s culture.

6. Conclusion This research has looked at the impact that national culture has on the transfer of knowledge between Eastern and Western European co‐operations. One of the frameworks used for the research was Hofstede’s cultural dimensions. They represent an initial help about cultural differences, being of no doubt of meaning for the general citizen, but intercultural actors dealing specially with topics like KT and knowledge sharing need something else that a mere clarification and classification of differences. This is a challenge that goes beyond that, it is the need of an intrinsic value modification. This modification could start by stopping the reciprocal blame that Westerners has against the East and vice‐versa towards a reciprocal experiential learning, where self‐critical reflection, real understanding, respect and integration of others are the basis to modify attitudes. Furthermore, the new concept of knowledge alienation was introduced, and its implications on the effectiveness in transferring knowledge were explored. In order to avoid knowledge alienation and to increase the knowledge receiver’s commitment to learn, Western knowledge has to be adapted or transformed in order to match more the Eastern European business reality and cultural environment, or even better, commonly developed it. It should be understood by Westerners that due to the Soviet Union’s past with its political influences, terms and concepts like management, marketing or even profits were very differently understood or even they did not exit. Finally, Eastern partners called more for an integrative and co‐operative way of learning, where opinions are asked for and respected, avoiding what they called imperialistic behaviours. Western respondents did reflect on some of their mistakes and act on it by e.g. changing business strategies and leadership behaviours. They acknowledge the importance of cultural awareness playing a vital role in the partner’s cultural understanding. They are claiming for learning from each other avoiding the David and Goliath metaphor towards a more brothers and sisters’ approach.

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Intellectual Capital in the Higher Education Institutions of Latvia in the Context of International Trade Airita Brenča and Rasma Garleja Department of Education Sciences, Faculty of Education, Psychology and Art, University of Latvia, Riga, Latvia Department of Development and Planning, University of Latvia, Riga, Latvia airita.brenca@inbox.lv rasma.garleja@lu.lv Abstract: An innovative capacity study of intellectual capital (IC) in the context of higher education institution marketing and higher education and science reform measures to be implemented by the state in the near future. Concretization of the concepts and indicators of IC, IC analysis in the higher education institutions of Latvia, based on the evaluation of IC components of academic management and marketing aspects in international trade has been carried out in the study. The study aims to characterize the higher education product intellectual value components and their changes according to modern academic management requirements. The objective of the study is to develop recommendations for the management of higher education of Latvia in order to ensure the demand for intellectual capacity on the local and export market. The research problem pertains to what has to be altered in the higher education programs, in the student achievement assessment system, the organization of the study process, based on international experience and export demand. Methods used in the study: monographic international literature review, comparative data analysis, internal customer (consumer) needs analysis, content analysis, evaluation of higher education academic personnel and expert evaluation. Models, structures and methodologies for IC measurement, evaluation and application, mainly used in corporate marketing analysis, created by different scientists exist and function more or less successfully in the theory and practice of the world. The end of the 90s may be historically considered a precursor for IC implementation in the practice of higher education institutions. A more serious focus was dedicated to IC research starting from 2005. At present, many countries see the international academic mobility and education mobility programs as the critical aspects of experience exchange, intellectual capital increase, maintaining of competitiveness and strengthening of mutual cooperation in a globalised world. The assessment of IC however is still insufficiently included in the academic management of higher education institutions, as well as up to now a single IC model for application in the practice of the universities has not been created. The authors conclude that of the traditional three IC components (human capital, structural capital and relationship capital) some indicators can be found in the reviews of Latvian universities, whereas a detailed and comprehensive analysis of the country IC measurements is not available and has not been carried out. The analysis of IC commenced at the higher education institutions of Latvia should be continued and visibility and application of IC has to continue to be included in the development planning documents, studies and university annual reports, as well as reflected in the national legislation, because IC constitutes the uniqueness of the higher education institution and ensures its competitiveness on the market. Keywords: intellectual capital, higher education academic management, capacity, corporate culture in cognitive action, higher education institution

1. Introduction The cognition that intellectual capital (hereinafter ‐ IC) is an important part of the organization's balance, which can be considered as a fixed asset and which is as necessary for the functioning of the company as industrial equipment in a factory or a desk in the office becomes increasingly stronger in the world. Intellectual capital consists both of the intellectual property (copyright and related rights, as well as industrial property types), and other goodwill (reputation, know‐how, experience, knowledge, contacts). In order for IC to become a profit boosting asset, it has to be identified, protected and developed. Already during the sixties the need for education in the promotion of the capacity development of society was discussed. For example, Nobel Prize winner Milton Friedman (1962) stated that stable and democratic society is impossible without a minimum level of literacy and knowledge of citizens and a widely accepted set of shared values. Education can contribute to both. IC is the collective knowledge of the individuals in an organisation or society. This knowledge can be used to produce wealth, multiply output of physical assets, gain competitive advantage and / or enhance value of other types of capital. IC is now beginning to be classified as a true capital cost because: 1) investment in people tantamounts to investment in machines and plants and 2) expenses incurred in education and training

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Airita Brenča and Rasma Garleja is equivalent to depreciation costs of physical assets. (Business Dictionary, 2010). IC may be divided into brain intelligence and emotional intelligence (Thompson, 2000). Brain intelligence is more relevant to knowledge and information capacity, whereas emotional intelligence is based on the value system of corporate imagery, culture, communication, feelings. Traditionally, the IC structure in organisations consists of:

Human capital (knowledge, skills, creativity, value system, competence, the level of culture);

The capital of an organisation (hardware and software, patents, innovation, values of the organisation, organizational structure, reputation, competitiveness);

Consumer capital (history, quality of life, interrelations, hierarchy of needs).

The structure of the intellectual capital in higher education institutions may be interpreted as: Human capital is the expertise of the higher education institution human resources (academic and administrative staff ‐ lecturers, researchers). Structural capital is the expertise that remains in the higher education institution irrespectively of the human resource variability (legally enforced intellectual property, databases, system, procedures, organizational chart, etc.). Relationship capital represents the external relationship resources that are related to the higher education institution in different ways (internal and external customers, the parents of the students, sponsors, cooperation partners, competitors, governmental and non‐governmental organizations, etc.). The methodological background for IC efficiency between service providers and consumers has not been developed. The intelligence of the human capital is characterized by education, level of culture, physical development, etc. The consumer IC is characterized by: attitudes towards different cultures, religion, language, communication, information technology management, computer science, management, etc. In the present interdependent economy achievements in innovative, high‐value sectors are essential for economic growth and the ability to create jobs in the coming decades. In order to create and fill the future jobs of the mentioned kind, heavily saturated with knowledge, highly skilled people who are able to respond to modern economic opportunities and requirements are needed (MEMO/11/613). According to the conclusion of the authors, intellectual capital is the mental value of human potential in education, research and socialisation processes. IC encompasses mental values, which are implemented in diverse structures: human capital, intellectual capital and relationship capital of the organisation. The demand for the structural elements of IC depends on the importance in the public relations system, demand in applied mental activities and commercialization of mental values.

2. Internationalisation and openness of higher education as an index, influencing the international trade balance International trade is the exchange of goods and services between countries. According to the UN definition, export and import transactions between residents and non‐residents are carried out in international trade. It promotes mutual competition and consequently the growth of the producers and providers of goods, who by taking care of the quality of the goods and services on the market ensure end‐user satisfaction. Latvia, as a sovereign country, has economic relationships with other countries – both with partners in the nearby Baltic States, as well as more distant partners in Scandinavia, Germany, Great Britain, Russia, etc. According to the data of the Central Statistical Bureau (CSB), the international trade turnover of Latvia amounted to 13 599.3 million Lats in 2011 or by 28.2% (2 992.5 million Lats) more than in 2010, including the export volume of 6 012.0 million Lats ‐ 28.1% (1 317.1 million Lats), whereas the volume of imports was 7 587.3 million Lats ‐ by 28.3% (1 675.4 million. Lats) more than in 2010. The product of higher education is important not only to Latvia, but also in international circulation. International trade of higher education is the exchange of higher education services between the universities of two or more countries. Service is an activity which is carried out in the form of exchange of goodwill with

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Airita Brenča and Rasma Garleja the aim of satisfying consumer needs, achieving high quality, useful effect (MSITS 2010). The services can be relatively divided into: state, commercial and social services (GATS, 2002), where the social service group includes education services. It has to be noted that the most significant share of the GDP of Latvia, approximately 70% in 2011 accounted for specifically by the service sector. The internationalization of tertiary education as a reflection of the globalization process of the economy and the societies and the increasing capacity of the universities has intensified over the last 34 years. According to UNESCO, 165 million students participated in the formal tertiary education worldwide in 2009, an increase by 65 million students since 2000 (65%). According to OECD data, in 2009 nearly 3.7 million post‐secondary (or level 3, tertiary education) students have joined foreign universities outside their country of citizenship. The highest admission numbers of international tertiary students in descending order are in Australia, Great Britain, Austria, Sweden and New Zealand. For some world powers internationalization of education in the context of international trade is an important source of income reflected in the economic indexes of the country. For example, Australia’s exports of education services are an important part of Australia’s service exports to the world (accounting for around 36% of total exports in 2009/ 2010). International education activity contributed $16.3 billion in export income to the Australian economy in 2010/ 2011. According to Australian Bureau of Statistics (ABS) education was Australia’s third largest export behind coal and iron, ahead of gold, tourism, crude oil and natural gas in 2011. Within Europe, the United Kingdom has the longest tradition of education export and its institutions are by and large the ones most active in transnational education projects. The value of UK education exports was estimated to constitute £ 14.1 billion in 2008/2009. This value is predicted to grow annually by about 4 per cent in real terms, so it would be worth about £ 21.5 billion in 2020 and £ 26.6 billion in 2025 (both in 2008/2009 prices). The value of education as an export from the UK needs to be much more fully recognised by the government and a coherent approach across departments and agencies developed. The export value of higher education specifically makes up a large share of this, worth £7.9 billion annually (Wild ReSEARCH 2011). In Latvia export travel expenses associated with acquiring higher education were 10.6 million Lats or 0.5% from a total amount 2.2 billion of services export, whereas such service import was 19.3 million Lats or 1.5% from a total service import of 1.3 billion Lats in 2011 according to the data of the Bank of Latvia. Internationalisation and openness of higher education systems requires a joint approach from a wide range of policy areas and stakeholders, to attract the best students, staff and researchers from around the world, to increase international outreach and visibility, and to foster international networks to excellence. The Europe 2020 strategy, its Flagship Initiatives and the new Integrated Guidelines put knowledge at the heart of the Union’s efforts for achieving smart, sustainable and inclusive growth; the Commission proposal for the Multiannual Financial Framework 2014 ‐ 2020 supports this strategy with a significant increase in the budget devoted to investment in education, research and innovation. It is because mainly the higher education plays a crucial role in individual and societal advancement, and in providing the highly skilled human capital and the articulate citizens the Europe needs to create jobs, economic growth and prosperity (COM (2011) 567 final). Europe is no longer setting the pace in the global race for knowledge and talent, while emerging economies are rapidly increasing their investment in higher education. While 35% of all jobs in the EU will require high‐ level qualifications by 2020, only 26% of the workforce currently has a higher education qualification. The EU still lags behind in the share of the researchers in the total labour force: 6 per 100, compared to 9 in the US and 11 in Japan. One of the EU’s core aims is to reduce unemployment thereby increasing the level of productive human capital within the EU. The employment rate is an indicator of human capital assets. To increase this human capital EU governments invest in labour market policy measures. The knowledge economy needs people with the right mix of skills: transversal competencies, e‐skills for the digital era, creativity and flexibility and a solid understanding of their chosen field. At the same time, higher education institutions too often seek to compete in too many areas, while comparatively few have the capacity to excel across the board. As a consequence, according to the latest Academic Ranking of World Universities only around 200 of Europe’s 4000 higher education institutions are included in the top 50, and only 3 in the top 20.

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Airita Brenča and Rasma Garleja Higher education systems require adequate funding, and the Europe 2020 strategy highlights the need to protect the growth‐enhancing areas of education and research when prioritising public spending. Yet, total investment in higher education in Europe is too low: 1.3% of GDP on average, compared with 2.7% in the U.S. and 1.5% in Japan (COM (2011) 567 final). Total public expenditure on education as % of GDP (for all levels of education combined) indicates that in 2009 in the EU‐27 countries combined it constitutes 5.41% from GDP, including 5.64% in Latvia and 5.64% in its neighbouring country Lithuania. The highest amount of investment % is in the Scandinavian countries: Finland 6.81%, Sweden 7.26% and Norway 7.32% (Eurostat 2012). According to the objectives of the EU 2020 strategy an investment of 3% of the EU GDP has been envisaged for R & D (the objective of Latvia is to reach 1.5% of the GDP), the proportion of young people leaving school early has been envisaged to fall below 10% for the EU (the percentage of early leavers from education and training in Latvia in 2011 decreased by 3.7% (11.8%) compared to 2008 (15.5%) (Eurostat, 2012)), and 40% of the EU persons aged 30 to 34 are expected to successfully complete higher education or equivalent (the goal of Latvia is to reach 34 ‐ 36%). IC is formed and implemented during a long‐time period. Therefore when elaborating the IC development strategy, it is necessary to clarify the structure of IC, the IC index system, influencing factors and management mechanisms. The IC research methodologies are widely used in the theories of knowledge management, marketing, risk theories. An important factor of IC is the management of knowledge capacity development. This is a changing process (doubles every four years, and in some industries even faster). Learning according to traditional methods hinders the pedagogical process. There is a need for a new education philosophy to meet the challenge (vision, corporate communication, team working methods, systemic, creative thinking, and motivation to explore, discover, and change). For example, a corporate information system for the solution of dialogue problems acts as an operational management tool, IC academic management. The ultimate goal of the higher education institutions is to raise intelligence capable of maintaining in development not only the potential of mind, but also technology and commerce, unite semantics and logic in the problem solving process. In accordance with the mission set out for education, the value of applying knowledge is formed by cognitive activity in the study process, research, the capital of ideas, innovation, corporate collaboration, education marketing, IC circulation, as well as academic management. Academic management in higher education consists of five components: 1) student enrolment and financial management, 2) curriculum planning and management, 3) organization of the study process and ensuring of infrastructure, 4) ensuring of quality requirements for study achievements and science management, 5) staff and student cognitive performance management (Elearn 2005). The IC of an organization establishes and maintains the synergy effect of the intellectual capital activities from the intangible intellectual resources. The marketing scope functions of IC are: research of consumer needs, target market identification, development strategy planning, implementation of innovation policy, IC pricing and analysis, communication policies in IC promotion on the market, labour market research, competition assessment, the study of the state of the market, opportunity and risk assessment, innovation marketing, corporate culture, etc. Thus, the marketing of the IC of an organisation is expressed in the interaction with the consumers, intermediaries, intellectual service providers and IC payback period and effectiveness (cultural communication space acquisition, procedural learning quality, value system alignment, etc.). As indicated above, the education product management includes research in an interdisciplinary context. In order to provide scientific substantiation for education product commercialization, education product management strategy, based on the synergy of materialized IC as a past performance result and human capital in the future activity (the potential of ideas) is necessary. In accordance with the objective of the study, the authors continue in‐depth study of the factor influence with the accentuation on the higher education product import and export development. An important condition for international trade is education export and import development, education environment, including the structure of intellectual conditions on macro ‐ mezo ‐ micro level, because the structure of human consciousness depends on the individual's relationship with the world and the significance of this relationship in the activities of life. Therefore, the task of modern education is to develop the

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Airita Brenča and Rasma Garleja intellectual potential, the ability to adapt to change on the education product market in a global competition situation, to adapt to innovative environment. The authors in Figure No. 1 offer IC management component framework for higher education.

Figure 1: Intellectual capital management component framework for higher education

3. Historical development of the term ‘intellectual capital’ The beginning of the first phase of IC was in the nineties and scientists focused on the development of concept awareness, defining of concepts, case study analysis and the development of primary definitions (Stewart 1991; Stewart 1994; Klein and Prussak 1994; Edvinsson & Sullivan 1996; Saint Onge 1996, Brooking 1996; Petrash 1996; Sveiby 1997; Edvinsson 1997; Haan & Lowendahl 1997, Sveiby 1997, Ross 1997; Edvinsson & Malone 1998; Klein 1998; Mouritsen 1998; Ulrich 1998; Knight 1999; Roots 1999). The second phase started in 2000, when terminology comparisons, measurements by a variety of methods, modelling and international studies were carried out, annual reports of companies in different industries were developed (Guthrie & Petty 2000; Brennan 2001; Bozzolan, Bont, Crossan & Hulland 2002; Neely 2002, Favotto & Ricceri 2003; Diefenbach 2004; Marr 2005; Abeysekera & Guthrie 2005; Amanda 2006; Shelemiah 2007; Ricceri 2008). Different models were developed in IC management. Some of the most well‐known are Sullivan’s Model (Van den Berg 2002), the Scandia Intellectual Capital Value Scheme (Roos, Roos, Dragonetti and Edvinsson 1997), Roos and Roos Categorisation (Roos and Roos 1997), Sveiby’s Model (Sveiby 1997), Wiig’s Model (Wiig 1997) and the Brooking’s Model (Brooking 1996). In the state or public sector, including the sector of services, generally known and accepted IC practice still does not exist. A few separate studies have been carried out, for example, the national IC has been researched from the methodological perspective and the national economic competitiveness reports have been developed (Malhotra, 2000, Ståhle and Ståhle 2004). With the help of the knowledge model and structural capital, human and technological capital variable summary the IC of the European Union has been evaluated (Navarro, Ruiz and Peña 2011).The authors used the INANK (Integral Analysis of Knowledge) model indicators and based on the 2006 data, expressing the estimates as a percentage of GDP. IC was estimated as a total of human capital (by adding labour skills and Recycle generators) and structural capital, including R & D and innovation. As a result, IC rates ranged from 14.71% (Malta) to 39.19% (Sweden). Sweden, Great Britain and Denmark were leading (with respectively 39.19, 38.07 and 35.80%), where the difference between Sweden and the United Kingdom is quite small. Countries in the top ten, in descending order, are Slovenia (34.41%), Germany (33.28%), Estonia (32.09%), Austria (32.05%), the Czech Republic (30.91 %), Finland (30.85%) and the Netherlands (29.53%). the IC of Latvia was estimated to rank 14th with 28.75% among 27 countries and groups of countries.

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4. Research of intellectual capital in the system of higher education The Austrian Research Centre (APC) was the first European research organization, which published an IC report in 1999. This organization is the largest organization, founded by the public sector of Austria and performs the function of an important link between the basic research in the universities and applied research in the companies. APC was perceived as a new instrument for the assessment of the intangible property not indicated in the annual reports, and as an essential part of corporate strategy. APC experience was so important that in 2007 the IC reports became mandatory for all Austrian universities. The Education, Science and Culture Ministry of Austria adopted the idea that IC reports promote transparency, intangible property management and determine performance orientation initiatives. On July 20, 2011 in Sopot (Poland) the first European Research Area Ministerial Conference on the IC theme 'Intellectual capital ‐ creative impact', which emphasized the role of universities in a globalised world, as they are significant knowledge and innovative thinking sources, was held. The academic staff of several universities has focused on IC studies not only in the public sector, but also in universities and research institutions ‐ the institutions with the task to generate knowledge and the development of research for the scientific community and the public. However it has to be admitted that IC assessment is still not sufficiently included in the academic management of the universities, as well as that up to now a single IC model for university applications in practice has not been created. Similarly, only a few important studies and documents can be singled out in the academic literature. The first one is IC Guidelines of Denmark, developed by Danish Agency for Trade and Industry (DATA‐ 2000). Studies of more global nature are included in the ICU report, which was developed in the framework of the University Observatory and the PRIME project (Sanchez 2001), RICARDIS study (EC 2006) and the University Observatory study (EOU 2006) study), in which Bontis (1998) classification of the IC was traditionally used (human capital, structural capital and relationship capital). The universities of Austria (Leitner 2004) presented a very important message for the IC model. This was followed by the IC report of Poznan University of Economics (Fazglagic 2005). One year later there were found some similarities between IC approaches at firm and political level in the European universities (Sanchez, Elena 2006). University of Johannesburg in South Africa developed a model to evaluate university IC management practices (Kok 2007). IC reports were mutually compared also in British universities (Bezhani 2007). In 2009, a study was conducted in the Italian universities on the correlation between IC and the scientific performance of higher education institutions (Palumbo, Berardino 2009), a study was also carried out with the aim to develop an IC assessment model, thus stimulating the understanding of the IC contribution to the university performance, and as a result a conceptual framework, where IC is integrated into the university assessment framework in Taiwan (Lee 2009) was offered. In 2010, the IC in the universities of Taiwan was analysed, based on indicators of innovation capital (Wu, Chen and Chen 2010), a study on the assessment of human capital, structural capital, relationship capital and intellectual property was implemented in Payam Nour University in Iran (Rafiee, MosavI and Amirzadeh 2010) and the role of intangible assets in higher education and research institutions was discussed (Secunda, Margherita, Elia and Passiante). A year later in the universities of Romania the possibility to combine prospecting technology and IC management was researched (Pérez Saritas, Pook and Warden 2011). In 2012 the direct influence of the leadership and strategy, human capital, structural capital and relationship capital on the implementation of the objectives of higher education institutions was tested in the Jordanian universities (University of Jordan, Jordan Al Zaytoonah University and Southeast University) (Najim, Al‐Naimi and Alnaji 2012). In the same year in the Romanian education system ‐ especially the tertiary / higher education, a theoretical framework for the correlation between trust, culture, reputation and IC was proposed (Suciu, Picioruș and Imbrișcӑ, 2012) and the IC model for Iranian education system (Ali, Zohreh, Khodadoost 2012) was developed.

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Airita Brenča and Rasma Garleja In the Table 'Intellectual Capital Research in Higher Education Institutions' (Appendix) fourteen studies have been analysed, their results have been published in scientific journals. The authors have indicated the key data for each study in the Table: the author and the country of the working place, object of the research, keywords, the research purpose and quintessence. In the Table IC has been indicated as a keyword in ten cases, IC measurement in one case and a new term ‘Innovation Capital’ has been developed in one more case (Wu, Chen and Chen 2010). In respect to the study site keywords ‘Universities’, ‘Higher Education Institution’, ‘University leadership’ are indicated. In some studies the keywords IC‐specific components or relevant aspects appear, whereas three studies display different keywords which suggests an innovative approach to the evaluation of IC – ‘Fuzzy Analytic Hierarchy Process’ (FAHP) (Lee 2009), ‘Vlsekriterijumska Optimizacija I Kompromisno Resenje’ (VIKOR) (Wu Chen and Chen 2010) and ‘Forward Planning’ (Perez Saritas, Pook and Warden 2011). As mentioned above in the article, in the private and the public or state sector of Europe, a well‐known, commonly used and accepted IC practice does not exist.

5. Overview of the IC characteristics in the higher education institutions of Latvia The university IC evaluation reports are also currently not developed in any of the 34 higher education institutions of Latvia, of which six are classical university type higher education institutions; two are state universities, 12 polytechnics and 14 higher education institutions founded by legal entities (private). In Latvia, under Article 19, paragraph 3 of the 'Research Activities Law' a higher education institution publishes a report on research activities in the form of a separate publication and on the Internet not later than six months after the end of the year. Public reviews of the higher education institutions of Latvia include significant data on scientific publications, research implemented, data on the development, research and education projects, reports on funding received and spent; information on the research results of the departments (including scientific publications, scientific articles, published monographs and teaching aids); scientific conferences, registered and maintained patents. These performance indicators exist in different presentations, not all of the indicators mentioned are presented in the reports, and also the scope and level of detail is different ‐ from 23 pages (Ventspils University) to 370 pages (University of Latvia), because no set criteria exist either in respect to the content or volume. In respect to the legalization of the term IC in Latvia in the laws, regulations or other documents there is no document to be mentioned. Implicitly to IC may be attributed 'Intellectual property protection and provision guidelines for 2008 to 2012', issued in accordance with the Cabinet Regulations No. 521 from August 26, 2008 and defining the challenges for meeting which it is necessary to implement certain government policies, such as gaps in the promotion of invention, the influence of European patent system harmonization, insufficient police capacity in relation to the protection of intellectual property rights, lack of research on intellectual property issues, gaps and inaccuracies in legislation relating to the protection of intellectual property rights. Policy guiding principles, objectives, action results, future action planning is addressed. According to the econometric estimates, each additional year of education increases the productivity and employee wages by an average of 6 ‐ 10% (Acemoglu 2007). The main statistical findings in 2009 indicate that employees with tertiary education earned twice as much as those with a low level of education (Eurostat 2012). In higher education the capacity of IC depends on the human resource theoretical knowledge, experience, scientific information and its availability, perceptual abilities, synergy skills and innovative technologies. At present, when the demand for highly qualified researchers has increased in the world, university IC is rather sensitive to market fluctuations. Higher education institutions, which do not invest into the growth of their human capital, are likely to encourage 'brain drain' not only from the higher education institution, but also from the country. Higher education increases human capital and hence also the productivity: a person with higher education can produce more added value during a man‐hour than a person without it and respectively receives a higher remuneration. The public benefit from education could be even higher, since education tends to increase wages not only for the educated person, but also for other members of society.

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Airita Brenča and Rasma Garleja In the present age of knowledge‐based global economy IC in universities is much more important than physical or tangible capital. Admittedly, under the conditions of the markets becoming increasingly more competitive the only chance for the universities to survive is to continuously increase their competitiveness, while simultaneously strengthening the IC position in their organization. As long as higher education institutions fail to recognize IC elements in maintaining their capacity, the application of IC is difficult, because it is not possible to work purposefully with it and effectively utilize it to the benefit of their own needs and those of the related parties. The authors conclude that some indicators of the traditional three IC components (human capital, relationship capital and structure capital) may be found in the reports of the universities of Latvia, however a detailed and comprehensive analysis of IC measurements is not available in the country and has not been carried out. The follow‐up analysis of IC in Latvian universities should be continued and the visibility and application of IC should continue to be used for development planning documents, studies and university annual reports, as well as reflected in the national legislation. It is necessary to recognize, that IC is the most important resource of higher education institutions for the increase of their competitiveness.

Acknowledgements This work has been supported by the European Social Fund within the project “Support for Doctoral Studies at the University of Latvia”

Appendix: Table 'Intellectual Capital Research in Higher Education Institutions' Author (country of the working place) Karl‐ Heinz Leitner, Michaela Shaffhauser‐ Linzatti, Rainer Stowasser (Austria)

Amir Fazglagic (Poland)

M.Paloma Sanchez, Susana Elena (Spain)

Andrew Kok (South Africa)

Research purpose / Object of the research (Keywords) 2004 Demonstrate the usefulness of data envelopment analysis (DEA) as a consulting and management tool that fulfils the requirements of quantitatively and comprehensively evaluating and benchmarking the efficiency of IC / Universities of Austria. (IC, Universities, Data Analysis, Austria) 2005 Analyses some fundamental challenges regarding the measurement of the IC of a university / The Poznan University of Economics. (IC measurement) 2006 Improve research management and contribute to comparative analysis in European universities; highlight some methodological and conceptual considerations in relation to the analytical framework developed within an on‐going experience – the Observatory of European Universities (OEU) / universities. (IC, Universities, Knowledge management, Intangible assets, Research, Organizations, Spain) 2007 Human capital, structural capital and customer capital are important variables of

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Quintessence

Results illustrate the existence of scale efficiencies of Austrian university departments and show a large heterogeneity within and among universities as well as between different fields of study with respect to their efficiency.

The IC measurement should be a platform for discussion about intangible assets in the university. The measurement of universities’ performance is essential if higher education system is to continuously regenerate itself by the intelligent use of knowledge management. Provides some insight into the utility of the framework. From a conceptual point of view, the authors found some similarities between IC approaches at firm and political level.

Indicates which of the aspects needs to be measurement and a new framework for

Airita Brenča and Rasma Garleja Author (country of the working place)

Ivoni Bezhani (UK)

Author / country of the working place Riccardo Palumbo, Daniela di Berardino (Italy)

Shyh – Hwang Lee (Taiwan)

Hung – Yi Wu Jui – Kuei Chen, I – Shuo Chen (Taiwan)

Mojtaba Rafiee, Mohammad Mosavi, Rasoul Amirzadeh (Iran)

Giustina Secundo, Alessandro Margherita,

Research purpose / Object of the research (Keywords) the whole IC management programme: indicate which forms is the part of knowledge management initiatives of institutes of higher learning / University of Johannesburg. (IC management, Knowledge management, Higher Education) Examines the amount and the nature of the voluntary IC disclosure of UK universities, the relation between performance and amount of IC disclosed; and the opinion of UK universities on a mandatory disclosure of IC / UK universities. (IC, Universities, Annual Reports, United Kingdom) Research purpose / Object of the research (Keywords) 2009 Investigates the correlation between some indicators promoted in international experience of measuring the IC and the scientific performance / Italian universities. (IC, Academic Research Performance, Research Evaluation Methods, Accountability, Governance) Developing an IC evaluation model to facilitate the understanding of the university performances / Shu‐ Te University. (IC, University assessment, Performance evaluation, Fuzzy analytic hierarchy process) 2010 Analysing the IC of universities based on indicators of innovation capital / Taiwanese universities. (Innovation Capital, Higher Education Institution, FAHP, VIKOR) The elements and four major items of IC are identified based on which the primary model for recognition of IC in Iranian universities / Payame Nour University. (IC, Human Capital, Structural Capital, Relational Capital, Intellectual Property) Discuss the role of intangible assets in higher education and research institutions and present a measurement framework, along with an illustrative application / Italian higher

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Quintessence measurement and management of IC is discussed.

New expertise regarding IC disclosure in higher education and forms a sound basis for future research. Universities could benefit in improving assessment of their intangible assets, performance measurements, allocation of resources and benchmarking exercise.

Quintessence

Analysis shows significant correlations among size of university, financial resources, teaching load, mobility and scientific performance.

A fuzzy approach is integrated with Analytic Hierarchy Process (AHP) method

Fuzzy Analytic Hierarchy Process (FAHP) is used in determining the innovation capital indicators by educational experts; the rankings of universities are determined by Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The relationship between the items and indicators of the model were verified and some indicators for evaluating IC in Iranian universities

Intangible assets are at the core of the mission of education and research organisations. The identification and measurement of IC are thus an operational priority to evaluate the

Airita Brenča and Rasma Garleja Author (country of the working place) Gianluca Elia, Giuseppina Passiante (Italy)

Susana Elena Pérez (Spain), Ozcan Saritas (UK), Katja Pook (Germany), Campbell Warden (Spain) Author / country of the working place Najim A.Najim Mohamed A. Al‐ Naimi, Loay Alnaji (Jordan)

Khalkhali Ali, Shakibaei Zohreh, R.Khodadoost (Iran) Marta‐Christina Suciu, Luciana Picioruș, Cosmin Ionuț Imbrișcӑ (Romania)

Research purpose / Object of the research (Keywords) education and research institution. (IC, Higher education, Intangible assets, Research) 2011 Explores the possibilities of combining foresight techniques and IC management/ Higher education system in Romania and Romanian universities. (IC, Higher Education, Forward Planning, Strategic Management, Romania) Research purpose / Object of the research (Keywords) 2012 Examines the direct impact of four components of IC on realizing university goals / University of Jordan, Al Zaytoonah university of Jordan, Middle East University (IC, University leadership, Human, Structural, Relational Capital, University Goals) Design a model to diagnose and manage IC in the education system of Iran / Iran education system. (IC, Education System, Model) Offering a theoretical framework for the liaisons between the trust, culture, reputation and IC, comparing the findings with situation of other cultures, like Japan and USA / Romanian educational system (IC, trust, cooperation, education, organisational culture, human capital, sustainable competitive advantage)

Quintessence alignment between strategic orientation and performance within such institutions.

A proposal of an integrated use of foresight and IC management for universities. The starting point for better integration of strategic management in higher education institutions. Quintessence

IC has a significant effect on university performance in meeting its goals. Leadership, human and relational capital has in general a significant effect on realizing majority of university goals and more than structural capital. IC model for Iran education system.

The structure and dynamics of the IC formation process in the Romanian higher education system.

References A Handbook for International Bar Association “General Agreement on Trade in Services” (2002) USA, 54 p. Able G., White F. (2011) Report “Education: A Great British Export?” // WILD ReSEARCH, p.5. Andriessen D.G., Stammba C.D. (2004) The Intellectual Capital of the European Union: Measuring the Lisbon agenda// Centre fort Research in Intellectual Capital, INHOLLAND University of Professional education. Ali K., Zohreh S., Khodadoost R. (2012) Designing a model to recognize and manage intellectual capital in education system // ELSEVIER: Procedia – Social and Behavioral Sciences 46, p.992 – 997. Брукинг Э. (2001) Интелектуальный капитал: Ключ к успеху в новой тысячелетия. СПб.: Питер, 2001.‐288 с. Business Dictionary (2010), BusinessDictionary.com Centrālās statistikas pārvaldes (CSP) dati par ārējo tirdzniecību. Pieeja tīmekļa vietnē www.csb.gov.lv, 2012.gada decembrī. COM (2011) 567 final, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: Supporting growth and jobs – an agenda for the modernisation of Europe’s higher education systems, p.2‐14. Edvinsson L., Malone S.M. (1997) Intellectual Capital: realizing your company’s true value by finding its hidden roots, Harper Collins Publishers, New York, 225 pages. Elearn (2005) Limited ed. “Management Extra: Reputation Management”, Great Britain; Elsevier Ltd, Italy. Friedman M. (1962) Capitalism and Freedom, University of Chicago Press, United States, 202 pages.

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Airita Brenča and Rasma Garleja Goleman D. (2002) Primal Leadership: Realising the Power of Emotional Intelligence.‐ Boston: Harvard Business School Press. Kok A. (1997) Intellectual Capital Management as Part of Knowledge Management Initiatives at Institutions of Higher Learning” The Electronic Journal of Knowledge Management Volume 5 Issue 2, pp 181 ‐ 192 , available online at.ejkm.com The Strategic Management of Intellectual Capital/ Klein A.D., editor (1998) Butterworth‐ Heinemann, Woburn, United States of America, 246 pages. Lee S.H. (2010) Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution in a university// ELSEVIER, “Expert Systems with Applications” 37, p.4941‐ 4947 Leitner H.K., Shaffhauser – Linzatti M., Stowasser R. (2005) Data envelopment analysis as method for evaluation intellectual capital, Journal of Intellectual Capital, Vol.6 Iss: 4pp. 528 – 543. Leitner H.K. (2002) Intellectual Capital Reporting for Universities: Conceptual Background and application within the reorganisation of Austrian universities, the paper presented at the Conference “The Transparent Enterprise. The Value of Intangibles” Autonomous University of Madrid. Ministry of Economy, Madrid, Spain. Nacionālo kontu uzskaites rokasgrāmata: Nacionālie konti. Praktisks ievads. Apvienoto Nāciju Organizācijas (ANO) publikācija (pārdošanas nr. E.94.XVII.4), Ņujorka, 2003, 148 lp. Najim A., Al‐ Naimi A., Alnaji L. (2012) Impact of Intellectual Capital on Realizing University Goals in a Sample of Jordanian Universities// European Journal of Business and Management IISN 2222‐1905 (Paper) ISSN 2222‐2839 (Online) Vol 4, No 14, p.153 – 162. Malhotra Y. (2000) Knowledge Assets in the Global Economy: Assessment of National Intellectual Capital // Journal of Global Information Management, 8 (3), 5‐ 15. OECD (2011), Education at a Glance 2011: OECD indicators, OECD Publishing. Peters T. (1994) Liberation Management: Necessary Disorganization for the Nanosecond Nineties, New York, Random House Publishing Group, 834 pages. Rafiee M., Mosavi M. and Amirzadeh R. (2010) Formulating and Elaborating a Model for the Recognition of Intellectual Capital in Iranian Universities// World Applied Sciences Journal 10 (1), IDOSI Publications, ISSN 1818‐4952, p.23‐ 28. Санников А. (2000) Интеллектуапьные активы: идентификация, оценка, управление (американский опыт)// Интеллектуапьная собственность, № 5.‐е. 40‐44. Sanchez P., Elena S. (2006) Intellectual capital in universities: Improving transparency and internal management // Journal of Intellectual Capital, Vol.7 Iss: 4 pp. 529 – 548. Secundo G., Margherita A., Elia G., Passiante G. (2010), Journal of Intellectual Capital, Vol.11 Iss: 2 pp. 140 – 157. Statistical Commission “Manual on Statistics of International Trade on Services 2010 (MSITS 2010)”, Geneva, Luxembourg, New York, Paris, Washington D.C., 190 pages. Stuart T.A. (1997) Intellectual Capital: The New Wealth of Organisations, London, United Kingdom, 280 pages. Suciu M.C., Picioruș l., Imbrișcӑ C.I. (2012) Intellectual Capital, trust, cultural traits and reputation in the Romanian education system // The Electronic Journal of Knowledge Management, Vol.10, Issue 3, pp.223 – 235, available online at www.ejkm.com Гапоненко А.Л. (2001) Управление знаниями. Мoсkва, ИПК госслужбы, 52 с. Thompson K. (2000) Emotional Capital, Oxford: Capstone.

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The Impact of Customer Knowledge Management Process on Service Recovery Performance Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey Faculty of Commerce, Mansoura University, Mansoura, Egypt nal.1987@yahoo.com a_Yehia75@yahoo.com azzamenbawey@mans.edu.eg Abstract: In our knowledge‐based economy, organizations must examine how they can better leverage knowledge assets and create added value. Customer knowledge represents an important organizational asset that organizations would utilize and manage to gain a competitive advantage. The primary aim of the current research is to empirically investigate whether the success, that an organization achieves, in managing customer knowledge would affect its service recovery performance; through examining the impact of Customer Knowledge Management (CKM) process on Service Recovery Performance (SRP), based on the perspective of the Egyptian National Railways' employees. It also attempts to measure how employees and customers evaluate the Egyptian National Railways' actual performance of service recovery .The current research developed a conceptual model to examine the impact of CKM process on SRP through integrating the process of CKM provided by Dalkir (2005) and the five‐dimension model of SRP presented by Liao (2007). Two questionnaires were formed in order to collect the primary data through personal interviews. The first questionnaire was issued to the employees of the Egyptian National Railways in order to investigate their opinions regarding both of CKM process and SRP dimensions. The second questionnaire was for the Egyptian National Railways' customers to measure their evaluation of SRP. A sample of 203 front‐line employees and 333 customers was used to test the conceptual model. Confirmatory factor analysis results supported the modified research model. The research results indicated that CKM process is positively and significantly affecting the service recovery performance of The Egyptian National Railways, and that, each stage of CKM process significantly affects SRP. In addition, there are significant differences between employees' opinions and customers' opinions regarding their evaluation to the ENR's service recovery performance. In summary, this research has demonstrated the value of managing customer knowledge effectively in order to achieve a higher performance on service recovery. Keywords: customer knowledge (CK), customer knowledge management (CKM), service failure (SF), service recovery (SR), service recovery performance (SRP)

1. Introduction Many factors have changed customers' role from being passive recipients of products to become more active and innovative; as a result many organizations consider their customers as knowledge partner (Sun 2010). Customer Knowledge (CK) represents an important organizational asset that organizations would utilize and manage to gain a competitive advantage (Yeung et al 2008). Customer knowledge management is considered as a continuous strategic process by which organizations enable their customers to move from being passive buyers and information sources, to become empowered knowledge partners (Chen and Huang 2011). CKM also represents an organizational approach that organizations utilize to support the role of their customers as value co‐creators within the organization (Belkahla and Triki 2011). On the other hand, Service Recovery (SR) refers to taking the appropriate action that would turn the mistake or failure in service delivery into a positive and profitable situation (Gustafsson 2009). Organizations can achieve a successful SR through: communicating with unsatisfied customers, apologizing to customer for the inconvenient situation, providing customer with a timely feed‐back about the problem and what is being done to solve it, empowering employees to act and make decisions regarding the problem at hand, and ensuring that employees are professional and well‐dressed when dealing with customers (Petzer, Steyn and Mostert 2009). By implementing a successful SR, organizations would be able to retrieve customers previously lost due to service failure(SF), minimize further losses and increase the loyalty of its customers (Chang, Lee and Tesng 2008). The primary aim of the current research is to empirically investigating the impact of CKM process on SRP among the Egyptian National Railways (ERN). It also aims at evaluating the SRP not only from customers' view point, but also from employees' view point; as it is recommended to use an integrated measurement to

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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey evaluate performance that derived from different perspectives (Ebeid 2010). In addition, Bitner, Booms and Mohr (1994) mentioned, it is important to evaluate the service performance from both service provider and customer perspectives; as the service encounter involves those two parties.

2. Literature review 2.1 Customer knowledge (CK) Customer Knowledge is "The dynamic combination of experience, value, scenario information and expertise insights; which is needed, created and observed during the process of transaction and exchange between customers and the organization" (Roy and Stavropoulos 2007: 1‐2). Customer knowledge is a vital organizational resource that organizations could manage to improve innovation, support research and development (Sofianti et al 2009), manage long‐term customer relationships and improve the processes of customer service and retention (Mjahed 2008).

2.2 Customer knowledge management (CKM) CKM is regarded as the process of capturing, sharing, disseminating, and applying customer knowledge to create value for both customer and organization (Parirokh, Daneshgar and Fattahi 2009). This process can occur between an organization and its customers and within the organization; in order to improve customer service, Customer Relationship Management (CRM), and customer retention (Mjahed 2008).

2.3 CKM process Dalkir (2005) presented an integrated CKM process model involving three major stages that are: 2.3.1 CK capture Knowledge capture refers to identifying and gathering existing knowledge both internally within the organization; and/or externally from its environment. 2.3.2 CK sharing During this stage customer knowledge is integrated, disseminated, and shared among employees and other decision makers within the organization. 2.3.3 CK acquisition and application During this stage employees understand customer knowledge (i.e. knowledge acquisition); and apply it in supporting and modifying existing services or in developing new innovative services.

2.4 Service failure (SF) Due to the characteristics of intangibility, inseparability, and variability of service, service failures are inevitable (Wang et al 2010). SF occurs when a customer has negative feelings, is dissatisfied, or has an unpleasant experience during a service encounter (Patterson, Cowley and Prasongsukarn 2006; Chang et al 2008). In other words, SF occurs when the customer's perceived service quality falls below customer expectations (Akbar et al 2010). Chang et al (2008) stated some aspects of service failure, which are :

The organization is unable to provide customer with the requested service.

The service is not executed according to standard procedure.

The service is delayed .

The core service falls below the acceptable level of quality.

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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey SF may upset or anger customers, but failure to address it immediately and effectively would result in customer dissatisfaction or complaints; so that organizations must adopt appropriate service recovery measures, and strategy; in order to save customers and minimize the customer loss (Chang et al 2008).

2.5 Service recovery (SR) SR theory is a new development in the area of service marketing and service quality management (Meng 2009). SR refers to taking the appropriate action that would turn the mistake or failure in service delivery into a positive and profitable situation. The success of the organization in implementing an effective service recovery would improve its customers’ sense of trust and increase their commitment to the organization; and as a result, those satisfied customers would share a positive word‐of‐mouth about the organization with others (Gustafsson 2009).Thus, SR is a valuable marketing tool which constitutes a second chance for the organization to satisfy its customers (Kuenzel and Katsaris 2009). The goal of service recovery is not only to correct specific instances of service failure, but also to improve the service delivery system; so as to precluding any future instances of failure, enhancing customers’ overall perceptions of service quality, and supporting long‐term customer relationships (Vaerenbergh, Vermeir and Lariviere 2010 ). Effective service recovery is not just an after‐thought, but is rather an intentionally designed part of a service delivery system that has been planned into the service design in support of the service concept (Chaharsoughi 2008). Organizations can implement service recovery before the occurrence, on the spot, or during the service delivery; or after a complaint has been lodged, and it can be related to a specific transaction or to the business relationship in general (Boshoff et al 2005).

2.6 Service recovery performance (SRP) SRP is defined as "the behaviors in which customer service employees who directly handle customer complaints engage to recover customer satisfaction and loyalty after service failures" (Liao 2007: 476). Low level of SRP leads to undesired outcomes for any organization; so that organizations need to understand the factors that affect the organizational efforts in response to SF in order to minimize its negative effects on organizational effectiveness (Rod, Ashill and Carruthers 2008). Organizations that suffer from SF need to manage their customer's knowledge; in order to know what customers need and expect organization to do regarding the SF situation. Then, they would compare such CK with actual SRP to determine whether it is effective or not (Boshoff 1999). In another form, organizations have to capture and share CK effectively; and when SF occurs, they would apply this CK to achieve a successful SR (Guo and Niu 2007). Liao (2007) presented a five‐dimension model to measure SRP, these SRP dimensions are: 2.6.1 Making an apology By apologizing to customers, the organization accepts the responsibility for service failure, and regrets for negative events. 2.6.2 Problem solving Beyond receiving an apology, customers typically expect the mistake to be corrected and the problem to be resolved in. If service employees fail to solve the problem, customers will feel that they have not received the outcomes they expect and deserve. 2.6.3 Being courteous It is an important dimension of SRP that consists of customer service employees’ behaviors that demonstrate politeness, respect, friendliness, and patience when interacting with the customers.

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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey 2.6.4 Providing an explanation It refers to providing customer with a clear and reasonable cause for SF. Customers view the explanation as an important piece of information, a valuable outcome, and a means to understand and control their service environment. 2.6.5 Prompt handling It refers to service employees' quick response to a customer complaint. Customers may view this prompt response as a valuable outcome and an appropriate way for the service employee to communicate and interact with customers.

3. Research model and hypotheses 3.1 Conceptual research model This research developed a simple model (figure 1) to examine the impact of CKM process on SRP that integrated the process of CKM provided Dalkir (2005) and the five‐dimension model of SRP presented by Liao (2007).

Figure 1: Conceptual research model

3.2 Research hypotheses The research attempts to test the following hypotheses: H1. CKM process affects –positively– SRP. H2. CKM process affects –positively– each dimension of SRP: H2.1. CKM process affects –positively– making an apology. H2.2. CKM process affects –positively– problem solving. H2.3. CKM process affects –positively– being courteous. H2.4. CKM process affects –positively– providing an explanation. H2.5. CKM process affects –positively– prompt handling.

H3. Each stage of CKM process affects –positively– SRP: H3.1. CK capture affects –positively– SRP. H3.2. CK sharing affects –positively– SRP. H3.3. CK acquisition affects –positively– SRP. H3.4. CK application affects –positively– SRP.

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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey H4. Each stage of CKM process affects –positively– making an apology: H4.1. CK capture affects –positively– making an apology. H4.2. CK sharing affects –positively– making an apology. H4.3. CK acquisition affects –positively– making an apology. H4.4. CK application affects –positively– making an apology. H5. Each stage of CKM process affects –positively– problem solving: H5.1. CK capture affects –positively– problem solving. H5.2. CK sharing affects –positively– problem solving. H5.3. CK acquisition affects –positively– problem solving. H5.4. CK application affects –positively– problem solving. H6. Each stage of CKM process affects –positively– being courteous: H6.1. CK capture affects –positively– being courteous. H6.2. CK sharing affects –positively– being courteous. H6.3. CK acquisition affects –positively– being courteous. H6.4. CK application affects –positively– being courteous. H7. Each stage of CKM process affects –positively– providing an explanation: H7.1. CK capture affects –positively– providing an explanation. H7.2. CK sharing affects –positively– providing an explanation. H7.3. CK acquisition affects –positively– providing an explanation. H7.4. CK application affects –positively– providing an explanation. H8. Each stage of CKM process affects –positively– prompt handling: H8.1. CK capture affects –positively– prompt handling. H8.2. CK sharing affects –positively– prompt handling. H8.3. CK acquisition affects –positively– prompt handling. H8.4. CK application affects –positively– prompt handling. H9. There are no significant differences between the Egyptian National Railways' employees and its customers in terms of their evaluation to SRP.

4. Research methods 4.1 Population and sample The current research has two populations: (1) Population of the ENR's employees that includes all front‐line employees (i.e. employees who deal directly with train passengers). (2) Population of the ENR's Customers consists of all the train passengers. A census technique was used to collect primary data from the employees' population, whereas a systematic sample consisting of 384 people was taken from the customers' population. The completed employees' questionnaires were 203 with responding rate of 85.7%; while, customers' completed questionnaires were 333 with responding rate of 86.7%.

4.2 Questionnaire design The first questionnaire consists of two parts. The first part was designed to examine CKM process and it contains four constructs (i.e. CK capture, CK sharing, CK acquisition, and CK application). The second part was designed to identify SRP and it includes five constructs (i.e. making an apology, problem solving, being courteous, providing an explanation, and prompt handling). While, the second questionnaire consists of one part containing the five constructs of SRP presented at the first questionnaire. All scales items were integrated from various previous studies. For measuring all variables, a five‐point Likert scale is used ranging from strongly disagree (1) to strongly agree (5).

4.3 Data collection Data collection was carried out by two structured questionnaires administered through personal interviews. The first questionnaire was issued to the employees of the ENR to identify their opinions regarding both of CKM process and SRP. The second questionnaire was provided to the customers of the ENR to investigate their opinions regarding the ENR's SRP.

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4.4 Reliability test To make sure that items on the instrument are measuring the same thing. Internal‐consistency reliability was measured using Cronbach’s alpha coefficient. Employees' Questionnaire Reliability

The internal‐consistency of all items of the scale is verified with alpha coefficient of 0.969. In addition, constructs Cronbach's alpha is ranging from a minimum value of 0.813 and a maximum value of 0.938 which indicates high internal consistency. Customers' Questionnaire Reliability

The internal‐consistency of all items of the scale is verified with alpha coefficient of 0.883. In addition, Constructs Cronbach's alpha is ranging from a minimum value of 0.738 and a maximum value of 0.860 which indicates high internal consistency.

4.5 Confirmatory factor analysis (CFA) CFA allows testing hypothesis that a relationship between the observed variables and their underlying latent constructs exists (Shaqrah 2008). CFA was conducted on the conceptual research model (figure 1); according to which there are 39 items (i.e. observed variables) supposed to be saturated on 9 factors (i.e. latent variables). The CFA results indicate that the first 8 factors has a sufficient number of items (at least two) loading on them to a significant (0.40) extent (Boshoff 1999). In addition, there are 7 problematic items which have factor loading less than 0.40, which in turn refers to the necessity of deleting these items before conducting any further analysis.

4.6 Modified research model CFA results indicated the necessity of deleting 7 problematic items (Cap3, Cap4, Shar4, Shar5, Acq3, Apol3, and Sol2) which have factor loading less than 0.40. Therefore, the modified scale would include 32 items. Moreover, both of providing an explanation items and prompt handling items have been integrated into a new construct called timely feedback as shown in figure(2). The modified 32‐item scale was subjected to reliability and validity tests. Results confirm internal‐consistency reliability of the scale items. CFA results support the modified model as all 32 items have factor loading greater than 0.40 and each of them is saturated on its proposed construct.

Figure 2: Modified research model

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4.7 Modified research hypotheses Based on CFA results, research hypotheses would be modified by substituting both of sub‐hypothesis H2.4 and sub‐hypothesis H2.5 with a new sub‐hypothesis which is: CKM process affects –positively– timely feedback. Moreover, Research hypothesis H7 would be modified to include both of hypotheses H7 and H8, so it would be: Each stage of CKM process affects –positively– timely feedback.

5. Results and discussion The results of simple linear regression tests indicate that: 1. CKM process has a positive and significant impact on SRP. 2. CKM process has a positive and significant effect on each dimension of SRP : 2.1. CKM process has a positive and significant impact on making an apology. 2.2 CKM process has a positive and significant impact on problem solving. 2.3 CKM process has a positive and significant impact on being courteous. 2.4 CKM process has a positive and significant impact on timely feedback. The results of multiple linear regression tests indicate that:

CK application has the greatest impact on SRP with β value equal 0.318, followed by CK acquisition with β value equal 0.209, and CK capture has the lowest impact on SRP with β value equal 0.20; while, there is no significant impact of CK sharing on the ENR's performance on SR.

CK application has the greatest impact on making an apology with β value equal 0.378, followed by CK acquisition with β value equal 0.182; and CK capture has the lowest impact on SRP with β value equal 0.175; while, there is no significant impact of CK sharing on making an apology.

CK capture has the greatest impact on problem solving with β value equal 0.309, followed by CK application with β value equal 0.265, and CK sharing has the lowest impact on problem solving with β value equal 0.165; while, there is no significant impact of CK acquisition on problem solving.

CK application has the greatest impact on being courteous with β value equal 0.246, and CK acquisition has the lowest impact on being courteous with β value equal 0.174; while, there is no significant impact of both of CK capture, and CK sharing on being courteous.

CK application has the greatest impact on timely feedback with β value equal 0.308, and CK acquisition has the lowest impact on being courteous with β value equal 0.263; while, there is no significant impact of both of CK capture, and CK sharing on timely feedback .

The results of Mann‐Whitney "U" Test illustrated that employees' mean rank is about 383; while, customers' mean rank is about 196; indicating that employees' evaluation to the ENR service recovery performance is greater than customers' evaluation. To conclude, the results of current research demonstrated that CKM process has a positive and significant impact on SRP; indicating that, when an organization succeed in managing its customer knowledge effectively, its performance in implementing a successful service recovery strategy would improve. This result confirms what Mjahed (2008) mentioned that, CKM represents one effective mean to enhance an organization's ability to implement a successful SR strategy. In other words, organizations have to capture and share CK effectively; and when a service failure occurs, they would apply this CK to achieve a successful SR (Guo and Niu 2007). The results also indicated that CKM process has a positive and significant effect on each dimension of SRP. Therefore, when an organization implements the CKM process effectively that's would be reflected on:

Its ability to provide its customers with the appropriate and desired apology for any service failure occurrence;

Its success in solving any problem could face its customers;

Its employees' success in dealing courteously with customers; and

Its ability to provide its customers with a reasonable and continuously updated explanation for any service failure and what is being done to solve it .

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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey CK application stage has the greatest impacts – among all other CKM process stages – on SRP and all of its dimensions except the dimension of problem solving which is affected by CK capture more than being affected by CK application. CK sharing stage doesn't have a significant impact on SRP, making an apology, being courteous and timely feedback. Whereas; CK capture stage doesn't have a significant impact on being courteous and timely feedback. While, CK acquisition stage doesn't have a significant impact on problem solving dimension. Finally, one of the important results of that research was that employees' evaluation to the service recovery performance is greater than customers' evaluation. This result means that employees overestimate their performance on service recovery, and that service recovery performance does not keep up with customers' expectations.

6. Research limitation The current research was attempting to measure the impact of CKM process on SRP all from employees’ perspective; however, it was found that employees overestimate their performance; so it was better to measure CKM process only from employees’ perspective and measuring SRP from customers’ perspective to get more accurate results.

7. Practical recommendations The ENR is recommended to apply the following guidelines in order to improve its service recovery performance:

Managing its customer’s knowledge effectively; in order to know what customers need and expect the ENR to do regarding any possible service failure.

Providing customers with sufficient information about: any change in the trains' timetables and the reasons for this change, any change in the service providing procedures, any new service or any improvement of the current services, the reasons for any service failure occurrence, once it happens, and the ENR's responsibility and regret when it fails in providing any service. All of this information must be provided in a timely manner.

Appling the service recovery strategy that maintain customers' satisfaction, through taking customers' opinions and expectations into account while implementing the service recovery strategy.

Setting its service recovery strategy as a part of its service improvement system, and activating proactive service recovery.

The ENR can achieve a successful service recovery through:

Apologizing to customer for the inconvenient situation, and announcing its responsibility and regret when it fails in providing the proper service.

Correcting mistakes and solving problems.

Encouraging its employees to interact with customers with politeness, respect, friendliness, and patience.

Providing customers with a timely feed‐back about the problem and what is being done to solve it.

8. Further studies recommendations In fact, the results of the current research would encourage a continuation of research regarding the following points:

Measuring CKM process from employees’ perspective and study its impact on customers’ evaluation to SRP.

Examining the impact of customer knowledge management process on proactive (preventive) service recovery.

Integrating CKM process with the other factors that could affect SRP (such as employee empowerment) and investigating their effects on service recovery performance.

Applying the same research model on other sectors; such as: financial institutions sector, airlines sector, governmental institutions sector.

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References Akbar, S. et al (2010) "Revitalization of Service Quality to Gain Customer Satisfaction and Loyalty", International Journal of Business and Management, Vol.5, No. 6, pp 113‐122. Belkahla, W. and Triki, A. (2011) "Customer Knowledge Enabled Innovation Capability: Proposing a Measurement Scale", Journal of Knowledge Management, Vol. 15, No.4, pp 648‐674. Bitner, M. J., Booms, B. H. and Mohr, L. A. (1994) "Critical Service Encounter: The Employee's Viewpoint", Journal of Marketing, Vol. 58, October, pp 95‐106. Boshoff, C. (1999) "RECOVSAT: An Instrument to Measure Satisfaction with Transaction‐Specific Service Recovery", Journal of Service Research, vol. 1, No. 3, pp 236‐249. Boshoff, C. et al (2005) "A Differentiated Approach to Service Recovery", NRG Working Paper, No. 05‐03. Chaharsoughi, M. T. (2008) "Prioritizing of Airline Service Recovery Solutions by Service Problem Deployment Technique with a Case Study in IranAir", M. Sc Thesis, Lulea University of Technology. 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(2007) " Organizational Characteristics, Knowledge Management Strategy, Enablers, and Process Capability: Knowledge Management Performance in U.S. Software Companies", PhD Dissertation, Lynn University. Kuenzel, S. and Katsaris, N. (2009) "A Critical Analysis of Service Recovery Processes in the Hotel Industry", TMC Academic Journal, Vol. 4, No. 1, pp 14‐24. Lee, K. C., Lee, S. and Kang, I. W. (2005) " KMPI: Measuring Knowledge Management Performance" Information & Management, Vol. 42, pp 469–482. Liao, H. (2007) "Do It Right This Time: The Role of Employee Service Recovery Performance in Customer‐Perceived Justice and Customer Loyalty after Service Failures", Journal of Applied Psychology, Vol. 92, No.2, pp 475‐489. Lopez‐Nicolasa, C. and Molina‐Castillo, F. J. (2008) " Customer Knowledge Management and E‐commerce: The role of customer perceived risk", International Journal of Information Management, Vol. 28, pp.102‐113. Madhoushi, M., Saghari, F. and Madhoushi, Z. (2011) " Survey of Customer Knowledge Management Impact on Customer Relationship Management: (Iranian study)", International Journal of Business and Social Science, Vol. 2, No. 20, pp 215‐226. Massa, S. and Testa, S. (2009) "A knowledge Management Approach to Organizational Competitive Advantage: Evidence from the Food Sector", European Management Journal, Vol. 27, pp 129–141. Meng, Y. (2009) "The Relationships between Service Recovery and Customer Satisfaction: An Experimental Study in Restaurant", www.seiofbluemountain.com/search/detail.php?id=4476. Mjahed, S. (2008), "Integrating Service Failure and Recovery into Knowledge Management", Communications of the IBIMA, Vol. 6, pp 15‐20. Niu, Y. (2010) "The Impact of Information Technology on Supply Chain Performance: A Knowledge Management Perspective", PhD Dissertation, University of North Carolina at Charlotte. Ogunde A. 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Nehal El‐Helaly, Ahmad Ebeid and Azza El‐Menbawey Patterson, P. G., Cowley, E. and Prasongsukarn, K. (2006) " Service failure recovery: The moderating impact of individual‐ level cultural value orientation on perceptions of justice", International Journal of Research in Marketing, Vol. 23, pp 263‐277. Peng, J., Lawrence, A. and Koo, T. (2009) "Customer Knowledge Management in International Project: A Case study", Journal of Technology Management in China, Vol. 4, No. 2, pp 145‐157. Petzer, D. J., Steyn, T. F. J. and Mostert, P. G. (2009) "Customer Retention Practices of Small, Medium and Large Hotels in South Africa: An Exploratory Study", African Journal of Marketing Management, Vol. 1, No.1, pp 32‐42. Rod, M. Ashill, N. J. and Carruthers, J. (2008) "The Relationship between Job Demand Stressors, Service Recovery Performance and Job Outcomes in a State‐Owned Enterprise", Journal of Retailing and Consumer Services, Vol.15, pp 22‐31. Roy, T. K. and Stavropoulos, V. (2007) " Customer Knowledge Management in the E‐business environment: Cases from Swedish Banks", M. Sc Thesis, Lulea University of Technology. Salomann, H. et al (2005) "Rejuvenating Customer Management: How to Make Knowledge For, from and About Customers Work", European Management Journal, Vol. 23, No. 4, pp 392–403. Salomann, H. et al (2006) "Advancing CRM Initiatives with Knowledge Management", Journal of Information Science and the Technology, Vol. 3, No. 2, pp 22‐43. Santos, C. and Fernandes, D. (2008) "Antecedents and Consequences of Consumer Trust in the Context of Service Recovery", Brazilian Administration Review, BAR, Curitiba, vol. 5, No. 3, p. 225‐244. Sofianti, T. D. et al (2009) "Customer Knowledge Management in New Product Development", Proceedings of Asia Pacific Industrial Engineering & Management Systems Conference, Kitakyushu‐Japan, December, pp 1268‐1279. Su, C., Chen, Y. and Sha, D. Y. (2006) "Linking Innovative Product Development with Customer Knowledge: a Data‐mining Approach", Journal of Technovation, vol. 26, pp 784‐795. Sun, H. (2010) "CKM‐embedded Innovation Marketing as Success Driver for Product Innovation: Theoretical Framework and Empirical Research", M. Sc. Thesis, Berlin university. Tax, S. S. and Brown, S.W. (1998) "Recovering and Learning from Service Failure", Sloan Management Review, Fall 1998, http://sloanreview.mit.edu/the‐magazine/1998‐fall/4016/recovering‐and‐learning‐from‐service‐failure/ , pp 75‐88. Tseng, S. (2009) "A Study on Customer, Supplier, and Competitor Knowledge Using the Knowledge Chain Model", International Journal of Information Management, Vol. 29, pp 488‐496. Vaerenbergh, Y. V., Vermeir, I. and Lariviere, B. (2010) "Why Do Process Recovery Communications Work? Investigating the Mediating Role of Stability Attributions and Perceived Relationship Investment", The 11th International Research Seminar in Service Management, La Londe les Maurres, France, May. Wang, Y. et al (2010) "The Relationship of Service Failure Severity, Service Rcovery Justice and Perceived Switching Costs with Customer Loyalty in the Context of e‐tailing", International Journal of Information Management, doi:10.1016/j.ijinfomgt.2010.09.001. Yeung, A. et al (2008) "Specific customer knowledge and operational performance in apparel manufacturing", International Journal of Production Economics, Vol.114, pp 520‐533. Zanjani, M. S., Rouzbehani, R. and Dabbagh, H. (2008) "Proposing a Conceptual Model of Customer Knowledge Management: A Study of CKM Tools in British Dotcoms", Journal of World Academy of Science, Engineering and Technology, Vol. 38, pp 303‐307.

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Questioning Prevailing Methodologies on IC, Knowledge‐Intensity and Knowledge Creation Yasmina Khadir‐Poggi and Mary Keating School of Business, Trinity College Dublin, Ireland poggiy@tcd.ie mkeating@tcd.ie Abstract: Intellectual capital and knowledge‐intensity in organisations are two related and emerging concepts whose centrality in our contemporary economies is paramount. Still, no clear understanding on the meaning of knowledge‐ intensity has been reached to date. This paper presents and contextualizes the methodological perspectives prevailing in the literature regarding those two concepts. In order to bring more clarity to our comprehension, an alternative approach to understanding knowledge‐intensity and IC is presented challenging the prevailing methodologies in the pertaining fields. After critically addressing some fundamental contradictions identified in the literature, an alternative approach is suggested in which a dynamic and holistic approach is preferred to the prevailing one. Then, the phrase “knowledge‐ intensity in organisations” is introduced as capturing best what is implied in the concepts of knowledge‐intensity before unveiling its meaning within an alternative methodological perspective. Keywords: IC, KIOs, knowledge‐intensity in organisation, ontology, methodology

1. Introduction Intellectual capital (IC) and knowledge‐intensity in organisations are two related and emerging concepts whose centrality in our contemporary economies is paramount. Still, no clear understanding on the meaning of knowledge‐intensity has been reached to date. The vast majority of existing studies adopt an input‐ and/or output‐based approaches when studying firms’ knowledge‐intensity. This approach is generally comprised of a list of characteristics an organisation possesses or not (Makani and Marche, 2010, von Nordenflycht, 2010). In addition to being descriptive, the related literature has a static and compartmentalised bias when approaching IC. It is static as it strives to create categories and/or classifications of those firms in the fashion pertaining to the industrial era (Poggi, 2010). Then, they tend to develop an abstract and truncated view of a complex concept such as knowledge. Indeed, it singles out tacit knowledge from explicit knowledge and knowledge‐ intensity and IC from knowledge creation. The knowledge‐intensive organisation (KIO) and the knowledge worker are approached separately and isolated from their knowledge environment and from their historical and cultural context. Further, scholars use a “positive” lens when studying knowledge‐intensity, and refer to it with identifiable variables such as expertise and levels of education. In our view, knowledge should be approached with a “negative” lens as it is triggered by the very absence of knowledge in a world where organisations regularly face uncertainties (Spender, 2011) and contradictions in their systems (Engeström, 1987, Blackler, 1995, Blackler, 2009). Overall, our argument is the following. The dominant methodological approach adopted in the field to date is biased and provides a fragmented and partial understanding on IC and knowledge‐intensity. The aim of this paper is to outline those biases and to provide an alternative methodological stance in order to understand these two concepts as embedded in our knowledge‐societies. The first section critically reviews the literature before highlighting some intrinsic limitations and developing some implications. A second section introduces a combined perspective on knowledge economies and organisations. Subsequently, a methodological framework is suggested and an original dynamic and holistic view of knowledge‐intensity and the process of knowledge‐creation are developed.

2. Conflicting perspectives on KIFs At the turn of the 1990s, a distinctive type of organisation is identified, the know‐how organisation (Sveiby and Lloyd, 1988) later labelled knowledge‐intensive firm (KIF) (Starbuck, 1992). Then, about a decade later during which this new field was seldom investigated, a marked resurgence of interest puts back the KIO on stage after 2004. This approach also encompassed the concepts of knowledge workers and knowledge work. However, some fundamental differences are observed in the philosophical perspectives adopted by the precursors of the

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Yasmina Khadir‐Poggi and Mary Keating field and those stemming from more recent contributions. The following section focuses on this particular aspect of a selected literature.

2.1 The precursors In their academic study of knowledge‐intensive organisations (KIOs), the first stream of scholars adopted generally a quite holistic and general approach. These then unusual types of firms were studied in relation to the context in which they were embedded. The first significant contribution pertaining to this field emanates from Sveiby and Lloyd (1988) who acknowledges the emergence of the KIOs that are ‘people‐dependant’. More specifically, the individual is viewed as the repository of know‐how. A point made by these theorists was that the organisational issues were not tackled with the right lens because of the dominance of the traditional thinking prevailing in the manufacturing era (Sveiby, 1992). Adopting a broader perspective, Drucker (1993, 1994) highlights the connection between the emergence of knowledge work and knowledge societies. He explained in many ways that the emergence of the knowledge workers and knowledge work so central in knowledge organisations is rooted in the fundamental mutations occurring in our societies. Frank Blackler questions the underlying paradigm on which the current idea of KIO and knowledge work is grounded, that is the conventional rational‐cognitive perspective where the rhetoric of traditional rationalism is still appealing (Blackler, 1993). To illustrate the point he designs within this fashion a typology of KIFs grounded on the different types of knowledge identified in literature (‘embrained’, ‘encoded’, ‘encultured’ and ‘embodied’). Then, he highlights the limitations of such a compartmentalised and truncated understanding as he favours a context‐based approach and views organisations as embedded social systems. Knowledge is a complex and dynamic asset that organisations should not consider they have but that they do. Organisations are holistic systems composed of interdependent entities that are all impacted by inside changes and decisions. Instead of knowledge, the author insists on using the term of knowing (which is a combination of knowledge and learning) that is more adequate for capturing the essence of KIFs (Blackler, 1995). Besides, the latter are also historically and culturally embedded (Blackler, 2009). And, the theoretical perspective of Activity Theory (Engeström, 1987) suggests a unit of analysis, the socially‐distributed system that focuses on the relationships existing between its different components. Finally, Nonaka and Takeuchi (1995) focused on the dynamics of knowledge creation and how knowledge crews interact in concert in order to do so. More specifically, Starbuck (1992) approached KIFs as organisations where learning is central and is performed through trial and error. He distinguishes clearly KIFs from information‐intensive firm or a professional firm and lays the ground for the advent of IC as, in his view, knowledge is a property of physical capital, social capital, routines and organisational culture; it is not necessarily and predominantly an attribute of individuals; it transcends the organisation. He also introduced a critical perspective on the conventional method used in carrying out research and outlines how the latter may force objects of study to fit certain patterns and prevent the researcher from making a significant contribution to research (Starbuck, 1993). The above scholars provided the first insights on KIOs and knowledge creation by questioning the industrial paradigm in which a theory of organisations was grounded and putting into perspective firms within this novel context. They also stressed the need for alternative methodologies of research. The context in which firms were embedded was a new one and knowledge was acknowledged as a central asset, but an asset of a new kind fraught with elusiveness and ambiguity (Alvesson, 1993). The overall approach on KIFs and knowledge creation was broad and focused on both the dynamics of internal relationships and external ones.

2.2 Most recent contributions Paradoxically, most of the recent contributions tend to overlook the above ontological concern and have taken the methodological approaches prevailing during the 60s and 70s (Blackler, 2009), a social constructionist perspective. They favour a more specialised stance whether stressing the importance of the worker and its experience or the organisation as a self‐sufficient entity or the existing between the two previous (Poggi, 2011). The following stream of authors is more concerned with the generalisation of the findings and their classification. They strive to elaborate specific definitions on KIOs and identify common characteristics in order to establish exploitable categories. These most recent research contributions on KIFs are developed since 2000.

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Yasmina Khadir‐Poggi and Mary Keating KIFs rely extensively on highly qualified individuals using primarily intellectual and symbolic skills in work (Alvesson, 2004). Its highly skilled individuals create market value through the application of knowledge to novel, complex situations (Swart and Kinnie, 2003). Greenwood (2009) offers a transversal and dynamic view of KIOs where he emphasised the integration and diffusion of knowledge throughout the value chain, the continuous learning culture within flatter and novel systems of management. Three later studies provide a deeper account on KIFs and, a list of characteristics are established in order to create identifiable categories. Using a two‐dimensional perspective combining the organisational or unit dimension and the worker dimension, Makani and Marche (2010) identified four types of KIOs: two unit‐ oriented firms (one expert‐driven such as medical firms and the other, innovation‐driven such as advertising firms) and two organisationally‐oriented firms (one expert‐driven such as investment companies and the other innovation‐driven such as business management consulting firms). The four types share in various intensity levels a certain number of characteristics such as worker’s independence, its expertise or the nature and size of the occupational network. Alternatively, Nordenflycht (2010) developed a taxonomy and theory of KIFs that are singled out through a combination of specific challenges and opportunities and best organisational response. He then identified four possible types of KIFs illustrated by organisational exemplars: technology developers such as biotechnology firms, neo‐professional service firms (consulting), professional campuses (hospitals) and regulated professional service firms (law, accounting…). A more recent study used the more holistic concept of intellectual capital (IC) and provided ‘knowledge‐intensity profiles’ rather than specific types of KIFs (Käpylä et al., 2011). Interestingly, so‐called knowledge assets are a combination of human assets, structural assets and relational assets. A more synthetic and holistic stance is preferred as it is difficult to summarize the entirety of those characteristics.

2.3 Conclusion on the literature reviewed Paradoxically, instead of espousing the underlying emerging philosophical perspectives adopted by the precursors that are better at capturing this so‐called new kind of organisations, the renewed interest in KIOs observed after 2000 tended to overlook it. Instead, KIFs are dissected as much as their nature allows it and their identified elements are studied in a compartmentalised way, isolated from their contexts. Thus, identifying an organisation as KIF results from a number of characteristics identified as central, such as a certain proportion of highly‐skilled workforce, leaner structure, expertise, complexity of work, etc. In the same fashion and despite its more holistic perspective, IC falls short of embracing the dynamics suggested between the components of KIFs as if knowledge‐intensity and knowledge creation were to be studied apart. This lacks a dimension that is not necessary observable such as the way organisations cope with uncertainty (Spender, 2011). The quest for categorisation or creation of a classification can also be misleading as it may force a variety of innovative organisations to match some identified and convenient leading pattern (Starbuck, 1993). It appears quite an oddity to qualify a law or accountancy firm or a hospital as KIO when they are pretty much an inescapable feature of the industrial age. However, they indeed present undeniable features pertaining to the realm of KIFs. Nordenflycht (2010) suggests a partial solution to this in suggesting that we “reinterpret past research” (p.167) in the light of these findings. What would appear like a slight divergence but that is in fact a fundamental one is stemming from the ontological and epistemological stances in which these research contributions are grounded. The insights developed by the precursors calling for novel methodologies, suggests some postmodernist and critical realism inclinations. They focus on the relations among people and the social world of practical activity where they see the locus of sensory experience (Slife and Williams, 1995). Admittedly, the postmodernist philosophical perspective lacks definition but is introduced as an alternative to grasp the unique features of the contemporary society (Alvesson, 2002). Critical realism envisages organisational research and analysis as historically, geographically and socially embedded (Reed, 2009). This concern for novel epistemologies is also now reemphasised in recent works (Blackler, 2009, Spender, 2011). Instead, the recent literature relies more on social constructionism where social reality is constituted through language or discourse (Reed, 2009) constructed and shared by people who live in it. Its language is constrained and created by social convention (Slife and Williams, 1995). This ontological concern implies two things: knowledge is treated like a tangible resource and the term KIF is limited when referring to the phenomenon under scrutiny.

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2.4 Implications The interest of critical realists is not on the identification of predictable patterns but on those deeper lying mechanisms which are taken to generate empirical phenomena (Alvesson and Sköldberg, 2009). There is an independently existing social reality that cannot be reduced to a discrete set of observable events or discursively manufactured inter‐subjective construct (Reed, 2009). First, knowledge is mostly addressed as a directly ‘observable’ entity expressed in proportions of educated people in the organisation or the existing levels of skills or expertise. It is sometimes approached in a truncated and compartmentalised way such as explicit and tacit knowledge (Polanyi, in Nonaka and Takeuchi, 1995). However, knowledge is an ambiguous and elusive asset (Alvesson, 1993, 2004) that can be hermetically isolated, truncated or specifically attributed to certain individuals or a particular system. For instance, a machine and its output can be positively observed and studied in isolation from other production centres but this logic cannot prevail in the case of knowledge. In short, knowledge has a dynamic dimension that is best captured by the term ‘knowing’ (knowledge and learning), something companies do rather than something they own (Blackler, 1995). Second, phrases such as KIOs or KIFs refer de facto to a specific category of firms next to others that are not; knowledge‐intensity is then restricted to fewer sectors and businesses. Information and technology firms and consultancies have attracted much attention and epitomise the KIF (Poggi, 2011) leaving out heavier capital‐ intensive companies that do not fit the knowledge‐intensive criteria. Those firms have attracted much attention as they have increased significantly in numbers since the beginning of the 1990s (Reich, 2002) and signalled a deep change in the structure of our entire economies. However, gradually, other organisations such as law or Accountancy firms or other traditionally so‐called professional service firms (PSFs) made the list get longer and had the unnoticed merit to open the field to forms of businesses that were previously denied such a calling. This approach also implies opportunities for making categories similarly to what is observed in the industrial era in order to identify managerial issues and provide ad hoc solutions. Instead, the phrase of ‘knowledge‐intensity in organisations’ is preferred to the terms KIFs or KIOs. Following the example of the philosophical perspective favoured by the precursors, ontology is of particular importance and cannot be collapsed with epistemology. Indeed, how the world is cannot be determined by the principles and tools through which we come to understand and explain it (Reed, 2009). Knowledge‐intensity in organisations points to the underlying mechanisms that must be studied. It opens up the scope of research and allows the investigation of other kinds of organisations such as hospitals, university campuses or a manufacturing company. It may be an organisational attribute; but above all it is a fundamental feature of our knowledge societies. The word ‘intensity’ rather than intensive indicates different variations in the degree to which firms are knowledge driven or not. Not all law firms or business consultancies have the same knowledge intensity. Some might be very successful when others are likely not; still no distinction of this kind is made in the existing literature when it is suggested that those companies are unique by their outstanding performance (and this is why they attracted so much attention in the first place) (Starbuck, 1993). At that stage, a law firm is categorised as knowledge‐intensive as well as an IT firm because it is described as such. Still, a dimension is missing to truly capture the knowledge‐intensity phenomenon. To better grasp the latter, it is suggested in the following section to put contemporary organisations in perspective within the knowledge age before subsequently unveiling what a critical realist or postmodernist stance reveal on knowledge‐intensity on organisations.

3. Organisations and techno‐economic paradigm Knowledge‐intensity in organisations arises from their pertaining to the current fifth techno‐economic paradigm (TEP). A TEP encompasses the underlying forces generating the dramatic upheaval in economic and social systems. It transforms work, consumption patterns and business organisations so those that are more compatible with the intrinsic values and patterns of the paradigm become the norm (Perez, 2010). The then emerging paradigm encompasses “the most successful and profitable practices in terms of organisational structures, business models and strategies” (Perez, 2010, p. 10). Then, the KIFs or KIOs mentioned previously are simply an emanation and a part of this TEP. It transcends organisations and is pervasive in their whole system. For instance, the use of New Technology of Information and Communication must be viewed as a

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Yasmina Khadir‐Poggi and Mary Keating societal standard and not as a distinguishing feature of KIFs. Organisations are de facto impacted and transformed according to the characteristics of the TEP. First, socio‐economic changes acknowledge globalisation as the driving force. The current paradigm is also characterised by high‐tech investment, high‐tech industries, highly‐skilled labour force, higher levels of education and, the emergence of skills and talents as a major resource. Second, technological changes depict the centrality and pervasiveness of innovation, technology, digital networks, internet, etc… Third, the observed organisational changes are the following ones: the resource‐based view of the firm, the importance of knowledge management, the transversality of knowledge among all sectors, knowledge as an input and a tradable output and, the importance of informal networks intra‐firms and inter‐firms among other things (Roberts, 2009; Perez, 2010; Dicken, 2011). Many of the described features of KIFs in the literature are in fact a reflection and extension of the prevailing paradigm. The importance of knowledge arises from the growing intangibility of our economies combined with higher educational levels (OECD, 1996). In addition, the availability of a technology able to free individuals from the organisational boundaries enables them to constantly enrich their knowledge, skills and, expertise. The leaner structures that characterises also KIFs (Alvesson, 2004) reflect the need for more flexibility and the pervasiveness of a technology that requires less specialised and low skilled employees. Indeed, the faster pace of change and the need to adapt quickly to constantly changing environments (Dicken, 2011) calls for a flexible organisation and empowered highly‐skilled workers able to make an important or simply a decision. In order to do so, the existing technology allows them to communicate efficiently, to use networks or databases to obtain needed information or gain access to external expertise, transform the results into a useful outcome that can inform their final decision. Overall, the argument is the following. The ‘new’ kind of firms identified in the 1990s and which knew a regain of interest lately are proceeding from the advent of the current fifth techno‐economic paradigm. First, this implies that an organisation may be considered as knowledge‐intensive not because it has a specific number of characteristics approached in an isolated and abstract fashion but because they are embedded in a social, technological and economic context described above and they are shaped and influenced by it. They do not exist independent of this background and, studying them as such is ill‐conceived. Second, considering KIFs as a specific category implies that their features match predominantly the content of the dominant TEP. If they do not, they may not be considered as such but rather reflect the previous paradigms or just be from a different nature such as a small family business doing craft work.

4. On knowledge‐intensity in organisations The prevailing constructivist ontological and epistemological perspective is insufficient at providing a clear and faithful meaning of knowledge‐intensity in organisation in a knowledge age. Central to the current paradigm is the growing importance of intangible over tangible accelerating the pace of change and the ensuing mutations occurring within organisations, but also empowering a larger number of workers that are better educated and endowed with more sophisticated skills than during the previous paradigm; they can carry their knowledge with them, develop it and use it inside or outside the boundaries of the organisation using networks. Consequently, the elusive nature of knowledge (Alvesson, 1993) lends itself very well to the development of the networked society and gradual emergence of the “boundaryless” organisation (Swart et al., 2007). Second, approaching the knowledge‐intensity concept whether from the firm’s stance or the worker’s one reduces the scope and the meaning of the knowledge asset in organisations. Indeed, knowledge cannot be limited to a sum of describable assets. It cannot be the quasi‐exclusive realm of the firm nor the worker. It transcends the organisation, and if well nurtured develops in a positive and upward spiralling dynamic that carries the organisation. Knowledge‐intensity in organisations calls for a holistic and dynamic perspective following the example of the precursors. As Starbuck (1992) observed, the expertise of people is paramount but so are the routines peculiar to the organisation’s system that participate to its success. The SECI model (socialization, externalisation, combination and internalization) (Nonaka and Takeuchi, 1995) is another example where knowledge is a shared resource that is transversal to all workers and the firm system in a manufacturing company.

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Yasmina Khadir‐Poggi and Mary Keating Similarly, Blackler (1993, 1995) refers to the Activity Theory framework developed by Engeström (1987), a socially‐distributed system that emphasises the relationships between the agents and the system to which they belong and how they are mediated by agents’ views, their language and, the state of technology. Individuals are not separated from the collective or the social from the technical. Further, the Activity System is culturally and historically embedded and, so is knowing, a combination of knowledge and learning (Blackler, 1995, 2009). Putting in perspective this Activity System within the Fifth TEP (Perez, 2010) or more simply in the current paradigm, gives its full dimension and meaning to knowledge‐intensity in organisations. The phrase KIOs or KIFs implies somehow that only a limited proportion of firms belongs the current techno‐economic paradigm, thing that is hardly conceivable. This shows through the repeated and conflicting attempts of classifications or typologies that are found in literature. It seems an uneasy exercise in an epoch where the nature of the activity of a firm is difficult to determine and where the overlapping between services and manufacturing is increasingly pervasive. Third, the concept of knowledge‐intensity in organisation attracted much attention as it was found characteristic of certain companies such as the IT and consultancy ones. Instead of looking at knowledge‐ intensity predominantly as a sum of certain assets or features they possess, we suggest to approach this from a dynamic and relational point of view. The Activity System contains inherent contradictions for each of its components. Thus, the different elements of the system have internal contradictions (i.e.: the agent is torn between stimulating his own advantage or the organisation’s one), but also contradictions between the elements and, between the studied system and the other identified systems with which it is related (Engeström, 1987, 1999). To sum up, the organisation envisaged as a whole is constantly coping with internal and external contradictions that influence its decision‐making processes and that alter its structure and content. Further, organisations are confronted on a regular basis to situations of knowledge‐absences or uncertainties. Instead of constructing recognizable categories, firms should be approached as a “unique space‐ time context of practice” where manager’s use of judgment to find a solution must be observed and, this gives IC its full dimension (Spender, 2011).

5. Conclusion The very much investigated concepts of knowledge‐intensity and IC are mostly viewed as emerging from specific organisational characteristics such as the proportion of highly skilled workers. Accordingly, subsequent research contributions arise from a micro‐approach on the phenomenon of KIFs paying a special attention to knowledge assets and striving to elaborate a classification where major categories are identified. This perspective ensues from a social constructivist stance. We argue that a postmodernist or critical realist philosophical approach captures better the meaning of knowledge‐intensity in organisations embedded in the fifth techno‐economic paradigm. Indeed, ontology is taking precedence on epistemology assuming that there is an objective reality out there that is independent from any discourse (Reed, 2009). The emphasis is on the underlying mechanisms at the origin of observed phenomena. It comprehends then knowledge‐intensity as a dynamic element that expresses itself when struggling into solving internal and external contradictions pertaining to a business system (Engeström, 1999). Further, firms are embedded historically and culturally into a wider context fraught with deep uncertainties that the judgement and skills of managers have to overcome (Spender, 2011). Overall the intensity in knowledge in organisations stems from the way they cope with and overcome inherent and constant contradictions of their systems as well as the greater uncertainties fostered by the current paradigm. Organisations are embedded into a constantly evolving TEP where they have to deal with knowledge‐absences and their business systems contradictions. Knowledge‐intensity emerges then from the way they cope with the situation to turn it into a successful outcome for the firm. The more successful and outstanding the firm, the more knowledge‐intensive it is. Knowledge is not positively observable as assumed by the literature. This view on knowledge‐intensity in organisations grounded in critical realism perspective and alternatively in the postmodernism one, has managerial implications. Instead of striving to categorize the firm in order to identify interchangeable managerial policies that may be implemented as an answer to uncertainty, each

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Yasmina Khadir‐Poggi and Mary Keating organisation should be understood as a particular case calling for specific solutions. It must then identify its areas of knowledge‐intensity and act upon them in order to stimulate the overall knowledge creation.

References Alvesson, M. (1993) Organisations as rhetoric: knowledge‐intensive firms and the struggle with ambiguity. Journal of Management Studies, 30. Alvesson, M. (2002) Postmodernism and social research, Buckingham, Philadelphia, Open University Press. Alvesson, M. (2004) Knowledge work and knowledge‐intensive firms, Oxford, Oxford University Press. Alvesson, M. and Sköldberg, K. (2009) Reflexive methodology: New vistas for qualitative research, London, Sage Publications Ltd. Blackler, F. (1993) Knowledge and the theory of organisations: Organisations as activity systems and the reframing of management. Journal of Management Studies, 30, 863‐884. Blackler, F. (1995) Knowledge, knowledge work and organizations: An overview and interpretation. Organization Studies, 16, 1021. Blackler, F. (2009) Cultural‐Historical Activity Theory and organisations studies. In: Sannino, A., Daniels, H. and Gutiérrez, K., D. (eds.) Learning and Expanding with Activity Theory. Cambridge: Cambridge University Press. Dicken, P. (2011) The Global Shift: Mapping the Changing Contours of the World Economy, London, Sage Publications Ltd. Drucker, P. F. (1993) Post Capitalist society, Oxford, Butterworth‐Heinemann. Drucker, P. F. (1994) The age of social transformation. The Atlantic Monthly, 274, 53. Engeström, Y. (1987) Learning by expanding: An activity‐theoretical approach to developmental research, Helsinki, Orienta‐ Konsultit. Engeström, Y. (1999) Innovative learning in work teams: analysing cycles of knowledge creation in practice. In: Engeström, Y., Miettinen, R. and Punamäki, R.‐L. (eds.) Perspectives on Activity Theory. Cambridge: Cambridge University Press. Greenwood, D. J. (2009) Are research universities knowledge‐intensive learning organisations? . In: Jemielniak, D. and Kociatkiewicz, J. (eds.) Handbook of Research on knowledge‐intensive organisation. Hershey, PA: Information Science Reference. Käpylä, J., Laihonen, H. and Lönnqvist, A., et al. (2011) Knowledge‐intensity as an organisational characteristic. Knowledge Management Research and Practice, 9, 315‐326. Makani, J.and Marche, S. (2010) Towards a typology of knowledge‐intensive organizations: determinant factors. Knowledge Management Research & Practice, 8, 265. Nonaka, I.and Takeuchi, H. (1995) The knowledge‐creating company: How Japanese Companies Create the Dynamics of Innovation, Oxford, Oxford Uiversity Press. OECD (1996) The knowledge‐based economy. Organisation for Economic Co‐operation and Development Retrieved from http://www.oecd.org/dataoecd/51/8/1913021.pdf Perez, C. 2010. Technological Revolutions and Techno‐economic Paradigms. Cambridge Journal of Economics, 34, 185‐202. Poggi, Y. (2011) The influence of the industrial era paradigm on knowledge‐intensive firms constructs. International Forum on Knowledge Asset Dynamics (IFKAD). Tampere, Finland. Reed, M. (2009) Critical realism: philosophy, method, or philosophy in search of a method? In: Buchanan, D. and Bryman, A. (eds.) The SAGE Handbook of Organizational Research Methods. London: Sage Publications Ltd. Reich, R. B. (2002). The future of success, London, Vintage. Roberts, J. (2009) The global knowledge economy in question. Critical Perspectives on International Business, 5, 285. Slife, B., D.and Williams, R., N. (1995) What's behind the research?: discovering hidden assumptions in the behavioral sciences, Thousand Oaks, Sage Publications, Inc. Spender, J. C. (2011) The problems and challenges of researching intellectual capital. In: Schuima, G. (ed.) Managing knowledge assets and business value creation in organisations: measures and dynamics. Hershey, New York: Business Science Reference. Starbuck, W. H. (1992) Learning by knowledge‐intensive firms. Journal of Management Studies, 29, 713‐40. Starbuck, W. H. (1993) Keeping a butterfly and an elephant in a house of cards: the elements of exceptional success. Journal of Management Studies, 30, 885‐921. Sveiby, K. E. (1992). Strategy formulation in Knowledge‐intensive industries. In: Hussey (ed.) International Review of Strategic Management. Sveiby, K. E.and Lloyd, T. (1988) Managing Know How: Add Value ... by Valuing Creativity London, Bloomsbury. Swart, J.and Kinnie, N. (2003) Sharing knowledge in knowledge‐intensive firms. Human Resource Management Journal, 13, 60. Swart, J.; Kinnie, N.and Rabinowitz, J. (2007) Managing across boundaries: human resources management beyond the firm, London, Chartered Institute of Personnel Development. von Nordenflycht, A. (2010) What Is A Professional Service Firm? Towards A Theory And Taxonomy Of Knowledge Intensive Firms. Academy of Management. The Academy of Management Review, 35, 154.

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Innovation and Earnings for SMEs José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García University of Cantabria, Santander, Spain josemanuel.lopez@unican.es fm.somohano@unican.es francisco.martinez@unican.es Abstract: Intellectual capital plays a fundamental role in today´s society in which knowledge and information are key elements for the development and the success of businesses. Its importance, and the value of putting it into the hands of stakeholders, has led to an increase in studies that propose models that try to measure and evaluate intellectual capital and has led to businesses applying and even publishing these studies as non‐financial information. In this sense, several lines of study have appeared that find it is good to disseminate its existence in a business through intellectual capital reports, Integrated Reports and through calls for greater improvement in a business’ financial information to adequately reflect these types of intangibles and satisfy the requirements of the users of this information. However, conceptual accounting frameworks contain some requirements to include these types of intangibles in financial statements. These requirements can be difficult to meet since there are authors and professionals who warn that this kind of financial information can make financial statements lose their relevance. We can consider the fact that the JOBS Act in the U.S., as 1 well as the Proposal of the Directive of the European Parliament and of the Council both call for the reduction in the informational demands of SME’s financial statements is another limitation to the greater improvement of financial information. We have observed two positions. On one hand, the call to amplify financial information to include aspects like the intangibles that are currently excluded but that are very relevant for stakeholders, for which more complete and detailed models and reports are proposed. On the other hand, a call to reduce the extent of the information required in financial statements is made and justified on the grounds of the related costs that SMEs must incur in terms of the cost/benefit relationship that this financial information provides. Our research, built on the resource‐based and dynamic capabilities theories, attempts to shed some light on the fact that, once again, the utility of the information contained in accounting or financial statements is being examined. To do this we analyse if the financial information contained in SME’s statements is not only important but also that when this information is taken into account with other, non‐financial information it provides a way to measure the effect of innovation. This type of intangible information allows SMEs to attain greater earnings and creates greater chances of survival, especially within an economic crisis environment, which can be considered to be very relevant for stakeholders. Nowadays, we are conducting the analysis of the results of the research. Keywords: intellectual capital, innovation, SMEs, patents, automotive industry, TIER

1. Introduction In today’s world, characterised by a knowledge based economy being the motor of society (Cowan and Van de Paal, 2000) in which tangible assets have had a considerable decrease in importance in the value creation process compared to the intangible assets, those businesses that know how to efficiently manage intangibles will be able to compete in better conditions (Sánchez, et al. 1999,). Authors like Hall (1992, 1993) and Teece (1998) highlight the importance of the intangible assets in general and of those based on knowledge specifically as being sources of competitive advantages and value creation for businesses. Intangible assets have been looked at from many different investigative angles. Among these, the ones that most directly affect our study are the ones concerned with the fields of accounting and organisation. From an organisational perspective, the definition of “intangible” is more in line with aspects related to Intellectual Capital (IC). This perspective takes these intangibles into consideration in a general way and is less strict than the accounting point of view because it includes assets, activities and the relationship between the intangibles controlled by a business (Sotomayor y Larrán, 2005) that will create knowledge and that can create competitive advantages which lead to better results. Roos and Roos (1997) indicate that in order to gain access to this knowledge that is held within these intangibles, it is convenient to utilise the different groupings that 2 are included in the wide scope of IC . For example, Sánchez, et al. (2012) justify their study on the effects that 1

On the 21 of June, 2012, the Official Journal of the European Union published the favorable Opinion of the European Economic and Social Committee. 2 For Roos and Roos (1997), real account balance statements do not provide information on the transformation from one category of IC to another. In order to be able to understand the cause of these changes, one must introduce an approach that takes into account the flows of each of the different categories of IC.

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García a report about IC can have on financial institutions being more inclined to provide financing to businesses that carry out innovative activities when these are not shown in the SME’s financial statements as a measure of their innovative capacity. Once again, the research on the relevance of financial information comes up and, in this case, we can consider two positions: One that requires more detailed, adequate and complete information, not only about intangibles or intellectual capital but also regarding the announcement of the earnings 3 And another that comes directly from the main conceptual current accounting framework, that places prudence above relevance and that certain rigidity and excessive demands can be attributed. For example, recognising intangibles in financial statements. The International Integrated Reporting Council follows a research proposal that defends the necessity to enhance financial information that, in a globalised spirit, advocates an international integrated conceptual framework that brings different aspects of financial and non‐financial information together into one coherent and unified structure. 4 5 Additionally, recent American and European rules set forth the convenience of simplifying the requirements for the financial statements of SMEs, moving away from the intellectual capital approach that others defend. These rules indicate that the elaboration of financial statements is considered to be one of the most bothersome obligations that exist for a business, particularly for smaller ones, which seems to say that the information provided is not considered to be sufficiently important. Therefore, a problem appears that is related to the value of this information and its utility in function of the costs incurred to obtain it. Consequently, our research can be justified by these different approaches: In reference to the organisational approach that requires more non‐financial information, in our case related to intangibles, that complements financial statements and provides relevant information for decision making. From an accounting point of view, which takes into account the cost of the information in terms of the structure of a company, the information includes the cost/benefit limitations for obtaining that data in such a way that the utility that it provides from being included compensates the effort and time dedicated to obtain it. Given the complexity of the scale of intellectual capital, we centre our work on innovation as being one of a business’ competitive advantages. The study of competitive advantages is line of study with great importance within the field of Organisation. In our case, we base our idea on the resource‐based and dynamic capabilities theories. According to these theories, strategy, its relationship to the attitude towards innovation and the success of a business in the long‐run are considered through obtaining greater survival possibilities. Additionally, the Knowledge‐Based View of the Firm says that the knowledge generated by IC is necessary for innovation because it’s a fundamental piece of the development of the knowledge strategy of a business. 3

The purpose of our research is not to take part in a discussion over the accuracy of the earnings shown in the account balance or if its current configuration based on net income provides greater relevance or informational quality in respect to other more novel approaches like using comprehensive income. We only use it for our calculations and analysis. 4 On the 5th of April, 2012, the president of the United States signed the JOBS Act (Jumpstart Our Business Start‐ups Act) trying to give a jolt to newly created, emerging and growing businesses while especially focusing on SMEs and their importance to the American economy. The companies that fall under this law are exonerated, among others, from having to follow these financial and governmental requirements during the first five years of existence. This new rule has given way to criticism among professional American organisations that argue that this means a return to very little financial regulation. 5 On the 21st of June, 2012, the Official Journal of the European Union published a Ruling from the European Economic and Social Committee on the “Proposal for a Directive of the European Parliament and of the Council on the annual financial statements, consolidated financial statements and related reports of certain types of undertakings” in which the proposal to reduce the administrative burden derived from the elaboration of financial statements was accepted while limiting the mandatory divulgence of certain information in the explanatory notes.

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García We use the work of Wiggins and Ruefli (2002); Ruefli and Wiggins, (2003, 2005) and McGahan and Porter (2002, 2005) as our framework. Additionally to the methodology that they use, we also take into account the limitations that these authors established for the sectorial classifications, the methodology utilised, the temporal period chosen or the influence of the managerial capacities on the earnings of the companies. Using these, we oriented our research towards innovation and the earnings of SMEs and we analysed if these types of enterprises should complement their financial information. To do this, we centred our research on innovation and on determined related to this such as patents, brands, patents cited as well as other available information on their web pages. All of this was done looking at the Spanish automotive industry. The structure of this paper is as follows. The next part summarises the most relevant research on innovation as a source of competitive advantages that produce better and longer lasting results for businesses. The third part of the paper details the objective that we set forth for our research, the hypotheses that we are currently working on and the methodology that we follow. We finish with a summary of our work.

2. Innovation, competitive advantages and their persistence through earnings The effect that innovation has on businesses as a source of competitive advantages is generally accepted by researchers (García Piqueres, 2011; Lin and Huang, 2008 ; Porter, 1980; Barney, 1986; Wiggins and Ruefli, 2002). Baumol (2002) and Jones (2002) also illustrate the importance of private investment in R&D as being the main source of growth in productivity on a macro and micro level. However, there are authors that do not consider the relationship between innovation and earnings to be so straightforward. Nelson (1991, 2008) is an author that argues against the existence of a strong correlation between innovation and the creation of wealth. This is because success causes a delay in profitability and process productivity and because industries have different innovation rates as well as different types of common innovations. Aside from the economic aspects, he declares that innovation in itself is not enough to cause a business to be successful and survive; to be effective a business needs a reasonable coherent strategy that defines and legitimises the way in which it is organised and managed and that allows for decisions on which new risks should be confronted and which should be left behind. Terziovski (2010) confirms this idea for industrial SMEs, for which the improvement in performance is related to the acknowledgement of strategic and innovative culture being closely aligned with the innovation process. This could mean that managers need to make a constant effort when maintaining strategies that combine innovation with the means to continually achieve objective and generate higher economic profits that those of their competitors. The capacity of a business to maintain a high level of economic performance has a long and varied history in the research into economics, business organisation and strategy (Nelson and Winter, 1982; Mueller, 1986; Geroski and Jacquemin (1988), Schohl (1990), Droucopoulos and Lianos (1993), Goddard and Wilson, 1996; Foster and Kaplan, 2001; Wiggins and Ruefli, 2002; McGahan and Porter, 2002; Coombs and Bierly, 2006; Henderson, et al., 2012; Fukugawa, 2012). Wiggins and Ruefli (2002) find that there are businesses that obtain persistently superior economic results during long periods of time. However, there are very few which in their opinion is consistent with the predictions of the vision based on the resources of the business. Furthermore, they find that the superior economic performance is not usually maintained in a stable and habitual way throughout time and almost all businesses that are able to achieve better results than their competitors are not able to defend this position because of the hyper‐competitiveness and, thus, the majority end up losing their superiority in the long‐run. This contradicts Porter’s theory of strategic groups with barriers to mobility. These authors maintained a principally methodological argument with McGahan and Porter based their 6 respective articles published in 2002 . Their differences are centred on the possible explanations of obtaining the superior competitive advantage with respect to their business competitors. For Ruefli and Wiggins (2003, p. 876‐877), there was little influence of the sectorial factors being predictors of business performance, whereas a greater influence of the corporate factor was found, conversely, to be a predictor of the classification of the profitability on a business level, which goes against the findings of the previous research 6

Part of the debate came from the mutatis mutandis assumption (that Wiggins and Ruefli advocated) instead of ceteris paribus (attributed to the research of McGahan and Porter).

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García done by Schmalensee (1985), Wernerfelt and Montgomery (1988), Rumelt (1991), McGahan and Porter (1997) and Chang and Singh (2000). However, this was consistent with Bowman and Helfat (2001), Roqueber, et al. (1996), Brush, et al. (1999); and McGahan and Porter (2002) since they found that the corporate effects had a greater influence than the sectorial effects. Ruefli and Wiggins (2003) add that “considering the four studies (including their own) that have similar results, the importance for the strategic management area is that reasonable evidence is provided, although not overwhelmingly so, that the corporate factors can have a significantly greater influence on explaining the business performance than the industrial factors. These results as well as the results obtained in previous research provided a strong inference that the directors have an important and significant role in outcome that a business obtains, just as March and Sutton (1997) and Meyer (1994) had argued”. The main conclusion from the Wiggins and Ruefli study for management practices is that the exceptionality that is demonstrated in order to obtain high levels of economic growth implies that this is very difficult to achieve. Therefore, this means that this is only achievable through strategies that are skilfully implemented and adapted during long periods of time and they may also have to be quite innovative, which give a lot of importance to the managerial and organisational capacities of the managers of businesses. Through this process, the directors decide to carry out technological innovations that tend to replace obsolete technology. These results are consistent with those obtained by other researchers that have studied how a difficult setting can strengthen the innovative attitudes of businesses (Naman and Slevin (1993); Zhara (1991) Vrakking (1990); Scherer (1992); Utterback (1994); Wolfe (1994); Balkin et al. (2000); Baker and Sinkula, (2002); Darroch and McNaugton (2002); Lyon and Ferrier (2002); Jiménez and Sanz (2011)). For that reason, innovation permits businesses to take on the complexities within their environment with greater possibilities of success and innovation is one of the factors that can influence the achievement of business objectives in a more determinant way. This can mean that it’s not very probable that the imitation and adoption of available 7 knowledge in the markets works as a means towards sustained superior performance . In our research we include the limitations that Wiggins and Ruefli indicate in their work to orientate our analysis and to establish a methodology. Among the methodologies, we considered those that referred to the separation of the sectorial classification by activity, the temporal time periods analysed, the methodology utilised, the data studied and, then, the starting points are established. In the next section we indicate the objective that we set forth for our research and how to address the limitations that these authors established.

3. Objective of the research and methodology Our objective is to find the non‐financial information of SMEs that is relevant and that complements the balance sheets in such a way that the group of stakeholders use the data to make decisions; and at the same time, can have this information available with some economic criteria for these types of businesses. Innovation is a source of competitive advantages for businesses if the results from innovative processes take time to bear their fruit and are difficult to relate. Sometimes in businesses that innovate, this can mean a great amount of time dedicated to resources that can lead to decreased earnings compared to others in the short‐ run. However, innovation improves and increases knowledge, which is the most valuable assets in today’s society, and which strengthens and prepares businesses to react to different circumstances in the market by adapting to always be in the vanguard and not falling behind their competitors. The current crisis especially affects SMEs because of the difficulty they have to access external financing and is when those enterprises that have maintained a coherent, strategic plan with the objectives to be attained (referring, among others, to innovation) will be able to handle the consequences of the economy’s situation and will have better results. 7

One of the results from Ruefli and Wiggins`(2002) research shows that when output is reduced to a certain point because of a hostile competitive environment, management could consider that the only way out that would give greater chances of survival is to go through an innovation process called creative destruction (Malerba and Orsenigo, 1993, p. 45‐71).

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García Therefore, our first hypothesis moves towards studying the relationship between the innovative attitudes of businesses (identified through an analysis of patents, cited patents, brands and information on their web pages) and earnings. Traditionally, even though expenditures on R&D have been used in order to identify the innovation (Pakes and Griliches, 1984; Griliches, 1998; Kleinknecht, et al., 2002), Coombs and Bierly (2006) find empirical evidence that leads them to suggest an introduction of other variables related to patents. Hence, we formulated the following hypothesis: H1: Of the business that receive patents, those with a higher number of patents than the average number of patents obtain better results in a crisis setting. Hirschey, et al. (2001) consider that one can obtain a complementary relationship between the information about the dissemination of the quality of patents and the expenditures on R&D from accounting information, which gives investors data of greater utility to be able to judge the economic success of the investments that were made by businesses in innovative activities. Therefore, according to Barth and McNichols (1994) and Amir and Lev (1996), the study of the relationship between financial (performance measures) and non‐financial (patents) information will provide more valuable data. Stuart (1999) and Coombs and Bierly (2006) propose using variables of the patents’ quality as citations for posterior patents. Lerner (1994, 1995); Lanjouw and Schankerman (2004); Hall, et al. (2006) and Van Zeebroeck (2011) indicate that, aside from the number of patents, the quality of these patents has a positive impact on the value of a company. What’s more, Trajtenber (1990) finds that the references of the patents, measured by the number of times that a patent is mentioned in a posterior patent, can describe the flow of knowledge of the organisation and determine where and how businesses go about developing their innovations. Narin et al. (1987) found in their investigations that the patent references were significant and positively correlated with financial performance. So, our second hypothesis is: H2: Businesses whose patents are cited by other and demonstrate that they are on the front line of their research obtain better results in a crisis setting. However, it is not very frequent that Spanish businesses patent their inventions or results from innovation. Among different motives, we can find that the costs of defending complaints, having an industrial secret o very little financial resources. While we hoped that the upper echelon companies would have better results, we ended up finding that a considerable proportion of them do not have registered patents or cited patents but did have information on their Web page that reflected similar developments or innovations to the ones shown by those companies that do have patents. The problem is detecting the result of this innovation that we are looking for that is available on their Web pages and to consider it in the analysis. Along these lines, we put forth our next hypothesis: H3: The businesses that show information related to R&D activities on their Web pages, similarly to those that have patents, are found in the upper echelon of businesses with better results, independently if they register patents or not. The limitations of the work done by Wiggins and Ruefli help to orientate the objective that we put forth by defining the methodology that we follow in this paper. The points we considered are: In addition to these authors, others have included the biases due to activities heterogeneous in industry classifications as result limitations. With the aim of minimizing it, we focus our research on a specific industry, the automotive, where we consider the innovation capacity at sectorial and firm level. In this way, we stratify 8 the companies according to their level as TIER in the supply chain, in such way that the sector innovation component could be more enclosed or homogeneous among firms. 8 Due to the complexity of the large number of activities carried out by companies in this sector, the industry has organized supply chain in "TIERS" which are organized according to their proximity to the OEM (Original Equipment Manufacturer). We believe that this make easier

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García Another requirement of previous research is to have a period of time long enough to analyse the persistence of superior performance. Following indications that the time windows do not cover very broad periods (Ruefli and Wiggins, 2005); we consider the period between the years 1999 to 2010 inclusive, and we divided it into three years windows 1999 to 2001, 2002‐2004, 2005‐2007, and 2008‐2010. Ruefli and Wiggins took for granted mutatis mutandis instead for other authors as McGahan and Porter which are based on ceteris paribus assumption. In our opinion, given the complexity of economic situation, there are plenty of factors that influence the results and we cannot establish an environment where all the aspects with influence in the future of the firms remain constant, so we took the postulation mutatis mutandis. The fact that we study the entire population 9 of the Spanish automotive industry, leads us to consider more convenient to adopt a non‐parametric approach, as indicated by Wiggins and Ruefli, according to the starting assumption. So that, we choose the iterative application of the non‐parametric Kolmogorov‐Smirnov 10 test to identify companies with a continued superior performance. This is an on‐going investigation, and currently we are considering three dependent variables, ROA (Return on Assets), ROE (Return On Equity), ROS (Return on Sales); (Coombs and Bierly, 2006 11 ), and four independent variables: patents; patents citations; trademark; and innovative activities in their web pages. We obtain data for 1,624 companies in the automotive sector. The Balance Sheets; Income Statements; and National Index of Economic Activities (CNAE 2009) are obtained from SABI database (System Iberian Balance Analysis). The patents of Spanish automotive sector firms have been obtained through the Spanish Patent and Trademark Office, INVENES database. We calculated dichotomous variables that tell us which companies have achieved increased performance ratios and earnings in different three year windows. These data allow us to examine as preliminary analysis whether there were significant differences among the companies that have better ratios continuously, related to sector classification and to time period in which they occur.

4. Recapitulation Our investigation is within the realm of the resource‐based and dynamic capabilities theories in terms of strategy, its relation with the attitude towards innovation, business success in the long‐run and achieving better chances of survival. Also, we look at the Knowledge‐Based View of the Firm given that what is created by IC is necessary for innovation since it is a fundamental to develop the innovation strategy of a business. As stated by Donate (2008), the differences in businesses’ results are basically from the heterogeneity of their knowledge bases. From all of this, one can see that the basic management characteristics for directors of the organisational processes that encourage that certain knowledge, known as strategic assets, can become the principal source of a business’ competitive advantage (Wiggins and Ruefli, 2002). Based on this, and considering IC as a source of a business’ knowledge while being the most valuable asset to obtain competitive advantages, and we concentrate on innovation. We identify innovation through the number of patents, brands and references to other patents as being complementary to the financial information in order to be able to achieve synergies that provide useful information for owners and stakeholders (Amir and Lev, 1996; Barth and McNichols, 1994; Hirschey, et al., 2001) and honestly reflect their market value (Fukugawa, 2012). our investigation and facilitates to reduce the heterogeneity of classification and make more homogeneous groups based on the activity of the companies. 9 Populations do not always meet the underlying assumptions of parametric tests and often they require inference procedures whose validity does not depend on these rigid assumptions. 10 For the iterative technique of Kolmogorov‐Smirnov, initially assumed that there is a unique performance distribution for the entire industry or reference set and any company has outperformed statistically significant. The distribution of income levels of each company will be iteratively tested against the distribution group during this period using the nonparametric Kolmogorov‐Smirnov two‐sample. Companies with performance distributions are statistically significantly different (α = 0.05) of the mode of the distribution per group were removed, and the process is repeated until the stratum of companies sharing the main distribution is stabilized. Companies excluded from stratum in the main action will then be used as the base to form a second layer, and the process is repeated. This iterative process will continue until no more inclusions or exclusions. 11 Coombs and Bierly (2006) also used another three dependent variables related to market value data of the company. However, in our research work with SMEs, we are not able to do that.

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José Manuel López Fernández, Francisco Manuel Somohano Rodríguez and Francisco Javier Martínez García We have observed two positions related to the usefulness of this information. The first is related to the organisational theory that calls for greater informative necessity, being more complex and exact, and that complements the account balances and gives greater relevance to the financial information in order to be able to make decisions. The second position is related to accounting rules, which are based more on prudence and establish strict requirements to integrate determined elements into the account balances. Additionally, the economics of information are considered for SMEs and simplifying the accounting statements and reducing the amount of information, especially the non‐financial kind, which is required for SMEs is supported. Our objective is to demonstrate that the non‐financial information of the SMEs resulting from innovative activities that they carry out (patents, cited patents, brands), can be considered relevant and complement the accounting statements in such a way that the group of stakeholders use those data to make decisions; and, at the same time, can be have that information available to them with certain criteria about the economics of information that is assumed by these businesses. We start with the repetitive procedure of Kolmogorov‐Smirnov to determine the businesses with higher continual performance (Wiggins and Ruefli, 2002; Ruefli and Wiggins, 2003, 2005). Once they are identified, we study the relation between this type of business and the non‐financial information that we obtained on their innovative activities. We look at if innovation provides competitive advantages, especially in a crisis setting like today, giving them greater chances of survival. According to Ruefli and Wiggins (2002, 2003 and 2005), by considering that the earnings obtained be businesses depend in a large part on managerial decisions, an orientation towards innovations and its necessary strategic and organisational coherence is one of the benefits of the managerial abilities. We used financial information obtained from the balances and earnings sheets of 1,624 businesses in the Spanish automotive sector (obtained on SABI) as well as non‐financial information (brands, cited patents, number of patents, information on their Web pages and sectorial classifications). The preliminary results that we found show us that there are statistically significant differences among the groupings of businesses by activity in the Spanish automotive sector, show continually better accounting ratios were obtained and the economic period in which they were produced.

Acknowledgements The SME Chair of the University of Cantabria is supported by the Banco Santander and the Secretary of Economy and Treasury of the Government of Cantabria. This study has been subsidised by the Secretary of Economy and Treasury of the Government of Cantabria.

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The Quality of Information in Project Management Jana Malá1, Ľubica Černá and Dagmar Rusková2 1, Department of Industrial Engineering and Management, Faculty of Materials Science and Technology, Slovak University of Technology, Slovak Republic 2 Department of Languages, Faculty of Materials Science and Technology, Slovak University of Technology, Slovak Republic jana.mala@stuba.sk"stuba.sk lubica.cerna@stuba.sk"stuba.sk dagmar.ruskova@stuba.sk"stuba.sk Abstract: Poor quality of information in modern organizations may be caused by many aspects, such as: the size and nature of the information, human factors, the organization’s culture, experience and skills as a manager and other team members, technology, last but not least, the quality of the inputted data. Applying a methodology of quality control helps organizations create effective management of their information. The method of quality information control depends on all those aspects. The importance of the organization should be given to dispose of an optimum amount of information in the required level of quality and especially to share this information. The quality of information is the key to the success of the project’s management; this also applies in many other areas. Understanding the mechanics of the control of information management and its class is essential, this is an experience that distinguishes successful information managers. With the increasing dependence of organizations on the quality of management, information and operational decisions "patches" IQ are no longer an equivalent way. Organizations must learn to recognize potential signs of the possible development of "patches" in order to devise solutions before problems arise. This, however, requires knowledge of information processing and the understanding of why these processes were carried out as they should be, or why they were unfulfilled. Organizations that deal with warning signs of IQ problems provide a smooth path for their customers a higher quality of information. A framework for data quality assessment should not only evaluate, but also plan, analyse and solve problems related to the quality of data for a proactive management. The role of the quality management project is to ensure that the project will satisfy the needs for which it was created and to start addressing them. Many projects end in failure, mainly because the project team concentrated their attention only to the written specification of the major products in development, and forget about other needs and expectations that participants attach to the project. It follows that it is equally important to put emphasis on the quality just as much as the scope of the project together with the time and costs required for its implementation. In the article I have described the results of my research as well as the plans for further research, the results of which should be the proposal of methodology for evaluation of quality of information in project management. Keywords: information quality, TDQM, dimensions of information quality, criteria for assessing information quality

1. Introduction Effects of the improper election of the quality of information can lead to the termination of a business. Moreover, the lack of the quality of information has a significant impact on customer satisfaction, as well as the operational costs and financial indicators. Thus, there is a growing need for the use of methods to assess the quality of information. Quality was defined by Juran (1974) as "fitness for use". This means that the quality is defined customers such as customer satisfaction which is considered analogous. It can be defined as meeting and exceeding customer expectations, as well as a perfectly produced product which has little value unless it is what the customer wants. Moreover, Juran (1974) introduced the term "cost of quality". Crosby (1979) however, argued that "quality is free“, because all the money spent on quality control is ultimately saved, due to less quality problems. Although this doctrine recommendation was originally developed for the manufacturing industry, the same principles were applied to the field of information quality.

2. Assessing the quality of projects Project Quality Management processes include all activities of the organization that determine quality policy objectives and responsibilities so that after the implementation of the project all customer needs are satisfied and guaranteed. The Quality Management System is implemented through policies, procedures and processes of quality planning, quality control and continuous process improvement activities as needed (PMI Global Standard, 2004).

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Jana Malá, Ľubica Černá and Dagmar Rusková The role of the quality management project is to ensure that the project will satisfy the needs for which it was created and to start addressing them. The role of project management processes is to meet or exceed the needs and expectations of participants. The project team must therefore build good relationships with key stakeholders, particularly with major customers of the project where it is necessary to clarify what they regard as quality. Many projects end in failure, mainly because the project team concentrated their attention only to the written specification of the major products in development, and forget about other needs and expectations that participants attach to the project. It follows that it is equally important to put emphasis on the quality just as much as the scope of the project together with the time and costs required for its implementation (Svozilová, 2011; Swable, 2007, Holtan, 2009). The quality management projects have three major processes: The planning process of quality is in setting quality standards which are applicable to the project and identify how they reach their fulfilment. A key part of quality planning is the integration of quality standards in the project proposal. In technical projects, it is also possible to determine the time duration for a maximum response from technical support (Help Desk), or as long as is necessary to deliver a replacement of a hardware component (PMI, 2004; Svozilová, 2011; Swable 2007). Process assurance quality ‐ describes how to use the planned and systematic activities concerned with quality, so as to ensure the utilization of all processes needed to meet its requirements. This is a periodic assessment of the overall effectiveness of the project and to check whether the project meets the quality standards. The process of carrying out quality control – the monitoring of specific project results and seeing whether they comply with relevant quality standards and to determine how to eliminate the causes of unsatisfactory results and to identify opportunities to improve the overall quality.

3. Total data quality management Looking at the quality of information recorded the significant progress in a relatively short time period. Researchers and practitioners are constantly engaged in solving problems of quality of information, quality of information definitions, the measurement, analysis, improvement tools, methods and practices. However, in the theoretically based methods for Total Data Quality Management (TDQM) ‐ a comprehensive quality control of the data is still lacking. This issue deals with Prof. Richard. Y. Wang, who is a pioneer and an internationally known leader in the investigation of data quality, edited by Deming's method of definition, measurement, analysis and improvement, information on production and suggested TDQM that emphasizes continuous improvement and the provision of quality information products (Hakim, 2007). The purpose of the methodology of TDQM is to deliver and inform consumers about high quality information products. Its objective is to implement the organization's top management and to express a policy of comprehensive data quality management. In order to obtain high quality information, the organization should implement TDQM. A determining factor of the TDQM cycle is to identify the important dimensions of IQ and the IQ requirements. Measuring the individual components create IQ metrics. The analysis identifies the basic components of IQ problems and IQ calculates identify the consequences of information of poor quality. Finally, the improvement of individual components provides techniques for improving IQ. Maintaining data quality is often problematic. There are many factors that can hinder IQ, these include inadequate provision of timely, complete and accurate reporting of data, undefined rules for the management of information, lack of processes for data collection and fragmentation, new methods for their management and dynamic management of the information lifecycle. According to research by Professor Hakim (2007), the factors that affect IQ can be divided into three areas: technology (IQ control and improvement approaches and techniques of data collection architecture, tools and techniques, creation of internal standards for IQ, application and process integration, IQ technology for data integration, data storage architecture, techniques for data cleaning), organization (leadership, commitment of senior management to IQ, development of appropriate policies and standards for IQ and their implementation, organizational structure, organizational culture, supplying

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Jana Malá, Ľubica Černá and Dagmar Rusková information about quality management, customer focus, audits and assessments, evaluating the cost / benefit trade‐offs, and teamwork communication, change of management, internal (internal) control system, access control, feedback to IQ), people (staff competence, performance evaluation and remuneration, relations between employees, management responsibilities, training), in each area, it is necessary to address the factors that may significantly or less significant have an impact on the quality of information in the organization (Hakim, 2007). A quality framework data model for a data environment must be based on a strategy that has a wide scope. This strategy sets out a business plan and relationship between data. Its aim is to create a framework of data quality tools that can be used for everyday work activities. The main components of data quality are in determining quality that will create a framework for quality assessment and the implementation of strategies (Hakim, 2007).

4. Data quality evaluation framework Data Quality Evaluation Framework (DQEF) establishes the processes and metrics (criteria) to assess whether the level of data dimensions (e.g., accuracy) is acceptable or not. In order to measure and define the concept of IQ, it is not enough to identify the common elements of IQ frameworks as individual entities themselves. In fact, the IQ must be considered in the context of its generation and subsequent use. And because the quality attributes of the data may vary depending on the context in which they are to be used. The definition of IQ in terms of the World Wide Web and its search engines largely depends on whether the information will be surveyed for creation, storage and maintenance, or to find information about its users (Hakim, 2007). A framework for data quality assessment should not only evaluate, but also plan, analyze and solve problems related to the quality of data for a proactive management. According to Eppler and Wittig, there are four objectives regarding IQ

framework for assessing the quality of data should provide a systematic and concise set of criteria by which to evaluate,

framework should provide a system to analyze and solve problems IQ,

also should be the basis for measuring IQ and proactive management,

and finally it should provide a community (the scientific community) with the concept maps that can be used for different design approaches, theories and phenomena on IQ (Hakim, 2007).

4.1 Maturity models and TDQM Maturity models are designed for process control in organizations. Based on the idea of the CMMI model, which consists of five levels:

Initial (teams at this level defined non‐implemented or only partially implemented processes),

Managed (is designed and project management activities are planned),

Defined (procedures are defined, documented and controlled),

Quantitatively Managed (products and processes are managed quantitatively),

Optimizing (the team continuously optimize its activities),

each level represents an evolutionary stage of quality information management capabilities. It is assumed that the distribution of the quality of information on several levels can easily achieve sub‐goals in an incremental way. Scholars from Australian universities Andy Koronios, Jing Gao and Saša Baškarada adapted TDQM methodology for improving the quality of information by aligning a phase TDQM cycle model at different levels of maturity. In addition, this provides additional guidance and identifies specific process areas that affect the quality of the information. Each level, except the first, sets out a number of information management processes regarding the quality and management of information.

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Jana Malá, Ľubica Černá and Dagmar Rusková Koronios, Gao a Baškarada compiled a process of information management and quality control of information to the different levels of the maturity evaluation model, this was in order to provide more specific guidance. The resulting model is shown in table 1, this maps each process regarding the quality category of information which is expected to be solved by this model. The first area process, shown in table 1 “roles and responsibilities in relation to information production", defines the roles and responsibilities of all employees in the organization in relation to the formation of product information, approaches, handling, etc. It defines both, authorship and accountability, including definitions of skills and abilities required in the position. It is expected that by implementing this process, organizations can increase the internal, level of the quality of their information. Other process areas are based on the same principle.

IM IQM IM IM IQM

Level 5

OPTIMIZING

Level 4 MANAGED

Level 3 QUANTIFIED

IQM

This maturity level, by definition, does not contain any process areas. All Information Products (IPs) together w ith their quality requirements have been defined and documented. Thus, relevant IQ dimensions and required degrees of adherence have been identified. Roles and Responsibilities in Relation to Information Products Information Dictionary and Information Syntax Rules Constraint Enforcement on Transactional Information Input/Access Authorization Procedures Information Quality Customer Focus (Internal/External) Roles and Responsibilities for Information Quality Management Information Quality Management Project Planning IQ metrics have been developed and IQ is being measured / assessed. Training and Mentoring Information Stew ardship and Ow nership Enterprise Information Architecture Model (Data Flow & Work Flow ) Information Classification Scheme Information Input Error Handling Information Quality Policies Management Information Quality Standards and Quality Practices Information Quality Assessment Information Consistency Assurance (Data Cleansing) Root causes of IQ problems have been identified and impact of poor IQ has been calculated. Meta-Information Management Information Redundancy Management Information Processing Error Handling Storage Retention Management (Offsite) Backup Storage and Restoration Information Security Requirements Root Cause Analysis (RCA) Information Quality Risk Management & Impact Assessment Processes causing IQ problems are continually being improved. Output Review and Error Handling Information Integration Management Information Disposal Management Continuous Process Improvement IQM Support for IT & Business Strategies Information Quality Accountability

Intrinsic IQ Representational IQ Contextual IQ Accessibility IQ

IM/IQM processes are not standardised or documented (they are ad-hoc). There is no aw areness of any IQ issues. No attempts are made to assess or enhance IQ. Organisation is only reacting to IQ problems as they occur.

REACTIVE AWARE

Level 2

Level 1

Table 1: Maturity of the quality management of information (created by Kaplan, Maxwell, (1994); CobIT 4.0, (2005))

x x x x x x x x x x x

x x x

x x x x x x x x x x x x x x

x x x x x x x

x x x x x x

x x x x x x x x x x x

x x x x x x x x x x x x x x

x x x x x

x x x x x x

4.2 Dimensions and basic criteria for assessing the quality of information Meade and Sarkis point out that the real environment no longer provides sufficient experience, skills, knowledge and information to achieve and increase competitiveness. It is essential to be able to transform knowledge, skills and information into products (CobIT 4.0, 2005). The ability to adapt is based on the results of two assumptions, information technology and process experience. The ability to “adapt/convert" should be maintained through continuous process improvement and learning (Kaplan, Maxwell, 1994).

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Jana Malá, Ľubica Černá and Dagmar Rusková Prof. Wang made a step forward beyond the work of professors Meade and Sarkis and found an analogy between the issues of the quality of industrial products and quality issues of information processing and further stated that information processing can be working on sensitive data to produce information products. Prof. Wang points out the organization to handle information such as managing one’s products, if one want to increase productivity (Turban, Aroson, Liang, 2004). Turban defined information as "data / data are managed in a way that gives meaning to the recipient“.A definition by Copeland and Simpson extended this to include “all communication or representation of knowledge such as facts or data in any environment and form“(Tate, 2010). Table 2: Dimensions of quality information (created by: Wang a Strong, 1996) Information quality category Intrinsic Representational

Dimension of information quality accuracy, objectivity, believability, reputation interpretability, ease of understanding, representation, consistent representation

Contextual Accessibility

relevancy, value‐added, timeliness, completeness, amount of information accessibility, security access

The result, the problem of the quality of information defined as a difference of one or more dimensions of quality, which is inappropriate data or a large part of suitable data for use (Strong, Lee, Wang, 1997). Verification of the quality of information is a complex process. Five basic criteria that are needed to be addressed in order to present information that can be identified as reliable include:

authority,

accuracy,

currency,

coverage,

objectivity.

These criteria have their origin in the world of printed media and are considered to be universal criteria that need to be addressed regardless of the media evaluated, each criterion must be addressed individually. Often, however, there is overlap between the various criteria, leading to discussions, such as "authorship" and "accuracy" – thus, for a more complete picture, these should be taken into consideration together. The mentioned five key evaluation criteria for assessing the quality of information will provide a starting point for assessment of the problems related to these features that are characteristic of all information (Tate, 2010).

5. The main causes of poor information quality in organizations The journey to reach the quality of information is tortuous. Poor quality information leads to chaos in the organization. It is necessary to identify the root cause of this situation. Professors Strong, Lee and Wang (1997) described 10 leading causes of IQ:

More resources of the same information produce different values.

The information generated by the subjective judgment may be biased

Making mistakes can lead to loss of information. The database must be protected in order to prevent overwriting by unauthorized persons, as well as other adjustments that can be performed only by those users who have administrator‐defined access. The recommended solution to this problem is: to introduce a statistical‐process control, improved process control, process control and improvement of appropriate incentives.

Too much information is not necessarily better.

Distribution systems ‐ for the organization, it is important to have well‐designed distribution channels. This means that the information must have a well‐defined format where all the systems in the organization, where the information is intended to be processed further ‐ read, analyzed and further use, are know.

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Information in the form of non‐numerical characters is difficult to index.

Advanced requirements analysis.

Change Task needs ‐ customer needs influence the change of information. Information systems should be designed for flexible reporting.

Requirements for security and privacy. The organization must be prepared by the security policy, which is to say, what kind of information is relevant to whom.

Until recently, there was a very low awareness of the pervasive problems of IQ and the related severity of financial and the operational costs of organizations. With the increasing dependence of organizations on the quality of management, information and operational decisions "patches" IQ are no longer an equivalent way. Organizations must learn to recognize potential signs of the possible development of "patches" in order to devise solutions before problems arise. This, however, requires knowledge of information processing and the understanding of why these processes were carried out as they should be, or why they were unfulfilled. Organizations that deal with warning signs of IQ problems provide a smooth path for their customers a higher quality of information (Strong, Lee, Wang, 1997).

6. The results of the research The main objective of the dissertation thesis is to elaborate the methodology for the application of quality information assessment in project management in the Slovak Republic. Based on the theoretical knowledge of the literature from the area of project management as well as the information management and monitoring costs of poor quality information, I have prepared the analysis of the current status of the issue in Slovakia. Before starting the research, I set out hypotheses Three hypotheses are proposed that will verify research and then evaluate it in order to design and build a methodology. Hypothesis 1: There is a relationship between the degree of IS used in project management and information quality. Hypothesis 2: Information Quality control is incorporated in project management methodologies applied in the Slovak industrial enterprises. Hypothesis 3: There is a relationship between the quality of information within project management and the projects quality (scope, budget, time etc.).The research I have divided into two parts: a structured interview and a questionnaire survey. So far, I realized the first part of my research ‐ structured interview in 15 selected companies in Slovakia. These were the companies with foreign capital participation, as well as purely Slovak enterprises. I conclude that firms manage their projects using methodologies of standards which help them in their implementation. However deficiency occurs, often fails to meet all the criteria of Triple Constraint established at the beginning which are quality, time and cost. Businesses in the implementation of their projects do not make databases for recording the process of the project, the shortcomings of project team members ‐ to what area they were specialized, the costs and results. The database would provide information that could help solve the following projects; it could prevent some situations, or they would be solved quicker. There are also missing databases of occurred errors. Enterprises pursuing during the implementation of the project cost, what was the cost of the project and alike. But many companies do not pursue the costs of incurred errors, and even if some of them do, they do not split them into individual types of direct and indirect costs of poor quality (Cost of Poor Quality CoPQ). Therefore, it is my aim to develop a methodology to assess the quality of information in the project management and to confirm my hypotheses. These are based on the survey of the Slovak industrial companies. Another part of the research will be conducted through a questionnaire survey in industrial enterprises in Slovakia. Questionnaire will focus on the quality of information in projects, method of verifying the quality of information, the evaluation criteria for the quality of information in the various stages of the project and monitoring the cost of non‐quality.

7. Conclusion In the literature, there are methods to help users manage their projects. Also, the literature is concerned with the quality, the quality of data and quality information. Each of the experts in the field prefers certain types of features to obtain quality information. However, the literature is not a comprehensive look at the quality of information in project management. The goal of this dissertation is to propose a methodology for evaluating the quality of information in project management. The research is aimed at industrial enterprises within Slovakia.

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Jana Malá, Ľubica Černá and Dagmar Rusková The aim proposing a methodology for evaluating the quality of information in project management is to create a tool that will not only help organizations to find their way in their projects, to build the database of projects which may be helpful in solving other projects, but also the effective use of information which the organization disposes of. For an organization, it is important to think about how to capture, share, do not loose and apply the right information at the right time and on the right place. Quality information is the main prerequisite for success not only in project management but also in many other areas.

Acknowledgements This contribution is a component presenting the results of research VEGA 1/1203/12 Quality Management in project management in industrial enterprises, which is solved by the Institute of Industrial Engineering, Management and Quality MTF STU.

References CobIT 4.0 (2005) Control Objectives Management Guidelines Maturity Models, The IT Governance Institute, USA, ISBN 1‐ 933284‐37‐4 Coppeland, C. W., & Simpson, M. (2004), The Information Quality Act: OMB's guidance and initial implementation (CRC Report to Congress, Updated August 19, 2004) [online] http://www.fas.org/sgp/crs/RL32532.pdf, cit. 25.08.2012 CROSBY, PHILIP (1979) QUALITY IS FREE: THE ART OF MAKING QUALITY CERTAIN, MCGRAW HILL, NEW YORK, ISBN 0‐07‐ 014512‐1 Hakim, L. (2007). Information Quality Management: Theory and Applications, Idea Group Publishing, ISBN 1‐59904‐024‐7 Holtan, M., Kremeňová, I., Šujanová, J. (2009) Directing successful projects with PRINCE2 In: CO‐MAT‐TECH 2009. Industrial Engineering, Management and Quality for 21st century. Proceedings of the 17th International Science Conference, Trnava 22.‐23. October 2009. ‐ Trnava: AlumniPress, ISBN 978‐80‐8096‐100‐8, p. 130‐136 Juran, J.M, Gryna, F. M. J., Bingham, R.S. (1974) Quality Control Handbook, 3. edition, McGraw‐Hill Book Co, New York Kaplan, B., Maxwell, J.A. (1994) Qualitative Research Methods for Evaluating Computer Information Systems, In Evaluating Health Care Information Systems: Methods and Applications, eds. J.G. Anderson CE Aydin & S.J. Jay, Sage, Thousand Oaks, CA, p. 45‐68 PMI Global Standard (2004), Guide to the Project Management Body of Knowledge, (PMBOK® Guide), Third Edition, Pennsylvania, Project Management Institute, ISBN 1‐930699‐50‐6 Strong, D.; Lee, Y.; Wang, R. (1997). 10 Potholes in the Road to Information Quality. Computer, Vol. 30, No. 9, (September 1997) page numbers (38‐46), ISSN 0018‐9162 Strong, D.M., Lee, Y.W, Wang, R.Y. (1997) Data Quality In Context, Communications of the ACM, vol.40, no. 5, May 1997, p. 103‐110 Svozilová, Alena (2011) – Projektový Manažment, Praha, Grada, Isbn 978‐80‐247‐3611‐2 Swalbe, Kathy (2007) – Řízení Projektů V IT, Brno, Computer Press, ISBN 978‐80‐251‐1526‐8 Šujanová, J. (2005), Znalosti v projektovom manažmente. In: Projektový manažment: metódy, nástroje a využitie projektového manažmentu v praxi : Medzinárodný seminár. ‐ Bratislava : STU v Bratislave, ISBN 80‐227‐2229‐4. ‐ S. 70‐72 Šujanová, J. ‐ Pavlendová, G. (2005), Riaditeľ pre znalostný manažment a jeho úloha v projektoch znalostného manažmentu. Chief knowledge officier and his role in the knowledge management projects. In: Vedecké práce MtF STU v Bratislave so sídlom v Trnave. Research papers Faculty of Materials Science and Technology Slovak University of Technology in Trnava. ‐ ISSN 1336‐1589. ‐ Č. 19 (2005), s. 89‐92 Tate, Marsha Ann (2010) ‐ Web Wisdom: How to Evaluate and Create Information Quality on the Web, CRC Press‐Taylor & Francis Group, ISBN 978‐1‐4200‐7320‐1 Turban, E., Aroson, J. E., & Liang, T. P. (2004) Decision support systems and intelligent systems (7th ed.). Upper Saddle River, NJ: Prentice‐Hall, ISBN 0‐13‐046106‐7 Wang, R. Y., Strong, D. (1996), Beyond Accuracy: What Data Quality Means to Data Consumers“ Journal of Management Information Systems, vol. 12, no. 4, 1996, p. 5‐3

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Relational Capital: The Role of Sustainability in Developing Corporate Reputation Patricia Martínez García de Leaniz and Ignacio Rodríguez del Bosque Faculty of Economics, University of Cantabria, Spain martinezrp@unican.es rbosquei@unican.es Abstract: Intellectual capital offers a potential source of sustainable competitive advantage and is believed to be the source from which economic growth may sprout. However, not many papers analyze the effect of sustainability in the elements involving intellectual capital. This paper seeks to highlight the key role played by corporate sustainability on corporate reputation as one of the key components of relational capital based on the knowledge‐based theory. Authors develop a structural equation model to test the hypothesis. The study was tested using data collected from a sample of 400 Spanish consumers. The structural equation model shows that sustainability plays a vital role as antecedent of corporate reputation and relational capital. Findings suggest that economic, social and environmental domains of sustainability have a positive direct effect on corporate reputation. Additionally, this study shows that economic sustainability is considered to be the most important dimension to enhance corporate reputation. The complicated economic environment currently experienced worldwide may affect the perceptions of Spanish consumers and their ratings. The crosscutting nature of this research inhibits an understanding of the variations in the perceptions of the customers surveyed over time, suggesting that this research could be expanded by a longitudinal study. Secondly, the current study has been conducted with consumers of hotel companies in Spain and it is not clear in how far the findings can be generalized to other industries, stakeholders or countries. This research allows managers to identify the activities in which companies can devote resources to in order to increase firm´s reputation. By knowing these specific economic, social and environmental activities, companies can understand, analyze and make decisions in a better way about its sector and about the stakeholders that assess these initiatives. Keywords: intellectual capital, relational capital, sustainability, corporate reputation

1. Introduction The justification of firm success has suffered an important change during the last years. The resource based view (Barney 1986, 2001; Dierickx and Cool 1989; Grant 1991), has involved giving a key responsibility to endogenous and firm‐specific factors in order to explain sustained generation of wealth and economic growth in organizations. Practitioners and scholars have highlighted the strategic relevance of intangible resources in rent generation. Intangible assets are primarily based on information and knowledge, so that, this assets are difficult to detect, imitate, replicate and to transfer in the markets (Martín de Castro, López and Navas 2004). The interest in the role that knowledge plays within organizations has developed one main research stream known as intellectual capital (Bueno 2000). This mainstream has been named by other scholars as the knowledge‐based view or as the knowledge‐based theory of the firm (Grant 1996; Spender 1996; Martín de Castro, López and Navas 2004). This paper can be considered as part of these research streams and shows a model about the relation between sustainability dimensions and corporate reputation, as one of the main components of relational capital, since the current academic literature does not have an understanding of how these notions interact in the context of the knowledge‐based theory of the firm. In this proposal three issues must be highlighted: (1) relational capital, (2) corporate reputation and (3) sustainability. Thus, this paper mains to offer an understanding of the relationship between sustainability and corporate reputation according to the knowledge‐based theory since the current academic literature does not have an understanding of how sustainability and corporate reputation interact. We divide the concept of sustainability into three main dimensions: economic, social and environmental. To our knowledge, in any case has been studied simultaneously the influence of sustainability dimensions on the corporate reputation, which is a knowledge gap in the academic literature regarding intellectual capital and the knowledge‐based theory. Our findings show that the economic, social and environmental domains of sustainability have a direct and positive effect on corporate reputation. This paper is structured as follows. The next section presents the theoretical framework and reviews the literature on intellectual capital, relational capital, corporate reputation and sustainability. Section three presents the research methodology. The development of hypothesis is presented in the fourth section followed by the presentation of the results. Finally, concluding remarks and implications for management are presented.

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2. Conceptual framework 2.1 Intellectual capital: The role of corporate reputation in developing relational capital Recent years have been marked by the increasing importance of the role of intangible assets in firms. Several authors declare that the current inclination for organizations is to focus more on intangible assets when seeking competitive advantages and less on material assets (Martín de Castro, López and Navas 2004) and that firms with an adequate intellectual capital have a better chance of survival (Hormiga, Batista and Sánchez 2011). In spite of the immense amount of research about intellectual capital, there is still no single definition commonly accepted. In this paper intellectual capital is defined as “the knowledge that can be converted into future profits and comprises resources such as ideas, inventions, technologies, designs, processes and informatic programs” (Edvinsson and Malone 1997). Several authors have recognized that economic wealth comes from knowledge assets or intellectual capital, and its practical application (Dean and Kretschmer 2007). However, the emphasis on this concept is relatively new, and the management of the organization´s intellectual capital has become one of the key tasks in the corporate agenda. Nevertheless, this labor is especially difficult because of the problems involved in the identification, classification and strategic evaluation of intellectual capital. In recent decades, various alternatives have been proposed for the categories that involve intellectual capital. One of the classifications with the greatest consensus among academics is the one based on three dimensions including human, structural and relational capital (Brennan and Connell 2000; Roos, Bainbridge and Jacobsen 2001; Marr and Roos 2005). Among these three domains, relational capital is recognized by many authors as the organization´s most important intangible resource by playing a fundamental role in firms. The dimension of relational capital is based on the notion that firms are considered not to be isolated systems but as systems that are, to a great extent, dependent on their relations with their environment (Martín de Castro, López and Navas 2004). Thus, this type of capital includes the value generated by relationships not only with customers, but with suppliers, shareholders and stakeholders, both internal and external. In this regard, the strategic role of corporate reputation in gaining competitive advantage and relational capital has strong support in the academic literature from the resource based view. Relevant authors such as Barney (1986), Dierickx and Cool (1989) or Grant (1991), highlight its importance. In this sense, Fombrun and Shanley (1990) sustain that a good reputation is important to obtain competitive advantage because provide relevant information to stakeholders about the firm. Corporate reputation is understood as the “set of perceptions held by people inside and outside a company” (Fombrun 1996). This notion, as the awareness or perception about corporate behavior by its stakeholders (Fombrun and Shanley 1990; Fombrun 1996), will influence relational processes with the agents of the closer environment. A firm’s reputation is produced by the interactions of the company with its stakeholders and by information about the company and its actions circulated among stakeholders (Fombrun 1996). Thus, reputation has an important influence upon stakeholder beliefs, attitudes, and behaviors when these groups have incomplete information regarding organizational characteristics (Weigelt & Camerer 1988). The foundation for the influence of reputation upon stakeholder behavior is derived from the game theory (Weigelt and Camerer 1988) and signaling theory (Wernerfelt 1988). The explanation to game theory models is that each agent has a set of privately known information that reflects their individual characteristics (Weigelt and Camerer 1988). These characteristics influence the preferences and future behaviors of stakeholders. Fombrun and Shanley (1990) suggest a number of potential signals that influence reputation with a range of stakeholders: (1) market signals such as market performance, market risk or dividend policy, (2) institutional signals as institutional ownership, social responsibility and sustainability, media visibility or firm size, (3) accounting signals such as accounting profitability and accounting risk and (4) strategy signals as differentiation or diversification position. The role of reputational signals is to reduce uncertainty as to whether explicit and implicit contractual claims will be fulfilled (Cornell and Shapiro 1987). Therefore, reputation has the effect of increasing the attractiveness of an exchange relationship (Smith 1992; Erdem and Swait 1998). By modifying stakeholder perceptions of uncertainty regarding the outcomes of an exchange with the organization, reputation reduces the perceived risk of the exchange. Ceteris paribus, reduced perceived risks, increases the propensity of stakeholders to enter into an exchange with the firm (Hayton 2005).

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2.2 Sustainability dimensions in business From a business point of view, sustainability connotes three dimensions: economic, social and environmental (Choi and Ng 2011; Sheth, Sethia and Srinivas 2011). In this research authors understand the notion of sustainability meaning “to meet the present needs without compromising the ability of future generations to meet their own needs” (WCED 1987). Sustainability is an approach firms are increasingly adopting to conduct business. However, results from several international studies show that this notion is being adopted slowly. Among the three dimensions previously mentioned, environmental sustainability has received the most attention to date. This dimension refers to the maintenance of natural capital (Goodland 1995). As Stern (1997) argues, environmental damage caused by consumption threatens human welfare and health. The main environmental concerns arising from rapid growth in consumption are two‐fold: environmental degradation risks and eco‐system resource constraints. Environmental risks are losses and harm such as biodiversity loss, deforestation and soil erosion due to climate change and pollution of water systems and land (Sheth, Sethia and Srinivas 2011). Eco‐system constraints suggest that the earth cannot support unlimited growth in consumption (Speth 2008). This orientation is limited when compared to more recent developments in the concern for the environment and to a broader orientation of sustainability having not only environmental aspects but also economic and social concerns (Choi and Ng 2011; Sheth, Sethia and Srinivas 2011). The economic dimension of sustainability refers to companies´ ability to create value and enhance financial performance. With the enduring international economic and financial crisis, society is deeply concerned with economic sustainability due to fear of general job losses and financial risks to government and public programs (Choi and Ng 2011). Several authors have tried to articulate the significance of the economic dimension of sustainability. Sheth, Sethia and Srinivas (2011) have identified two different aspects of the economic dimension. The first one is related to conventional financial performance such as cost reductions, and the second issue relates to economic interests of external stakeholders such as a broad‐based improvement in economic well‐being and standard of living. To finish, social dimension of sustainability describes the consideration of societal issues like tolerance toward others or equal rights (Goodland 1995) and is concerned with the well‐being of people and communities as a noneconomic form of wealth (Choi and Ng 2011).

2.3 Sustainability and corporate reputation By revealing sustainability initiatives, companies are able to facilitate the projection of a social image (Gray, Kouhy and Lavers 1995) which will lead to increased corporate reputation and reduce reputational risks (Fombrum, Gardberg and Barnett 2000; Bebbignton, Larrinaga and Moneva 2008). Actually, the inclusion of social and environmental activities in the corporate agenda is a part of the conversation between organizations and their publics and it provides information on firms´ activities that help educate, inform and change perceptions and expectations of these stakeholders (Adams & Larrinaga 2007). Corporate reputation can be conceptualized as the “set of perceptions held by people inside and outside a company” (Fombrun 1996). A company´s reputation is the perceptions of its relevant stakeholders, such as customers, employees, owners, suppliers and strategic partners, society and community (ranging from both local to international, including current and future generations), government or non‐governmental organizations, among others. An advanced corporate reputation acts as both an intangible asset and a source of strategic advantage increasing companies´ long term ability to create value (Caves and Porter 1977) since corporate reputation is composed of a company´s unique set of skills in delivering both economic and non‐economic benefits (Fombrum 1996). Sustainability is increasingly seen as a determinant of corporate reputation since firms show externally that they are aware of the need of managing a wider range of social and environmental issues (Friedman and Miles 2001). Furthermore, this concept is relied upon to enhance corporate reputation (Becker‐Olsen, Cudmore and Hill 2006; Pirsch, Gupta and Grau 2007) and academic literature has recently suggested that companies may use sustainability as a way to manage their reputation risk (Bebbington, Larrinaga and Moneva 2008). Sustainability has been found to reduce public scrutiny, providing a license to operate in society and enhancing the latitude of public tolerance when things go wrong (Klein and Dawar 2004). In this way, sustainability may act as a barrier permitting the company a certain degree of tolerance for error in what, through the responsibilities imposed by its reputation and the promises made in its marketing communications, audiences have come to expect (Pomering and Johnson 2009). As previously mentioned, academics and practitioners attribute considerable power to corporate reputation built on sustainability aspects. General benefits attributed to sustainability include investment appeal, market share, business performance and organizational attractiveness, among others (Maignan, Ferrell and Hult 1999; Luce, Barber and Hillman 2001). Firms that act

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Patricia Martínez García de Leaniz and Ignacio Rodríguez del Bosque in a socially responsible manner and have a history of fulfilling their obligations to various stakeholders are creating reputational advantage (Miles and Covin 2000). The influence of sustainability on corporate reputation has been theoretically proposed but, as far as it is known, in any case has been analyzed the influence of sustainability dimensions on corporate reputation. The importance of knowing if such influence exists in practice and determining its magnitude is due to the fact that this effect would provide empirical support for the idea that sustainability is an important source of competitive advantage (Caves and Porter 1977; Fombrun 1996) generating multiple business benefits. Hence, and based on the previous literature review we propose: H1: The economic dimension of sustainability has a positive direct effect on corporate reputation. H2: The social dimension of sustainability has a positive direct effect on corporate reputation. H3: The environmental dimension of sustainability has a positive direct effect on corporate reputation.

3. Methodology 3.1 Data collection and sample Personal surveys of customers were conducted in Spain according to a structured questionnaire in order to test the hypotheses. To design the research sample, a non‐probability sampling procedure was chosen (Trespalacios, Vázquez and Bello 2005). Particularly, a convenience sample was used. From the target sample of 400 questionnaires, 382 questionnaires were completed, 18 were discarded as incomplete. Hence, the final response rate was 95.5 %. Table 1 displays the main characteristics of the research. Existing well‐established multiple‐item 7‐point Likert scales were adopted to measure our variables. Sustainability dimensions were measured using a seventeen‐item scale from Martínez, Pérez y Rodríguez del Bosque (2012). To finish, we measured corporate reputation with four items developed by Ahearne, Jelinek and Rapp (2005). The final measures are provided in the Appendix. Table 1: Research technical record Universe Scope

Hotel clients over 18 years of age Spain (The Autonomous Community of Cantabria)

Date of fieldwork Sample Sampling procedure

April 2011 382 valid questionnaires Quota sampling according to the criteria of 1) sex and 2) age

Processing of data

PASW v. 18.0, EQS v. 6.1

3.2 Psychometric properties of the measurement instrument In order to achieve the objectives of our research, the authors followed Anderson and Gerbing´s (1988) two‐ stage procedure. The psychometric properties (reliability and validity) of the measurement instruments were assessed by a confirmatory factor analysis containing all the multi‐item constructs in our theoretical framework by using EQS v.6.1 (Bentler 1995). The reliability of the measurement scales proposed was evaluated using the Cronbach´s alpha coefficient and by an average variance extracted (AVE) (Hair, Black, Babin and Anderson 2010). The values of these statistics exceed the minimum recommended values of 0.7 and 0.5, respectively (Hair, Black, Babin and Anderson 2010), which confirm the internal reliability of the model. In addition, all the items are significant at a confident level of 95% and their standardized lambda coefficients exceed 0.5 (Steemkamp and Van Trijp 1991), confirming the convergent validity of the model. Finally, in order to confirm the discriminant validity, the confidence intervals for the correlation of the constructs are estimated and compared with the unit. In none of the cases did the intervals contain the value 1. Therefore, the measurement model proposed is correct. Finally, the goodness of fit of the analysis was verified with the Satorra‐Bentler χ2 (S‐B χ2) (p <0.05) and the comparative fit indices NFI, NNFI, IFC and IFI, which are the most common measures for confirmatory tests (Uriel and Aldás 2005). All values were greater than 0.9 (Bentler 1995), indicating that the model provides a good fit. Table 2 shows the statistics calculated to verify these properties and the main goodness of fit indicators.

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Patricia Martínez García de Leaniz and Ignacio Rodríguez del Bosque Table 2: Confirmatory factor analysis of the final model Factor

ECO

SOC

ENV

REP

Item ECO1 ECO2 ECO3 ECO4 SOC1 SOC2 SOC3 SOC4 SOC5 SOC6 ENV1 ENV2 ENV3 ENV4 ENV5 ENV6 ENV7 REP1 REP2 REP3 REP4

Std. lambda 0.816 0.883 0.788 0.849 0.773 0.685 0.773 0.700 0.709 0.770 0.761 0.764 0.722 0.718 0.787 0.761 0.748 0.891 0.898 0.780 0.900

Cronbach´s α

AVE

0.902 0.697 S‐Bχ2 441.82 (p=0,000)

0.876 0.542

BBNFI=0.905 BBNNFI=0.931 CFI=0.941 IFI=0.941 RMSEA=0.061

0.985 0.579

0.925 0.755

4. Analysis of structural relations and hypothesis testing Table 3 and Figure 1 show the standardized coefficients for the structural relations tested. As it is shown, the goodness of fit indices for the structural model show a good fit so that it is possible to test the proposed hypotheses. H1, H2 and H3 are supported (β=0.326*; β=0.228*; β=0.173*) as the economic, social and environmental dimension of sustainability have a positive direct effect on corporate reputation. This study shows that economic sustainability is considered to be the most important dimension to enhance corporate reputation (β=0.326*; p<0.05*), followed by social sustainability (β=0.228*; p<0.05*). These results give empirical support to the idea that the efforts made by companies towards sustainability will be rewarded by the projection of a positive reputation. Therefore, the proposed model is totally supported by the results Table 3: Structural equation model results Hypotheses H1 H2 H3

Structural relationship Economic dimension Reputation Social dimension Reputation Environmental dimension Reputation BBNFI=0.905 BBNNFI=0.932 CFI=0.942 S‐Bχ2 438.23 (p=0,000)

Std. coefficient (Robust t‐value) 0.326 (4.480)* 0.228 (2.300)* 0.173 (1.982)* IFI=0.942 RMSEA=0.060

Contrast Accepted Accepted Accepted

p<0.05*

5. Conclusions, limitations and future lines of research The results of this study provide support for our argument that the dimensions of sustainability will positively influence corporate reputation as one of the main components of relational capital. The authors have developed a structural equation model to test the hypothesis. The three hypotheses suggest that economic, social and environmental domains of sustainability have a positive direct effect on corporate reputation. In this sense, it seems that the economic and social dimensions of sustainability present the greatest influence on this intangible asset. Such findings are relevant since they add several contributions to the existing academic literature.

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Figure 1: Structural model estimation Firstly, this study shows that economic sustainability is considered to be the most important dimension to enhance corporate reputation (β=0.326*; p<0.05*). Therefore, we could generalize that, in order to increase corporate reputation, it is necessary to understand the economic domain from a broader perspective and not only in terms of profit maximization. Thus, companies must reveal information to their stakeholders regarding issues such as obtaining the greatest possible profits, achieving long‐term success, improving its economic performance and ensuring their survival and success in the long run. Secondly, social sustainability also encompasses a great influence on corporate reputation (β=0.228*; p<0.05*). Social initiatives such as helping to solve social problems, playing a role in society that goes beyond mere profit generation, actively collaborating in cultural and social events, or committing to improving the welfare of the communities in which companies operate, are actions that companies should devote resources to in order to strengthen reputation. This way, by providing relevant information to stakeholders about the firm regarding sustainability, companies will obtain a competitive advantage based on a good reputation. This research improves our understanding of reputational capital, corporate reputation and sustainability. Given that limited empirical research addresses the nature and consequences of sustainability in the context of intellectual capital, this study provides a starting point for future work in this area. Our study makes theoretical distinctions between the key dimensions of sustainability and contributes to understanding their effect on a firm´s reputation. Empirical support for the role that sustainability dimensions play in corporate reputation encourages both researchers and practitioners to examine the nature, antecedents and consequences of reputational capital. The present study has a number of implications for practitioners. The most important implication for practitioners is that economic, social and environmental dimensions of sustainability have a direct and positive impact on corporate reputation. This should give managers the argument they need to justify the costs that

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Patricia Martínez García de Leaniz and Ignacio Rodríguez del Bosque are associated with sustainable issues. Apart from that, this research allows managers to identify the activities in which companies can devote resources to in order to increase firm´s reputation. By knowing these specific economic, social and environmental activities, companies can understand, analyze and make decisions in a better way about its sector and about the stakeholders that assess these initiatives. At present, it is not sufficient for managers to know the perceptions that consumers have about companies and the reputation arising from them, but it is also necessary to know the factors causing these perceptions and reputation, so that it is possible for managers to control these aspects efficiently and effectively. Additionally, these findings suggest that the areas of corporate reputation and sustainability are strongly interrelated, so it follows that these concepts could be managed in an integrated way. Companies are encouraged to explore how corporate sustainability and reputation activities could positively be managed jointly, since organizations may manage these concepts in separate business areas. Finally, to refine the findings of this study, some limitations are outlined. Firstly, with the enduring international economic and financial crisis, society is deeply concerned with economic sustainability. The complicated economic environment currently experienced worldwide may affect the perceptions of Spanish consumers and their ratings. The crosscutting nature of this research inhibits an understanding of the variations in the perceptions of the customers surveyed over time, suggesting that this research could be expanded by a longitudinal study. Secondly, the current study has been conducted with consumers of hotel companies in Spain and it is not clear in how far the findings can be generalized to other industries, stakeholders or countries. Future research could extend this research by including different stakeholders´ expectations of corporate sustainability and reputation.

6. Appendix 1

Ident. Item I think this company… ECONOMIC DIMENSION ECO1 Obtains the greatest possible profits ECO2 Tries to achieve long‐term success ECO3 Improves its economic performance ECO4 Ensures its survival and success in the long run SOCIAL DIMENSION SOC1 Is committed to improving the welfare of the communities in which it operates SOC2 Actively participates in social and cultural events SOC3 Plays a role in society that goes beyond mere profit generation SOC4 Provides a fair treatment of employees SOC5 Provides training and promotion opportunities to their employees SOC6 Helps to solve social problems ENVIRONMENTAL DIMENSION ENV1 Protects the environment ENV2 Reduces its consumption of natural resources ENV3 Recycles ENV4 Communicates to its customers its environmental practices ENV5 Exploits renewable energy in a productive process compatible with the environment ENV6 Conducts annual environmental audits ENV7 Participates in environmental certifications CORPORATE REPUTATION REP1 I consider that X is a respected company REP2 I consider that X is a recognized company REP3 I consider that X is an admired company REP4 I consider that X is a prestigious company

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Adopting a Trust‐Based Framework to Generate Social Capital: Espousing Social Learning and Social Capital for Enhanced Innovation, Improved Performance and Competitive Advantage Athar Mahmood Ahmed Qureshi and Nina Evans University of South Australia, Adelaide, Australia Athar.Qureshi@unisa.edu.au Nina.Evans@unisa.edu.au Abstract: Since the start of the twenty first century, scholars of the theory of social capital, intellectual capital and knowledge management have investigated the role of trust in the creation of social capital and the ways in which social capital increases innovation, performance, success and competitive advantage. However, a roadmap to enhance innovation, performance, success and competitive advantage has not been developed yet. In this article we seek to contribute to this body of work by developing a roadmap with the following arguments: (1) trust facilitates the activation of social learning; (2) trust‐based social networks are effective mechanisms to drive social learning; (3) social learning facilitates the generation of social capital; (4) social capital contributes to innovation, increased performance and competitive advantage. We suggest a trust‐based framework that incorporates these overall arguments by using trust‐ based social networks to generate social capital to ultimately enhance innovation. Keywords: trust, social learning, social capital, innovation

1. Introduction In the twenty first century, substantial emphasis is placed on the innovation and the innovative capability of the firms in the knowledge management (KM) literature. The most significant benefit that is usually associated with innovation and with facilitating knowledge acquisition, knowledge assimilation, knowledge transformation and knowledge exploitation is usually that it creates a competitive advantage for the organisation (Cohen & Levinthal 1990). Furthermore, disseminating, sharing and transfer of knowledge are the factors that contribute to the success of organisations (Grant 1996). Moreover, Tullio (2011) asserted that the role of knowledge in an organisation is crucial and that the organisation is conceptualised as an institution due to its nature of knowledge absorption and knowledge integration (Grant 1996). Therefore, the broader the scope of knowledge integration, the more difficult it becomes to replicate that knowledge (Grant 1996) and hence, the competitive advantage will be gained. Five decades ago, March and Simon (1958) identified the critical importance of external knowledge for the sustainability and innovativeness of organisations. They indicated that, most of the time, it is the borrowing of knowledge that drives organisations to inventions and that it is not only due to the innovations. Furthermore, the contextual ability of an organization is to translate the ‘change’ into performance and the KM literature has established the concept of absorptive capacity (AC) in order to measure this translation (Cohen & Levinthal 1990; Zahra & George 2002). AC is the measurement of organisations’ imitating capability with regard to processes, services or products (Francalanci & Morabito 2008). The AC of an organisation is also referred to as the knowledge absorption capability (Cohen & Levinthal 1990; Zahra & George 2002). It is the ability of the organisation to identify, assimilate, and exploit the external knowledge to commercial ends (Cohen & Levinthal 1990). AC is the ability to “exploit less commercially focused knowledge such as basic scientific research or new IT solutions” (Francalanci & Morabito 2008). Moreover, AC has slowly but steadily begun to gain a foothold in information systems (IS) research. This is probably due to the fact that these days technology is more focused on acquiring and disseminating knowledge effectively and efficiently. For example, the way the social software is transforming organisational cultures is reverting organisations back into the tradition of socialisation. Information and communication technologies (ICT) play a significant role in facilitating the flow of the knowledge in a firm and also supports the knowledge‐based view of the firm, where knowledge is considered as the most important resource (Tullio 2011). On the other hand, the various other theories of the firm are merely the conceptualisations that explain, predict and structure its behaviour. They are designed to address a specific set of organisational characteristics and behaviours (Grant 1996; Machlup 1967). Among the ICT based resources, information systems are used to create, enhance, and expedite KM in organisations (Alavi & Leidner 2001). At present, the majority of the researchers’ focus is either on the improvement of the technology itself

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Athar Mahmood Ahmed Qureshi and Nina Evans or on the social impacts they have on their users. Less (if any) emphasis is found in the KM literature on the social antecedents of their usage. Mayer, Davis and Schoorman (1995) in their seminal investigation asserted that ‘trust’ is a crucial construct (social) for organisations and is gaining critical attention among the trends of “workforce composition” and the “organisation of the workplace”. Trust is “not behaviour (e.g. cooperation) or a choice (e.g. taking a risk) but an underlying psychological condition that can cause or result from such actions” (Sitkin, Rousseau, Burt et al 1998). Trust is defined as the “willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party” (Mayer, Davis & Schoorman 1995). Furthermore, being “vulnerable” is an indication to something of greater importance to be lost (Boss 1978; Zand 1972). Where vulnerability is an indication of risk‐taking, “trust is not taking risk per se, but rather it is a willingness to take risk” (Mayer, Davis & Schoorman 1995). Moreover, Rosanas (2009) defined the organisational trust as the “relationship between two people where one takes an action making him vulnerable to the other”. In this paper, we reconceptualise the knowledge‐based view of the firm from a social capital (SC) perspective. Knowledge is the backbone for innovation. It has to be created, acquired, shared, transferred and absorbed through social integration mechanisms based on trust (Qureshi & Evans 2012, 2013c, 2013a, 2013b). This knowledge creation, acquisition, sharing, transfer and absorption processes through social integration mechanisms will generate SC and hence facilitate the creation of intellectual capital (Nahapiet & Ghoshal 1998). This will also help in achieving innovation, competitive advantage, improved performance and success. Therefore, we propose to adopt a trust‐based framework to assist organisations with achieving these complex and challenging, yet achieve‐able goals. Although trust may seem trivial, it is in fact crucial in terms of today’s concern over growth, prosperity, innovation and competitive advantage. In this write‐up, we adopt a view that social networks (SN) are the most powerful, reliable and efficient means to social integration. The literature review section draws literature from the KM domain and supports the argument.

2. Literature review 2.1 Social capital The concept of SC has existed for a number of years, ever since trivial communities formed and humans have started interacting with the anticipation of sharing and trusting (e.g. Moore 1994; Platteau 1994; Woolcock 1998). However, the present SC term and its associated meanings became popular amongst researchers from various disciplines (e.g. Bourdieu 1977; Bourdieu 1984, 2008; Coleman 1988; Granovetter 1973, 1978, 1983, 1985, 1992, 2005; Granovetter & Swedberg 2001; Putnam 1993). Among the researchers, there is a contrast of opinions. Most of them merely focus on the benefits of SC, while some differ in the handling of the concept. Those who differ hold the viewpoint that the SC subsists between individuals, and it can only be studied at the individual level. This paper also adopts the later viewpoint. In the network terminology and representation, SC exists in the relationships among the nodes. The nodes in the network represent individuals and the relationship represents the social relationship. Each node behaves the same way as a physical human and therefore enables productivity in a similar fashion. Consequently, SC exists between individuals, and it can be accumulated from among individuals (Cross & Cummings 2004; Qureshi 2011). This view of SC is based on the principle that ‘my connections can help me’ (Cross & Cummings 2004; Qureshi 2011). SC, therefore, is the exchange of knowledge within established relationships for a set purpose and by engaging them to produce tangible and intangible benefits. Furthermore, this form of knowledge refers to the all‐inclusive result of a group work in an organisation (social knowledge), where the group includes knowledgeable members and together they build relationships based on trust and interactions (Ruzic 2011). In an IT context, as indicated by Ruzic (2011), social knowledge is the use of social media to create, transfer and preserve the organisational knowledge, group knowledge and social knowledge. Such a form of relationships indicates the significant need for a type of glue that can strengthen the bond of relationships. In this paper, we adopt a view that this glue is ‘trust’. SC can be represented in many ways. Five dimensions of SC are identified from the literature (Bourdieu 1983; Coleman 1988; Qureshi 2011), namely networks‐lateral associations (differ according to density or size), reciprocity‐expectation (short or long term compassion and amenities), trust‐willingness (taking initiatives or

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Athar Mahmood Ahmed Qureshi and Nina Evans risk), social norms (shared values that direct behaviour and interaction), and personal and collective efficacy (voluntary effective engagement with community). On the same token, Narayan and Cassidy (2001) presented seven dimensions of SC. Both the set of seven and five dimensions are closely similar and carry synonymous terms. Furthermore, SC is susceptible to many interpretations and usage (Greeley 1997a, 1997b; Qureshi 2011). The literature indicates the two perspectives that SC is based on the individual’s potential (financial and non‐financial) or on their relations and not in themselves (Coleman 1988, p.98; Qureshi 2011). To summarise, SC is context dependent. It may transform in various forms, e.g. obligations, trust, intergenerational closure, values, and sanctions (Bourdieu 1983, p.249; Qureshi 2011). In addition, the relationships form a complex network of interactions and communications (Fukuyama 1995b, 1995a; Putnam 1993; Qureshi 2011). For example, SC is created when people start doing the voluntary contributions over the lunch break, when the focus of their discussions is on social and organisational aspects (Qureshi 2011). These findings have important consequences for the broader domain of SC and trust, hence, this notion of communication and relationship highlights the importance of trust as a construct that establishes relationships to ignite the processes of knowledge sharing, transfer and absorption (Qureshi & Evans 2012, 2013a, 2013b).

2.2 Social learning Knowledge was described as a power by the early researcher and writer Francis Bacon in 1597. The classical Latin phrase ‘nam et ipsa scientia potestas est’ translates as ‘‘for also knowledge itself is power’’. Mishra and Bhaskar (2011) discovered a clear source of power from the literature i.e. the capability of an organisation to learn, create, or gain knowledge. As a construct, knowledge arbitrates these activities. The learning abilities and generating new ideas among other creative properties are the transforming dynamics of an organisation, in order to become a learning organisation. Every organisation is a learning system and have its structured or unstructured processes to learn during the three stages of organisational learning, namely acquisition, dissemination, and utilisation (Nevis, DiBella & Gould 1995). Knowledge acquisition is the development and creation of skills, visionary insights and relationships among them. Knowledge dissemination (sharing) is the process of knowledge diffusion among other people in organisation, i.e., to share what has been learned. Knowledge utilisation is the application of the learning and integration of the knowledge in the organisational systems (Nevis, DiBella & Gould 1995). Furthermore, Nevis, DiBella and Gould (1995) suggested that in order for an organisation to improve its learning capabilities, it has to focus on one of the stages of the learning cycle (Gunsel, Siachou & Acar 2011). Moreover, Zahller (2011) described this rich and often undervalued subject that, organisations must adapt to valuable (innovative) goals in order to survive in this competitive era. They should also change their ways and actions. They must take conscious measures to change their actions in response to changing environments and circumstances, and in order for learning to occur. They must deliberately link their actions to productivity. In addition to that, Zahller (2011) has indicated that there are many similarities between organisational learning and psychology, because, the initial learning originates from an individual level. This learning will then become organisational learning once it is shared and stored. The social learning theory (SLT) is derived from the work of Gabriel Tarde (1843‐1904). SLT is an attempt to describe factors to determine how people think and behave. It is regarded as a category of learning theories, arguing that human behaviour is determined by cognitive factors, environmental influences, and behaviour (Taher & Krishnan 2011). Furthermore, there are four main stages through which social learning occurs, namely close contact, imitation of superiors, understanding of concepts and role model behaviour. In addition to that, there are corresponding constructs and factors of social learning, namely cognitive factors (knowledge, expectations, attitudes), environmental factors (social norms, access in community), influence on others (ability to change own environment) and behavioural factors (skills, practice, self‐efficacy) (Taher & Krishnan 2011). Behaviour is what “changes the environment” (Taher & Krishnan 2011). The two types of behaviour related to social learning, respondent and operant have been identified in the literature (e.g. Bandura 1963, 1968, 1969, 1977; Davis & Luthans 1980; Miller 1941; Rotter 1954, 1960). The respondent behaviour can be understood by past indications. It is generally thought of as emotional. The operant behaviour is what changes the environment and thus create rewarding or penalising circumstances (Taher & Krishnan 2011). Therefore, SLT incorporate both the cognitive framework as well as behavioural framework because learning incorporates

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Athar Mahmood Ahmed Qureshi and Nina Evans attention, memory and motivation (Bandura 1963, 1968, 1969, 1977; Davis & Luthans 1980; Miller 1941; Rotter 1954, 1960; Taher & Krishnan 2011). Therefore, social learning is the catalyst for generating SC, enables organisational learning and hence, facilitates intellectual capital development (Nahapiet & Ghoshal 1998). As indicated above, social learning in organisations is highly dependent on behaviour as well as cognitive frameworks. Trust is the basic fundamental ingredient when it comes to behaviour and relationships. Focusing on trust will therefore enhance the positiveness in cognitive and behavioural factors (Lin 2011; Lin, Tsung‐Hsien & Binshan 2012). Trust, consequently influences the efficacy of social learning and generation of SC. Adopting a trust‐based framework will therefore guide organisations to transform their human capital into SC through social learning processes. In this paper, the authors therefore formulate the following propositions: P1: the higher the degree of trust in an organisation the higher the level of socialisation P2: the higher the degree of trust‐based socialisation in an organisation the higher the level of social learning P3: the higher the degree of social learning in an organisation the higher the level of organisational learning P4: the higher the degree of social learning in an organisation the higher the level of social capital P5: the higher the degree of social learning in an organisation the higher the level of trust

2.3 Social networks At the start of 20th century, terminologies like webs, bonds and ties became famous among social science researchers (Scott 2002). SN are considered a metaphor that is alluding to social patterns, transport and electric wiring (Scott 2002). In this era of knowledge‐based economy, it is therefore essentially important to understand the phenomenon of SN, their powerful concept, and to understand how social beings (humans) accomplish their objectives and function in organisations. Sastrowardoyo (2009) asserted that SN are a powerful channel to connect people to achieve a set goal. Supporting this Conway (2001) said that "the utility of the network perspective is at least partially derived from the ease with which the concept can be expressed and applied. It is at once a concept and framework whose applicability is immediately recognisable by practitioners, whilst its academic pedigree has been firmly established”. Furthermore, in the context of SC, SN have a strong influence on the understanding of human beings. The ostensible uncomplicatedness of SN seems to contradict the reality, where the notion imitates both the intricacy of human systems and that of networks (Sastrowardoyo 2009). Affirming the complexity of this phenomenon, Buchanan (2002) described a SN as "disorderly and complex". The SN concept existed for a long time and it has been sustained in ways other than the face‐to‐face environments (e.g. postal, telephone and internet communications) (Sastrowardoyo 2009). KM literature has established that SN facilitates the creation of knowledge (Griffith, Sawyer & Neale 2003; Nonaka & Takeuchi 1995). It is through these informal SN that an individual’s explicit and tacit knowledge transforms, and builds upon one another. Later, SN will leverage the social‐ and organisational‐ level knowledge (Chou 2005), where, the social interactions are dynamic and fluid in nature (Obembe 2006).The concept embodies social as well as network aspects. The focus of this paper is on the social (human) aspects in a network setting. In an era where economies are based on knowledge, collaboration and innovation, Cross, Parker, Prusak et al (2001) highlighted the importance of understanding SN and their strength. Organisations are increasingly centralising their effectiveness and innovativeness on the properties of knowledge. Furthermore, they (Cross, Parker, Prusak et al 2001) have asserted that organisations must pay attention to the sets of relationships their employees rely upon when they want to achieve their objectives. However, the quality of relationships in a SN is determined by the quality of interactions, i.e., SC. Therefore, trust, norms, and identification are the key elements of SC (Dixon 2007). KM literature has well defined the need and sources of information of an individual in an organisation (e.g. Cross, Parker, Prusak et al 2001), which is essentially a component of information retrieval. Figure 1 represents the outcome of an empirical study (Cross, Parker, Prusak et al 2001)– which concludes that managers receive their valuable information from other people, more than their own personal sources. This hereby highlights the importance of SN in an employee’s workplace and also highlights the importance of trust to cultivate SN.

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Figure 1: Sources of Information– adapted from Cross, Parker, Prusak et al (2001) In another recent study (Esterhuizen, Schutte & du Toit 2011), questions are raised over the conceptual foundations of knowledge conversion. The argument presented is that the knowledge conversion takes place in the presence of a relationship between tacit knowledge and social practices. Furthermore, they identified that the knowledge creation processes are the critical enablers for innovativeness, and hence emphasised the importance of socialisation, which enables a firm to reach its highest maturity level with greater efficiency. Moreover, according to Nonaka, Toyama and Konno (2000)’s knowledge creation (SECI) model, organisations create their knowledge through interactions between tacit and explicit knowledge. This process of knowledge conversion enables explicit and tacit knowledge to grow in both quantity and quality (Esterhuizen, Schutte & du Toit 2011). From the literature, there are four modes of knowledge conversion, namely socialisation, externalisation, combination and internalisation. The people (social) component is a vigorous element and without which other three components wouldn’t be possible. Socialisation is identified as crucial because it is the underlying process that supports innovation capability maturity (Esterhuizen, Schutte & du Toit 2011). Therefore, the knowledge of the workers in an organisation is a critical resource. However, aside from the rewarding and attractive policies organisations are adopting, to keep their valuable (skilful) employees (as assets), there is a need to put more effort into systematic ways of working (e.g. knowledge sharing, transfer and absorption through trust‐based SN), where knowledge that is embedded in people is shared among people (Cross, Parker, Prusak et al 2001) to generate SC. The literature has thoroughly examined the strength of SN and their direct influence on innovativeness. In the context of organisations, Singh (2005) has conceptualized SN as the “facilitators” of effective knowledge diffusion. Furthermore, innovation at organisational level is often considered to be a set of processes to create social connections among employees, their ideas and their resources, to harvest innovative combinations (Obstfeld 2005). A SN is a powerful mean that connect people to achieve a purposeful goal (Sastrowardoyo 2009). Likewise, in Nonaka (1999)’s view, knowledge is created when individuals interact with other individuals or environments. This viewpoint is well acknowledged among the KM researchers. In addition, Sastrowardoyo (2009) in her doctorate dissertation, highlighted the need to emphasis on the importance of understanding SN, their potential and strength, and the connections between SN and collaboration, SC, innovation and information diffusion. Moreover, Obstfeld (2005) asserted that the key to innovation is combination, and SN activity is the best utility for it. Among the potential advantages of closed, dense, or cohesive networks are trust, cooperation, and the potential to build knowledge through interactions and exchange of ideas (Ahuja 2000; Coleman 1988). Therefore, SN enable individuals to interact closely and connectedly (Lin 2011) in order to nurture organisational innovativeness and diffusion (Bell 2005; Brachos, Kostopoulos, Soderquist et al 2007; Sparrowe, Liden, Wayne et al 2001). Henceforth, “engineers are not just people who sit in drawing offices and design machines, they are also, willy‐nilly, social activists” (Law & Callon 1988). Connecting with previous arguments, several social and technological systems rely on the notion of trust when following recommendations, as agents make their decision based on the trustworthiness of other agents, with

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Athar Mahmood Ahmed Qureshi and Nina Evans whom they interact (Richters & Peixoto 2011). Lin (2011) asserted that managers should encourage employees to participate in SN that facilitate social interaction among knowledge workers by enhancing interpersonal trust, informal communication, and reciprocal relationships. This will increase the maturity of KM. Furthermore, Ruan, Ochieng, Price et al (2012) studied the construction industry and identified that collaborative working environment can dramatically improve the overall performance because; parties have mutual support, that is based on trust. Moreover, studying the trust transitivity in SN, Richters and Peixoto (2011) suggested that the existence of entirely confident trust is a key requirement for the “viability of global trust propagation” in larger systems. Therefore, trust is the glue that not only keeps the different nodes in a SN together but also generates trustworthiness for individuals to be relied. Trust strengthens relationships which will consequently expand a SN and enhances the AC of an organisation (Van Den Bosch, Wijk & Volberda 2003; Volberda, Foss & Lyles 2010). In this paper, SN are considered to be the most powerful, reliable yet challenging and diverse vehicle for socialisation in organisations. SN are the most effective, efficient and adaptable social integration mechanism to enable social learning and organisational learning, to generate SC, to transform SC into intellectual capital, to enhance AC, to boost innovation, to improve performance and to achieve competitive advantage. The paper, therefore, makes the following propositions: P6: the higher the degree of trust in an organisation the higher the focus on social networks P7: the higher the degree of focus on social networks in an organisation the higher the level of social learning P8: the higher the degree of focus on social networks in an organisation the higher the level of social capital P9: the higher the degree of focus on social networks in an organisation the higher the level of trust

3. Suggested framework The trust‐based framework shown in Figure 2 incorporates a roadmap to achieve innovation through SC generation.

Figure 2: Trust‐based framework – adopted from Qureshi and Evans (2013a)

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Athar Mahmood Ahmed Qureshi and Nina Evans The framework sketches a number of stages to be achieved progressively prior to achieve the ultimate set of goals. The framework does not only guide to the culture of innovation but also guides to the culture of knowledge, that which incorporates knowledge sharing, knowledge transfer and knowledge absorption (SC development). Furthermore, the framework outlines a set of antecedents, enablers and the consequential benefits for each antecedent and a stage. From among the enablers, socialisation mechanisms (SN) and IT has been highlighted as the most significant enablers to achieve the stage‐wise achievements as well as the progression to the next stage. Moreover, the set of thought processes that were taken in developing the framework is the logical flow, connectivity and the inter‐dependence of the each of the five constructs in the framework, namely trust, knowledge sharing, knowledge transfer, knowledge absorption and the AC (Qureshi & Evans 2013a). The framework guides to a steady progression by adopting the two significant enablers, namely IT and the SN (Qureshi & Evans 2013c, 2013a). In addition, innovation is not the only achievement indicated by the framework; rather, the framework is a guide to achieve various other objectives (e.g. knowledge culture, knowledge retention, improved performance, competitive advantage and success) that are vital for the transformation of human capital into SC and ultimately into intellectual capital. In the light of this paper, trust‐based socialisation mechanisms are the catalyst for social learning, organisational learning, SC generation and the transformation of SC into intellectual capital. Therefore, the trust‐based framework justifies the set of arguments developed by the authors.

4. Conclusion In this paper, we have presented a comprehensive literature review and suggested the adoption of a trust‐ based framework as a roadmap to guide the generation of social capital and the transformation of social capital into intellectual capital. The paper seeks to offer a holistic approach for studying how trust influences social learning, organisational learning, social capital generation, innovation, improved performance and competitive advantage through social networks.

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Intellectual Capital Evaluation: Return on Assets Methods Versus Market Capitalization Methods Agne Ramanauskaite and Kristina Rudzioniene Vilnius University Kaunas faculty of humanities, Kaunas, Lithuania agne.ramanauskaite@khf.vu.lt kristina.rudzioniene@khf.vu.lt Abstract: According to the current standards of accounting, only a minor segment of intellectual capital (IC) is presented in financial statements of enterprises as it usually does not satisfy one of the criteria of property recognition in financial accounting, namely, reliable valuation. This results in the need to integrate into the financial accounting such evaluation methods which would enable enterprises to reliably establish the value of IC or its constituent parts in monetary units. A number of scholars have dealt with methods of IC valuation. However, no uniform opinion has been reached yet regarding which of the evaluation methods (return on assets or market capitalization) enable(s) to establish the value of the IC of an enterprise and its constituent parts in monetary units. Hence the objective of the present research is to explore and systemize the advantages and drawbacks typical of these methods and to outline the theoretical aspects of the most appropriate method of IC evaluation in monetary units. The main methods applied in the present article are synthesis and generalization of academic writings. The results of the research and its conclusions are based on the analysis of academic investigations conducted by various authors and the resulting publications. The article generalizes on analyses of methods of IC evaluation suggested in researches of a number of scholars, provides comparisons and reveals advantages as well as drawbacks of these methods. A synthesis of return on assets (ROA) and market capitalization (MC) type methods establishes that the value of the IC of an organization in monetary units is more reliably defined by MC methods. Even though the main disadvantage of these methods is the use of the enterprise market value (MV) as the background yet subjectivity (which is the principal drawback of ROA methods) is thus avoided. Nevertheless, the application of MC methods is limited as they can only be employed for those enterprises whose MV may be reliably established. Keywords: intellectual capital, intellectual capital evaluation, return on assets methods, market capitalization methods

1. Introduction Methods of intellectual capital (IC) valuation of an enterprise have been researched by a number of authors (Bouteiller 2002, Ratnatunga 2002, Rodov et al. 2002, Lev et al. 2003, Andriessen 2004a, 2004b, Bareisis 2004, Muller 2004, Sitar et al. 2004, Pukenaite 2005, Vaskeliene 2007a, 2007b, Pukeliene et al. 2007, Rodriguez‐ Castellanos et al. 2007, Tan et al. 2007, Van den Berg 2007, Jurczak 2008, Kuzmina 2008, Sveiby 2010, Ramanauskaite 2012, Salman et al. 2012, et al.); their works mention and suggest more than sixty different methods of IC valuation. Different methods provide different opportunities, and none of the methods published in academic writings is capable of satisfying all the objectives that may have been set while some specific methods of IC valuation will work only in specific industries or merely in specific enterprises (Vaskeliene 2004, Wall et al. 2004, Campos et al. 2007, Palumickaite 2008, Sveiby 2010). This happens because of complexity of IC valuation (Bontis 2002) since in the process of valuation one of the core difficulties is encountered: the borderline between IC and other forms of capital is often blurred as IC is frequently involved in material capital (e.g. technologies and knowledge in a new airplane) as value creation is grounded upon the interaction of the intellectual and material capital; the stronger the interaction the harder it is to single out the IC and to evaluate it as a distinct entity (Lev 2001). Besides, when evaluating the IC, indicators based on the potential of value creation in the future are mostly considered. Yet, they are highly dangerous as all projections into the future are nothing more than guesses which may spectacularly fail if unpredicted changes take place (Borneman et al. 1999). Another issue in the search of methods of IC valuation is that academic works exhibit a trend of developing yet other new methods, advising novel categories and groups of indicators, ignoring already completed theoretical work, employing “subjective measurement”, giving preference to qualitative methods, and, in the majority of cases, not even seeking universal acceptability (Campos et al. 2007, Palumickaite 2008). Hence most currently existing methods are complicated and limited qualitative or theoretical proposals with limited proof of practical applicability, which complicates the development of a single and universal method of valuation of the IC of an enterprise. This is proven by the results of researches (Wall et al. 2004, Campos et al. 2007, Pukeliene et al. 2007, Palumickaite 2008) that none of the current methods or models has gained universal recognition of theoreticians and practitioners, and, consequently, none is being applied in enterprises at the national or international level. Thus the issue has not been resolved yet.

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Agne Ramanauskaite and Kristina Rudzioniene Consequently, the present article seeks to systemize and generalize already conducted theoretical and empirical researches in order to assess principles, advantages and drawbacks of IC evaluation methods which could be integrated into the financial accounting, and thus to contribute to the process of creation of this standardization system. Currently, with no international or national regulation of this process being employed, each enterprise has to decide which method optimally matches its objective(s), circumstances and the needs of information users. History demonstrates that those enterprises that never gave up ultimately evolved their own systems of IC valuation and applied them in practice also managed to develop their potential of IC (Wall et al. 2004, Sveiby 2010). That is why the object of this research is IC evaluation methods (return on assets – ROA and market capitalization – MC), and the aim is to explore and systemize the advantages and drawbacks typical of these methods and to outline the theoretical aspects of the most appropriate method of capital evaluation in monetary units. The paper is structured as follows. Section 2 outlines the methods of valuation of IC and reveals their classification according to general principles of valuation presented in various academic writings. Section 3 reveals the results of the empirical research by presenting the exploration and systemization of the advantages and drawbacks typical of ROA and MC methods. Finally, section 6 concludes the paper.

2. IC valuation methods in academic writings Academic writings provide various methods of IC valuation: financial and non‐financial, applying quantitative, or, more frequently, qualitative methodology, external and internal, valuating IC as a universality or striving to present the value of its separate components or elements, on the basis of the traditional financial accounting of enterprises or employing market indicators to identify the established situation in the market; there are also management methods when the causes of the established situation are sought; some methods present a systematic single index‐manifested value of IC while others consider multiple factors influencing the activity of an enterprise and so on (Vaskeliene 2004, Campos et al. 2007, Pukeliene et al. 2007). Many authors in order to systemize and reveal features common in various methods or in order to identify shared features classify them according to certain criteria. Usually, scholarly works present classifications based on general principles of valuation and single out 4 groups of methods (Table 1; source: compiled by the authors according to Engstrom et al. 2003, Lev et al. 2003, Muller 2004, Wall et al. 2004, Sitar et al. 2004, Westnes 2005, Kok 2007, Pukeliene et al. 2007, Vaskeliene 2007a, Vaskeliene 2007b, Jurczak 2008, Kuzmina 2008, Sveiby 2010, Znakovaite et al. 2010, Karas et al. 2011, Salman et al. 2012). Table 1: Classification according to general principles of valuation No. 1.

Group of methods MC Methods

ROA Methods

Direct IC Methods Scorecard Methods

Features Based on the calculation of the difference between the market value (MV) of an enterprise and its assets which is equaled to the value of IC. These methods are hard to apply in non‐profit entities or enterprises of the public sector. Based on pre‐tax average income versus average capital unit calculation. Afterwards, the obtained result is compared with the average value of the industry branch and the result is treated as the average of return on IC. Part of these methods is based on discounted cash flow calculation and does not avoid some errors. Based on valuation of IC in monetary units by identifying specific components or elements. Based on identification of various components of IC and attribution of specific indicators or indices intended to measure these components. The difference from the first type lies in the fact that this type does not seek evaluation in monetary units.

Studies (e.g. Ramanauskaite 2012) have shown that most methods are assigned to the ‘scorecard’ group, i.e. IC is valuated without employing monetary units but rather by attributing indices or indicators to its specific components. Yet both scorecard methods and direct IC methods are usually employed for the valuation of constituent parts of IC while ROA methods and MC methods are used for the valuation of IC as an entirety. The latter methods are also referred to as evaluation methods (Ramanauskaite 2012) since they enable to evaluate the whole of the IC of an enterprise in monetary units. This provides an opportunity of integrating them into financial accounting and thus supplementing financial statements with financial data of the IC of an enterprise. Table 2 (source: compiled by the authors according to Lev et al. 2003, Sitar et al. 2004, Andriessen 2004b, Muller 2004, Rodriguez‐Castellanos et al. 2007, Jurczak 2008, Kuzmina 2008, Sveiby 2010, Ramanauskaite

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Agne Ramanauskaite and Kristina Rudzioniene 2012, Salman et al. 2012) presents IC evaluation methods which are the most frequently outlined in academic papers and can possibly be integrated into financial accounting. Table 2: Core methods of IC evaluation ROA methods

No.

MC methods Market to book value/ Market to book ratio Market value added

Calculated intangible value

CIV

Economic value added The value explorer / Weightless wealth tool kit

EVA

MTBV / MTBR MVA

TVE / WWTK

Tobin’s q

KCE

FiMIAM

Financial method of intangible assets measurement

Knowledge capital earning

In order to assess which of these methods – ROA or MC – enable(s) to establish the most accurate value of the IC of an enterprise in monetary units, advantages and drawbacks of these method groups (as presented in academic writings Luthy 1996, Skyrme et al. 1998, Maree 2001, Andriessen 2002, Bontis 2002, Bouteiller 2002, Ratnatunga 2002, Rodov et al. 2002, Abeysekera 2003, Lev et al. 2003, Malhotra 2003, Andriessen 2004a, Andriessen 2004b, Bareisis 2004, Kannan et al. 2004, Seetharaman et al. 2004, Steenkamp 2004, Wall et al. 2004, Kasselman 2006, Ortiz 2006, Iswati et al. 2007, Pukeliene et al. 2007, Rodriguez‐Castellanos et al. 2007, Van den Berg 2007, Jurczak 2008, Ipate et al. 2009, Fragouli 2010, Sveiby 2010, et al.) are investigated, and on the grounds of their synthesis, the main principles of these method groups are listed.

3. Research results The analysis of various ROA methods indicated that the following criteria served as the calculation background: 1) profitability (e.g. profitability of the assets of an enterprise, profitability of the invested capital) or 2) calculations of the average profit of an enterprise in terms of past and forecast data which is applied for deriving the IC value. It is plausible that all these methods are based on the evaluation of one or several components presented in Figure 1 (source: own work) thus seeking to single out the profit or the rate of return created by the IC of an enterprise.

Figure 1: Components considered in ROA methods Having researched the fundamental ROA methods, three directions of their application can be singled out: (1) the average rate of return of an enterprise in comparison with the average rate of return of the industrial sector; the difference between the two levels of rates is equaled to the rate of return of the IC of an enterprise. However, the authors doubt whether this difference could reflect the whole profit created by the IC of the enterprise as a part of the average asset profitability of the industry is also reflected in IC profitability; hence this difference could be treated as competitive advantage which would be one of the elements of the relational capital and would be more appropriate to use for the return on all the assets of the enterprise rather than for the evaluation of the IC of the enterprise. Besides, the identification of average rate of return of the industrial sector is rather complicated if no commonly (regionally or nationally) applied system is available. Otherwise, (2), the average generated profit of the capital invested into the enterprise is compared with the net price of the invested capital; then, their difference is equaled to the profit generated by the IC of the enterprise. However, this difference should probably be related with the efficiency of the management of the enterprise and thus assess the return received by the shareholders which is not necessarily IC‐only generated profit. Besides, when calculating the rate of return of the invested capital, the valuator’s subjectivity is inevitable as in order to evaluate the economic profit of the enterprise, various financial accounting data corrections are required. As a result, the calculations of this indicator are complex, and the extensive list of possible variables makes it non‐standard and complicated to compare; besides, real life provides scarce and insufficient proof for this method. In the third scenario, (3) the average basic profit of the enterprise is

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Agne Ramanauskaite and Kristina Rudzioniene calculated on the grounds of former and forecast data of income and expenses which is compared with the profits generated by the tangible and financial capital of the enterprise by applying the benchmark rates of return which may undoubtedly differ depending on the industrial branch and various circumstances. In one of the options, after having calculated the return on IC rate or amount in monetary units, ROA methods offer three opportunities of establishing the IC value: (1) after deducting the average amount of profit tax payments, to apply WACC or consider the market interest rate to calculate the current value of the IC of an enterprise; (2) to forecast the profit of the IC of an enterprise for 10 to 15 years into the future and to calculate its current value by employing a selected discount rate; or (3) for the obtained IC‐generated profit of an enterprise, to apply the average expected return on IC after taxes rate which is calculated by employing correlations between return on assets and cash flow, traditional earnings or IC earnings and thus calculate the IC value of an enterprise. The analysis of the core MC methods demonstrated that in calculations based on these methods, the MV of the enterprise serves as the background by claiming that it is MV that reflects the real value of an enterprise and both the tangible and the intellectual capital it possesses. Yet this comparison should be highly criticized because 1) the MV of an enterprise is impacted by a number of factors which are not necessarily related with the tangible or intellectual capital of an enterprise or has no impact on it; 2) with the altering attitude of the participants of the market, the MV of an enterprise rises or falls every day; hence it is not reliable short‐term and cannot serve as a background; 3) if IC is only used to explain MV, then a question arises whether it can possess any value at all; in this case, if it does possess some value it must influence the MV of the enterprise. However, MV is highly precise, it is a value which can be easily established at any given moment being unaffected by the subjectivity of the valuator, forecast data or other factors of the valuation process; hence it is extremely reliable and should be employed in IC evaluation. The only task in this field is its proper application/ explanation. It should be highlighted that MV cannot be established for all enterprises, which restricts the scope of valuated enterprises. However, having considered the fact that investment decisions are usually taken by individuals participating in the share market, in order to satisfy their increasing need for information, the most adequate solution is namely the application of IC evaluation methods based on the MV of an enterprise. MC methods compare MV with 1) the book value of an enterprise; 2) the replacement cost of the assets of an enterprise or 3) the value of invested capital. The comparison of the MV of an enterprise with the book value of the enterprise is criticized because 1) its part may be represented as alterations of the value of tangible capital entities that are not reflected in financial statements; 2) it may reflect likely results of the growth of an enterprise and 3) the book value of an enterprise depends on national law acts and standards that are applied for the financial accounting of the enterprise where any asset employed in the activity is singled out and registered separately while MV covers an enterprise as a whole, as an indivisible object; hence, the difference between these values/ assets is incomparable from region to region. Yet, the likely results of the growth of an enterprise may be treated as constituent parts of IC as the required staff in a controlled system possessing external potential incites the growth of the enterprise while notable changes of the objects of tangible capital on the grounds of the current accounting standards and principles should be reflected in financial statements; at the same time, insignificant changes will likely not distort the valuation results. Besides, different accounting standards or principles applied in different regions are inseparable from the accounting standardization and globalization process; in the future, data presented in financial statements will be ever more comparable from region to region since statements will be produced by employing the same accounting principles. Besides, the application of traditional annual statements of an enterprise decreases the potential subjectivity due to the inclusion of other data into the process of valuation. The comparison of the MV of an enterprise with the replacement cost of its assets is criticized because practical application of this method is quite complicated as the calculation of the replacement cost (especially regarding some specific assets) is far more complicated than the establishment of a value when using the data of financial statements of an enterprise. The authors of the present paper agree that the calculation of the replacement cost will undoubtedly be affected by the subjectivity of the valuator and the risks of imprecision of the applied variables. Meanwhile, the comparison of the MV of an enterprise with the value of the invested capital is criticized by the authors of the present paper as IC cannot be equaled to the difference between the invested capital and the MV of an enterprise just because the profit from the invested capital may be invested

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Agne Ramanauskaite and Kristina Rudzioniene into the development of both tangible and intellectual capital; hence this difference will not necessarily reflect the growth of namely IC. The established difference between the enterprise market and book value when applying MC methods is divided into two parts (Figure 2; source: own work): 1) the realized IC of an enterprise; and 2) erosion of the IC of an enterprise.

Figure 2: Explanation of the difference between the market and book value of an enterprise Attention should be paid that the real IC of an enterprise diminishes with the accumulated erosion of IC and thus the realized IC of an enterprise is obtained. It should be noted that it is merely a hypothetic difference between the enterprise market and book value since not a single MC method provides an algorithm how to calculate the values of the indicated constituent parts.

4. Conclusion The authors generalize on the conducted synthesis of ROA methods and emphasize that these methods typically exhibit the subjectivity of a valuator as a part of the data employed in the process of valuation is forecast‐based. Besides, lack of use of average data is not eliminated. Furthermore, the rate of return of specific capital groups and their indirect calculations applicable in the process of valuation remain unclear. It is possible to claim that no variable in this calculation process is precise, and their establishment is inseparable from the factor of subjectivity thus depriving one of an opportunity of comparing the obtained results among themselves. In the generalization of the conducted synthesis of MC methods, the authors claim that the usage of MV in the process of valuation helps one avoid the valuator subjectivity‐related disadvantages; this value is precise and possible to establish at any given moment. It measures an enterprise as an entirety by covering both identifiable and unidentifiable objects of the capital as well as the liabilities of the enterprise. The comparison of this value with its book value simply and plainly reveals whether the enterprise possesses any capital which is not presented in its financial statements. One of the MC methods, FiMIAM, by applying the weights established within the enterprise, distributes them across the three IC components, i.e. the human, organizational and relational factors thus establishing their value in a monetary equivalent. This identification of the values of IC components is well‐grounded and logical just because of the fact that all the IC components and elements are interwoven as they are worthless separately; hence, the separation of their values is an extremely complex or even insurmountable challenge. In conclusion, the value of the IC of an organization in monetary units is more reliably defined by MC methods. Even though the main disadvantage of these methods is the use of the enterprise MV as the background yet subjectivity which is the principal drawback of ROA methods is thus avoided. Nevertheless, the application of MC methods is limited as they can only be employed for those enterprises whose MV may be reliably established.

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Agne Ramanauskaite and Kristina Rudzioniene Andriessen, D. (2004b) Making Sense of IC. Designing a Method for the Valuation of Intangibles, Elsevier, Inc., USA. Bareisis, V. (2004) „Intelektinio kapitalo ivertinimo modeliu apzvalga“, Lietuva ant ES slenksčio: nauji iššūkiai ekonomikai ir vadybai, septintoji respublikinė doktorantų ir magistrantų konferencija, pp. 5 – 10. Bontis, N. (2002) „Assessing Knowledge Assets: A Review of the Models Used to Measure IC“, International Journal of Management Reviews, vol. 3, pp. 41 – 60. Borneman, M.; Knapp, A.; Schneider, U.; Sixl, K.I. (1999) „Holistic Measurement of IC“, Paper read at International Symposium, Measuring and Reporting IC: Experience, Issues, and Prospects, Amsterdam, Finland, June. Bouteiller, C. (2002) „The Evaluation of Intangibles: Advocating for an Option Based Approach“, Paper read at VIth Alternative Perspectives on Finance Conference, Hamburg, Germany, August. Campos, E.B.; Ordonez de Pablos, P. 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(2006) „IC (Intangible Assets) Valuation Considering The Context“, Journal Of Business & Economics Research, Vol. 4, No. 9, pp. 35‐42. Palumickaite, J. (2008) Organizacijos intelektinio kapitalo vertinimo modelis, Summury of Doctoral dissertation, Kauno technologijos universitetas. Pukeliene, V.; Palumickaite, J.; Matuzeviciute, K. (2007) „Intelektinio kapitalo matavimas ir vertinimas: teorinis aspektas“, Taikomoji ekonomika: sisteminiai tyrimai, No.1/1, pp.103‐114. Pukenaite, L. (2005) „Finansinis intelektualaus kapitalo vertinimo metodas (FiIKVM)“, Smulkaus ir vidutinio verslo plėtros perspektyvos integracijos į Europos Sąjungą kontekste: mokslinės‐praktinės konferencijos pranešimų medžiaga, pp. 88‐91, ISSN 1648‐1717. Ramanauskaite, A. (2012) „Classification of IC Valuation Methods“, Paper read at Trends in Economics and Management for the 21st Century: International Conference, Brno, Czech, September. Ratnatunga, J. (2002) „The Valuation of Capabilities: A New Direction for Management Accounting Research“ [online], http://cmawebline.org/publication/jamar‐v1‐1‐editorial.pdf. Rodov, I.; Leliaert, P. (2002) „FiMIAM: financial method of intangible assets measurement“, Journal of IC „Measuring intellectual capitalism“, Vol. 3, Iss. 3, pp. 323 – 336. Rodriguez‐Castellanos, A.; Arregui‐Ayastuy, G.; Vallejo‐Alonso, B. (2007) „The Financial Valuation of Intangibles: A Method Grounded on an IC‐Based Taxonomy“. On: Joia, L.A. Strategies for information technology and IC: challenges and opportunities, Information Science Reference, Idea Group Inc., United Kingdom, pp. 66‐90. Salman, R.T.; Mahamad, T.B. (2012) „IC measurement tools“, International journal on social science economics & art, Vol. 2, No. 2, p. 19 – 26.

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Agne Ramanauskaite and Kristina Rudzioniene Seetharaman, A.; LockTengLow, Kevin; Saravanan, A. S. (2004) „Comparative justification on IC“, Journal of IC, Vol. 5, No. 4, pp. 522‐539. Sitar, A.S.; Vasic, V. (2004) „Measuring IC: Lessons Learned from a Practical Implementation“, Paper read at IC and Knowledge Management – Proceedings of the 5th International Conference of the Faculty of Management Koper, Portorož, Slovenia, November. Skyrme, D.J.; Amidon, D.M. (1998) „New Measures of Success“, Journal Of Business Strategy, Vol. 19, No. 1, pp. 20‐24. Steenkamp, N. (2004) „Investigating the possible value omitted in the balance sheet – a New Zealand perspective“, Paper read at The fourth Asia Pacific Interdisciplinary Research in Accounting Conference (APIRA), Singapore, June. Sveiby, K.E. (2010) „Methods for Measuring Intangible Assets“ [online], http://www.sveiby.com/articles/IntangibleMethods.htm. Tan, H.P.; Plowman, D.; Hancock, P. (2007) „IC and financial returns of companies“, Journal of IC, Vol. 8 No. 1, pp. 76‐95. Van den Berg, H.A. (2007) „Measurement Models in the IC Theory“. On: Joia, L.A. Strategies for information technology and IC: challenges and opportunities, Information Science Reference, Idea Group Inc., United Kingdom, pp. 49‐65. Vaskeliene, L. (2004) „Intelektualaus kapitalo vertinimo poreikio ir galimybių studija Lietuvos organizacijose“, Transformacijos Rytų ir Centrinėje Europoje: mokslo darbai, pp. 378–386. Vaskeliene, L. (2007a) „Development of organizational IC measurement methodology: problems and soplutions“, Ekonomika ir vadyba 2007 – Tarptautinės mokslinės konferencijos pranešimų medžiaga, pp.165‐173. Vaskeliene, L. (2007b) „Organizacijos intelektinio kapitalo vertinimo metodų dichotomijos raiška: teorinė studija ir empiriniai įrodymai“, Socialiniai tyrimai, No. 2(8), pp. 150‐159. Wall, A.; Kirk, R.; Martin, G. (2004) IC: Measuring the Immeasurable? CIMA Publishing, Elsevier Ltd., Burlington, Great Britain. Westnes, P. (2005) „What is IC? Defining and describing the concept“, Arbeidsnotat RF, No. 054. Znakovaite, A.; Pabedinskaite, A. (2010) „Intelektinio kapitalo valdymas transporto sektoriuje“, Mokslas – Lietuvos ateitis, No. 2 (2), pp. 126‐133.

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University Missions: Compatible and Complementary? Theory and Empirical Analysis Through Indicators Mabel Sánchez‐Barrioluengo INGENIO (CSIC‐UPV) Universitat Politècnica de València, Valencia, Spain msbarrioluengo@ingenio.upv.es Abstract: Over the last years HEIs acquired a new role in the promotion and support of regional economic development. As a consequence, and to facilitate this process, the modernization of universities ranks high in the European policy agenda. Part of this redefinition of universities roles is based on the “three mission” heuristic, namely that HEIs’ contribution to economic and social development is carried out by engaging (1) teaching (2) research (3) interaction with socio‐economic environment. The traditional view does not explain in detail if and how the three missions are related to one another, and that the growth of one is implicitly suggests the beneficial for the others. The present paper challenges this perspective and takes the view that university missions are constructs connected by complex relationships. In so doing, we make two contributions to the literature: first we explore the connection between the theoretical rationale of university missions, and second we assess the complementarity among missions. Our empirical study on Spanish public universities nd corroborates this hypothesis by finding complementarity between research (2 mission) and interaction with the socio‐ rd economic environment (3 mission), and substitutability between the former and teaching (1st mission). The paper calls for a critical reflection of university engagements with the missions: rethinking whether all higher education institutions should be simultaneously developing all three missions may be vital to ensuring their contribution to the socio‐economic development of regions. Keywords: university, teaching, research, third mission, complementarity, Spain

1. Introduction Higher Education Institutions (HEIs) have undergone structural and functional changes in recent years (Youtie and Shapira, 2008). These can be observed in the progressive transformation of the missions engaged by university from being traditionally based on teaching and research, to including a broad range of market‐ oriented and knowledge transfer activities. Accordingly these non‐strictly‐ economic contributions, also known as ‘third mission’, have increased expectations about university as a vehicle for the development of regional innovation systems (OECD, 2007) and placed the modernization of HEIs high in the European policy agenda (EC, 2006). But prior to said modernization, we argue, it is crucial to understand the nature of and the relations across HEIs´ functions. The present paper offers a broader perspective based on the idea that university missions are constructs connected by complex relationships of complementarity or substitutability. Building on this the paper also offers a critical reflection as on whether it the expectation that university engage all of them simultaneously is realistic. The integration of research and the third mission implicitly assumes compatibility, and even complementarity, across all missions (Geuna, 1999; Etzkowitz, 2004). Theoretical studies argue the need for a closer relationship among the missions (Ormerod, 1996) for a proper contribution of HEIs to the development of modern knowledge‐based societies and economies. However few studies test their relationship from an empirical point of view (Landry et al., 2010; Palomares‐Montero et al., 2012) and rather focus on the relationship between specific activities (which are treated as proxies) as a part of an overall mission and little attention has been paid to the tensions between properly missions. A major barrier to understanding missions is the connection between the theoretical rationale of university and the practical implementation of indicators for their measurement (Molas‐Gallart, 2002). Being HEIs complex organizations, indicators measure the multitude of activities which they engage. The study of university missions is mostly theoretical given that the concept of mission is rather abstract and difficult to measure. Empirical studies need indicators to measure the different activities that HEI engage in (Molas‐ Gallart, 2002). However the indicators in the literature contribute to a scattered and incoherent picture and a lack of consensus about their development (Bonaccorsi and Daraio, 2007) and use. Treating missions as a construct implies knowledge about which indicators are the most appropriate for their identification.

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Mabel Sánchez‐Barrioluengo This work elaborates an empirical study of Spanish HEIs. Spanish context is an interesting case study because the incorporation of the second and third missions was not a sequential procedure for universities. The paper addresses the following questions: Do missions cluster the set of activities developed by universities? Are university missions related? If so, what is the type of relationship that exists? Are indicators suited to their measurement? Which are the most appropriate indicators to explain them? This paper seeks to make two contributions to the literature. Firstly, it explores the connection between the theoretical rationale of university missions and the practical implementation of indicators for their measurement. Secondly, we assess the complementarity among the universities’ three missions by studying the relation among them.

2. Universities and their missions: An overview 2.1 The birth of the missions Similar to society, the role of the university has evolving over time (Youtie and Shapira, 2008). The medieval university focused on teaching. Beginning in the nineteenth century, HEIs took on a more active role exemplified by the formation of Berlin’s Humboldt University. The new university model attached importance to scientific research and the production of knowledge (Geuna, 1999). Teaching and research became the core of the ‘classical’ university at the time. Later, a set of exogenous events led to changes in the modus operandi of universities. The most relevant was the adoption of a new mission, seen as complementary to the traditional missions of teaching and research and aimed at increasing the contribution of universities to the socioeconomic development of their environment (OECD, 2007). According to Molas‐Gallart et al. (2002, p.2) the ‘third mission’ is defined as “the generation, use, application and exploitation of knowledge and other university capabilities outside academic environments”, i.e., the interactions between universities and their socioeconomic environment (ISEE). These three missions are now considered to be inseparable and are carried out in an interconnected way by HEIs. Then the first hypothesis: Hypothesis 1: Universities’ activities cluster in three missions: teaching, research and the ‘third mission’.

2.2 University missions and their controversial relationship The addition of academic research as a core university mission entailed acceptance of compatibility and even complementarity with traditional teaching (Geuna, 1999). However some authors show that this relationship was far from obvious. Some propose a positive relation between teaching and research (Colbeck, 1998), others show a negative relationship (Barnett, 1992) and some deny any relation (Marsh and Hattie, 2002). Theoretical arguments reinforce the negative relation. Sample (1972) argues that specialization is one of the reasons for this link: research is highly specialized whereas teaching has to be broad. When the third mission emerged the literature focused on analysis of its relation with research activities, and the complex relations with the private sector became especially relevant: dissemination of knowledge and autonomy (Nelson, 2004) versus financial interest (Noble, 1977) or short‐long term. However, just as teaching and research have become integrated, it seemed logical that the third mission should be similarly incorporated (Etzkowitz, 2004). The debate on the effect of ISEE in scientific production remains open. It has been argued that engagement in university‐industry relations produces high quality research output (Etzkowitz and Leydesdorff, 2000) because these activities have complementary effects. Study of the relationship between the first and the third missions is scarce and the literature provides no clear evidence on it. Ormerod (1996) argues from a theoretical point of view that there is strong complementarity among research, teaching and consultancy. However Landry (2010) finds that, in practice, there is a substitution effect between teaching and publications, complementarity between the latter and ISEE, and absence of a relation between the activities of the first and third missions. We formulate a set of sub‐hypotheses to identify the relationship among the university missions:

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Mabel Sánchez‐Barrioluengo Hypothesis 2a: Teaching is negatively related to (substitute for) research. Hypothesis 2b: Research is positively related (complementary) to the third mission. Hypothesis 2c: There is no relation between the first and third missions (independents).

2.3 Indicators as measurement of the missions The study of university ‘mission’ is mostly theoretical given that this concept is rather abstract and difficult to measure. This is an inherent difficulty in trying to achieve a consensus to develop and use indicators for their measurement (Bonaccorsi and Daraio, 2007). One of the most important byproducts of universities is human capital (Duch and García‐Estévez, 2011) and graduates are one of the principle mechanisms facilitating knowledge spillovers from universities (Audretsch et al., 2005). For this reason number of enrolled students and graduates are often used as indicators of education production (Daraio et al., 2011). Financial resources notably influence the activities of universities (Landry et al., 2010). According to him funding relies on three sources: teaching revenues (part of internal university resources), funding from university research, and funding from industry. Hypothesis 4a: The first mission is a construct that is determined by three indicators: enrolled students, graduates and teaching revenues. Some authors consider that both undergraduate and postgraduate students are associated with teaching activities (Beasley, 1995). However within the Spanish context the postgraduate phase, which is characterized by masters and doctoral students, and production of theses, is related mainly with the second mission (Palomares‐Montero et al., 2012). The most widely used indicator to quantify research performance is number of publications (Giese, 1990). Although publications in journals included in the Institute for Scientific Information (ISI) is a frequently used measure, some authors consider that a broader range of publications and indicators is needed for the social science and humanities fields (Nederhof, 2006). For this reason, the inclusion of articles published in scholarly journals, or distinguishing the internationality of the journal is necessary. As suggested above, research funding is an important aspect in the characterization of second mission activities. In this case, financial resources have a public and competitive character and are studied generally in terms of number of research projects financed by competitive public grants or the income derived from them (Bozeman and Gaughan, 2007). Hypothesis 4b: The second mission is a construct that is determined by several indicators: postgraduate students (masters and PhD), number of theses, number of research projects, research project income, and publications (in Spanish, foreign and ISI journals). A specific case of research projects are those in which non‐academic agents, specifically firms, collaborate. Molas‐Gallart (2002) considers non‐academic research collaborations as activities related to both the second and third missions. Patents also present duality because they are often treated as a natural research output (Etzkowitz, 1998), related to the university’s second mission, but sometimes are considered a scientific finding to be commercially exploited (Meyer‐Krahmer and Schmoch, 1998), related to the third mission. This latter view is related closely to royalties, the mechanism occasionally used to measure university‐industry interaction (Thursby and Thursby, 2002). But third mission activities encompass other mechanisms (D'Este and Patel, 2007): consultancy activities (Link et al., 2007); contracts and research and development (R&D) projects (Bozeman and Gaughan, 2007) and spin‐offs (Landry et al., 2007). Income from these activities reverts to the universities as contract research revenue and is also used to measure the third mission (Molas‐Gallart and Castro‐Martínez, 2007). Certain activities related to teaching are also linked to the third mission if non‐ academic agents participate. This is the case of training activities; under‐graduate students work in companies (Molas‐Gallart, 2002). But analysis of this as a third mission activity has been rather ignored. Hypothesis 4c: The third mission is a construct involving several indicators: training students, applied and granted patents, collaboration on academic research, contract research income, number and revenues of R&D contracts and consultancies, royalties and spin‐offs.

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3. Empirical analysis 3.1 Spanish context According to Larédo (2007) a country’s institutional framework is particularly important in the evolution of the university’s missions. This study is based on the Spanish context, which is a particular case in the incorporation of missions into the universities. In countries such as Germany, France and the United States, research and ISEE were incorporated into the university missions as a sequential procedure. However, in Spain, the introduction of the second and third missions was not a gradual process. The 1983 Reform of Higher Education promoted research in the universities and introduced incentives for conducting contract R&D with socioeconomic agents. The Spanish science and technology policy was based on the injection of funds which had a significant impact on the outputs of universities. The abrupt appearance of research and ISEE as part of the university’s missions did not question the potential impact on teaching. Their introduction ex alto implicitly assumed a positive relation between research and ISEE, which reinforces the complementarity hypothesis. The Spanish higher education sector includes 73 universities. 48 are public institutions and 25 are private. Universities are some of the most important agents in the Spanish R&D system with 26.8% of total R&D expenditure, accounting for 47.1% of employment of full time researchers in 2008. But the majority of this contribution is due to public universities, which represent a quarter of total R&D expenditures and almost half of the researchers in Spain (INE, 2008b). The importance of these institutions in the Spanish research system places them at the center of this work. Excluding the National Distance Education University, our study population is composed of the remaining 47 HEIs.

3.2 Sources and variables Table 1 presents the indicators used and their definitions. The third column of the table includes the sources. Data are for 2007 and 2008 and we use the cumulative value of the indicator measures for each university. The typology of the region in which the university is located can positively influence size and the indicators related to students. To avoid biased results and to control for university size, the indicators for students (enrolled and graduates) and teaching revenues are divided by the number of researchers. Table 1: Definition of the variables and descriptive statistics

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3.3 Analysis We ran an Exploratory Factor Analysis (EFA) to cluster activities that distinguish among university missions and subsequently we conducted a Confirmatory Factor Analysis (CFA) based on Structural Equation Modeling, to test the complementarity among missions and the validity of the indicators proposed to measure them. EFA identifies the minimum number of dimensions used to explain the maximum amount of information (Hair et al., 1998) and involves principal components analysis (Varimax rotation; Kaiser normalization). The theoretical model for the CFA is presented in Figure 2. The advantage of this methodology lies in the possibility of measurement abstract concepts (constructs) and the indication conceding a possible relation. Following Olsson et al. (2000), we use Generalized Least Squares (GLS) to test our model with few observations. EFA is not too restrictive with respect to the variable assumptions (Hair et al., 1998) but the results can be affected by different units of measurement (Salvador‐Figueras and Gargallo‐Valero, 2006). On the other hand, CFA requires normal and independent variables (Ullman, 2000). Due to differences in the nature of our variables (Table 1) and to avoid problems in our results we used typified variables. We also applied data imputation techniques to replace missing values (the Expectation Maximization algorithm) in order to take account of the information from all universities.

4. Results and discussion Table 2 presents descriptive statistics. Spanish public universities, on average, had 38 enrolled students and 5.3 graduates per researcher in the two‐years 2007 and 2008. The revenue from teaching activities was €17,000. Postgraduate students numbered 4,000 on average, with more than 60% PhD students and 40% masters. The average number of theses was 146. The funds for research come from the National Plan and universities obtained 70 research projects and €20 million on average. When firms participate in research, university research income reduces to a quarter. In terms of publications, HEIs published over half in foreign and ISI journals and the remainder in Spanish journals. Spanish universities had less than 20 patent applications and less than 10 patents granted every year. Revenue from commercialization activities (royalties) reached just over €85,000 per university. Contract research income was €11 million and R&D contracts €18 million on average (total contracts, not per year). In 2007 and 2008 Spanish universities created 220 new spin‐ offs. EFA identified three components explaining the 22 indicators; which correspond to the three university missions of teaching (third component), research (second component) and the third mission (first component). Since we know that the activities of the universities are partly represented, we can explain 63.7% of the total variability. Figure 1 shows the factor loadings in the rotated matrix according to the positioning of the indicators for each of the three factors. The CFA model and the parameter estimates are depicted in Figure 2. Goodness of fit is determined mainly by the chi‐squared statistic. A non‐significant result implies adequacy of the final model. To complement it we use three incremental fit indices ‐NNFI, CFI and RMSEA‐ because they are likely to reject correct models when the number of observations is small (Hu and Bentler, 1999). Despite this limitation, we observe that the values for the first two indices are above 0.95, and are below 0.05 for the last one, which indicates good model fit. The correlation among latent variables captures the relationship among missions and provides the most striking finding in the study. All coefficients are significant. There is a positive relationship between the second and third missions but it is negative between these two missions and teaching. That is, there is a relationship between all the university’s missions so that research and ISEE are complementary but show a substitution effect with teaching. Figure 2 shows the factor loadings (standardized solution) from the CFA. Their significance indicates the validity of the indicators for explaining each construct. The chi‐squared statistics, obtained for the standardized solution in each structural equation, capture the importance of the indicator for explaining mission variability.

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Figure 1: Results of the exploratory factor analysis The indicators related to undergraduate students and teaching revenues in the first mission are valid to explain this construct. In this case, the number of enrolled students per researcher explains the highest percentage of variability (99.7%). Although apparently postgraduate students are part of a student’s education stages, these indicators are more relevant to the second mission in the case of the Spanish public universities. This means that masters and PhD students (in public universities) have a greater research than professional component.

Figure 2: Structural equations modeling for the confirmatory factor analysis

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Mabel Sánchez‐Barrioluengo Publications in foreign and ISI journals have the highest explanatory power for research (89.7% and 87.1% respectively). Patent applications refer to both the second and third missions (although the scores lie more on the side of the latter). However, granted patents are only significantly related to the third mission. These results categorize them as a scientific finding to be commercially exploited, in accordance with Meyer‐Krahmer and Schmoch (1998). Granted patents also show a negative sign, but no significant, in relation to the second mission, meaning that they are not related to the indicators measuring research. This result can be explained by the ‘secrecy problem’ (Florida and Cohen, 1999) which refers to the tighter restrictions on the publication of research findings. Publications allow researchers disseminate the knowledge while patents protect research outputs and the results are not accessible for the wider society. On the other hand, while research project income may explain the second mission, collaborative projects with firms show a negative and significant relationship with research and a positive and significant with ISEE. The ‘skewing problem’ (Florida and Cohen, 1999) explains this result. Skewing refers to the alleged shift in research efforts from basic to applied research. In this case, while universities develop research as an end in itself leading to more basic projects, firms are more worried about its application and their financial rewards (Noble, 1977). The majority of indicators for the third mission are mostly statistically significant. The variability explained by contract research income is 99.1%, while by granted patents is 92%. The indicator for training students is not significant for either mission.

5. Conclusions Each university is the result of different processes of social, economic and cultural development. In the modern knowledge societies, universities contribute to economic development though fulfillment of these three missions (OECD, 2007) and it is commonly accepted that they are key repositoires of new knowledge and human capital. However the complementarity among missions was taken as given when the second and the third missions were introduced in HEIs. This paper claims the attention over potentially unrealistic expectations over the capacity of universities to fulfill all these roles at the same time. The present study on Spanish public universities provides an overview of the impact of all three missions. Our results suggest that greater efforts on research or ISEE activities are mutually beneficial but are detrimental to teaching. This strengthens the necessity to focus on single missions to achieve quality and excellence. This is the model that has been proposed by both academics and policy makers who believe that each university should develop a specialized focus on only one mission (Geuna, 1999; EC, 2005). Different models of a modern university are possible because HEIs are out of date and urgently need modernizing if they want to play their part in Europe’s drive for more growth (EC, 2006; David and Metcalfe, 2007). Rethinking whether all HEIs should be simultaneously developing all three missions may be vital to ensuring their contribution to the socio‐ economic development of regions. The Spanish model of the university‐ISEE relationship rests on contracts (mostly R&D contracts), which contrasts with the American model which is based on patents (AUTM, 2010). Although the experience in the US shows that too much emphasis by HEIs on acquiring and exploiting intellectual property rights can hamper knowledge‐sharing and collaborative research with the business sector (David and Metcalfe, 2007), Spanish evaluation system continues to attach great importance to patenting and licensing activities and patents granted pursue economic exploitation as per the proposal in Meyer‐Krahmer and Schmoch (1998). Narrow policy emphasis on other linkages may obscure not only the presence of other types of university‐industry interactions that are less visible but are equally and even more important (D'Este and Patel, 2007). Human capital creation is one of the most important activities developed by universities because graduates are one of the principle mechanisms facilitating knowledge spillovers and the principal connection between firms and universities. Training students are a mechanism to link universities and firms, but in the Spanish context this activity is not developed in an appropriate way by the universities, because this indicator is not suitable for the measurement of any missions. This means damage for the industry because do not only have less access to knowledge of recent scientific research but also do not receive enough abilities to solve complex problems, perform research and develop ideas (Salter and Martin, 2001). While it is true that finding a balance between the objectives of the academic and business worlds is not easy, it is necessary for universities’ activities to be successful. In fact the collaboration between firms and universities benefits both: enterprises improve the probability of innovative outcomes and HEIs seemingly have a more significant impact than any

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Mabel Sánchez‐Barrioluengo other type of collaborative partner. The equilibrium should involve: developing an understanding of industrial practice and providing an education that equips students with more generic and long‐lasting skills (Salter and Martin, 2001); open dissemination of scientific knowledge for the advancement of science and tighter restrictions on the publication (Tartari et al., 2012); and autonomy to establish researchers agendas and application and firms' financial rewards (Noble, 1977). Future research should integrate a functional dimension to check the effect of these results on externalities in the region in order to test if the detrimental effect of teaching is indirectly decreasing the impact of HEIs on the expected economic growth.

Acknowledgements This work was supported by the Ministry of Education, Culture and Sports of Spain which funded the author’s PhD fellowship through the F.P.U. program.

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A Conceptualization Linking Intellectual Capital, Dynamic Capabilities and Performance of Knowledge‐Intensive Service Firms Corentin Vermeulen Centre de Recherche Public Henri Tudor, Luxembourg, Grand‐Duchy of Luxembourg corentin.vermeulen@tudor.lu Abstract: The purpose of this paper is to develop a conceptual model hypothesizing mechanisms by which intellectual capital of knowledge‐intensive service firms contributes to their performance. In order to extent the current understanding, this paper anchors in the resource‐based view with a dynamic capability approach. This innovative theoretical lens is appropriate for knowledge‐intensive service firms since it recognizes their ability to integrate and reconfigure intellectual capital to address their rapidly changing environment. Accordingly, this paper considers the mediating role of radical and incremental innovation capabilities in the relationships between intellectual capital and performance. The moderating role of incremental and marketing capabilities is also considered under particular circumstances. This paper contributes to the current literature by identifying relevant dynamic capabilities of knowledge‐ intensive service firms but also by considering their moderating role, under particular circumstances. From a managerial perspective, this paper contributes to understand how these firms could improve and sustain their performance. Keywords: intellectual capital, dynamic capabilities, performance, knowledge‐intensive service firms, conceptual model

1. Introduction The intellectual capital (hereafter IC) is recognized as an important driver of performance (Bontis et al., 1998, 2000, and 2009; Youndt et al., 2004), especially for knowledge‐intensive service firms (Kianto et al. 2010). Nevertheless, the underlying mechanisms remain under‐researched (Hsu et al., 2012a). The concept of dynamic capability (hereafter DC), which refers to the firms’ ability to reconfigure and transform resources in order to address rapidly changing environments, provides useful solution to explore this mechanisms. Building upon this concept, some pioneers (Hsu et al., 2012a &b) found evidence supporting the mediating role of DC between in the relationships between IC components and the performance of high‐tech and listed Taiwanese companies, thereby suggesting that IC should be considered with a dynamic perspective. Nevertheless, as they explained, there is no evidence that their results may be generalized to all industries. Moreover, they considered the R&D among the DC, which is not necessarily appropriate to all industries. Since the knowledge‐ intensive service firms compete in highly changing environments (Kianto et al., 2010), it makes relevant to explore the existence and the role of inherent dynamic capabilities in the mechanisms by which IC contributes to their performance. However, to the best of my knowledge, no literature has already addressed this research area. To bridge the gap, this paper proposes the underlying research question: Do and, if any, how the IC components of knowledge‐intensive service firms interact with dynamic capabilities to contribute to their performance? This paper aims to contribute in answering this research question. Building upon prior literature it first defines the concept of IC and DC and further highlights overlaps and complementarities between these concepts. In a second part, building upon the Resource‐Based View (hereafter RBV) theory, this paper proposes a conceptual model hypothesizing different mechanisms by which IC contributes to the performance of service firms. Among the hypothesized relationships, the mediating and moderating roles of DC are considered.

2. Defining and positioning the concepts 2.1 Intellectual capital By considering the conceptualization proposed by Meritum (2002), IC refers to all kind of assets without physical substance which are either formally owned and used or informally deployed and mobilized. IC is widely recognized as a multidimensional construct (Youndt et al., 2004) encompassing the Human Capital (hereafter HC), Structural Capital (hereafter SC) and Relational Capital (hereafter RC) while being more than the sum of these capitals (Meritum, 2002).

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Corentin Vermeulen The concept of HC has been introduced by Schultz (1961) and Becker (1962) and conceived as the resources embedded in people. It relates to the body of knowledge, skills, know‐how, expertise and education rooted in employees (Becker, 1962). The concept of SC is embedded with the firm and defined as the combination of knowledge that stays within the company when the employees go home (Edvinson and Malone, 1997; Meritum, 2002). It encompasses everything that supports the employees’ productivity (Bontis, 2001). More concretely, it refers to the institutionalized knowledge and codified experience embedded within databases, information systems, processes, patents, manuals and structures (Youndt et al., 2004). The concept of RC is rooted within the concept of social capital as conceived by the sociologists (Burt, 1992; Coleman, 1988) and organization theorists (Nahapiet and Ghoshal, 1998). The MERITUM Project (2002) defined RC as “all resources linked to the external relationships of the firm, with customers, suppliers or R&D partners. It comprises that part of Human and Structural Capital involved with the company’s relations with stakeholders (investors, creditors, customers, suppliers, etc.), plus the perceptions that they hold about the company.”

2.2 Dynamic capabilities In the roots of the RBV, Penrose (1959) emphasized that the value creation comes from the use rather than the possession of resources and that how much the value is created depends from the way firms deployed their resources. Nevertheless, the following literature, mainly Barney (1991), formalized the RBV with a much more static approach (Priem and Butler, 2001). More precisely, the process by which strategic resources provide a company with a competitive advantage remained a black‐box (Priem and Butler, 2001; Williamson, 1999). Later on, some pointed out the inadequacy of the RBV to explain how and why firms achieved competitive advantage in situations of rapid and unpredictable change (Eisenhardt et al., 2000; Teece et al., 1997). In the light of a need to expand the RBV paradigm, Teece et al. (1997) and Eisenhardt et al. (2000) introduced the concept of DC as “the firm’s ability to integrate, build and reconfigure internal and external competences to address rapidly changing environments” (Teece et al., 1997: p.516). Both the RBV and the DC approach share the same assumptions. Firstly, they assume that resources are path‐dependent and heterogeneously distributed across firms. Secondly, both the RBV and DC consider the way resources of firms contribute in achieving their competitive advantage (Lockett and Thompson, 2001). Therefore, DC is currently considered as a way to reinforce the dynamic perspective of the initial RBV, thereby coming as a complement to the initial RBV theory (Ambrosini and Bowman, 2009; Newbert, 2005). The firm’s competitive advantage and performance do not just come from its assets structure and underlying degree of imitability but are also explained by its ability to reconfigure and transform them in order to address rapidly changing environments. DC reside in organizational processes shaped by the firms' positions, learning paths and technological opportunities. They aim to renew or reconfigure the bundle of resources in such a way firms can sustain or enhance its competitive position in a changing environment. (Teece et al., 1997; Eisenhardt et al., 2000) DC have singular characteristics. They are paths dependents and embedded in the firm (Eisenhardt et al., 2000; Teece et al., 1997). Consequently, they cannot be bought and firms need to build them (Makadok, 2001). Moreover, DC refer to organisational processes that are used intentionally and deliberately. They are concerned with intentional strategic changes, not with those resulting from non‐deliberated actions, ad hoc problem solving interventions or luck (Ambrosinin and Bowman, 2009).

2.3 Overlaps and complementarities Exploring the dynamic attribute of IC sheds light on both static and dynamic intangibles, namely the intangible resources and the intangible activities (Meritum, 2002). Building upon this distinction allows highlighting overlaps but also complementarities between IC and DC. They are discussed below and schematically represented in Figure 1. Intangible resources are static. In that sense, they refer to resources as conceived by the RBV. Those which encompass simple resources or ordinary capabilities by which resources are used (Amit and Shoemaker, 1993)

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Corentin Vermeulen and remain “stable” if no event or action is taken to alter them (Ambronsini and Bowman, 2009. In contrast, DC are not capabilities in the sense of the RBV, they are not ordinary capabilities (Ambronsini and Bowman, 2009). DC are capabilities devoted to refreshing the resource‐based of the firm, including ordinary capabilities, with the aim to continually achieve and secure a competitive position for the firm (Ambronsini and Bowman, 2009). In changing environments, DC could be deployed to reconfigure or refreshed the intangible resources of the firm. Moreover, this is supported by the fact that intangibles are highly mutable (Dzinkowski, 2000). Therefore, in the lens of the RBV, both IC as intangible resources and DC are two different but complementary concepts that could be considered to explore the mechanisms by which firms achieve (or not) competitive advantages and performance in changing environments. According to Meritum (2002), intangible activities are concerned about acquiring and developing new intangible resources, sustaining and improving existing intangibles resources while measuring and monitoring them. Intangible activities are therefore dynamic and “may give rise to new intangibles resources or improve the value of the existing ones” (Meritum, 2002, p. 14). In parallel, building upon the work of Teece et al. (1997), Bowman and Ambrosini (2003) explained DC may be differentiated between “generic” organisational processes that reconfigure, leverage, create and shed resources. Intangibles activities roughly refer to some of these organizational processes, suggesting overlaps between IC and DC concepts, at least partially.

Figure 1: Convergences and divergences between IC and DC

3. Theoretical foundation: Resource‐based view with a dynamic capability approach In order to propose a model hypothesizing different mechanisms by which IC contributes to the performance of service firms, this paper anchors in the theoretical foundation of the RBV but will consider the DC approach as a reference. A great proportion of empirical studies have relied on the early theoretical incarnation of RBV, as provided by Barney (1991), in order to define the RBV and develop hypothesis (Newbert, 2007). However, the empirical literature supporting the RBV provides evidence that capabilities and core competences contribute significantly to the firm’s competitive advantage and/or performance while resources do not (Newbert, 2007). Possessing VRIN resources is important but not sufficient to achieve competitive advantages. Academics have highlighted the importance to process them in such a way their full potential is realized (Mahoney and Pandain, 1992; Peteraf, 1993), further encouraging the reinforcement of dynamic perspectives within the theoretical foundation of RBV (Barney and Mackey, 2005; Teece et al., 2007). The DC approach consists in testing the relationships between the firm’s competitive advantage or performance and the interactions between specific resources and capabilities.

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Corentin Vermeulen Since DC are considered to explore the mechanisms by which IC contribute to the performance of service firms, overlaps between the two concepts should be avoid. To anchor in the RBV with a DC approach and build upon the complementarities between IC and DC, the proposed model will further consider:

IC as intangible resources. In the light of potential overlaps between DC and intangible activities (see above), only the intangibles resources will be considered when referring to IC. By referring to intangible resources, IC encompasses a stock of intangible resources and ordinary capabilities that are highly mutable but stable if no action are taken to alter them.

DC as continuous organizational processes which activate the bulk of intangibles resources to be in line with the changing environment. They do not refer to the ordinary capabilities in the RBV sense but rather to capabilities concerned by impacting and reshaping the intangible resources of firms to secure their competitive position in a changing environment.

While early empirical studies using the DC approach only provided low level of support in exploring the firm’s performance (Newbert, 2007), several elements allow justifying the use of such a theoretical approach in this paper. Firstly, in contrast to other RBV approaches, this theoretical approach allows emphasizing the process by which intangible resources are deployed and the mechanisms by which they interact with capabilities to achieve competitive advantages. The DC theoretical approach is therefore in line with the growing importance in the RBV theory to consider the processes by which resources are exploited (Mahoney and Pandain, 1992; Peteraf, 1993). Secondly, since resources are empirically found to be unrelated to competitive advantage, Newbert (2007) argued that one possible reason for this poor support is the elimination of the strong relationship between capabilities and performance when capabilities interact with resources. Nevertheless, pervious empirical researches have demonstrated positive, direct and indirect relationships between intellectual resources, and performance (Bontis et al, 2000, 2009; Mention and Bontis, forthcoming). Therefore, given these empirical supports, it may be expected that the suggestion of Newbert (2007) will not apply in the context of intangible resources. Thirdly, being introduced in the late 90s (Eisenhardt et al., 2000 and Teece et al. 1997), the empirical support of the DC theoretical approach is still in its infancy. Until 2007, very few researches used the DC approach, preventing to draw definitive conclusions on its irrelevance. Moreover, recent empirical researches followed and supported hypothesis using this theoretical approach, notably in the context of IC resources and the firm’s performance (Hsu et al., 2012a & b). Altogether, the adequacy of the DC approach to open the process‐related black‐box of the RBV, the need to perform further empirical tests to support and understand the DC theoretical approach, the positive relationships between IC and performance and the recent empirical evidence supporting the DC approach to explain the mechanisms by which IC contributes to the firm’s performance are strong arguments to offset the early poor support for this approach and to foster its consideration in this paper.

4. The mechanisms by which IC contributes to the performance: A model proposition 4.1 Conceptualizing IC by using a component‐level approach IC is more than the sum of its components (Robert, 1999 in Meritum, 2002). IC is a multi‐components construct and its components cannot be considered individually. In order to contribute in opening this black‐ box at the level of service firms, this paper will conceptualize IC by using a IC component‐level approach. It appears the most appropriate approach since it allows expecting and identifying different relationships in the mechanisms by which IC contributes to the performance of service companies. In contrast, conceptualizing IC with holistic approach allow considering but not identifying all of these interactions or fully exploring the mechanisms by which IC components contributes to the firm’s performance. Past studies provided evidence that IC components interact with each other in the value creation process (Bontis et al., 1998, 2000, and 2009, Sharabati et al., 2010). Nevertheless, these inter‐relationships may differ according to the industry of consideration. On overall, these studies suggest that firms have to find and encourage the right connectivity between the IC components with regard to the specificity of their industry. The more firms emphasise on the right connectivity between IC components the more they are expected to perform. Although several studies have already investigated the inter‐relationships among IC components of service firms, they will be hypothesized in the proposed model. The relevance of their consideration is twofold. Firstly,

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Corentin Vermeulen in order to provide a complete picture of the mechanism by which IC contributes to the performance of service firms, the inter‐relationships among IC components should be considered. Secondly, Bontis et al. have mainly tested a generic mechanism in many ways on different industries (Mouritsen, 2006). Conversely, this paper aims to propose and test a mechanism which is purposely adapted to service firms with regards to their specificities. By doing so, this paper will contribute to the current literature by revisiting a generic mechanism according to the service firm’s specificities. For these two reasons, the present paper will consider how IC components of service firms coexist between each other and how they contribute to the performance of service firms. The hypotheses underlying the proposed model are discussed in the sections below and represented in Figure 2.

4.2 Relationships among IC components and their influence to performance Service firms heavily rely on HC since delivering services heavily depends on the human value added (OECD, 2000). While the HC is often considered as the most important IC component, Kianto et al. (2010) argued, in line with empirical findings of Bontis et al., (2000), it is even more crucial for service firms since the production of services is personnel‐intensive and tend to demand multi‐faced and complex knowledge to a greater extent. Therefore, a positive relationship between HC and performance of service firms may be expected and tested through the following hypothesis: H1: The human capital positively influences the performance of service firms Technologies and databases are growing in importance in the production and supply of services. Kianto et al. (2010) argued that the impossibility to storage services is leading service firms to rely on ICT systems. For some service firms, ICT systems as well as processes and routines are also deployed with a codification purpose. It allows mitigating some operational risks and/or to achieve economies of scale when delivering high‐volume services. In light of these elements, a positive relationship between SC and the performance of service firms may be expected and tested through the following hypothesis: H2: The structural capital positively influences the performance of service firms Employees heavily contribute to implement and improve the ICT systems and processes of their firms. Moreover an appropriate and an efficient use of ICT systems, processes and databases also rely on the employees’ expertise. A positive relationship between HC and SC may therefore be expected and hypothesized as follow: H3: The human capital positively influences the structural capital of service firms As compared to product‐oriented companies, the service firms need to be in closer relationships with their clients and to customize their service offerings in a greater extent (Tether et al., 2008; Hurmelinna‐Laukkanen et al., 2010). Consequently, the RC is also an important source of performance for services firms, even more than for product‐oriented companies (Kianto et al., 2010). The importance of RC for the performance of service firms leads to the following hypothesis: H4: The relational capital positively influences the performance of service firms The HC of service firms may have an influence on their RC. Some have argued the employees of service firms have an important impact on the perceived value of clients (Namasivayam et al., 2006). It may be easily assumed the behaviour of employees helps service firms to set up trustworthy relationships with their clients. Moreover, their knowledge, skills and competences help service firms to understand, anticipate and meet the clients’ needs which, in turn, help to create strong and privileged business relationships. In light of these elements, a positive relationship between HC and RC may be expected and hypothesized as follow: H5: The human capital positively influences the relational capital of service firms

4.3 The relationships between intellectual capital, dynamic capabilities and performance Service firms face changing customer demands in such a way they need to learn and develop new services in faster cycles, more unexpectedly and in smaller fractions (Kianto et al., 2010). By taking the theoretical lens of the RBV with a dynamic perspective, it may be expected that service firms deploy DC in order to maintain a

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Corentin Vermeulen competitive edge in their highly changing environment. By considering the way IC contributes to the performance of service firms, it may be conceived (as discussed above), that DC are deployed in order to refresh, reconfigure and secure their intangibles resources which, in turn, affect their performance. A mediating variable explain why and how a relationship between two other variables occurs. A variable is said to mediate a relation between two other variables when it accounts for this relationship (Baron and Kenny, 1986). As a mechanism by which intangible resources are refreshed to contribute to the performance, DC may be expected to mediate the relationships between IC components and performance of service firms. While the mediating role of DC is significant for industrial high‐tech firms when R&D and marketing capabilities are considered (Hsu et al., 2012a), there is no evidence for service firms. Moreover, R&D capabilities are not relevant for service firms. According to the conception of DC in this paper, the incremental and radical innovation capabilities are relevant to operationalize DC as mechanisms mediating the contribution of IC to the performance of service firms. Different IC components and various interrelationships between them influence the incremental and radical innovation capabilities of organizations (Subramaniam and Youndt, 2005). From that perspective IC may be expected to be an antecedent of innovation capabilities of service firms. From another perspective, innovation capabilities may be conceived as an organizational process that activates the intangible resources of service firms. More precisely, DC, as innovation capabilities, may be considered as a generative mechanism through which IC is refreshed to further contribute to the performance of service firms. This leads to expect that the contribution of IC to the performance of service firms is, at least, partially mediated by DC. Building upon H1, H2 and H4, the mediating role of DC will be tested with the following hypotheses: H6: The human capital positively influences the dynamic capabilities of service firms H7: The structural capital positively influences the dynamic capabilities of service firms H8: The relational capital positively influences the dynamic capabilities of service firms H9: The dynamic capabilities positively influence the performance of service firms

Figure 2: Final model In case DC don’t or partially mediate the relationships between IC components and performance of service firms, the moderating role of DC may be explored on the direct relationships between IC components and performance. A variable is said to moderate a relationship between two others when it affects the impact of this relationship (Baron and Kenny, 1986). Their incremental innovation capability, as a way to refine and reinforce the current services, may also influence the impact of the direct relationships between IC components of service firms and their performance. In addition, their marketing capability may also be

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Corentin Vermeulen conceived as a DC moderating the relationship between IC components and performance. The rationale is that the marketing capability, as a way to understand the market’s need and to orient services in such a way the clients’ needs are appropriately satisfied, allow service firms to reorganize their intangible resource‐based in such a way it continuously provides competitive services. The moderating role of DC on the direct relationships between IC components of service firms and their performance will be tested under the following hypotheses: H10: The dynamic capabilities enhance the positive influence of human capital on the performance of service firms H11: The dynamic capabilities enhance the positive influence of structural capital on the performance of service firms H12: The dynamic capabilities enhance the positive influence of relational capital on the performance of service firms

5. Conclusion, contributions and further researches By taking the theoretical lens of the RBV, with a dynamic perspective, this paper proposes a model hypothesizing different mechanisms by which IC of knowledge‐intensive service firms contributes to their performance. By relying on survey data obtained from executive managers of Belgian and Luxembourg knowledge‐intensive service firms, the results are expected to suggest that HC positively influences both SC and RC which in turn contribute to performance. The contribution of SC and RC towards performance are expected to be mediated by the incremental and radical innovation capabilities and moderated by the marketing capability and, under particular circumstances, by the incremental innovation capability. The academic interest of this paper is multiple and its originality operates at different levels. Firstly, the proposed model provides the necessary hypotheses to further empirically test the relationships among IC and DC of service firms and their contribution to their performance. This will allow contributing in bridging the empirical gap requested to support the DC theoretical approach and the RBV theory as a whole, as highlighted by Newbert (2007). Secondly, by considering how IC‐components coexist with regard to the specificities of service firms, the proposed model aims to revisit and complete the generic mechanism of Bontis (1998). Thirdly, by focusing on service firms, this paper provides the necessary conceptions to extend the findings of Hsu et al. (2012a) on another industry than the semiconductors industry. Fourthly, the originality of the paper stems from the consideration of the moderating role of DC in the mechanisms by which IC contributes to the performance of service firms. Finally, it should contribute to enrich the literature covering the IC of service firms. In addition, this paper brings important managerial contributions. Understanding the mechanisms by which IC contributes to the performance of knowledge‐intensive service firms is relevant to understand how these firms could improve and sustain their performance. According to this paper, managers need to acknowledge that acquiring intellectual capital is necessary but not sufficient to sustain performance. Rather, it is the relationship between intellectual capital and innovation capabilities that allows them to continually adapt their services in a highly changing environment and, as a result, to sustain their performance. In addition, managers need to consider the marketing and incremental innovation capabilities in order to influence, and therefore to maximize, the contribution of intellectual capital to the performance of their knowledge‐intensive service firms.

References Ambrosini, V. and Bowman, C. (2009) "What are dynamic capabilities and are they a useful construct in strategic management?", International Journal of Management Reviews, Vol. 11, No. 1, pp. 29‐49. Amit, R. and Shoemaker, P.J.H. (1993) “Strategic Assets and Organizational Rents”, Strategic Management Journal, Vol. 14, pp. 33‐46 Barney, J. (1991) “Firm Resources and Sustained Competitive Advantage”, Journal of Management, Vol. 17, No. 1, pp. 99‐ 120. Barney, J. and Mackey T. (2005) “Testing Resource‐Based Theory”, Research Methodology in Strategy and Management, Vol. 2, pp. 1–13. Baron, R. M. and Kenny, D.A. (1986) "The moderator‐mediator variable distinction in social‐psychological research: conceptual, strategic and statistical considerations", Journal of Personality and Social Psychology, Vol. 51, No. 6, pp. 1173‐1182. Becker, G. S. (1962) “Investment in Human Capital: A Theoretical Analysis”, Journal of Political Economy, Vol. 70, pp. 9‐49.

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Corentin Vermeulen Bontis, N. (1998) “Intellectual Capital: An Exploratory Study that Develops Measures and Models”, Management Decision, Vol. 36, No. 2, pp. 63‐76 Bontis, N., Keow, W.C. and Richardson, S. (2000) “Intellectual Capital and Business Performance in Malaysian Industries”, Journal of Intellectual Capital, Vol. 1 No. 1, pp. 85‐100. Bontis, N. (2001) “Assessing Knowledge Assets: A Review of the Models Used to Measure Intellectual Capital”, International Journal of Management Reviews, Vol. 3, No. 1, pp. 41‐60. Bontis, N. and Serenko, A. (2009) "A Causal Model of Human Capital Antecedents and Consequents in the Financial Services Industry", Journal of Intellectual Capital, Vol. 10, No. 1, pp. 53 – 69. Bowman, C. and Ambrosini, V. (2003) “How the Resource‐Based and the Dynamic Capability views of the Firm Inform Competitive and Corporate Level Strategy”, British Journal of Management, Vol. 14, pp. 289‐303 Burt, R. S. (1992) Structural Holes: The Social Structure of Competition, Cambridge, MA: Harvard University Press. Coleman, J. S. (1988) “Social Capital in the Creation of Human Capital”, American Journal of Sociology, Vol. 94, pp. 95‐120 Dzinkowski, R. (2000) "The Measurement and Management of Intellectual Capital: an Introduction", Management Accounting, February 2000, pp. 32‐35 Edvinsson, L. and Malone, M. S. (1997) Intellectual Capital—Realizing Your Company’s True Value by Finding Its Hidden Roots, Harper Collins Publishers, Inc., New York. Eisenhardt, K.M. and Martin, J.M. (2000) “Dynamic capabilities: what are they?”, Strategic Management Journal, Vol. 21, No. 10, pp. 1105‐21. Hsu, L‐C. and Wang, C.H. (2012a) “Clarifying the Effect of Intellectual Capital on Performance: The Mediating Role of Dynamic Capability”, British Journal of Management, Vol. 23, pp.179‐205. Hsu, I‐C. and Sabherwal, R. (2012b) “Relationship between Intellectual Capital and Knowledge Management: An Empirical Investigation”, Decision Sciences, Vol. 43, No. 3, pp. 489‐524. Hurmelinna‐Laukkanen, P. and Ritala, P. (2010) “Protection for Profiting from Collaborative Service Innovation”, Journal of Service Management, Vol. 21, No. 1, pp. 6‐24 Kianto, A., Hurmelinna‐Laukkanen, P. and Ritala, P. (2010) "Intellectual Capital in Service‐ and Product‐Oriented Companies", Journal of Intellectual Capital, Vol. 11, No. 3 pp. 305 – 325. Lockett, A. and Thompson, S. (2001) “The Resource Based View and Economics”, Journal of Management, Vol. 27, pp. 723– 754. Mahoney JT and Pandain Jr. (1992) “The Resource‐Based View Within the Conversation of Strategic Management”, Strategic Management Journal, Vol.13, No. 5, pp.363‐380. Makadok, R. (2001) “Toward a Synthesis of the Resource‐Based and Dynamic‐Capability views of Rent Creation”, Strategic Management Journal, Vol. 22, pp. 387–401 MERITUM (2002) Proyeto Meritum: Guidelines for Managing and Reporting Intangibles, Meritum, Madrid. Mouritsen, J. (2006) "Problematising intellectual capital research: ostensive versus performative IC", Accounting, Auditing & Accountability Journal, Vol. 19, No. 6, pp. 820 ‐ 841 Nahapiet,J. and Ghosal, S. (1998) “Social Capital, Intellectual Capital, and the Organizational Advantage”, Academy of Management Review, Vol. 23, pp. 242 266. Namasivayam, K. and Denizci, B. (2006) “Human Capital in Service Organizations: Identifying Value Drivers”, Journal of Intellectual Capital, Vol. 7 No. 3, pp. 381‐93. Newbert, S. L. (2005) “New Firm Formation: A Dynamic Capability Perspective”, Journal of Small Business Management, Vol. 43, No. 1, pp. 55‐77. Newbert, S. L. (2007) “Empirical Research on the Resource‐Based View of the Firm: An Assessment and Suggestions for Future Research”, Strategic Management Journal, Vol. 28, pp. 121‐146. OECD (2000) “The Service Economy”, Business and Industry Policy Forum, available in the OECD Web Site: http://www.oecd.org/dataoecd/10/33/2090561.pdf Penrose, E. T. (1959) The Growth of the Firm, Wiley, New‐York. Peteraf, M.A. (1993) “The Cornerstones of Competitive Advantage: A Resource‐Based View”, Strategic Management Journal, Vol. 14, No. 3, pp. 179‐191. Priem, R.L. and Butler, J.E. (2001) “Is the Resource‐Based ‘View’ a Useful Perspective for Strategic Management Research?, Academy of Management Review, Vol. 26, No. 1, pp.22‐40. Schultz, T. (1961) “Investment in Human Capital”, American Economic Review, Vol. 51, pp.1‐17. Subramaniam, M. and Youndt, M. A. (2005) "The Influence of Intellectual Capital on the Types of Innovative Capabilities", Academy of Management Journal, Vol. 48, No. 3, pp.450‐463 Teece, D.J., Pisano, G. and Shuen, A. (1997) “Dynamic Capabilities and Strategic Management”, Strategic Management Journal, Vol. 18, No. 7, pp. 509‐533. Tether, B.S. and Tajar, A. (2008) “The Organizational‐Cooperation Mode of Innovation and its Prominence amongst European Service Firms”, Research Policy, Vol. 37 No. 4, pp. 720‐39. Youndt, M. A., Subramaniam, M. and Snell, S.A. (2004) “Intellectual capital profiles: an examination of investments and returns”, Journal of Management Studies, Vol. 41, pp. 335–361. Williamson, O. E. (1999) Strategy Research: Governance and Competence Perspectives. Strategic Management Journal, Vol.18, pp. 509‐533.

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Intellectual Capital Information in Organizations ‐ Prevalence and Correlations With Organizational Performance Janet Wee and Alton Chua Nanyang Technological University of Singapore, Singapore cwee003@e.ntu.edu.sg altonchua@ntu.edu.sg Abstract: The series of economic downturns in the past decade has raised the importance of intellectual capital (IC) in building organizational resilience, particularly on the sustainability of organizational performance (OP). Likewise IC information is deemed important as it is used for decision‐making and could enhance stakeholders’ confidence. One area that has attracted little attention in both the research and business communities is the way in which IC information is made available. Current mandatory corporate filings in most countries lack information on IC in view of difficulty to systematically disclose IC Information to organizational managers and stakeholders Against this context, this study seeks to examine the prevalence of IC information disclosed by organizations and ascertains whether the presence of IC information correlates to OP from three perspectives, namely human capital, relational capital and organizational capital. This study is drawn from Annual reports and Responsibility Statements published for FYE2011 in English by the Global Fortune 500 companies in Europe. Findings show that IC information on human capital is most widely reported, followed by organizational capital and relational capital. IC scholars can leverage on the findings as springboard for new ideas in generating more research on IC information. Stakeholders will benefit from the open disclosure to make more informed investment judgments. Keywords: intellectual capital, intellectual capital information, organizational performance, Europe, annual reporting

1. Introduction The turbulent conditions in the global economy over the last decade have accentuated the importance of intellectual capital (IC) in building organizational resilience. In fact organizations that have weathered the economic shocks seem to be those that recognize the value of IC and regularly communicate its performance to stakeholders. Scholars have long noted a positive relationship between IC and organizational performance (OP) (Edvinsson, 1997; Stewart, 1997; Liu, 2009) . Even so, there has been a call for a deeper understanding of the role of IC in sustaining resilience and competitive advantage in view that industries are becoming more dynamic, competitive and knowledge‐intensive (Sveiby, 2007; Eccles, 2001; Lev, 2001). While organizations have long acknowledged that IC is a driver of value creation rather than its physical and financial capital (Sullivan, 2000; Cumby, 2001), it lacks legitimate acceptance. Scholars have argued that traditional financial and management accounting reports lack the recognition of IC, with the exception of intellectual property, and are unable to systematically disclose IC information to organizational managers and stakeholders (Firer, 2003; Pulic, 1998). In addition, current mandatory corporate filings in most countries lack content on the organization’s IC and are not sufficient to provide insights on the organization’s ability to address pertinent sustainable business issues. The importance of sustainability in the organization’s performance has grown, particularly in the past decade, following the series of global economic downturn. The traditional focus on OP comprising revenue growth, profitability and valuation, has been extended to include three focus areas, namely, business continuity, risk management and productivity (Marsh, 2012; Al Bawaba, 2010; Kryriasoglou, 2012; Rudrajeep, 2011; Eurosif, 2011). A changing trend is also evolving in the mandatory corporate filings to include more information, particularly IC information, on the organization that relates to business continuity, risk management and productivity. This changing trend is driven by factors such as human, organizational, technology and regulatory forces (Hassan, 2010; Dumay, 2009; Orens, 2009). IC information is growing in importance in today’s context as it is increasingly used for decision‐making (Ousama, 2011). While scholars take the view that IC information may vary between industry sectors, there were no references made to the importance of IC information to OP. Extant literature centered on IC often focused around revenue and valuation, and has attracted little attention in the way IC information is made available to stakeholders.

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Janet Wee and Alton Chua Against this context, this study seeks to examine the prevalence of IC information disclosed by organizations and ascertains whether the presence of IC information, from three focus areas, namely human capital, relational capital and organizational capital, correlates to OP, which encompasses the revenue performance of the organization and the productivity of the organization. The study expands literature on IC information, adding new perspective to IC. To businesses, this study serves as a guiding benchmark to improve intangible asset reporting by leveraging on correlations that exist between IC information and OP. The arrangement of the rest of the paper is as follows. Section 2 reviews existing literature on IC information and OP. Section 3 presents the methodology adopted in this study. Section 4 specifies the analysis and major findings respectively. Finally, the conclusion in Section 5 offers a few implications for business organizations and scholars in the IC community.

2. Literature review IC can be defined as the stock and flow of knowledge within the organization that can be converted into financial value (Edvinsson, 1997; Stewart, 1997). IC is generically defined in three categories, namely human capital, organizational capital and relational capital (Davenport, 1998). Human capital refers to employees’ knowledge, representing their competencies, experiences and know‐how. Organizational capital refers to organizational knowledge. Examples include intellectual property such as patents and trade secrets, and the processes and technology embedded within the organizational operations. Finally relational capital refers to the relationship that the organization has with parties outside of the organization. Examples include business relationships with customers and suppliers, customer loyalty, employee loyalty and business alliances. Many academics and practitioners have shown that IC is invaluable to organizations in creating and sustaining the organization’s competitive advantage (Zéghal, 2010; Villalonga, 2004; Liu, 2009), particularly in today’s dynamic environment. Scholars have shown that IC is important to OP (Cumby & Conrod, 2001; Sullivan, 2000). IC information disclosure of an organization suggests that its management is cognizant of the role and value of IC. It bodes well for the organization as a whole. Thus, there is a strong theoretical basis to argue that IC information disclosure is related to OP. Extant literature confines OP to financial performance. In this study, OP is broadened to cover revenue performance, in view of its importance during economic crisis, and asset turnover in consideration of the importance of productivity of the organization during downturns. The importance of IC information as a topic has begun to gain attention and importance in both the research and business community, particularly in the past decade, as a result of significant events, changing the dynamics of organizational disclosure (Abhayawansa, 2009). IC information was first introduced as a voluntary disclosure by organization since the 1990s (Ousama, 2011) with mandatory disclosure of IC information making inroads in the early 2000 (Eurosif, 2011). It was influenced by events such as the economic downturns of the Global and Asian Financial Crisis, the collapse of the dot‐com era, terrorist attacks such as those of September 11 in 2001; and the advancement in technology such as the extravagant processing capacity and rising connectivity of the Internet and social media, and the rise of identity thefts, privacy and technological ethical issues. Constituents of IC information mirror the components of IC in human capital, organizational capital and relational capital (Meritum, 2002; Sveiby, 2001; Edvinsson, 1997). Human capital information is associated with the organization’s human resources. Examples include time allocated for training, attrition rate of staff, human resource segmentation and education background. Organizational capital information covers information on the development of the organization’s intellectual property, improvement, investment and innovation of technology and processes. Relational capital information is associated to external relationships of the organization. For example, it focuses on the turnover rate and growth of the organization’s business relationships. Economic events in the past decade have resulted in organizations incorporating IC information into existing frameworks of corporate social responsibility, renamed to “Responsibility” or “Sustainability” reports (Sustainability Reports), or similar naming conventions, to address organizational sustainable issues (GRI, 2012). IC information is deemed important in interpreting early signs of OP (Firer, 2003). OP is primarily an analysis of the actual output or results of an organization as measured against its intended output, which comprise of its goals and objectives (Richard, 2009). It is often analyzed for its financial

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Janet Wee and Alton Chua performance, market performance and shareholders’ value performance. Numerous researchers have argued that current financial measures are not sufficient to evaluate OP, and that more IC information is required for decision‐making (Eccles, 2001; Lev, 2001; Mouritsen, 2001; Ousama, 2011). IC information allows stakeholders to make informed judgments on the OP, particularly organizations that are listed on stock exchanges (Schuster, 2006; Heitzman, 2010). Stockbroking analysts, whose portfolio of listed organizations in knowledge intensive sectors such as technology and biotechnology, are especially concerned with IC information, as they are relevant factors to the future potential growth of an organization and its OP (Mavrinac, 1996; Barth, 2001).

3. Methodology Data Source The data used in this study is drawn from publicly available Annual reports and Responsibility Statements (ARS) published for FYE2011 in English by the Global Fortune 500 companies (Fortune500) in Europe that are listed of stock exchanges. These organizations were chosen for two reasons. Firstly, as listed entities on the stock exchanges in Europe, they are required to produce public ARS, which lend themselves for analysis. Secondly, the research was inspired by the ongoing economic crisis faced in Europe, which makes European organizations good contenders for this study. By limiting the analysis to the European Fortune500, the effects of disparate organizational sizes and operating environments can be reduced. IC information is extracted from Sustainability Reports and the management review section of the annual reports for content on human capital, organizational capital and relational capital respectively. The study focuses on IC information that has been compiled in a table, reflecting measurements that are compared across two or more years. Existence of IC information compiled in tables is focused as it reflects better accountability of IC in place within an organization. OP for this study is focused on the revenue performance of the organization and the productivity of the organization, in terms of asset turnover. Revenue is focused here rather than profitability as generating the top line figure is most important during economic downturns. Likewise, productivity is focused, as it is a key component to organizational sustainability. There are 173 European companies (EC) listed under the Fortune500, constituting 34.6% of the Fortune500. 40 EC were dropped, as 13 EC do not have ARS published in English and 27 were not listed on any stock exchange, making the final dataset 133. Our review of the ARS of these EC shows that only 109 (82.0%) have published IC information in English. IC information in ARS is preferred as these listed organizations on the stock exchange have editorial control over the information published and are less susceptible to the potential risk of external media interpretations or falsification (Campbell, 2000; Guthrie, 1989). Data Analysis Content analysis and multiple regression methods are applied in this study. The IC information is reviewed from the angle of three components, namely human capital, relational capital and organizational capital. Analysis is made to evaluate the prevalence of the components of IC information in ARS as well as their correlation to OP. Content analysis is a process, which gathers and codifies both qualitative and quantitative information into pre‐defined categories (Guthrie & Abeysekera, 2006) where quantitative approach transforms observations into quantitative statistical data while the qualitative summarizes and classifies elements or parts of the text material and focuses on intentionality and its implications. This method has been reported as a reasonable methodology for data collection and has been used by many researchers in the review of annual reports (Gray, et al., 1995; Guthrie et al., 2004). It is useful to identify relationship and concepts that would otherwise be undetected within standard term, a sentence or a paragraph. The most reliable form of content analysis is to search the text or words for specific terms, so that the coder does not have to make any subjective judgment about the meaning or importance of the subject matter. However, words cannot be interpreted and coded without the context of a sentence (Milne & Adler, 1999; Srnka & Koeszeg, 2007), particularly in an international study where different styles of English language in the countries investigated can result in different interpretation. As content analysis is inevitably subjective, the coding method needs to be reliable for

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Janet Wee and Alton Chua valid conclusions to be drawn. Thus training of the coder is required to ensure reliability of the content analysis. Two independent reviewers evaluated the dataset of 173 EC. The reviewers were trained and familiarized with the objectives of the project, and understood the concepts underlying IC information in ARS. Every relevant IC information that is compiled in a table, reflecting the components of IC, is marked “Yes” if it was found in the ARS or “No” if not found. The scores were then compared and any discrepancies in the evaluation were addressed by a combined re‐assessment between the two reviewers. A sample size of 34 EC, approximately 21.3% of the total dataset, was evaluated by both reviewers to test for inter‐coder reliability. Cohen’s (1960) Kappa measure of 0.866, indicating acceptable level of agreement between the reviewers. Regression Analysis method is most widely used as statistical tools for discovering relationships among variables (Draper & Smith, 1998). It allows for testing the relationship between a set of independent variables and a dependent variable at a time. We use this methodology to examine whether IC information is an important variable in the determination of OP.

4. Results and discussion Descriptive Statistics Shown in Table 1, there are 20 European countries represented in this dataset that are distributed unevenly. In the leading position is France, which is represented by 28 organizations (21.2%), followed by Britain with 26 organizations (19.5%) and Germany with 23 organizations (17.3%). Table 2 shows the descriptive statistics of the dependent variables in this study. Table 1: Breakdown of Countries of EC Fortune500 Country

Frequency

Percentage

Country

Frequency

Percentage

France

21.10

Ireland

1.50

19.50

Sweden

1.50

Austria

0.80

Colombia

0.80

Britain

Germany

17.30

Switzerland

7.50

Italy

6.00

Finland

0.80

Netherlands

6.00

Hungary

0.80

Spain

6.00

Luxembourg

0.80

Russia

3.80

Norway

0.80

Belgium

2.30

Poland

0.80

Denmark

1.50

Turkey

0.80

Total

133

100.00

Table 2: Descriptive statistics of dependent variables

Type

Mean

Minimum

Maximum

Unit

Revenue

Dependent

60.59

5.17

470.17

US$ billion

Asset Turnover

Dependent

0.68

0.02

2.25

Ratio

Prevalence of IC Information All EC report some IC Information in their ARS. Out of the 133 EC, 109 or 82.0% have published a standalone Sustainability Report. Findings show that most organizations report human capital information (97.7%), followed by organizational information (71.4%) and least on relational capital information (18.8%), refer to Figure 1. A further breakdown of the figures for each of the IC information component is shown in Figure 2 below. Most organizations reported human capital information that focus on the segmentation of human resources (72.9%), which comprised mainly geographic distribution of employees. A standout feature in human capital IC

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Janet Wee and Alton Chua information is gender distribution, particularly the presence and role of women in the work environment. Approximately 52.5% of the dataset disclosed the organization’s commitment to training employees and 44.4% reported figures on the organization’s attrition, reflecting the balance of organizations in retaining talent and managing overheads. Most organizations (54.89%) that reported information on organizational capital are focused on safety rather than the improvement in the efficiency of operational matters. Only 6.77% disclosed their efforts in intellectual property, highlighting their investments and progress in patents, industrial design and branding. Within this dataset, some organizations have leveraged on the number of awards and employee cum organization certification to raise their recognition. A small dataset of 18.8% reported information on relational capital, which covers mainly numbers and distribution of customers and business alliances, with limited coverage on supplier relations.

Figure 1: Segmental IC Information Disclosure by EC in Fortune500

Human Capital

Organizational Capital

Relational Capital

Figure 2: Breakdown of the IC information – human capital, organizational capital and relational capital Table 3 below provides a summary of IC information examples based on human capital information, organizational capital information and relational capital information. These information were obtained through content analysis of the respective EC’s ARS. Table 3: Examples of IC Information disclosure of EC in 2011 Global Fortune 500 IC Information Human Capital Information

Relational

Training Attrition HR Segmentation Customers

Examples Training hours per employee, Training spend by profession/function, e‐Learning hours per employee, Number of people trained by region Attrition by gender and region, Breakdown of staff departure by cause, Employee fluctuation ratio, Retention of leadership talents Gender diversity and opportunity, Female representation in management, Staff by level and type of contract, Employee by educational background Workforce by geographic area/division Customers by region/country, Customer satisfaction, Customer

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Janet Wee and Alton Chua IC Information Capital

Suppliers Alliances

Organizational Capital (71.4%)

Intellectual Property Technology Processes (Safety)

Examples compliance Number of suppliers, Number of brands representation, Number of occupational accidents contractors Partnerships, initiatives and foundations, Memberships in associations, Number of business associates Total patents/industrial design/trademarks/copyrights held and applications filed, Principal brands and brand architecture, Awards, certifications and recognition. Investments in technology and innovation software Idea management, Investment/training in health and safety, Accident statistics, Number of medical consultations or medical exams

The findings in this study add depth to previous research undertaken on IC information disclosure. A study of 257 reports from listed Spanish companies for 2000–2001 shows differences in disclosure levels by categories of intellectual capital, with focus on strategy, customers and processes and less on information about research, development, and innovation (Garcia‐meca et al. 2005). Another study examining the annual reports of the top 30 firms listed on the Colombo Stock Exchange for the period 1999 to 2000, using the ‘content analysis’ method, found that the most organizations reported organizational capital and the second most reported was human capital (Abeysekera and Guthrie 2005).

Correlation of IC Information to Organizational Performance Multiple regression analyses were used to examine the relationship between IC information and OP. Two regression models were constructed, each comprising of nine independent variables, that are representative of the three components of IC information, namely human capital information, organizational capital and relational capital information. Training, Attrition and HR Segmentation represent human capital information. Organizational capital information is represented Intellectual Property, Technology and Processes. Relational capital information is represented by Customers, Suppliers and Alliances. The dependent variables are market capitalization (MC) and the growth of price to book value per share (GPB). Model 1 in Table 4 below shows that the combined effects of all nine independent variables account for 13.2% of the variability of the dependent variable Revenue. There is statistical evidence to support the correlation between the prevalence of IC information to Revenue [F(9,123)=2.08, p=0.036<0.05]. The strengths of correlation of independent variables to the organization’s Revenue are as follows: HR Segmentation (0.22) and Intellectual Property (‐2.17). Likewise for Model 2, the combined effect of all nine independent variables account for 13.9% of the variability of the dependent variable Asset Turnover [F(9,123)=2.21, p=0.026<0.05). The variances to these predictive 2 models, however, are noted to be small (R < 50%). The strengths of correlation of independent variables to the organization’s Asset Turnover are as follows: Attrition (‐0.21) and Customers (‐0.24). Table 4: Regression models Model 1 DV: Revenue 2 DV:

Independent Unstandardized coefficients Standardized t Sig. R square F Variables B Standard Error Coefficients (Constant) 39.40 12.42 3.17 0.00 0.13 2.08 Training ‐14.56 8.24 ‐0.17 ‐1.77 0.08 Attrition ‐1.77 8.07 ‐0.02 ‐0.22 0.83 HR Segmentation* 10.68 4.63 0.22 2.31 0.02 Customers 26.95 17.42 0.14 1.55 0.12 Suppliers 48.05 26.43 0.15 1.82 0.07 Alliances ‐0.72 20.98 0.00 ‐0.03 0.97 Intellectual Property* ‐22.91 10.55 ‐0.20 ‐2.17 0.03 Technology 5.62 24.85 0.02 0.23 0.82 Processes 10.10 8.27 0.12 1.22 0.22 (Constant) 0.79 0.11 7.21 0.00 0.14 2.08 Training ‐0.03 0.07 ‐0.04 ‐0.37 0.71

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Janet Wee and Alton Chua Model Asset Turnover

Independent Variables Attrition* HR Segmentation Customers* Suppliers Alliances Intellectual Property Tech Processes

Unstandardized coefficients Standardized t Sig. R square B Standard Error Coefficients ‐0.15 0.07 ‐0.21 ‐2.17 0.03 ‐0.01 0.04 ‐0.03 ‐0.27 0.79 ‐0.39 0.15 ‐0.24 ‐2.55 0.01 0.39 0.23 0.14 1.69 0.09 0.23 0.18 0.11 1.27 0.21 0.09 0.09 0.08 0.92 0.36 0.18 0.22 0.07 0.84 0.40 0.06 0.07 0.08 0.88 0.38

Note: *p < 0.05 While previous studies have not been able to show a definitive predictive model on the relationship of the prevalence of IC information to OP, the studies have supported the correlation between IC information, particularly human capital information, to the OP (Ousama, 2011; Boedker, 2004; Brennan, 2001; Abdolmohammadi, 2005; Firer, 2003; Bontis, 2000; Maditinos, 2011; Saenz, 2005). A recent study involving empirical data of 96 Greek companies listed in the Athens Stock Exchange from four different economic sectors, over the three‐year period of 2006 to 2008, failed to support its hypotheses but concluded that there is a statistically significant relationship between human capital efficiency and financial performance (Maditinos, 2011).

5. Conclusion In meeting with the changing economic cycle and stakeholders’ sophistication with information in view of accessibility through technology advancement and social networks, organizations, particularly those listed on the stock exchanges, have to step up in their corporate disclosures to include more IC information. The study of 133 EC from the Fortune500 companies shows that IC information is prevalent in these companies, particularly in the disclosure of human capital in regards to its investments and commitment to training, talent hiring and retention. The seniority, responsibilities and role that women have within an organization are significant. Studies have shown that women have a positive impact on organization as they bring forth essential managerial skills in building relationships, facilitation, empowerment and development of self‐ knowledge (Colwill, 1999). While the regression model shows statistical evidence of the relation between the prevalence of IC 2 information to OP, the strength of the relationship has low variability (R <50%). Mouritsen et al (2001) argued that IC information cannot be simply read and analyzed like financial statements as there are no traditional methods to interpret Sustainability reports, thus making comparison between organizations and analysis difficult. The study also found statistical evidence to support the correlation between the presence of IC information to Revenue, particularly HR Segmentation (R=0.22) and Intellectual Property (R=‐2.17). There is also statistical evidence to support the correlation between Attrition (R=‐0.21) and Customers (R=‐0.24) to the organization’s Asset Turnover (p<0.05). There are three limitations to consider in this research. Firstly, the ARS of the EC in the Fortune500 are limited to English language publications of listed entities on the stock exchanges, and do not include organizations which are non‐listed. Secondly, these listed organizations considered may not equate to, or be representative of, the whole organization of the respective EC. Finally, the EC represents less than two percent of the listed companies in the European continent. However, the dataset appears to be small, the findings of this study remain significant. This study has highlighted the relevance of IC information in ARS and OP, which will be useful to researchers and organizations alike. IC scholars can leverage on the findings as springboard for new ideas in generating more research on IC information. Stakeholders will benefit from the open disclosure to make more informed investment judgments. For the accounting professionals and chief financial officers, this research could provide insights to intangible asset reporting with the use of IC information and how it can be used to improve the organizational reporting to create and realize value for the organization. To managers this research emphasize the importance for managers to be aware of IC and the significance in managing IC in particular

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Janet Wee and Alton Chua human capital, relational capital and organizational capital. Management need to make a conscious effort to benchmark and report IC information to stakeholders as this will lead to better OP

References Abdolmohammadi, M. J. (2005) 'Intellectual capital disclosure and market capitalization', Journal of Intellectual Capital, 6(3), 397‐416. Abhayawansa, S. and Abeysekera, I. (2009) 'Intellectual capital disclosure from sell‐side analyst perspective', Journal of Intellectual Capital, 10(2), 294‐306. Al Bawaba (2010) 'The first and last line of organizational defense', Al Bawaba, n/a. Barth, M. E., Kasznik, R. and McNichols, M. F. (2001) 'Analyst coverage and intangible assets', Journal of Accounting Research, 39(1), 1‐34. Boedker, C., Guthrie, J. and Cuganesan, S. (2004) 'The Strategic Significance of Human Capital Information in Annual Reporting', Journal of Human Resource Costing & Accounting, 8(2), 7‐22. Bontis, N., Keow, W. C. C. and Richardson, S. (2000) 'Intellectual capital and business performance in Malaysian industries', Journal of Intellectual Capital, 1, 85‐100. Brennan, N. (2001) 'Reporting intellectual capital in annual reports: Evidence from Ireland', Accounting, Auditing & Accountability Journal, 14(4), 423‐436. Campbell, J. Y. (2000) 'Asset pricing at the millennium', Journal of Finance, (55), 1515‐1567. Cohen, J. (1960) 'A coefficient of agreement for nominal scales', Educational and Psychological Measurement, 20(1), 37‐46. Colwill, J. and Townsend, J. (1999) 'Women, leadership and information technology with corporate strategy', Journal of Management Development, 18(3), 207‐216. Cumby, J. and Conrod, J. (2001) 'Non‐financial performance measures in the Canadian biotechnology industry', Journal of Intellectual Capital, 2(3), 261‐272. Davenport, T. and Prusak, L. (1998) Working knowledge: How organizations manage what they know, Boston, MA: Harvard Business School Press. Dumay, J. C. (2009) 'Reflective discourse about intellectual capital: research and practice', Journal of Intellectual Capital, 10(4), 489‐503. Eccles, R. G., Herz, R. H., Keegan, E. M. and Philips, D. M. H. (2001) The value reporting revolution, New York: PricewaterhouseCoopers. Edvinsson, L. and Malone, M. (1997) Intellectual Capital: Realizing your company's true value by findings its hidden brainpower, New York: Harper Business. Eurosif (2011) 'Consultation on non‐financial reporting by companies (2011)', [online], available: http://www.eurosif.org/policy/lobbying‐activities/corporate‐transparency [accessed Firer, S. and Williams, S. M. (2003) 'Intellectual capital and traditional measures of corporate performance', Journal of Intellectual Capital, 4(3), 348‐360. Garcia‐meca, E., Parra, I., Larran, M. and Martinez, I. (2005) 'The explanatory factors of intellectual capital disclosure to financial analysts', European Accounting Review, 14(1), 63‐104. GRI (2012) 'Global Reporting Initiative', [online], available: https://http://www.globalreporting.org/information/about‐ gri/what‐is‐GRI/Pages/default.aspx [accessed Guthrie, J. and Parker, L. D. (1989) 'Corporate sorcial reporting: A rebuttal of legitimacy theory', Accounting and Business Research, 19(76), 343‐352. Hassan, M. S., Saleh, N. M., Jaffar, R. and Shukor, Z. A. (2010) 'Intellectual Capital Disclosure Quality: Lessons from Selected Scandinavian Countries', IUP Journal of Knowledge Management, 8(4), 39‐60. Heitzman, S., Wasley, C. and Zimmerman, J. (2010) 'The joint effects of materiality thresholds and voluntary disclosure incentives on firms disclosure decisions', Journal of Accounting and Economics, 49(1/2), 109‐132. Kryriasoglou, J. (2012) 'Business Controls for the 21st Century', Social Science Research Network, 16. Lev, B. (2001) Intangibles: Management, measurement and reporting, Washington DC: The Brookings Institution. Liu, D. Y., Tseng, K. A. and Yen, S. W. (2009) 'The incremental impact of intellectual capital on value creation', Journal of Intellectual Capital, 10(2), 260‐276. Maditinos, D., Chatzoudes, D., Tsairidis, C. and Theriou, G. (2011) 'The impact of intellectual capital on firms' market value and financial performance', Journal of Intellectual Capital, 12(1), 132‐151. Marsh (2012) Asia Directors' Series. Mavrinac, S. and Boyle, T. (1996) Sell‐side analysis, non‐financial performance evaluation and the accuracy of short‐term earnings forecast, Boston, MA. Meritum (2002) Guidelines for Managing and Reporting on Intangibles (Intellectual Capital Report), Brussels. Mouritsen, J., Larsen, H. T., Bukh, P. N. and Johansen, M. R. (2001) 'Reading an intellectual capital statement: Describing and prescribing knowledge management strategies', Journal of Intellectual Capital, 2(4), 359‐383. Orens, R., Aerts, W. and Lybaert, N. (2009) 'Intellectual capital disclosure, cost of finance and firm value', Management Decision, 47(10), 1536‐1554. Ousama, A., Abdul Hamid, F. and Abdul Rashid Hafiz, M. (2011a) 'Effects of intellectual capital information disclosed in annual reports on market capitalization', Journal of HRCA : Human Resource Costing & Accounting, 15(2), 85‐101.

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Janet Wee and Alton Chua Ousama, A., Fatima, A. and Majdi, A. (2011b) 'Usefulness of intellectual capital information: preparers' and users' views', Journal of Intellectual Capital, 12(3), 430‐445. Pulic, A. (1998) Measuring the performance of intellectual potential in knowledge economy, translated by Computer and Information Science, 12‐32. Richard, P., Devinney, T., Yip, G. and Johnson, G. (2009) 'Measuring organizational performance: Towards methodological best practice', Journal of Management, 20(10). Rockness, J. (1985) 'An assesment of the relationship between US corporate environmental performance and disclosure', Journal of Business Finance & Accounting, 12(3), 339‐354. Rudrajeep, P., Torstensson, H. and Mattila, H. (2011) 'Organisational resilience and health of business systems', International Journal of Business Continuity and Risks Management, 2(4), 372‐398. Saenz, J. (2005) 'Human capital indicators, business performance and market‐to‐book ratio', Journal of Intellectual Capital, 6(3), 374‐384. Schuster, P. and O'Connell, V. (2006) 'The trend toward voluntary corporate disclosures', Management Accounting Quarterly, Winter, 7(2), 1‐9. Stewart, T. A. (1997) Intellectual Capital: The new wealth of organisations, New York: Doubleday/Currency. Sullivan, P. H. (2000) Value‐driven intellectual capital: How to convert intangible corporate assets into market value., New York: John Wiley & Sons Inc. Sveiby, K. (2001) The "Invisible" balance sheet, Stockholm: Affarfgarblen. Sveiby, K. (2007) 'Methods for measuring intangible assets', [online], available: http://www.sveiby.com/articles/IntangibleMethods.htm [accessed Villalonga, B. (2004) 'Intangible resources, Tobin's Q, and sustainability of performance differences', Journal of Economic Behaviour and Organization, 54(205‐230). Wiseman, J. (1982) 'An evaluation of environmental disclosures made in corporate annual reports', Accounting, Organizations and Society, 7(1), 53‐63. Zéghal, D. and Maaloul, A. (2010) 'Analysing value added as an indicator of intellectual capital and its consequences on company performance', Journal of Intellectual Capital, 11(1), 39‐60.

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Particular Aspects in the Intellectual Capital Management of the Romanian SMEs Roxana Mironescu, Andreea Feraru and Catalin Drob Faculty of Economics Vasile Alecsandri University of Bacau, Bacau, Romania roxy_mironescu58@yahoo.com andreea_feraru26@yahoo.com totanul@yahoo.com Abstract. In our days, there are two approaches about the application of the concept of Knowledge Management. In the Western Europe we put emphasis on: (1) explicit knowledge, (2) measuring and managing existing knowledge, (3) treating the organization as a vehicle for the information processing. In Japan, KM it is understood mostly by 1) highlighting tacit knowledge, 2) creating new knowledge, 3) extensive participation of all the members of an organization, whether in private or in public sector, the crystallization of a learning oriented culture from the perspective of a living organism, able to create a circuit of continuous innovation. In conclusion, this new management concept has two important dimensions:(1) the assessment of knowledge; (2) a judicious management of the human capital. The economic environment where the SMEs are competing prove a continuous process of changing. Switching from a post‐industrial based economy to a knowledge based economy has changed the way the small businesses manage their assets. The knowledge based economy, which includes today even the SMEs from Romania, alongside with other types of organizations, puts a great emphasis on the exploitation of the intellectual capital. Each country, company and individual depends increasingly more on knowledge, which materializes in: patents, skills, technologies, and customer information about suppliers. At the level of the SMEs, the technology and the associated processes act upon the individual knowledge, and especially upon the side of the intellectual tacit component. The management and the leadership are a powerful integrator in the nonlinear segment. The leadership is important by its power to act on knowledge, on the intelligence and on the individual values. The organizational vision and mission are also interesting integrators, which act mainly on the individual emotional intelligence. The organizational culture appears as a powerful integrator, because it acts mainly on the individual intelligence and on the values and creating models of the organizational behavior. The main category of the incorporated analysis is: an elementary analysis of the intellectual capital issues in the SMEs from the North‐ Easter region of the country. Also, in this paper, there are addressed two very present and major categories of problems, such as: the entrepreneurs’ characterization in Romania, especially for those in the above mentioned region; the perception of the latest economic and social developments proved by the entrepreneurs in Romania and their impact on the potential organizational research and innovation Keywords: intellectual capital, structural capital, relational capital, small and medium enterprises, competitiveness

1. Introduction In Peter Drucker's vision for the future, other factors will be successful: ”the traditional factors such as production ‐ land, labor and capital ‐ have not disappeared. But they became secondary. Knowledge is the only resource which is really relevant today”. (Drucker, P. 1988) The most widely used and accepted interpretation is the Knowledge Management as the process of generating added value for the organization's intellectual capital. It combines a wide range of practices used by the organizations in order to identify, to create, to store and to share knowledge, so that they can be reused in a process of continuous learning within the organization. The Knowledge Management processes are based on: innovation‐creation of the new knowledge; learning and assimilating the new knowledge; interactivity – the partners share knowledge. The Knowledge Management is the most recent and innovative pathway for training, certification and international cooperation in the global management and consulting, launched this decade from the United States, through several activities and projects coordinated by the specialists from the International Knowledge Management Institute (Washington DC) towards all the five continents. A conceptual basic model of the knowledge in an organization may be(see fig. 1): The major focussed theme of the KM community in Romania had in particular to support all the managers, experts and entrepreneurs, coming even from the SMEs area, motivated to use the new know‐how and the

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Roxana Mironescu, Andreea Feraru and Catalin Drob KM accumulated, in the the access, the management, in the evaluation and the audit of the projects and investments that are based co‐financed from the EU funds. ACTION- APPLIED KNOWLEDGE- DATABASE (Information - Systems based on data of the organization)

BASIC RULE (Applied knowledge, heuristics, programmable procedures) KNOWLEDGE

COMMON KNOWLEDGE

Figure 1: The basic model of the KM

2. Research utility The outcome of the research is to evaluate the intensity of each component of the intellectual capital that contributes to determine the stage of development in terms of generating intellectual capital. These results may be used by the SMEs managers, to observe, modify and improve the intellectual capital performance in the organization they manage.

3. Methodology Taking into account the requirements of the research paper we used a series of tools and techniques, as follows: a continuous empirical survey, a document analysis, a questionnaire‐based survey. The research methodology of this work was based also on the implementation of different projects between 2010‐2011. In order to accomplish the intellectual capital evaluation in the SMEs from the North‐East region of the country, we used a complex questionnaire which seeks to determine the existing level of intellectual capital in the analyzed organizations, at a certain time, focusing on assessing the intensity in each of its parts. The questionnaire on the evaluation of the intellectual capital in SMEs is a model that can perform this analysis; it is useful to assess the generation and the development of the intellectual capital in creating value and achieving the sustainable competitive advantages. The preparation of the statements is based on the organizational integrators (mission and vision, management and leadership, organizational culture, technology) that are found in the subsections of the questionnaire. The target group for this pilot research questionnaire were the SMEs in various areas of economic life: the traditional industry, construction, agriculture, forestry, electricity, gas, water, transport and services industry, telecommunications industry, trade and finance, insurance and real estate industry. The structure of the questionnaire contains three important sections: statements about the human capital; statements about the structural capital and statements about the relational capital Subsection A.1. The professional competences evaluation .

The statement: ”The employees in your firm have a general knowledge acquired through the educational system”;

The statement: ”In your firm the employees participate to brainstorming sessions, to solve the different problems appeared inside the teams/departments/sections”.

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Roxana Mironescu, Andreea Feraru and Catalin Drob Subsection A.2. The employees’behaviour evaluation.

The statement: “A mutual trust is promoted in your firm”;

The statement: “ In your firm the rate of the indiscipline is at an worrying level”

Subsection A.3. The intellectual abilities evaluation.

The statement:“ The employees prove the ability necessary to perform the work, solving team common problems“;

The statement:“ The employees are encouraged to prove and to develop new abilities, complementary to their current activites“;

The statement:“ Inside your organization, there the employees have the opportunity to verify, from time to time, their intellectual potential, by certain specific tests, applied by external specialists”.

For each of the statement there was determined a score, enabling to conclude about the analyzed phenomena.

4. Content The heterogenity that defines the SMEs, due to their entrepreneurs’ diversity, characterizes also a certain extent of the applied management in this sector. The main differences that arise in the management of the SMEs compared to the large companies are composed by some characteristics, such as:

the highest degree of integration of the policies and practices in the managerial duties;

the forecast for the time horizon is limited;

a more hostile attitude face to the external environment components (government agencies, local government, health agencies and others);

the failure or the existence of an incipient management information system and the use of the management techniques and methods;

the presence of small managerial teams where the components have multifunctional roles and often, the lack of the specialized staff in the human resources field, marketing field, finance field;

generally speaking, a limited ability to influence the business environment;

a greater cohesion among the employees because of better relationships across the working groups and related to the company management;

a closer relationship between motivation and profit of the managerial teams;

a greater flexibility to change than in the excessively bureaucratic larger firms;

a greater inclination towards innovation and creativity;

the managerial mistakes have a greater impact on business than in the case of larger enterprises;

a closer link between efforts / results and rewards / sanctions.

In this context, KM facilitates the creation, the communication and the application of Knowledge of all kinds to get the greatest value from the execution of a specific activity (core competencies). Inside the SMEs, the KM is used to solve problems, especially where we are dealing with an innovative product or service. The KM facilitates establishing superior relationships with the customers, the partners and the suppliers. The KM govern and improves the operating practices and processes.

5. Findings and discussions The most widely used and accepted interpretation is that Knowledge Management is the process of generating added value for the organization's intellectual capital. It combines a wide range of practices used by organizations to identify, create, store and share knowledge, so that they can be reused in a process of continuous learning within the organization. The Knowledge Management processes are based on: innovation‐creation of new knowledge; learning and assimilating new knowledge; interactivity – the partners share knowledge.

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Roxana Mironescu, Andreea Feraru and Catalin Drob Our inquiry found out some issues, such as: a significant percentage of 70% of respondents (managers in SMEs) is given by those who are between 35 and 60 years old and that they have enough working experience; the employees have a higher general training than the average level; a major part of the SMEs do not use participatory methods to increase the level of the internal Knowledge; the level of the professional competences is considered to be satisfactory in relation to the requirements of the organization. The SMEs employees create a constructive work environment, they manifest a mutual trust and most of them have an appropriate work behavior, adjusted to the internal standards. The jobs and the teams formed inside the analyzed SMEs are stimulating the development of the intellectual skills, which reduces the need of involving external experts, appealing those experts would transform tacit knowledge into explicit knowledge. The organizational communication provides the necessary information for the employees and contribute to the establishment of certain fair and effective relationships between managers and employees, between colleagues, but also with the people outside the organization. Based on this research findings, we can say that the members’ continuous interest for knowledge is directly influenced by their level of satisfaction, of the trust and of the affective commitment significantly established between the members of a SME. At a first view, the results show that the members’ affective commitment to develop the Knowledge Management is identified to have greater dominant effect in an open organizational culture, where the managers have special communication abilities and disponibility for the innovative ways to produce, to sell or to promote their work results.

6. Conclusions The Knowledge Management is required to be applied in order to reduce efforts, both economically and in terms of the human efficiency. The staff from a classical organization continually reinvent the processes and ways to make things work, in a permanent costly activity. In contradiction, the modern organizations, including here the SMEs, understanding the significance of the intellectual capital, use the Knowledge Management as a means to adapt themselves to the continuous changing environment, by early identification of the opportunities and avoiding risks; they have a business behaviour matching with the strategic views of the organization; they strengthen their capacity to get a long term market position which conserve their competitive advantages. Our paperwork also tried to understand the profile of the present manager in a Romanian SME and the way he copes with the challenges of the knowledge economy. By this research, we intended to underline the significance of the innovative spirit and the value of the man and his knowledge. in SMEs of our country, in an overall approach, during the last three years, in integrated studies.

References Agapie, A., Bratianu, C. (2010) Repetitive Stochastic Guesstimation for Estimating Parameters in a GARCH(1,1) Model, Journal for Economic Forecasting, Institute for Economic Forecasting, vol.0(2). Allaire, Y; Firsirotu, M. E., (1993) L’entreprise stratégique: penser la stratégie. Gaëtan Morin, Québec. Allaire, Y; Firsirotu, M. (July, 1984)Theories of Organizational Culture. Organizational Studies. No. 5. Brătianu, C., (2006), Un model de analiză a capitalului intelectual organizațional. Revista de Management si Marketing, 1(3). Drucker, P.F., (2003) Managing in the Next Society, St. Martin's Griffin. Drucker, P. (1988) The coming of the new organization, Harvard Business Review. Edvison, L., Malone, M. (1997) Intellectual Capital, Harper Business, New York; Guenon, R. (2008) Criza lumii moderne, Bucureşti: Ed Humanitas; Harrison, R.( 2009) Learning and Development, Editura CIPD, Fifth Edition, Edinburgh; Hersey, P.and Blanchard, K. H. (1996) The management of organizational behavior, Englewood Cliffs, NJ: Prentice‐Hall. Krogh, von G., Ichijo, K., Nonaka, I., (2000) Enabling Knowledge Creation: How to Unlock the Mystery of Tacit Knowledge and Release the Power of Innovation, Oxford University Press, USA. Marin, D.and Verdier,Th.(2001) Power inside the Firm and the Market: A General Equilibrium Approach, University of Munich and DELTA, Paris, Mimeo. Nicolescu, O. and Verboncu, I. (2008) Fundamentele managementului organizatiei, Editura Universitara, Bucuresti. Nonaka, I.,Takeuchi, H., & Umemoto, K. (1996) A theory of organizational knowledge creation.International Journal of Technology Management, Special Issue on Unlearning and Learning for Technological Innovation, 11(7/8), 833‐845. Shapero A., (Summer 1979) Entrepreneurship and Economic Development, Proceedings of NEED. Sveiby, K.E. (2001), Intellectual capital knowledge management, uploading as http://sveiby.com/articles/IntellectualCapital.html. Veblen, T. (2005)The Theory of Business Enterprise, New York: Cosimo Inc.

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The Role of Intellectual Capital in the Entrepreneurial Firm Innovation Helena Santos‐Rodrigues1 and Liliana Alves2 1 Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal and CIEO – Centre of Spatial Research and Organizations, Algarve University, Portugal 2 Reserch Schoolarship from Instituto Politécnico de Viana do Castelo, Viana do Castelo, Portugal hsantos@estg.ipvc.pt lialves@estg.ipvc.pt Abstract: This article aims to explore the scientific focus of the role of intellectual capital in the innovation of the entrepreneurial enterprise. To achieve the proposed objective we developed a literature review explaining the triple division of intellectual capital into human capital, structural capital and relational capital. The concept of entrepreneurship and innovation are other critical concepts that are important in our literature review. The study analyzes the work already done and presents a summary of the results achieved. We verified that the research concludes that innovation is positively related with intellectual capital. The literature shows that behind is an enterprising entrepreneur (human capital) that provides internal and external connections, enhancing thus the dynamic growth of intellectual capital and business entrepreneurship. The entrepreneur (human capital) is the one who stands out as a promoter of the company, managing the company focused mainly on innovation and adaptability. Keywords: intellectual capital, innovation, entrepreneurship

1. Introduction The impacts of new firms in the local and regional economy is crucial, henceforth perceive the factors that contribute to the survival and the success of the company is the most important and the most difficult challenge. Many authors conclude that intangible resources are crucial to the development of the company, some saying that they are more important than tangible resources in certain critical periods of the company. (Lichtenstein & Brush, 2001; Teece, 2000; Thornhill & Gellatly, 2005) Intellectual capital as precious intangible resource to achieve competitive advantage is studied by several authors and it is also regarded as a significant factor for the success of the company and for entrepreneurial innovation. Therefore, intellectual capital, innovation and entrepreneurial company are interesting concepts to perceive how they are related and influence each other. The entrepreneurial approach of the resources and capabilities of the company and its potential value creation has changed and the focus on intangible resources is assuming increasing importance among researchers and entrepreneurs. Moreover, sometimes the company needs to regenerate at a faster changing rate than the market rate. The speed at which changes happens the company, currently, requires an entrepreneurial vision and planning, often based on innovation. Just as the intellectual capital and innovation are connected, innovation and entrepreneurship are also related. For this, it is significant to perceive the role of intellectual capital ‐ considering human capital, structural capital and relational capital ‐ in the innovation process of entrepreneurial enterprise. The present paper aims to point out the role of intellectual capital in the innovation process of entrepreneurial companies through a study of the state of art, based on scientific production in this field. We analyzed the work already done on the subject focus and the main conclusions. In this work, we don’t have the objective to present new empirical evidence, but to show the importance and intrinsic theoretical and empirical evidence of this matter to propose future research.

2. Literature review Authors such as (Roos, Roos, Dragonetti, & Edvinsson, 1997) consider that intellectual capital includes all intangible processes and assets that normally are not shown in the balance. It is the sum of the knowledge of its members and their practical translation. (Spender & Marr, 2005) and (Grant, 1991) defend that it is important to entrepreneur has a good sense to which are the important basis of the firm. The knowledge is the primary sources of the firm profitability and where the firm can establish its identity and frame. (Timonen & Paloheimo, 2011) and (Drucker, 1999) research about knowledge workers and its importance in modern organization. (Drucker, 1999) thought in knowledge workers as the “most valuable asset” and they are the most potential source to production equipment in modern organization, thinking in processes of production in own means. Intellectual capital is usually accepted by several authors has been divided into three types of

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Helena Santos‐Rodrigues and Liliana Alves components: human capital, structural capital and relational capital. (Davenport, Prusak, & Wilson, 2003); (I.A.D.E.‐C.I.C, 2003); (Santos‐Rodrigues, Figueroa, & Jardon, 2011b) For the study of entrepreneurship, an entrepreneur is seen as an individual person with a set of characteristics and personality traits that enhance the creation of the organization. (Gartner, Carland, Hoy, & Carland (1988) Fregetto (2010) conducted a study on this subject and concluded that what characterizes the entrepreneur is a different vision of reality and its powers; on the other hand, what characterizes the enterprise is the change. So innovation is closely connected with entrepreneurship and intellectual capital (Thornhill, 2006). Innovation is defined by Roos, et al. (1997) as "an intellectual agility, closely linked to competition, the ability to use knowledge and skills, the ability to build on prior knowledge and generate new knowledge.” This means that innovation involves the creation of new knowledge or a new recombination of existing knowledge. The relationship between innovation and organizational survival is being studied by several authors that indicate the actual existence of a connection between intellectual capital, innovation and power (Bontis & Fitz‐enz, 2002). There is also a very strong and positive relationship between intellectual capital and business performance, supported by the findings of Cabrita & Bontis (2008) applied to the Portuguese banking sector, in the same sense Santos‐Rodrigues, Pereira‐Rodrigues, & Cranfield (2012) verify a relationship between intellectual capital and financial performance of a company from the logistics sector. Santos‐Rodrigues, Figueroa, & Jardon (2011a) also verify a positive relationship between intellectual capital and innovativeness of the company’s applied to the automotive industry in Galicia and Northern Portugal. Faria, Santos‐Rodrigues, & Morais (2012) reached the same conclusion in the case of a hospital. The results propose that intellectual capital of new firms is positively associated with the event perceived by the entrepreneur. Therefore, human and relational capital plays a fundamental role in the development of new firms, while structural capital is relatively important as it is rooted in the new companies, since its inception (Hormiga, Batista‐canino, & Sánchez‐medina, 2011). Research in the area of entrepreneurship and intellectual capital refers to two types of connection that the entrepreneur develops in their company: external connections and internal connections. Concerning the investment in human capital it constitutes and strengthens relational capital and structural capital. So, the intellectual capital is a factor of competitiveness and success for the company, it is important to treat each component of intellectual capital as unique and with idiosyncratic properties, with their power, identity and performance. (Santos‐Rodrigues, et al., 2011a) on the other hand, there are evidences of a real dynamic between the different intellectual capital components, having been verified that these interrelate successfully, for, in the case under consideration, directly or indirectly interconnected in the innovative capacity company. Authors conclude that, despite their individuality, human capital, structural and relational only have real ability to function when they interact.

3. Conclusion The three main concepts of this study are intellectual capital, innovation and entrepreneurship. We analyze the state of the art concerning the relationship between these three concepts of great importance and, although it was not an easy task we verify that there is a lack of research linking these three concepts, and that there is some recent, although not fully, conclusive results. Still, some suggestions were noted and taken as significant. First, it was concluded that there is a positive correlation between innovation and the intellectual capital components. In addition to an inter‐connected or stand‐alone, all components of intellectual capital (human, structural and relational) affect the performance, results, innovation and sustained competitive advantage; in particular we verify that there is some evidence of its importance in entrepreneurial firms. Various authors agree that intellectual capital and the performance of the company have a strong and positive relation. Concerning the literature review we hypothesis that intellectual capital (human, structural and relational capital) is a drive to innovative capacity in entrepreneurial firm. Many topics can be explored in each type of intellectual capital. In human capital, concerning the entrepreneur profile some topics as Intrinsic Motivation, Extrinsic Motivation and Risk can be researched. On the other hand, in structural capital, the entrepreneurial firm structure can reveals its influence in firm innovative capacity studding topics as Trust, Innovation Culture, Risk, Reward, and Vision. Finally, Network, Alliances, Collaboration, Firm’s Communication are some of topics of the relational capital of entrepreneur firm with interest to understand its influence in innovative capacity of an entrepreneur firm. We propose this innovative capacity analysis in process, in product and / or management. Concerning the authors that research the theme, we suggest that the human capital is the intellectual capital with more

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Helena Santos‐Rodrigues and Liliana Alves influence in innovative capacity of entrepreneurial firm. In our future study we perspective a positive relation between intrinsic motivation and innovative capacity in firm management; the team work culture is connected with innovative capacity of entrepreneur firm and a better innovation product; the network of firm contribute to sustainable innovation on firm.

Acknowledgements This paper is partially supported by the Portuguese Foundation for Science and Technology.

References Bontis, N., & Fitz‐enz, J. (2002). Intellectual capital ROI: A casual map of human capital antecedents and consequents (Vol. 3, pp. 223‐247): Journal of Intellectual Capital. Cabrita, M. R., & Bontis, N. (2008). Intellectual capital and business performance in the Portuguese banking industry (Vol. 43, pp. 212‐237): International Journal of Technology Management. Davenport, T. H., Prusak, L., & Wilson, H. J. (2003). Who´s bringing you hot ideas and are you responding? (Vol. 81, pp. 58‐ 64): Harvard Business School Press. Drucker, P. F. (1999). Knowledge‐worker productivity: The biggest challange. California Management Review, 41(2), 79‐94. Faria, J., Santos‐Rodrigues, H., & Morais, C. (2012). A Influência do capital intelectual na capacidade inovadora de um hospital. Vila Real, Portugal: XXII Jornadas Luso‐Espanholas de Gestão Cientifica. Fregetto, E. (2010). Entrepreneurship: state of art. Washington: International Council for Small Business. Gartner, W. B., Carland, J. W., Hoy, F., & Carland, J. A. C. (1988). Who is an entrepreneur? Is the wrong question (Vol. 12, pp. 11‐32): American Journal of Small Business. Grant, R. M. (1991). The Resource‐Based Theory of Competitive Advantage: Implications for Strategy Formulation. California Management Review, 33(3), 14‐35. Hormiga, E., Batista‐canino, R., & Sánchez‐medina, A. (2011). The role of intellectual capital in the success of new ventures (Vol. 7, pp. 71 ‐ 92): International Entrepreneurship and Management Journal. I.A.D.E.‐C.I.C. (2003). Modelo Intellectus: medición y gestión del capital intelectual. Madrid: Documentos Intelectos. Lichtenstein, B. M. B., & Brush, C. G. (2001). How do 'resource bundles' develop and change in new ventures? A dynamic model and longitudinal exploration. (Vol. 25, pp. 37‐59): Entrepreneurship: Theory and Practice. Roos, J., Roos, G., Dragonetti, N. C., & Edvinsson, L. (1997). Intellectual capital: navigating in the new business landscape. London: Macmillan. Santos‐Rodrigues, H., Figueroa, P., & Jardon, C. (2011a). Intellectual Capital and Firm’s innovativeness: 3th European Conference on Intellectual Capital. Santos‐Rodrigues, H., Figueroa, P., & Jardon, C. (2011b). The main intellectual capital components that are relevant to the product, process and management firm Innovativeness (Vol. 1, pp. 271‐301): International Journal of Transitions and Innovation Systems. Santos‐Rodrigues, H., Pereira‐Rodrigues, G., & Cranfield, D. (2012). Intellectual Capital and Financial Results: A Case Study. Cartagena, Espanha: 14th European Conference on Knowledge Management (ECKM). Spender, J. C., & Marr, B. (2005). A Knowledge based Perspective on Intellectual Capital. In B. Marr (Ed.), Perspectives on Intellectual Capital ‐ Multidisciplinary insights into Management, Measurement and Reporting (pp. 183‐195). Oxford, U. K.: Elsevier. Teece, D. J. (2000). Strategies for knowledge assets: the role of the firm structure and industrial context (Vol. 33, pp. 35‐ 54): Long Range Planning. Thornhill, S. (2006). Knowledge, Innovation and Firm Performance in High ‐ and Low – Technology Regimes (pp. 687‐703): Journal of Business Venturing. Thornhill, S., & Gellatly, G. (2005). Intangible assets and entrepreneurial finance: the role of growth history and growth expectations. (Vol. 1, pp. 135‐148): International Entrepreneurship and Management Journal. Timonen, H., & Paloheimo, K. S. (2011). Leading Issues in Knowledge Management Research Leading Issues in Knowledge Management Research (Vol. 1). Reading, U.K.: Academic Publishing International Ltd.

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The Aleatoric leadership role - The choreography of intellectual capital in the NGO (non-profit organization) Paulina Święcańska Artistic Foundation PERFORM, ul. Kwatery Głównej 46B/10, 04-294 Warszawa, Poland paulina.swiecanska@gmail.com

Abstract: Contemporary leadership in modern culture management organisations: mostly operating in the form of NPOs (foundations and associations), is a sui generis art form. Improvisation, flow, connection, flexibility are some of the notions associated with aleatorism applied to the context of cultural NPO management. Not only is a modern leader expected to understand and motivate their subordinates, manage the organisational command structure, respect corporate tradition and mission, they also have to be emphatic enough to perceive the volatile dynamics of all human related elements making up the IC creation process. Through the examples of two different NPOs active in the Polish independent art segment, the author demonstrates the strengths and weaknesses of aleatoric leadership. The research provides a rare insight into this unorthodox management philosophy derived from the arts (music and dance) related to contemporary artistic forms (composition, performance, show) via a choreography based on dance. In other words, a cultural animator becomes a type of dance choreographer – passionate and unconventional in their efforts to cultivate and enhance corporate IC. Not only is the proposed research focused on specific NPO leaders, it also refers to mainstream business executives: likely to be inspired and enriched by this novel approach to choreography style management. Keywords: aleatoric leadership, choreography, intellectual capital, non-profit organisation management

1. Introduction Aleatorism represents a direction in contemporary music of deliberately introducing an element of chaos to both composition and performance. The author can use a random factor at the stage of composition or leave some latitude to the performer. The musical notation is based on a purposefully indeterminate record. 

Another method is to build a composition around short components, the order of which is randomly selected at run-time work (e.g. Klavierstück XI by Stockhausen).

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Sometimes alongside composed works, participation of other sounds, are not subject to notation, for example, in one of the compositions by John Cage, which was used 12 randomly radio sets being retuned during the performance.

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Other methods used to compose aleatoric music for an instrumental ensemble of any structure, organized an ad hoc basis, in a purely random fashion.

Important, however, is that it is not improvisation aleatorism (spontaneous action) but rather planned activities in which the composer, choreographer and (in our case) the leader consciously decide to introduce an element of chaos into various configurations in order to: 

delegate the responsibility to subordinates for each element of work in a way that motivates them to become more engaged in the task;

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create an autonomous space for the ideas and creativity of the subordinates, which will make them more involved and identified with the company;

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provide a space for positive randomly selected element (sometimes multidimensional) of corporate development, which may occur under the aleatoric management system;

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incorporate a safety valve for the employees as well as the leader – a linear development system devoid of an element of chaos leads to routine behavior and limits the degree of involvement on the part of the employees in the company's development

The contemporary role of leadership in modern companies is a complex and highly individualized issue depending on the ability to strike a delicate balance between predefined, formalized business priorities, allowing a creative space for the employees, an element chaos triggered by the introduction of alternative solutions, operating efficiency and a favorable atmosphere in the workplace. These are all elements of the jigsaw puzzle making up a coherent unified magnum opus, whose management and creation is a form of artistic expression.

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Paulina Święcańska The characteristics of leadership attitudes and behaviors are also defines the skill set of a dance choreographer: 

improvisation (she can improvise in challenging circumstances);

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connection (she has close association with the group and herself);

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flexibility (she is ready to embrace change);

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knowledge (she is equipped in formal acumen and practical skills);

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empathy (she is empathic to both humans as well as to the situation);

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feel (she is first of all a human and then a leader);

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courage (as a model for subordinates – the ability to be held accountable for decision making, also if it fails);

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passion (her job is not imposed on her);

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flow (she is able to develop harmoniously: with pleasure, ease and without undue effort and strain)

Basin on the example of two NGOs active in Polish independent arts, I will present the strengths and weaknesses of aleatoric leadership. To perform the analysis, I have selected two highly differentiated NGOs: PERFORM Art Foundation, a young organization that mainly deals with international, interdisciplinary art projects implemented in customized and innovative way – the examples under review are “100 Dancers” and “Dance Inter Space” realized in 2012. ‘Zawirowania’/ Turbulence (an international festival, band, dance school) an experienced organization, which over the past few years of market activity has developed three independent structures to disseminate alternative culture based on a variety of structural and organizational synergies (2005-2012) Mission: PERFORM Art Foundation is an organization focused on promoting performance arts. The Foundation was set up to address the need of a new platform on which work will be independent, creative and innovative, as well as a career starting point for artists in a variety of fields including art dance, theater, music, visual and performance. The Foundation's mission is to make contemporary performative art presented on Polish and foreign scenes professional, both in terms of artistic and organizational merit. It is also important to realize artistic projects that are socially relevant and promote the development of arts and culture in Poland and beyond. Structure: The founders are two women who have pursued joint projects since 2005. Thanks to several years of cooperation and mutual trust, they have decided to set up a foundation, which can synergize the skills and work experience numerous individuals from Poland and abroad, as well as to implement projects of socially necessity assisting the development of culture and art in Warsaw. The Foundation was established in 2011. In 2012, it managed to complete 6 artistic projects in collaboration with about 100 individuals (artists, entertainers, performers). In 2013, it is planning to execute 10 projects inter alia in artistic education (the fourth edition of the festival Warsaw Flow, ECITE 2013 European Contact Improvisation Teachers Exchange, PERFORmative Warsaw Calendar, Idea in Motion,) Management: The Foundation has an open-end management architecture, in which there is no formalized hierarchy or a fixed pay scale. The artists realize projects that they want to create and themselves determine their own pay. It is a foundation incorporated under Polish law, financed mainly via municipal and ministerial grants but also increasingly reaching out to individual sponsors. The two people heading in the foundation are responsible for: 

First Foundation President - administration, accounting and current affairs (coverage of social media , website traffic and graphical design).

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Paulina Święcańska 

Second Art Director – project portfolio selection, human resources recruitment, project creation, implementation and due diligence projects. Thus, there is no adverse competition at the board level and the management structure and complementary.

The management style: The aleatoric is a model is used by the majority of projects implemented by the Foundation. As an example, I will highlight two projects completed in 2012: 

100 DANCERS "

This international meeting of integrated research and artistic dialogue with the performance – also in the public space. The participant were dancers and choreographers involved in creating and teaching in the area of improvisation, contact improvisation and performance studies. The “DANCERS 100” event was also a meeting point for musicians and new media artists who had the chance to explore their own topics to every research. The overriding objective of the 100 DANCERS was to facilitate the exchange of artistic and research qualities in the field of dance, music and new media, as well as to develop large-scale public performances. It was a creative and artistic creative platform. In this project, the leaders were formed spontaneously as well as within groups and subject areas on which joint work was being conducted. Everyone had a chance to submit her own project and convince the other participants. The most promising ideas attracted volunteers in a natural way. Under this project, everyone was self: motivated, mobilized and controlled because they all wanted to prove themselves. The role of leadership (the artistic director of the Foundation) was to arrange the work location (the Contemporary Arts Center in Warsaw), as well as to select artists from around the world who would take part in the project. All action carried out in the urban performance spaces and as well as coordinated by the project participants.

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Paulina Święcańska 

,, Dance Inter Space "

Inter Space Dance Project was an interdisciplinary performance exercise set in the city of Rzeszów in an event conducted under the auspices of the National Centre for Culture: The European Culture Stadium. The performance was designed to revitalize urban architecture and display art in unconventional places. Direct contact with the audience and their immediate response contributed to this intricate art form, which can be referred to as urban space performance. Dancers from Polish and Ukrainian converged in the city and employed such dance techniques such as improvisation, contemporary, contact improvisation, slow-motion, authentic movement, physical dance. The aleatoric structure designed by the coordinator of the project included dance warm-up exercise for the residents of the city, merging in fragments of urban architecture, slow-mo ball techniques and space sculpture. The quality of movement and structure, i.e. (duration of various elements, spaces, colors, costumes) were chosen by the leader/choreographer. However, the motion, costume design, performance order was determined by the artists who had also been randomly selected from the group of Polish and Ukrainian dancers.

Photo: www.perform.org.pl

Photo: www.perform.org.pl Both projects were carried out by highly qualified and dynamic artists. Both the leader and the artists were partners in a common dialogue. The work on what we believed in and what stood for was a genuine pleasure. Each of the teams was composed of passionate people. The leader/choreographer did not have to supervise anyone, as the participants were competent, creative and most of all responsible.

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Paulina Święcańska In the future, the role of the leader in artistic PERFORM Foundation will be limited to the selection of strategic choices and methods to increase the efficiency through scale effects relating to exploring foreign markets. In the commercial world, such a model of management is functioning in the company Valve Corporation ( founded in 1996 by Gabe Newell and Mike Harrington). 

Zawirowania / Turbulence

Historical background: The International Dance Theatre Festival Zawirowania was founded in Warsaw, Poland in 2005, as a meeting point of modern dance ensembles from Central and Eastern European (CEE) countries: the Czech Republic, Slovakia, Hungary and Poland. It has since expanded into Russia, Ukraine and Belarus and it has then spread to further European countries. Since 2008, Zawirowania has gone global. As a live platform of dialogue and exchange, it annually displays from 16 to 20 of its most intriguing shows of the last season. At present, the festival takes turns in targeting specific world regions: Scandinavia in 2011, in 2012 African countries, in Asia in 2013 (planned). Zawirowania: the biggest dance festival in Poland is the most significant event of its kind in all CEE.

Photo: Marta Ankiersztejn 

Management structure:

After more than eight years of operation, the foundation has established three independent sections: Theater, dance, festival and dance school, which complement one another. Now this dance festival has become the largest event of contemporary dance expression in Poland. Turbulence and the dance theater dance school run by the members of the team have won the acclaim and prestige locally and in foreign markets. All these three structures are managed by one leader - the director and the main manager, who last year began to gradually implement the aleatoric management system. However, in contract to the previous organization, not all of the solutions have proven effective, mainly as they may have been introduced too hectically. Certain employees (hitherto unexposed to creative thinking and

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Paulina Święcańska self-determination in important matters) were overwhelmed by apprehension and would make serious mistakes. The previous foundation assumed an aleatoric management system at the outset whereas in this case, the multiple hierarchy had to introduce an element of improvisation: something completely new for both the employees and for the leader, who had to change her habits in management styles. Currently, the taking place in the Foundation after eight months of new system implementation comprises: 

+ Foundation's expansion to international markets;

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+ Increase participation in dance workshops;

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+ Implementation of several individual ideas which have a high probability of success;

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+ delegation and devolution of tasks from the leader (downward);

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+ Nice atmosphere in the team dance theater

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+ Implementation of a larger number of artistic projects;

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+ hiring passionate individuals;

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+ tailor made training programs;

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_ staff redundancies;

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_ a difficult start (a high margin of error);

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_a trying period for the newly hired and creative staff;

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_work stress during new system implementation

The year 2013 will see the ninth edition of the festival, the dance team is to be expanded by the new international additions and the dance school will break even (economically). The plan is to hire new creative and entrepreneurial employees who want to realize their ideas in a variety of fields (including public relations, international cooperation), which will contribute to the development of Turbulence. The Director/Leader will consolidate the strategy for the coming years, develop a network of international contacts and personally coordinate only the key and high-profile projects - Dance Festival and its subsequent editions. In both cases, the role of the aleatoric leader brought immeasurable benefits / advantages in the development of intellectual capital via: 

Enhanced employee creativity;

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Implementation of only those tasks that will bring satisfaction: both financially and conceptually( for the foundation and all the contributors);

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Team-spiritedness in everyday work;

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Implementation of new ideas proposed by the Foundation staff;

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Time economies;

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Stronger ties between the employees and the Foundation;

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Joint learning.

Currently, both Foundations are cooperating sharing experiences and leveraging human resources on a demand driven basis. The leaders of both organizations are working together internationally so that they can address a larger number of interesting project initiatives. Competition and hard work has been replaced by cooperation and work passion as well as trust in what is to be done. Both foundations are involved in the dissemination of culture and promoting pro-social alternative arts. Both foundations have a stable market position (at the time of crisis and cultural ignorance when even a small percentage of the population concerned by upscale culture can be regarded as a tremendous achievement). The leader of the NGO is primarily a 'selector' – focusing on people with passion and ideas and her management strategy is to create a safe space that will be filled by employee ideas, while its organizational framework will be friendly and positive.

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