Proceedings of the 8th European Conference on Innovation and Entrepreneurship ECIE 2013

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

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



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

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


Copyright The Authors, 2013. All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors. Papers have been double-blind peer reviewed before final submission to the conference. Initially, paper abstracts were read and selected by the conference panel for submission as possible papers for the conference. Many thanks to the reviewers who helped ensure the quality of the full papers. These Conference Proceedings have been submitted to Thomson ISI for indexing. Please note that the process of indexing can take up to a year to complete. Further copies of this book and previous year’s proceedings can be purchased from http://academicbookshop.com E-Book ISBN: 978-1-909507-61-6 E-Book ISSN: 2049-1069 Book version ISBN: 978-1-909507-59-3 Book Version ISSN: 2049-1050 CD Version ISBN: 978-1-909507-62-3 CD Version ISSN: 2049-1077 The Electronic version of the Proceedings is available to download at ISSUU.com. You will need to sign up to become an ISSUU user (no cost involved) and follow the link to http://issuu.com Published by Academic Conferences and Publishing International Limited Reading UK 44-118-972-4148 www.academic-publishing.org


Contents Paper Title

Author(s)

Page No.

Preface

vii

Committee

viii

Biographies

xi

Volume One Examining Determinants of Innovation Culture in Egyptian Organizations

Hadia Abdel Aziz and Sandra Marcos

1

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

Tuomo Alasoini

9

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

Petra Andries and Ute Stephan

17

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

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

26

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

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

34

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

Alina Badulescu and Roxana Hatos

45

Environmental Obstacles and Support Factors of Social Entrepreneurship

Alina Badulescu, Sebastian Sipos-Gug and Adriana Borza

52

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

Zuhal Baltas and Handan Odaman

61

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

Olimpia Ban, Esin Sayin, Dorin Coita and Ali Eleren

69

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

Fernando Barbosa and Fernando Romero

79

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

Fernando Barbosa and Fernando Romero

88

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

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

96

Organizational Innovations – Constituents and Determinants Within Underdeveloped and Immature Markets

Muamer Bezdroband Aziz Šunje

i

105


Paper Title

Author(s)

Page No.

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

Katarzyna Bratnicka, Bartłomiej Gabryś and Mariusz Bratnicki

118

Innovation and Entrepreneurship Assessment Initiatives: A Critical View

Cagri Bulut, Eda Evla Mutlu and Murat Nazli

126

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

Alex Carlos and Regina Leite

136

Individual and Mandatory Innovation in Automotive Industry: A Case Study

Cristian Chiru, Versavia Ancusa, Razvan Bogdan and Bogdan Suta

145

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

Piotr Chwastyk

154

Platform Strategies for Open Government Innovation

Brian Cleland, Brendan Galbraith, Barry Quinn and Paul Humphreys

162

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

Teresa Costa and Luísa Carvalho

173

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

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

180

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

Renata Paola Dameri, Federico Fontana and Roberto Garelli

189

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

Luc De Grez and Dirk Van Lindt

198

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

Stan De Spiegelaere , Guy Van Gyes and Geert Van Hootegem

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

Jaroslava Dědková and Denisa Skrbková

212

Towards Sustainable Business Models: Necessity, Opportunity or Challenge?

Nikolay Dentchev and Jan Jonker

221

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

Dan Constantin Dumitrescu, Nicoleta Trandafir Mănescu and Edward Debelka

228

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

Smile Dzisi, Joshua Ofori-Amanfo and Benjamin Kwofie

235

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

Luis Figueroa

243

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

Nicoleta Valentina Florea and Mihaela Badea

252

SMEs’ Internationalisation Through Strategic Alliances: A Qualitative Study

Mário Franco, Heiko Haase and Sandra Figueiredo

261

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204


Paper Title

Author(s)

Page No.

The Business Model of the Entrepreneurial University

Olaf Gaus and Matthias Raith

268

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

Oleg Golichenko and Svetlana Samovoleva

278

Involving Students in Ideas Generation – a Bulgarian Case

Elissaveta Gourova, Tzvetelina Teneva and Tsvetoslava Kyoseva

287

Emancipatory Māori Entrepreneurship in Screen Production: Theory and Application

Ella Henry

296

Research on the Trust Governance in the Venture Capital Syndication

Heyin Hou and Weixing Qu

303

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

Steen Høyrup

313

Innovative Approach in Managing the Process of Manufacturing Removable Partial Dentures

Danut Iorga, Alexandru Ghiban and Cezar Scarlat

322

Entrepreneurial behavior and interactivity of Sri Lankan farmer groups

Chandana Jayawardena and Madushi Abeyrathne

333

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

Jan Jonker and Nikolay Dentchev

340

Innovation Process Planning: Aim, Scope and Constraints

Magdalena Jurczyk – Bunkowska

347

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

Alexandros Kakouris, , Niki Perdikaki and Panagiotis Georgiadis

355

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

Tomasz Kijek

363

Employee Driven Innovation: Bridging Open and Close Innovation Management Practices

Eric Michael Laviolette, Renaud RedienCollot and Ann-Charlotte Teglborg

370

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

Jun Li and Weihe Gao

378

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

Sophie Liénart and Annick Castiaux

384

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

María Jesús Luengo, Teresa Areitio and María Obeso

392

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

Sabrina Luthfa Karim and Hanjun Huang

401

The Impact of the Economic Downturn on Innovative Performance in Poland

Anna Matras-Bolibok

409

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Paper Title

Author(s)

Page No.

Céline Maximin-Tieu

417

Failing to Succeed: A Network Theoretic Comparison of Global Accelerators

Patrick McHugh, Chris Whipple and Xiaoyang Yang

425

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

Ioana Mester and Daniel Badulescu

434

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

José Monteiro-Barata

442

Using Strategic Alliances to Facilitate Community Based new Venture Creation

Peter Moroz, Bob Kayseas and Robert Anderson

454

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

Bernd Neutschel, Olaf Gaus, Matthias Raith and Sándor Vajna

463

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

Sandra Nunes, Teresa Costa and Luísa Carvalho

471

Organizational Innovation – can job Enrichment Enhance Employee?

Morena Paulišić, Tea Golja and Barbara Unković

482

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

Ruslan Pavlov

490

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

Sebastian Pfotenhauer, Dan Roos, and Dava Newman

498

The Internationalization Process of German HighTech SMEs: An Empirical Analysis

Andreas Pinkwart and Dorian Proksch

507

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

Aneta Ptak-ChmielewskaI

515

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

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

525

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

Cristina Rodrigues and Filipa Vieira

533

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

Anna Sacio – Szymańska

543

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

Tarek Sadek and Rafik Loutfy

555

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

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Paper Title

Author(s)

Page No.

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

Josune Sáenz and Andrea Pérez-Bouvier

564

IS Resilience in SMEs in Post-Earthquake Christchurch

Amitrajit Sarkar and Stephen Wingreen

573

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

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

581

How SMEs Mitigate Risks When Embarking in Open Innovation Projects

Adrian Dumitru Tanţău and Eliza Laura Paicu (Coraş)

588

How Planguage Measurement Metrics: Shapes System Quality

Man-Chie Tse and Ravinder Singh Kahlon

597

A Study of Customer Feedback and Employee Driven Innovation

Jiro Usugami

605

Space Technology Transfer: A Systematic Literature Review

Karen Venturini and Chiara Verbano

613

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

Chiara Verbano, Karen Venturini and Avi Wasser

623

Companies’ Innovativeness Influenced by Organizational Structures

Annika Vesterinen and Kalle Elfvengren

633

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

Vessela Warren and Barry Davies

641

Student Entrepreneurial Intentions: Two Perspectives

Doan Winkel, Jeff Vanevenhoven, Mark James and Eric Liguori

649

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

Urszula Wnuk and Ludmiła Łopacińska

661

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

Danielle Wood, Sebastian Pfotenhauer, Wiljeana Glover and Dava Newman

669

Entrepreneurial Attitudes and Entrepreneurship’s Potential in East Timor

Tomas Xavier, Filipa Vieira and Cristina Rodrigues

677

PHD Papers

687

Marketing Support of Innovative Projects

Gulnara Chernobaeva

689

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

Anneline Chetty

698

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

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

705

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

Frédéric Dufays

715

Innovations, Standards and Quality Management Systems: Analysis of Interrelation

Raimonda Liepiņa, Inga Lapiņa, Jolanta Janauska and Jānis Mazais

723

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Paper Title

Author(s)

Page No.

Achieving Performance of Organization by Developing a Model of Innovation Management

Andreea Maier, Marieta Olaru, Dorin Maier and Mihai Marinescu

731

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

Dorin Maier, Marieta Olaru and Andreea Maier

739

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

Petra Merenheimo

747

Firms’ Response to Peer Behaviour

Daniel Neicu, Stijn Kelchtermans and Peter Teirlinck

755

Firm Structure and Problems of Governance in the Italian SMEs

Adalberto Rangone

762

Understanding Entrepreneurial Performance in a Networked Social Environment

Carla Riverola and Francesc Miralles

773

Performance Measurement and Management in SMEs

Ted Sarmiento and David Devins

782

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

Dorotéa Silva, Fernando Romero and Filipa Vieira

791

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

Nazlihan Ugur

797

Non Academic Papers

808

Incubators as Enablers for Academic Entrepreneurship

Frank Gielen, Sven De Cleyn and Jan Coppens

809

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

Janet Lea Sernack

818

Work in Progress Papers

825

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

Daniel Badulescu and Mariana Vancea

827

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

Vítor Figueiredo and Mário Franco

831

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

Bart Henssen

835

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

Julie Hermans

838

Finding New Competitive Intelligence: Using Structured and Unstructured Data

Ravinder Singh Kahlon and Man-Chie Tse

842

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

Karla Phlypo

847

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

Angela Poulakidas, Robert Hisrich and Claudine Kearney

851

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

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

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

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

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

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

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

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

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

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

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

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Biographies of Presenting Authors Dr. Hadia H. Abdel Aziz is an Assistant Professor of Entrepreneurship and Innovation Management at the German University in Cairo. She has vast practical experience in the areas of SME financing, financial innovation and entrepreneurship which also constitute her main research interests. Dr. Tuomo Alasoini coordinates workplace innovation and development activities in Tekes (the Finnish Funding Agency for Technology and Innovation). He is Adjunct Professor of Sociology at the University of Helsinki and director of Tekes programme “Liideri – Business, Productivity and Joy at Work”. He is an active member of the European Workplace Innovation Network EUWIN. Versavia Ancusa received her PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. She is currently a Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Ancusa’s main research interests are affective computing, fault tolerance and reliability, complex networks. Robert B. Anderson is a Professor of entrepreneurship with the University of Regina. He has authored or coauthored more than 150 peer-reviewed articles (more than 40 of these refereed journal articles) on economic development and entrepreneurship, two books on the subject and co-authored of a third, and co-edited of a handbook research on indigenous entrepreneurship. Petra Andries (petra.andries@kuleuven.be) is a senior researcher at the Centre for R&D Monitoring (KU Leuven). Her research interests are in innovation management and entrepreneurship in general, with a particular interest in new venture development, collaborative innovation and knowledge management. Paula Anzola Román, BA, MBA is a Researcher/contributor at the Department of Business Administration at Public University of Navarra. Her research has been focused in Open Innovation and Business Models. María Teresa Areitio, PhD is University Professor at Department of Industrial Economics at the University of Basque Country, Spain. She has managed some research projects and she has contributed to scholar area with articles and books. Her current work focuses on knowledge management, TICs and innovation in the EHEA and international economy. Manuel Luís Au-Yong Oliveira earned a distinction for his PhD degree in Industrial Engineering and Management from the University of Porto and is currently a part-time lecturer both at the University of Aveiro and at the University of Porto. Manuel is affiliated to INESC TEC. Alina Badulescu is Professor of Economics and PhD coordinator at the Faculty of Economics and Doctoral School in Social Sciences of the University of Oradea, Romania. She graduated Bucharest University of Economics and since she has authored and co-authored numerous journal articles and books. Her interests include economics, but promoting young researchers’ activity as well. Daniel Badulescu graduated Bucharest University of Economic Studies and has a PhD in Economics. He is Associate Professor in Business Economics and Business Financing at the Department of Economics, University of Oradea, Romania. His current research interests include economics, business economics and business finance. Olimpia-Iuliana Ban Ph.D. in Marketing, West University of Timisoara, Romania, 2005. Now is associate professor and Head of Economy Departament at University of Oradea. Fernando Barbosa is an invited lecturer in the Department of Production and Systems Engineering at the Engineering School of the University of Minho. He holds a B.Sc. in Management from Portucalense University, and an M.Sc. in Industrial Engineering from the University of Minho. He is a Business Consultant and Trainer in several organizations. Bartłomiej J.Gabryś is Assistant Professor at Chair in Entrepreneurship at the University of Economics in Katowice, Poland. He received his Ph.D. in corporate entrepreneurship. His present research focuses in the area

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of corporate entrepreneurship and growth. His research were presented at EURAM, BAM, AOM, ISBE, RENT conferences or published by Wolters/Kluver and Routledge. Muamer Bezdrob is a cofounder and director of the PING ltd. Sarajevo. He graduated at the Faculty of Electrical Engineering in Sarajevo, where he was an assistant professor. He earned his MSc and his PhD at the School of Economics and Business in Sarajevo. Muamer lives in Sarajevo with his wife and their son. Razvan Bogdan received his PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. He is currently Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Bogdan’s main research interests are in dependability of computer systems, human-machine interfaces, embedded systems, complex networks. Katarzyna Bratnicka, is Ph.D. student at the University of Economics in Katowice, Poland. She received her Master degree in human resources management. Her present research focuses in the area of corporate entrepreneurship and creativity. Her research was presented at EURAM, BAM, AOM and ISBE conferences. Mariusz Bratnicki, is a Professor in management and holds the position of head of Chair in Entrepreneurship at the University of Economics in Katowice, Poland. His present research focuses on the area of corporate entrepreneurship, creativity and organizational performance. His research were presented at EURAM, BAM, AOM, ISBE, RENT conferences or published by Routledge. Dorotéa Bueno da Silva is Ph.D. Student in Industrial and Systems Engineering at the Production and Systems Department, School of Engineering, University of Minho, Portugal. She obtained a Master degree in Industrial Engineering at the Production Engineering Pos-Graduate Department, Paraíba Federal University, Brazil after graduating in Psychology at the Paulistana University, Brazil. The theme of her doctoral research is evaluation of innovation programs for SME, with a special focus on the evaluation of their indirect effects. Cagri Bulut is Associate Professor of Management, Ambassador of ENT-Division, of Academy of Management to Turkey, and Chair of Department of Business Administration, Faculty of EAS, Yasar University, Turkey. Alex Lôbo Carlos is a Brazilian Navy Officer, born in Rio de Janeiro in 1974. He graduates in Nautical Sciences and postgraduates in economics. Currently he is completing a Master in Management at the University of Minho, Portugal. Luísa Carvalho: Professor of Economics, Entrepreneurship and Innovation. Department of Economics and Management, Business School – Setúbal Polytechnic Institute – Portugal since 1999. Researcher in CEFAGE – University of Évora- Portugal. PhD in management, McS in economics. Author of several publications in national and international journals and book chapters. Pr. Annick Castiaux holds a PhD in Physics from the University of Namur and teaches innovation and technology management. Her research considers a systemic approach of innovation, trying to detect paradoxes that can lead to emergent technologies or business models. She focuses on agent-based simulations, to realise in silico experiments helping to understand innovation strategies. Paula Castro is a Undergraduate Student, University of Sao Paulo, Brazil. Develop a international internship in Business School – Setúbal Polytechnic Institute during 1st semester of 2013. Gulnara Chernobaeva is an Associate Professor and Post-doctoral Fellow at the Department of Innovation and Project Management, Omsk State University, Russia. She teaches several marketing courses. Her main research interest is marketing communications. Currently, she investigates marketing project support. Gulnara additionally has extensive experience of working as Head of Marketing at leading Omsk companies. Dr Anneline Chetty completed a Masters in Town & Regional Planning and a PH.D with a focus on Public and Private sector approaches towards the provision of Business Development services for SMMEs in the eThekwini Municipality. Authored the book: Promoting entrepreneurship in South Africa. Excellent understanding of Economic development issues globally.

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

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

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

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Chandana Jayawardena - BSc (Hons), MBA. is presently a doctoral researcher attached to the Department of Management and Marketing, Faculty of Management and Economics, Tomas Bata University in Zlin, Czech Republic. His research interests focus on Career Development, Managerial Competencies, and Employees Behaviour at work. He is an academic staff member of the University of Peradeniya, Sri Lanka Jan Jonker is a Professor of Corporate Sustainability at the Nijmegen School of Management of the Radboud University Nijmegen (The Netherlands). His research interest are in sustainable strategy development, (new) business models and transition thinking. Magdalena Jurczyk-Bunkowska studied production management at Warsaw University of Technology, where she received a PhD title in 2004. Currently, she works at Opole University of Technology as a researcher and lecturer. She was a member of Polish Academy of Science. Now, her fields of research and interest are innovation management especially operational approach covering innovation process planning. Ravinder Singh Kahlon is a PhD student at Ulster University. His research interest surrounds KM Strategies and Systems, especially in performance measurement metrics and critical success factors implementing KM within organisations. He works with IT consultancies that specialises in top-quality innovative IT Solutions, to enable KM within organisations. Tomasz Kijek, PhD in Economics conducts teaching and research activities in the Department of Economics and Management at the University of Life Sciences in Lublin, Poland. His research interests focus on innovation, innovation capital, knowledge and a firm’s competitiveness. He is the author and co-author of several scientific publications, including chapters of monographs and articles. Beti Kostadinovska Dimitrovska, a Ph.D. student at the Faculty of Economics-Skopje, works as a Project officer in the European Information and Innovation Centre in Macedonia within the Ss. Cyril and Methodius University in Skopje. Beti is responsible for the research and innovative component providing innovative, R&D and IPR services to SMEs and academia sector. Eric Michael Laviolette Associate Professor of Strategy and Entrepreneurship at Novancia Business School, Paris with a doctoral degree in Management at University of Lyon. His research builds on organizational and management theories to analyse entrepreneurial processes within innovation systems. He has published several papers on spin-offs, incubators, entrepreneurial skills & leadership development and international entrepreneurship. Regina Leite is an Assistant Professor in organizational behaviour and HRM in the School of Economics and Management at the University of Minho. She received the PhD degree in management from de University of Minho. Her current research interests include work and non-work spheres, organizational commitment, privacy issues, sexual harassment, change and innovation. Bart Leten is Assistant Professor in Innovation Management at the Vlerick Business School and the KU Leuven (MSI department). His research focuses on corporate innovation and international business strategies, and deals with various topics such as open innovation, IP strategies, industry-science links, R&D internationalization and organizing for innovation. Sophie LiÊnart is a 4th year PhD student in Management Science from the University of Namur, Belgium. Under the supervision of Pr. Dr. Annick Castiaux, she is researching the integration of energy efficiency requirements into the innovation process of information technology products and services, and its impact on business strategy. Raimonda Liepiņa, Mg.oec., Lecturer of Riga Technical University, Faculty of Engineering Economics and Management, Department of Quality Technologies. Almost 10 year experience as Head of Conformity Assessment Coordination Division in the Internal Market Department of the Ministry of Economics of the Republic of Latvia. Area of research interests: conformity assessment, among them standardization, accreditation, metrology.

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

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

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

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

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

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

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Failing to Succeed: A Network Theoretic Comparison of Global Accelerators Patrick McHugh, Chris Whipple and Xiaoyang Yang Brown University, Providence RI, USA pmchugh@brown.edu christopher_whipple@brown.eu xiaoyang_yang@brown.edu Abstract: Accelerators are firms that invest small amounts of capital in early‐stage companies, typically for a 4% to 10% equity stake, and provide mentoring for limited time periods, typically 3 to 4 months, to help build the business case to support these firm’s future funding needs. During the mentoring periods accelerator management is actively involved with the portfolio firms and provides extensive networking support. The 2012 publication U.S. Seed Accelerator Rankings identified 71 U.S. accelerators and noted that their numbers are growing rapidly. In the U.S. alone it is estimated that more than 1,400 start‐up companies are mentored annually by such firms. Accelerators are also growing rapidly and have become critical nodes in the entrepreneurial ecosystem. Understanding relative accelerator performance and the characteristics driving superior performance can have a multiplier effect on overall start‐up success. To that end, we consider two research questions in this paper: Do top‐ranked accelerator portfolio firms display similar survival rates? And, what accelerator characteristics correlate with variations in portfolio firm survival? Network theory informs the hypotheses investigated in this study. In this study we compare the survival performance of accelerator portfolio firms in Silicon Valley and Ireland to those of other leading geographically dispersed accelerators. An analysis of the node characteristics in these ecosystems suggests that Silicon Valley portfolio firms will experience higher failure rates and Irish accelerator portfolio firms will experience lower failure rates then other regions. In contrast, network theory also suggests that hubs, such as accelerators, can help embed nodes, such as start‐ups, in preferred networks and that such networking can enhance firm outcomes, such as survival. Network theory also suggests that establishing network ties comes at a cost, and that accelerator and start‐up resources must be adequate to enable useful network connections. Smaller cohort sizes and larger capital investments are evaluated to determine if the additional resources resulting from these practices benefit firm survival. The resulting hypotheses are evaluated via t‐tests and regression analyses on data from the portfolio firms of 18 top‐ranked accelerators. Our results suggest that Irish accelerator portfolio firms experience lower failure rates than portfolio firms from other regions. Interestingly these results demonstrated only modest absolute differences in regional outcomes despite significant differences in the outcome objectives of the regional funding sources in Silicon Valley and Ireland which were considered in detail. Variation in accelerator practice on funding levels and cohort size were not found to significantly impact firm outcomes although accelerator experience was found to be significant to portfolio firm survival. Keywords: accelerators, start‐up networks, entrepreneurship, firm survival

1. Introduction The first seed accelerator was the “Summer Founders Program” which aimed to combine seed‐stage investing with mentorship for young entrepreneurs. The program became the well‐known accelerator Y Combinator. This success started a global movement of institutions that combined funding and education services for entrepreneurs. Accelerators have become an increasingly important part of the tech start‐up scene. These programs provide new entrepreneurs with mentorship, advice and practical training on technical, business and fundraising topics to help them get from idea to product to launch and beyond. The accelerator typically takes an equity stake in the firm in exchange for a small amount of cash and entry into the program. Understanding relative accelerator performance and the characteristics driving superior performance can have a multiplier effect on overall start‐up success. To that end, we consider two research questions in this paper: Do top‐ranked accelerator portfolio firms display similar survival rates? And, what accelerator characteristics correlate with variations in portfolio firm survival?

2. Literature review Accelerators and their portfolio firms operate in geographic regions that vary significantly in the level of support available to start‐up firms. While all the accelerators considered in this study are “leaders” they represent significant geographic dispersion, including several from the regionally rich entrepreneurial ecosystems of Silicon Valley and Ireland. Silicon Valley and Ireland were the regions with the largest number of top ranked accelerators in this study. To inform our understanding of regional differences and their potential

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Patrick McHugh, Chris Whipple and Xiaoyang Yang impact of firm survival these two regions were compared to the others in our data. We also consider the impact of networks and accelerator practice on firm performance.

2.1 Geographic context Varieties of capitalism theory suggests that varying national institutional frameworks, such as financial markets or labor, creates divergence in business practice between localities (Hall and Soskice 2001, Hollingsworth 1997). The active role of government in shaping technology policies makes them an important player to consider in these comparative studies (Casper, 2007). As an example of such variation, Rosenberg (2002) notes difficulties, outside the U.S, for venture firms to syndicate deals (limiting available capital) and to identify experienced managers to staff their portfolio firms. These regional ecosystem differences can impact relative firm performance. We next specifically consider the Silicon Valley and Irish entrepreneurial ecosystems, the two regions with the largest number of top ranked accelerators in our study. 2.1.1 Silicon Valley’s networked ecosystem Many regions try to emulate Silicon Valley, such as the Silicon Plateau in Bangalore, India and the Silicon Bog in Dublin, Ireland (Munford 2013). Lee et al (2000) suggest a number of features of Silicon Valley’s environment critical to its success including a high‐quality/mobile work force, results‐oriented meritocracy, risk‐taking norm, tolerance of failure, and an open business environment. As noted by Bahrami and Evans (1995) Silicon Valley technology firms have a very high failure rate, yet the region continues to thrive. They credit this success to an ecosystem of flexible recycling of failures supported by swift action and continuous inter‐firm mobility of staff. This extensive mobility creates dense personal networks throughout the region (Lee 2000). New companies are constantly being formed in the Valley with 1,749 seed funding rounds reported in 2012 (Kramer and Patrick 2013). At a personal level, Silicon Valley entrepreneurs are perceived as being motivated to “change the world”, going beyond the strong success motivator observed in entrepreneurs more broadly (Lee, 2000). This tolerance of failure, speed of response and richness of alternatives suggest that the stakeholders in a Silicon Valley early stage venture will be motivated to quickly evaluate opportunities and cull lower potential investments quickly. This rapid re‐direction suggests the following hypothesis: H1: Silicon Valley accelerator portfolio firms will see lower survival rates than accelerator portfolio firms in other regions. 2.1.2 Ireland’s entrepreneurial ecosystem Ireland has seen much success developing its technology driven economy. The country has been rated as a top destination for foreign direct investment and second in Europe for its rate of entrepreneurial activity. There are 14 venture firms active in the country with complementary seed and development capital provided by Enterprise Ireland, a public sector organization. In 2011 63 start‐ups received seed funding creating a total pipeline of 200 early stage high growth potential firms in the country (IVCA 2012). Enterprise Ireland defines High Potential Start‐Up (HPSU) firms as businesses with the potential to develop an innovative product or service for sale in international markets with the potential to create 10 jobs and €1m in sales within 3 to 4 years. The key strategic mission of Enterprise Ireland is growth of wealth and employment creation (Enterprise Ireland 2013). Historically financial failure in Ireland has been viewed harshly in the Irish legal system with severe penalties for bankruptcy (although these laws are currently being reconsidered). The Irish early stage investment ecosystem has much fewer nodes then that in Silicon Valley. Its seed capital funding is also provided by an enterprise with a success metric of both modest financial performance and job creation. With fewer alternative opportunities in the network stakeholders are posited to be more likely to work to sustain and build an existing opportunity as opposed to shifting their investment of time and capital rapidly, suggesting the following hypothesis: H2 Irish accelerator portfolio firms will see higher survival rates than accelerator portfolio firms in other regions.

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Patrick McHugh, Chris Whipple and Xiaoyang Yang

2.2 Network theory Accelerators help start‐ups build their networks. Network nodes are the actors or agents between whom relationships form in a network (Scott 2000). Complex network theory (CNT) provides a useful theoretical framework for analysis where there are heterogeneous self‐organized nodes, such as we see in start‐up networks (Ferrary and Granovetter 2009). CNT acknowledges that networks are not randomly structured (Newman 2003; Newman, Barabasi and Watts 2006) and that their structure results from the behaviour of the networking nodes (Granovetter 1973). The complex network approach suggests a need to holistically analyze networks (Gulati, Nohria and Zaheer 2000, Zaheer, Gozubuyuk and Milanov 2010) highlighting the importance of heterogeneity and completeness to explain the weakness or the robustness of a network. Nodes can serve as hubs that, without hierarchical authority, orchestrate network activities to ensure the creation and extraction of value (Dhanaraj and Parkhe 2006). Ferrary and Granovetter (2009) suggest that hubs, such as seed accelerators, can perform signalling and embedding roles on behalf of the start‐up firm. Node fitness is defined as a node’s ability, competence or aptitude (Bianconi and Barabasi 2001; Barabasi 2002) and CNT suggests that nodes with higher fitness should be linked to more frequently. Most complex networks display a fit‐get‐rich behaviour with the fittest node eventually gaining the most connections (Barabasi, Newman et al. 2006). Since seed accelerators help embed start‐ups in their networks, better connected accelerators should lead to better connected portfolio firms. Better network connections should improve the start‐ups fitness leading to enhanced firm success and accelerators with more experience are posited to have had the time to build these network connections, suggesting the following hypothesis: H3 Portfolio start‐up firms will see higher survival rates if their accelerator has been operational for a longer period of time. Expanding and maintaining network connections for a new start‐up comes at a cost. Burt (1992) and Hansen (1999) note that time and energy are limited and that there is an upper bound to the benefits provided by network connections set by the time and resources available to an agent. These observations suggest that having more resources, such as improved assistance from accelerator staff due to smaller cohort sizes or increased capital investment, can lead to enhanced benefits to an accelerator portfolio firm. These observations suggest our final two hypotheses: H4 Portfolio start‐up firms will see higher survival rates if their accelerator has smaller cohort sizes. H5 Portfolio start‐up firms will see higher survival rates if their accelerator provides larger capital investments.

3. Methodology and results To analyze these hypotheses data was collected on the portfolio firms of leading global accelerators. The dependent variable used as a success measure was firm survival. Firm survival was measured by firm status postings on the accelerator’s website (Y combinator and Tech Stars) or by the existence and currency of the firm’s website. Web site status data was collected via web searches for firms started in 2011 or earlier to assure a minimum of 1+ years between the firm’s entry into the accelerator and its’ web presence . This was done to control for delays in website removal due to prepayment of hosting services. Firm survival is a common metric of entrepreurial firm performance (SBA 2013).

3.1 Data An online query for the “Best Accelerators in America” identified 4 industry rankings which were then compiled into a master list. 20 unique accelerators were thus identified. A few accelerators were featured in all 4 lists. For the analysis we focused on accelerators that showed up in more than 1 list, narrowing our research to 10 U.S. accelerators. A similar query for “Best International Accelerators” identified a ranking of 8 additional unique global accelerators for analysis. To calculate portfolio company failure rates, we identified the list of sponsored companies from each accelerator. This information was available from the accelerator websites. If the accelerator advertised whether the companies were active, out of business or acquired, we simply took those figures as fact. Otherwise, we went through and checked each company to see if they were still active. Our definition of active was having an active website updated within the last year (2012). A Google search on the company names was conducted to look for their website. If this yielded nothing, we next looked into their

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Patrick McHugh, Chris Whipple and Xiaoyang Yang Crunchbase profile, looking for either a more up to date link to their website, or information about acquisitions or business failures. If this still did not give us an answer, we Google searched for the company name and the word “acquired”, looking to find an article about an acquisition. If all these paths yielded no information we considered the company out of business. A language barrier existed for some of global companies, even if they attended an accelerator in the U.S. complicating the data collection. Also complicating the search was that most of the foreign accelerators did not have their companies use Crunchbase, as none of the companies from the global accelerators had a Crunchbase profile. This process was followed for each accelerator, with the exception of Y Combinator and Tech Stars. Both Tech Stars and Y Combinator published lists of their portfolio companies with current statistics about their state as a company, falling under the 3 categories of active, out of business, or acquired. For all companies, where the data was available, we recorded the name of the company, the year the company was sponsored, the current link to the website, and where the company was sponsored (if an accelerator had multiple locations, like Dream It Ventures), and recorded its status with a 1 if it was active or acquired, or a 0 if it was out of business. Survival data on 1,105 firms were included in the analysis.

3.2 Methods T‐tests were conducted for an initial analysis of hypotheses. The entire data set of 1,104 firms were included in the analysis. This analysis was then complemented with a logistic regression to provide a more nuanced understanding of the hypotheses. A dummy variable, coded as 1 if the accelerator was located in Silicon Valley, was created to analyze hypotheses 1. A dummy variable, coded as 1 if the accelerator was located in Ireland, was created to analyze hypothesis 2. The accelerator’s experience, measured by the length of time the accelerator had been in business prior to working with the portfolio firm, was used as a proxy for the accelerator’s network connectivity for the analysis of hypothesis 3. Since survival has a temporal dimension (it is harder to survive for 3 years than for 1) a control was added for the “age” of the portfolio firm. Variables for the average cohort size and capital invested were also included to evaluate our final hypotheses. The logistic regression model used in the analysis follows: DV (firm web site survival) = β0 + β1(Silicon Valley location) + β2(Ireland location) + β3(2012 – year company graduated from the accelerator) + β4(accelerator experience) + β5(cohort size) + β6(capital invested). For the regression analysis firm level data from seven accelerators could not be included in the final analysis. Tetuan Valley in Spain includes an incubator as well as an accelerator so the data from this site was dropped from both analyses. Springboard in the U.K. is a new accelerator with no performance data available yet for their portfolio firms. For Tech Stars, Y Combinator, 500 Start‐ups, NDRC LaunchPad and Open Network Lab we do not have sponsored years for the portfolio firms precluding the use of our control variable. A sample size of 253 firms remained for the regression.

3.3 Descriptive observations Table one and two provide descriptive information about the accelerators analyzed in this study Table 1: U.S. accelerators ranked by failure rates

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Patrick McHugh, Chris Whipple and Xiaoyang Yang Table 2: Global accelerators ranked by failure rate

The average 1 or more year survival rate for Silicon Valley accelerator portfolio firms (578 firms from 4 accelerators) was 89.5%. The average 1 or more year survival rate for Irish accelerator portfolio firms (70 firms from 3 accelerators) was 95.8%. Finally, the average 1 or more year survival rate for all other top ranked global accelerators (456 firms from 9 accelerators) was 89.5%. At a descriptive level the Irish portfolio firms appear to have a higher survival rate then those of other leading global accelerators. In general, the survival rate of the accelerator’s portfolio firms is significantly higher than that for general U.S. start‐ups. The U.S. Small Business Administration notes that 70% of employer firms survive at least two years (SBA 2013) while the two year survival rate for the firms in this analysis was 79.4%. Accelerators with more than 1 year experience at the point where a firm entered their service were observed to have portolio firm survival rates of 89% compared to 83% for accelerators with less experience suggesting support for hypothesis 3. Figure 1 provides a breakdown of accelerator expereince at the point when the various portfolio firms engaged.

Figure 1: Accelerator experience at time of portfolio firm engagement Cohort size was evaluated for intakes with less than or equal to 20 firms. Little variation in firm survival rates were observed (85.8% and 85.5% respectively) suggesting no support for hypothesis 4. Average cohort size varies significantly among accelerators; however within a very small range as noted in Figure 2.

Figure 2: Accelerator cohort size

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Patrick McHugh, Chris Whipple and Xiaoyang Yang Finally, investment levels were considered where portfolio firms with investments of > $25,000/firm having survival rates of 88.4% and those with ≤ $25,000 of investment having survival rates of 81.9% suggesting support for hypothesis 5 from these descriptive statistics.

Figure 3: Accelerator investment capital In the next section, we consider whether these descriptive observations are statistically significant.

3.4 Results 3.4.1 t‐test results To evaluate hypotheses t‐tests and logistic regression were conducted. The t‐test for the survival of Silicon Valley accelerator portfolio firms versus all other portfolio firms was found to not be significant. The mean failure rate for the Silicon Valley firms was 11% versus a 10% rate for the alternative locations. The t‐test comparing the Irish accelerator portfolio firms versus all other portfolio firms was found to be significant at a 90% confidence level. The t = ‐1.695, df = 86.254, Sig = 0.094 and the mean difference in failure rate is ‐ 5% with a standard error of +/‐ 3%. The t‐tests are not supportive of hypothesis 1 that Silicon Valley portfolio firms will have higher failure rates than those in other locations; however, at a 90% confidence level, the t‐test results are supportive that Irish accelerator portfolio firms do have lower failure rates that those in other locations. The t‐tests for the accelerator characteristics of experience, cohort size and investment levels were all found to not be significant providing no support for hypotheses 3 through 5. 3.4.2 Logistic regression analysis Logistic regressions require that observations be independent requiring tests for bivariate and multicollinearity among the predictor variables. Table 3 presents the results of the bivariate correlation analysis indicating numerous correlations among the predictor variables. A tolerance test indicated multicollinearity concerns as well. Based on these results the variables in the logistic regression model needed ot be adjusted. The new model was run incorporating only two variables, SV and Completion date – accelerator start date, our expereince measure (note “Ireland” was dropped as a variable since only 6 of the original 70 firms remained in the dataset providing too small a sample for analysis). The logistic regression overall model was found to be significant with a Chi‐square of 7.493 and a Sig = 0.024. 2 2 The Cox and Snell R was equal to 0.29 and the Nagelkerke R was equal to 0.052. the classification table indicates the models predictive efficacy at 85.8% however this was achieved by assuming all firms in the database survive. Figure 4 shows that the “accelerator experience” variable is significant. The odds ratio (Exp(B)) suggests that the odds of survival increase by 1.459 for each year increase in the accelerator’s experience.

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Patrick McHugh, Chris Whipple and Xiaoyang Yang Table 3: Bivariate correlations among logistic regression predictor variables

Table 4: Variables in the logistic regression equation

4. Discussion In summary our empirical results provide support for hypotheses 2, that Irish accelerator portfolio firms will experience superior survival rates and hypothesis 3 that portfolio firms of more experienced accelerators will experience superior survival rates. Hypotheses 1,4 and 5 were not supported by our analyses. In this study we took a network theoretic view. As CNT suggests, we evaluated both the nature of the nodes, such as variation in the ojectives of regional capital providers and entrepreneurs, and the characteristics of the ties, with more ties anticipated in rich entrepreneurial ecosystems such as Silicon Valley. In Silicon Valley the nature of the nodes suggested a potentially reduced survival rate for portfolio firms while the rich ecosystem, and its radily available ties, could be expected to drive superior survival, creating counter pressures on this outcome. In Ireland the nature of the nodes and the locally rich eco‐system both suggest superior portfolio firm survival. This variation in pressure from the regional nodes and ties is visualized in Figure 5.

Table 5: Varying directional network pressures on portfolio firm survival outcomes These varying pressures and outcomes do raise the question of what is the “best” measure of success. Is firm survival even an appropriate measure? If Silicon Valley accelerator portfolio firms had experienced lower survival rates, as we anticipated, would this have been a “bad” thing? We suspect not. For example, failing to succeed is a well known mechanism in Silicon Valley as noted in our literature review. We suggest that the

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Patrick McHugh, Chris Whipple and Xiaoyang Yang critical question is are the outcomes supportive of the objectives of the key stakeholders, such as the local investors and entrepreneurs in the region? An interesting observation from this study is not just that Irish accelerator portfolio firms have superior survival rates but that these rates are only modestly different from those of the other accelerators observed in this study. These accelerators operate in 12 different regions with quite different ecosystems; however, outcomes, at least as measured by firm survival, are quite similar. Another interesting observation from this study is the similarity in processes between the various accelerators. Investment levels varied within a $50,000 range and cohort size varied between 5 and 20 firms. This tight bandwidth of variation may explain our inability to detect statistically significant differences in performance between the accelerators on these variables; the variation may be occurring in such a tight band that it is not statistically material to outcome, as we observed. Our logistic regression analysis did suggest that accelerator experience matters to firm survival. Accelerators, when new (< 1 year old), have reduced survival rates for their portfolio firms. This observation that experience matters is theorized in the context of network deveopment; however, alternative explations, such as operational improvements or superior selectivity with experience are equally possible. Finally, the newness of the accelerators was also quite startling. In this study we analyzed the top accelerators in the world and none of them had portfolio firms that “graduated” from their programs more than 4 years ago. This is a new and evolving industry worthy of continued analysis as we suggest in the next sections.

4.1 Implications for practice This study has important implications for practice. It suggests that location does matter; however, its’ impact is quite modest, once one is working with well rated accelerators such as the ones analyzed in this study. It suggests that at the early stages of firm development working with respected accelerators outside Silicon Valley will not negatively impact a new firms ability to survive. Finally, when selecting an accelerator to work with, the benefit of acclerator experience was noted.

4.2 Future work This study is exploratory in nature. We focused on the leading global accelerators, the majority of whom operate in developed regions, many of which are extremely rich entrepreneurial ecosystems such as Silicon Valley and Dublin, Ireland. The results of this work needs to be compared to accelerators operating in less well established regions and regions with greater diversity in terms of the local objectives of critical stakeholders, such as early funding providers. Qualitative studies are also needed to understand why accelerator experience, which is developed quite rapidly, is so beneficial to the accelerator portfolio firm survival outcome. Finally firm survival is a basic measure of outcome. It would be informative to focus on additional outcome measures such as capital raised or venture relationships established as better measures of the scalability of the accelerator portfolio firms.

References Barrami, Homa and Evans, Stuart. (1995) “Flexible Recycling & High‐Technology Entrepreneurship”, California Management Review, Vol 37, No. 3. Barabasi, A. (2002) Linked: the new science of networks, Perseus, Cambridge, MA. Baxter, W. (2010) “Why Reform of Ireland’s Bankruptcy Legislation is Urgent”, Accountancy Ireland, Vol 42, No 5, pp 7‐8. Bianconi, G. and Barabasi, A. (2001) "Competition and multiscaling in evolving networks", Europhysics Letters, Vol 54, pp 436‐442. Burt, R. (1992) Structural Holes: The Social Structures of Competition, Harvard University Press, Cambridge, MA. Chong‐Moon, L., Miller, W., Hancock, M., Rowen, H. (2000) The Silicon Valley Edge, Stanford University Press, Stanford, CA. Casper, S. (2007) Creating Silicon Valley in Europe, Oxford University Press, Oxford. Dhanaraj, C. and Parkhe, A. (2006) "Orchestrating Innovation Networks", Academy of Management Review, Vol 31, No. 3, pp 659‐669. Enterprise Ireland. (2013) https://www.enterprise‐ireland.com/en/funding‐supports/Company/HPSU‐Funding/ Ferrary, M. and Granovetter, M. (2009) "The role of venture capital firms in Silicon Valley's complex innovation network", Economy and Society, Vol 38, No 2, pp 326‐359. Granovetter, M. (1973) “The Strength of Weak Ties”, The American Journal of Sociology, Vol 78, No 6, pp 1360‐1380.

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Patrick McHugh, Chris Whipple and Xiaoyang Yang Gulati, R, Nohria, N, and Zaheer, A. (2000) “Strategic Networks”, Strategic Management Journal, Vol 21, pp 203‐215. Hall, J. and Hofer, C. (1993) "Venture capitalists' decision criteria in new venture evaluation", Journal of Business Venturing, Vol 8, pp 25‐42. Hall, P. and Soskice, D. (2001) Varities of Capitalism, Oxford University Press, Oxford, U.K. Hansen, M. (1999) “The search transfer problem: the role of weak ties in sharing knowledge across orgainzation subunits”, Administrative Science Quarterly, Vol 44, No 1, pp 82‐111. Hochberg, Y. and Kamath, K. (2012) U.S. Seed Accelerator Rankings: http://www.kellogg.northwestern.edu/faculty/hochberg/htm/Accelerator%20Companion%20FINAL.pdf Hollingsworth, R. and Boyer, R. (1997) Contemporary Capitalism: the Embeddedness of Institutions, Cambridge University Press, New York, N.Y. IVCA. (2012) http://www.ivca.ie/wp‐content/uploads/2012/04/IVCA‐Ire‐The‐vestment‐Opp‐.pdf Kaplan, S., Sensoy, B. and, Stromberg, P. (2009) "Should Investors Bet on the Jockey or the Horse? Evidence from the Evolution of Firms from Early Business Plans to Public Companies", The Journal of Finance, Vol 64, No. 1, pp 75‐115. Kramer, B and Patrick, M. (2013) “Silicon Valley Venture Capital Survey – Fouth Quarter 2012” http://www.fenwick.com/publications/pages/silicon‐valley‐venture‐survey‐fourth‐quarter‐2012.aspx Munford, M. (2013) “Silicon Plateau, Silicon Gulf and Silicon Bog: who can match the Valley” The Telegraph, http://www.telegraph.co.uk/technology/news/9918665/Silicon‐Plateau‐Silicon‐Gulf‐and‐Silicon‐Bog‐who‐can‐match‐ the‐Valley.html Newman, M. (2003) “The Structure and Function of Complex Networks”, SIAM Review, Vol 45, No 2, pp 167‐256. Newman, M., Barabasi, A., and Watts, D. (2006) The structure and dynamics of networks, Princeton University Press, Princeton, NJ. Rosenberg, D. (2002) Cloning Silicon Valley, Pearson Education, London. SBA (2013) http://web.sba.gov/faqs/faqindex.cfm?areaID=24 Scott, J. (2000) Social Network Analysis, SAGE Publications, Thousand Oaks, CA. Zaheer A, Gozubuyuk R, and Milanov H (2010) “It’s the connections: The network perspective in interorganizational research”, Academy of Management Perspectives, Vol 24, No 1, pp 62‐77.

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Sustainability Among Tourism and Hospitality Industry’s Ventures: From Awareness to Specific Practices Ioana Mester and Daniel Badulescu University of Oradea, Romania imester@uoradea.ro daniel.badulescu@gmail.com Abstract: Sustainable entrepreneurship as environmentally friendly entrepreneurship focused on responsibilities to future generations has special meaning in tourism and hospitality industry. Indeed, tourism relies on clean, un‐altered natural environment. Hence, firms involved in these fields are supposed to be more aware of the importance of sustainability issues and also more informed about and to possess more elaborate knowledge about these concerns. Furthermore, customers in tourism and hospitality are assumed to be more interested in supplier attitudes and practice regarding sustainability. As already stated in literature, implementation of sustainable business practices generates gains and benefices, even if much of them are unfortunately defined as losses avoided (in terms of image, reputation, potential customers etc.). Moreover, life‐style entrepreneurs and the principle of ‘acting locally’ are of particular importance in tourism and hospitality industry. Consequently, a lot of instruments and techniques have emerged to promote sustainable business, i.e. codes, labels, audits etc. Our paper investigates the question of sustainability‐oriented attitudes and practices among ventures operating in the tourism and hospitality industry. Using a survey‐based research, we address particular issues such as: Are ventures operating in tourism and hospitality really concerned about sustainability and the impact of their activities on the environment?, Which are the factors driving venture concern about sustainability and environmental impact?, What is their perception on the benefices and gains associated with sustainability practices? What do firm managers/representatives think about sustainability as a competitive advantage in attracting visitors/customers? Do they have adequate related knowledge? Have they actually undertaken specific measures to make their business more environmentally friendly, e.g. energy saving, use of renewable energy, water management, waste management, use of eco products, alternative fuels, promoting local products/attractions etc.? Keywords: sustainability attitudes and practices, tourism and hospitality industry, survey

1. Introduction Environmental related concerns have preoccupied the public policy agenda and business initiatives for more than three decades, fuelled by the fear of the scarcity of the natural resources, the rapid pace of human development and its implications for future generations. The issue of sustainable development has been explicitly conceptualized in Brundlandt Report (WCED), that defines it as ”the development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (World Commission on Environment and Development 1987, p. 43). The tourism sector was among the first to be aware of the importance of this vision, even if the first initiatives were rather declarative or isolated. The explanation of the adherence to the above mentioned principles consists probably in understanding of the fact that the viability and prospects of the industry are inseparably linked to the quality of the natural environment and of the human relations, and the ambiance of specific destinations. However, the transition from awareness to practical application, from moral imperative to business practice was not easy, often leading to confusion, difficulty and errors. The various forms of tourism within time and space, the various sizes of tourism ventures, the composite nature of the tourism product, where the level of environmental impact is hard to monitor and regulate, make it difficult to implement a single policy, especially when business interests, performance and profitability requirements are threatened (Hobson and Essex 2001, p. 134). In this paper we aim at examining how tourism ventures understand and practice sustainability actions, how aware they are of the actual and perceived benefits and barriers associated with sustainability practices. The research is based on a survey conducted among representatives of ventures operating in tourism and hospitality industry and will enable us to draw some conclusions and identify implications and suggestions for policies to foster implementation of sustainable practices within tourism.

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2. The literature on sustainable tourism and sustainable business practice 2.1 Sustainable tourism The concept of sustainable tourism emerged mainly during the last decades, following the popularization of the concept of sustainable development and the growing awareness regarding the potential negative environmental impact of tourism (Bramwell and Lane 1993 or Horobin and Long 1996), and also the dependence of the sector on the features, quality and viability of the environment. The impact of tourism on the environment is complex and difficult to detect in a single statement. This impact refers to both environmental degradation as a result of the increasing number of visitors, and the effects of business activity in tourism, e.g. transportation, water consumption above normal standards, waste of heating and electricity, massive investments in environmental, social or cultural fragile areas, global procurement strategies etc. Hence, we can conclude that sustainable tourism induces responsibilities for both consumers and tourism companies. Unfortunately, the highly heterogeneous nature of the tourism product often acts as a deterrent factor, restricting the adoption of homogenous rules, which are generally accepted for tourism sector sustainability. The fact that sustainable tourism takes various conceptual shapes and has practical reasons, which combine business practices with moral and social responsibility, determines some researchers to doubt the realistic and sincere involvement in these actions. Thus, Berry and Ladkin (1997) consider the use of sustainable tourism rather as a simple trick, a marketing approach to attract new customer segments and to reassure those consumers who are concerned about certain moral implications of tourism. Other researchers argue that waving the threat of resource degradation motivates some tour operators to promote new destinations, instead of contributing to environmental conservation (Wheeller 1992) and (Hobson and Essex 2001, p.135). Pearce (1986) or Bartelmus (1989) are sceptical about the materialization and precision of environmental actions in general and about the sustainability of tourism in particular. Moreover, they find it impossible to coerce an entire sector to contribute to a better "green" world, without endangering the existence of various sub‐sectors such as transportation or construction, as those last sectors are not only consumers of non‐ renewable resources but also important polluters. However, sustainable tourism shares several features which are generally accepted. Firstly, sustainable tourism supports and respects the social, economic and environmental concerns of host communities, taking into account in their development strategies the local particularities and requirements. Secondly, it involves rational consumption allowing a natural, unmediated regeneration of resources. It also aims at promoting sustainable tourism actions which mitigate the depletion of natural resources and combat pollution of any kind. Finally, tourism as an economic activity which respects the above mentioned principles is able to provide consumers with comprehensive, satisfying and meaningful experiences (Hobson and Essex, 2001, Angelkova et al. 2012, UNWTO 2005). The way in which these goals can be implemented seems to be optimistic and quite confusing at the same time, taking various forms: from encouraging energy savings (lighting and heating) to waste collection or supporting the local economy by local purchasing. Moreover, some actions consider re‐dimensioning tourist flows in order to prevent degradation of natural and cultural sites due to congestions or excessive consumption. It is important that the outcome of these actions should not be regarded only in terms of environmental gains. There are also other benefits: monetary benefits (due to savings reported after reducing operating costs), increasing reputation, providing pleasant experiences for visitors, attracting influential customers and investors, improving job satisfaction for staff and a positive and encouraging response from local community (Swarbrooke 1994, Hobson and Essex 2001, Notarstefano 2007).

2.2 Examples of sustainable practices in tourism The literature on how sustainable tourism goals are effectively implemented reports a variety of situations, depending on sector, type and size of the ventures, segments of tourists, form of tourism etc. Investigating sustainability practices among hotels, Kirk (1996) finds that major hotel chains have assimilated relatively quickly and on a large scale sustainability issues and environmental rationality, raising awareness and sustainability responsibility among employees, suppliers and business partners. The resources, organization and expertise of major hotel chains have allowed them to make effective decisions enabling them to improve

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Ioana Mester and Daniel Badulescu their public image and thus to increase tourist interest in those brands. On the other hand, among small tourism companies, the results were much less visible and the actions proved to be more difficult to implement. Small tourism ventures face obstacles and restrictions due to both economic reasons (e.g. cost of clean or energy saving equipment), and poor experience and knowledge, or family and personal reasons. Investigating the hospitality sector in the UK, Stabler and Goodall (1997) indicate a real affinity of hoteliers for sustainable tourism, but also a limited or even a lack of understanding of tourism‐environment interaction. Sustainable practices were dominated by conventional and low efficiency actions, i.e. recycling (33%), low energy consumption devices (28%), lead free vehicles (27%) or double glazing (24%). They identify as reason for inaction “a high degree of complacency amongst the businesses, with satisfactory current environmental performance, low priority to environmental matters within their business and potential increased costs” (Stabler and Goodall 1997, pp. 19‐33). Another survey on managers within large and medium sized hotel groups in the UK (Brown 1994) indicated that main incentives for environmental initiatives are cost savings, followed by the environmental protections. Sometimes, the promotion of various local initiatives was delayed or excessively formalized by the decisions, procedures and controls of head‐office management. In some cases, representatives of major luxury hotels express reluctance to engage in sustainability policies, considering that this could affect the image of luxury consumption, and even “the enjoyment of a guest’s stay”. Analysing the attitudes towards tourism sustainability and environment protection of owner managers of small tourism companies in the Yorkshire Dales National Park (UK), Horobin and Long (1996) suggested that, although there is a lot of affinity for the general principles of sustainability, there is general confusion around the concept of sustainability and even the environmental concern. Although 76% of the respondents are prepared to accept the link between the environment and their business, however, many of them say they didn’t find the occasion, incentive or time to put these beliefs into practice. An important share of small companies owners (i.e. 65%) do not see the chance to turn ” their own business practices “green” as an "opportunity" and between 59% and 80% are not aware of any information sources (programs, publications) or they didn’t take time to seek and obtain such information. Most respondents (i.e. 66%) indicate they have undertaken actions for promoting sustainable tourism, particularly by recycling, using green products, reusable energy‐saving equipment etc. However, a significant part declare not to be satisfied with the excessive time spent carrying out these actions, the quality (or lack) of information and support, and they even plan to return to some classic products, which are non‐environmentally friendly but more efficient and probably cheaper. Briefly, ”they see environmentally concerned activities on the same level as any householder might. The most common reasons for taking action were a combination of a sense of responsibility, a distaste for the throwaway society and practical common sense” (Horobin and Long 1996). Hobson and Essex confirm that awareness and involvement of operators in sustainable tourism is limited on the short term, and the impact is perceived only in terms of operating costs and tourist turnover. Generally, the benefits of such policies are felt more in the large hotels, while “small businesses do not have the interest, resources or time required to introduce environmental management practices” (Hobson and Essex 2001, p. 144). Another aspect of the implementation of sustainable tourism practices is given by the customer requirements and behaviour. Trying to find a typology of environmental interest among consumers in Denmark, Hjalager (2000) indicates that rural locations tend to host vacationers with a high focus on environmental issues, while hotels or youth hostels, predominantly in urbanised areas, host vacationers less interested in these issues. As stated, “44% of the visitors to the metropolitan area claim that the environment has no importance for their choice of destination” and if the visit is associated with business and study reasons, only 18% of them show an interest in environmental matters. According to a European Commission survey (1998), although some segments of the population are more interested in sustainable tourism, less than 9% of the respondents actually experienced any problems with the state of the environment in their touristic destinations, and even a smaller proportion changed their original choice of holiday destination when they learned about environmental deficiencies. While some tourists are willing to pay more for environmentally less damaging products, around 71% of them prefer lodging in hotels that show concern for the environment, but they are not willing to pay more for them (Kirk 1996). Hjalager (2000), citing Björk’s researches on Finnish tourist

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Ioana Mester and Daniel Badulescu choices, shows that tourists will choose an eco‐resort, if it has the same price as a normal hotel. If an ordinary, non‐eco destination offers a reduction on a certain value, the cheaper alternative will be chosen. The efforts of tourism operators to ensure quality in the hotel sector focus on tangible achievements (e.g. comfort, number, size and equipment of premises, cleaning) that directly determine the number of stars of the unit. On the other hand, recognition of quality standards is made through certificates such as ISO 9001 and ISO 14001, which actually communicate to potential customers that the hotel respects and promotes international quality standards. Unfortunately, these certificates do not say anything about the elements of sustainable tourism, which are particularly important for exceptional natural resource based tourism. Even though the efforts of international technical committees to promote an ISO specifically addressed to sustainable tourism have little chance of success, there are numerous proposals for adequate standards of sustainable tourism (European Commission 2012, pp.11‐14). One of them is CST (Certificate for Sustainable Tourism), which is able to facilitate ”the achievement of a better image and reputation on the part of the hotels and contributed to modify the behaviour and attitude of employees in what concerns the respect for the environment and the care shown to natural resources” (Vasconselos‐Vasquez et al. 2011, p.554). Another solution could be to adopt Eco‐labels (such as Eco‐Flower) in order to make more visible the tourism operator’ efforts to protect the environment, to economize private and governmental promoting resources, but also to capitalize on all the advantages offered by a truly Europe‐wide well‐known brand (Lebe and Zupan 2012).

3. Research methodology The objective of our research is to investigate the question of sustainability‐oriented attitudes and practices among tourism and hospitality ventures. Using a survey‐based research, we address particular issues such as: Are ventures operating in tourism and hospitality really concerned about sustainability and the impact of their activities on the environment? Which are the factors driving venture concern on sustainability and environmental impact? What is their perception on the benefices and gains associated with sustainability practices? What do firm managers/representatives consider about sustainability as a competitive advantage for attracting visitors/customers? Do they have adequate related knowledge? Have they actually undertaken specific measures to make their business more environmentally friendly? The research hypotheses analysed are the following: H1. The managers' perception regarding the impact of hospitality industry on the environment is correlated with the number and type of their actions taken to protect the environment; H2. The level of the market targeted by the ventures is positively correlated with the existence and the number of environmental standard certification they own; H3. The managers' perception regarding the impact of hospitality industry on the environment is correlated with the existence of an environmental certificate, with the existence of certain actions to protect the environment or at least with some interest showed to protect it. The survey was conducted in March 2013, among 83 ventures operating in tourism and hospitality industry in Bihor County, Romania. The sample was selected by using the random stratified proportional sampling procedure. The questionnaire consisted of 23 both closed and open‐ended questions. They were divided in two sections: general questions related to the profile of the respondents and specific questions regarding awareness, attitudes and behaviours related to the environmental impact of the businesses in tourism and hospitality industry. We used Cronbach's Alpha method for the analysis and confirmation of the survey’s reliability and of the measurement scale. We grouped the questions referring to their perception about environment protection, getting α = 0.804 coefficient, which indicates a reliable scale. The elimination of any item leads to a lower Alpha.

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4. Description of the sample Almost a third of the ventures in our sample are guest houses, 42% are clubs and restaurants while 19% of them are hotels. The size of the companies was evaluated using both the number of employees and the annual turnover. The majority of our sample consists of small sized companies, with less than 49 employees (86%), only 2% of them with more than 250 employees. Meanwhile, most of the ventures have an annual turnover under 35,000 EUR (60.5% of them), and 32.6% having an annual turnover between 35,000 and 7,300,000 EUR. The actions reported by firm representatives as already undertaken in order to protect the environment are as follows: the use of energy saving light bulbs (100% of the firms), water saving devices (90.69%), the use of environmental friendly products (74.4%), recycling glass (69.76%), recycling plastic recipients (53.48%), the use of movement light sensors (7%), towel policy (4.65%), renewable energy source (i.e. solar panels: 2.3%). Most of the respondents consider that the most important advantage associated with their sustainability practices has been the lowering of the electricity and water consumption costs (see Figure 1).

Source: authors' calculations based on dataset Figure 1: Benefices and gains associated with the sustainability practices of the firms Thus, 81.6% of the representatives consider that their business gained some advantages or benefits by protecting the environment. When asked about the reasons why they have not taken any or more actions to protect the environment, most of the respondents could not indicate any reason, and only 16.27% of them explained this situation as being the result of high prices.

5. Results and discussions Research Hypothesis H1. The managers' perception regarding the impact of hospitality industry on the environment is correlated with the number and type of their actions taken to protect the environment. The questions based on which we are going to test the validity of this research hypothesis are: Q11. How significant is, in your opinion, the impact of the hospitality industry on the environment? Q18. Have you undertaken any actions within your company which could lead to the protection of the environment? Q19. If yes, which exactly are these? We have determined the number of actions taken to protect the environment and we have constructed the cross tabulation between the answers of the respondents in our sample, as presented in Table 1. A majority of 62.79% of the respondents from our sample consider that ventures operating in tourism and hospitality have a medium impact on the environment, whilst only 18.6% believe its impact is significant.

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Ioana Mester and Daniel Badulescu To validate research hypothesis H1 we use χ2 – Chi‐squared method. As χ2 = 38.76, i.e. much higher than 0, there is a strong correlation between the above mentioned variables. As the calculated value is much higher than the critical one (23.6 for 16 degrees of freedom and a 5% significance level), the null hypothesis is rejected, therefore there is a strong correlation between the two variables not only in the sample but also for the total population. Table 1: Distribution of responses to questions related to research hypothesis H1 The number of the actions undertaken to protect the environment The environmental impact of the hospitality industry Insignificant Medium Significant Total

1 3

4

5

6

7

8 9 10 Total

0 0

2

2

4

4

0 4

0

16

0 2 22

6

13

7

2 2

0

54

2 0

4

2

4

0 0

2

16

2 2 26 12 19 15 2 6

2

86

2

Source: authors' calculations based on dataset Therefore, research hypothesis H1: The managers' perception regarding the impact of hospitality industry on the environment is correlated with the number and type of their actions taken to protect the environment is validated at the sample level and the total population level. Research hypothesis H2. The level of the market targeted by the ventures is positively correlated with the existence and the number of environmental standard certifications they own. The questions used to test the validity of H2 research hypothesis are: Q7. What is the target market of your company? and Q14. Does your company possess an environmental certificate? Table 2: Distribution of responses to questions related to research hypothesis H2 Target market ‐ average score Number of environment certificates 0

1 1.5

2

4

0

34

6

0

44

1

2

10

24

0

2

38

2

0

0

2

2

0

4

Total

6

10

60

8

2

86

2.5 3 Total

Source: authors' calculations based on dataset After investigating the existence and the number of environmental certificates the companies possess, we associated scores ranging from 1 to 3 to each target market (i.e. 3 for the luxury consumers, 2 for average consumers, 1 for economy class) and determined the average score. The cross tabulation between the answers of the respondents is presented in Table 2. A significant proportion of the companies in the sample (i.e. 70.76%) target the average consumer; at the same time, more than a half of the ventures do not own any environmental certificate (i.e. 51.16%). The distribution of the frequencies shows a weak correlation between the two variables at a sample level. As the calculated value of the Chi squared test, i.e. 28.29 is higher than the critical one (i.e. 15.51), for 8 degrees of freedom and a probability of 95%, we can conclude on the existence of a correlation between the two variables not only in our sample but also at the total population level.

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Ioana Mester and Daniel Badulescu Consequently, research hypothesis H2: The level of the market targeted by the ventures is positively correlated with the existence and the number of environmental standard certifications they own is validated. Research hypothesis H3. The managers' perception regarding the environmental impact of hospitality industry is correlated with the possession of an environmental certificate, with the accomplishment of certain actions to protect the environment or the evidence of some interest to protect it. The questions used to test the validity of this research hypothesis are: Q11. How significant is, in your opinion, the impact of the hospitality industry on the environment?, Q12. Did you employ any actions in order to protect the environment?, Q13. Can you give examples of national or international entities that protect the environment? and Q14. Does your company have an environmental certificate? We assume it should be a positive correlation between the awareness of the environmental impact of the tourism and hospitality industry, and the actions accomplished to actually protect it. We assign a score, ranged from 0 to 5, showing the extent and to which the ventures in our sample involve themselves in protecting the environment. We have assigned 0 points to those respondents who gave negative answers to questions 12, 13 and 14, and 1 point for each positive answer; the company score is determined by summing up the three scores mentioned above. The cross tabulation between the responses and the assigned scores is presented in Table 3. Table 3: Distribution of responses to questions related to research hypothesis H3 Scores at Q12, 13 and 14 The 0 environmental impact of the hospitality industry on the environment Insignificant 0 Medium Significant Total

1

2

3

5 Total

6

10

0

0

16

8 14 22

8

2

54

0

6

0

16

8 22 40 14 2

86

2

8

Source: authors' calculations based on dataset The distribution of the frequencies shows a medium intensity and a direct correlation between the two variables. Since calculated χ2 (i.e. 16.36) is higher than the critical value for 8 degrees of freedom and a 5% significance level (i.e. 15.51), the null hypothesis is rejected, and therefore there is a weak correlation between the two variables at the level of total population. Among the reasons why the company does not have a certificate: 30.2% of the respondents consider that having an environment certificate is not a priority for the venture, or it has not been a matter of interest and 9,3% of them believe that having one would not bring any advantages to the company. Therefore, research hypothesis H3. The managers' perception regarding the environmental impact of hospitality industry is correlated with the possession of an environmental certificate, with the accomplishment of certain actions to protect the environment or the evidence of some interest to protect it is validated.

6. Conclusion While investigating attitudes and behaviours related to promoting sustainability‐oriented business practices, we have conducted a survey‐based research among managers and company representatives operating in tourism and hospitality industry in Bihor County, Romania. The research revealed a consistent interest for an effective sustainable tourism but also some barriers and limits in understanding the problems of sustainability, a short term focusing and a prevalence of conventional and low efficiency actions. After testing the research hypotheses we found out that managers/representatives understand that hospitality industry has a significant environmental impact and they undertake a series of actions in order to protect the environment. However, these actions are scaled, limited and reduced in efficiency. They consider that achieving and maintaining a

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Ioana Mester and Daniel Badulescu target market is fostered by possessing quality certificates which cover also environmental issues, even if those certificates do not say much on the concern of the operators in the industry to practice an effective sustainable tourism. However, an important share of them are actually interested in environmental issues, they are aware of the importance of practicing sustainable tourism, they try to obtain those certificates and meet their requirements, and act accordingly. As far as the company has other medium term goals on, and obtaining such a certificate appears as a waste of time and money with no tangible advantages, their interest and actions for environmental protection and promoting sustainability in tourism and hospitality will be reduced. However, our findings are limited, mainly due to limited the sample that was available, but research has to be pursued in order to deepen the analysis and find out different issues related to sustainability concern among the companies operating in tourism and hospitality industry.

References Angelkova, T., Koteski, C., Jakovlev, Z. and Mitrevska, E. (2012) “Sustainability and Competitiveness of Tourism”, Procedia ‐ Social and Behavioral Sciences, Vol 44, pp 221‐227. Bartelmus, P. (1989) Environment and Development. London: Allen and Unwin. Berry, S. and Ladkin, A. (1997) “Sustainable Tourism: A Regional Perspective”, Tourism Management, 18(7), pp 433‐440. Bramwell, B. and Lane, B. (1993) “Sustainable tourism: an evolving global approach”, Journal of Sustainable Tourism, 1(1), pp 1‐5. Brown, M. (1994) “Environmental Auditing and the Hotel Industry: An Accountant's View”. In: A.V. Seaton et al., ed. Tourism: The State of the Art. Chichester: Wiley, pp 675‐681. European Commission (1998) Facts and Figures on the Europeans on holidays 1997‐1998, Directorate General XXIII. European Commission (2012) Summary Report of the Consultation on the European Charter for Sustainable and Responsible Tourism, Enterprise and Industry Directorate‐General, Service Industries, Tourism Policy, Brussels. Hjalager, A.‐M. (2000) “Consumerism and Sustainable Tourism”, Journal of Travel & Tourism Marketing, 8(3), pp 1‐20. Hobson, K. and Essex, S. (2001) “Sustainable Tourism: A View from Accommodation Businesses”, The Service Industries Journal, 21(4), pp 133‐146. Horobin, H. and Long, J. (1996) “Sustainable Tourism: the Role of the Small Firm”, International Journal of Contemporary Hospitality Management, 8(5), pp 15‐19. Kirk, D. (1996) Environmental Management for Hotels. Oxford: Butterworth‐Heinemann. Lebe, S. S. and Zupan, S. (2012) “From Eco‐ignorance to Eco‐certificate: Environmental Management in Slovene Hotels”. In: D. Leslie, ed. Tourism Enterprises and the Sustainability Agenda Across Europe. Ashgate Publishing Limited, pp 135‐ 150. Notarstefano, C. (2007) “European Sustainable Tourism. Context, concepts and guidelines for action”, Global Jean Monet th th Conference, The European Union and World Sustainable Development, Brussels,5 – 7 November 2007. Pearce, D. (1986) Blueprint for a Green Economy. London: Kogan Page. Stabler, M. and Goodall, B. (1997) “Environmental Awareness. Action and Performance in the Guernsey Hospitality Sector”, Tourism Management, 18(1), pp 19‐33. Swarbrooke, J. (1994) “Greening and Competitive Advantage”, Insights, Vol 5, pp 43‐50. UNWTO (2005) Sustainable Development of Tourism. [online], http://sdt.unwto.org/en/content/about‐us‐5, [Accessed 12 March 2013]. Vasconselos‐Vasquez, K., Balbastre‐Benavent, F. and Redondo‐Cano, A. M. (2011) “Is Certification for Sustainable Tourism Complementary to ISO 9000 Certification? The Case of the Parque del Lago Hotel in Costa Rica”, Revista de Turismo y Patrimonio Cultural, 9(4), pp 543‐557. Wheeller, B. (1992) “Alternative Tourism: A Deceptive Ploy”. In: C. Cooper, ed. Progress in Tourism. Recreation and Hospitality Management, Vol 4. London: Belhaven pp. 140‐145. World Commission on Environment and Development (1987) Our Common Future, Oxford: Oxford University Press.

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Innovation, Design and Competitiveness: Results From a Portuguese Online Questionnaire José Monteiro‐Barata Economics Department, Instituto Superior de Economia e Gestão‐Technical University of Lisbon (ISEG‐UTL), Lisbon, Portugal jmbarata@iseg.utl.pt Abstract: This paper is an output of a Portuguese public research project (FCT): DeSID ‐ “Design as a Company’s Strategic Resource: a Study of the Impacts of Design” (2007‐2011). The DeSID research project was created with the main purpose to make a diagnosis of the use of design inside the Portuguese manufacturing industry, since that characterization was never done. “DeSID survey” allowed us to understand in broaden terms the way business field evaluates the role of design and designers. The main drivers for the use of design in the companies are the “image/reputation” followed by the “innovation ability”. The relationship between design and innovation is relevant for the majority of firms. From a brief analysis of the survey results it is also possible to acknowledge that Portuguese firms in general still underestimate the potential of design as a strategic resource. This paper, firstly, includes an exploratory empirical analysis on determinants of design in the Portuguese manufacturing industry, using factor analysis. Secondly, we will try to discover the explanations behind the "level of maturity" of design in Portuguese industrial structure ("the design ladder") through discriminant analysis. Keywords: design, design strategy, innovation, Portuguese industry

1. Introduction The DeSID research project ‐ a Portuguese public research project (FCT): DeSID ‐ “Design as a Company’s Strategic Resource: a Study of the Impacts of Design” (2007‐2011) ‐ was created with the main purpose to make a diagnosis of the use of design inside the Portuguese manufacturing Industry. The project arose from the necessity to gather data about the design situation inside Portuguese companies since that characterization was never done. The Portuguese Foundation for the Science and Technology (FCT) funded the project that started on the 3rd of September from 2007 and finished in January 2011. This paper refers to one of the activities of the research project: the National Survey on Design within the Portuguese Manufacturing Industry. Design is one of the most important 'nonprice' factors in competition and business performance (Potter et al., 1991, p. 3). The term design includes disciplines ranging from engineering, product and industrial design to fashion and textiles, graphics and communications, interiors, exhibitions and architecture. Design involves creating concepts, plans and instructions, usually in response to a brief provided by a firm or client that enable a two or three dimensional object that did not exist previously to be made. For a company, creativity is the generation of ideas, design is the “formatting” of ideas and innovation is placing those forms in new and/or different contexts. Design can create value at different levels of the value chain (Mozota, 2002, p. 94). We must see design as a facilitator, differentiator, integrator and communicator (Hayes, 1990). After this brief introduction, a general explanation on the inquiring process will be added (second chapter). Thirdly, we will present the definition of “level of maturity” of design. Following this presentation, the paper will include an exploratory empirical analysis on determinants of design in the Portuguese manufacturing industry, using factor analysis; after this essay, we will try to discover the explanations behind the “level of maturity” of design in Portuguese industrial structure (“the design ladder”) through discriminant analysis (fourth chapter). The paper finalises with some conclusives notes.

2. The DeSID questionnaire: sampling process and demography of the respondent companies An online survey, addressed to a sample of Portuguese manufacturing companies, was developed and launched by the DeSID research project.

442


José Monteiro‐Barata The questionnaire that was created had six sections: I) General Characterization of the Company; II) Perception of the Importance of the Use of Design; III) Identification of the Drivers and Enablers of Design Exploited by the Company; IV) Attitude and Action of the Company’s Top Management towards Design Use; V) Company’s Evaluation of Design Results; VI) Barriers to the Use of Design. The questionnaire requested information concerning the activities of design and its role in the company business. The responses are circumscribed to the activity in the years 2005 to 2007. The best estimates were also accepted in the absence of precise figures for those years. In the current context favourable to spreading of new information technologies and communication the choice of an online survey was supported mainly by the possibility of automating the entire cycle of gathering and processing of information ensuring data integrity. After the pilot test result, the inquiry process was implemented. About the methodological process see: Romão et al., 2007. The universe was formed by the Continental manufacturing industry, 2005. The total number of companies was 44,626. The sample size was 1.505 companies. The sample was stratified by categories of size and sector of activity. Technically, the confidence interval was 95,5% and the sampling error was 3%. The final number of respondent companies was 99, which gives a response rate of 6,6%. This online survey was preceded by an online pilot survey (conducted among a sample of 60 firms). Concerning the basic demography of the respondent companies we acknowledge that the majority is located in the North of Portugal being more than 1/3 installed in regions that have an industrial tradition, from Águeda to Guimarães. The large majority of the companies has Portuguese capital. An expressive percentage of the companies (40,8%) has started its activity in the period after 1974 (Portuguese Revolution) and until the end of the eighties decade. The sectors of Non Metallic Minerals, Metallic Products, Furniture and Food and Beverages account for about half of the respondent companies (49,5%). About 80% of the companies have less than 250 employees at service. The most relevant class is the one that has “50 to 99 employees” (25,8%). The turnover level slightly more expressive is the one of “1 to 5 million Euros” (25%). About 21% of the companies present sales over 25 million Euros. It can be considered that the set of respondent companies have an export orientation, with about 27% among them that export more than 75% of its production. However, 21% of the companies do not export. The main drivers for the use of design in the companies are the “image/reputation” followed by the “innovation ability”. The relationship between design and innovation is relevant for the majority of firms (see Teece, 1986; Brown, 2009; Verganti, 2009). The intensity in design in the Portuguese manufacturing industry (total value spent on design activities as a percentage of net sales) was 0.69% (2007). This analysis was tested through a dozen of "case studies" carried out by the project. All the main results of this project were presented in DeSID (2011).

3. “Levels of maturity in the use of design” in companies In order to deepen the understanding the typologies of use of design in companies, two questions were raised that expressed different “levels of maturity in the use of design”. This level of maturity is a notion developed by the Danish Design Centre (DDC) in 2003 and is presented in Figure 1 under the designation of ‘Design Ladder’. According to DDC (2003), the design ladder is a useful 4‐step model for grouping companies' design maturity on the basis of their approaches towards design (design management). The higher a company is up the ladder, the greater strategic importance design has for the company. First step: Non‐design ‐ design is a negligible part of product development, etc. and any design activity fall in professional groups other than designers. Second step: Design as styling ‐ design is seen solely as relating to the final physical form of a product. This can be the work of a designer, but is usually created by other employees. Third step: Design as process ‐ design is not a result but a method that is integrated early on in the development process. The production outcome requires contributions from a range of specialists. Fourth step: Design as innovation ‐ the designer works closely alongside the company's owners/top management on a complete or major renewal of its business concept.” (DDC, 2003)

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José Monteiro‐Barata

Source: DDC, 2003 Figure 1: The design ladder The two questions were related with the design activity firms developed in the past (2005‐2007) and the one they predict for the future (2008‐2010). Data obtained in these two questions assumed a decisive weight in the work of determining the position in the design ladder firms have. In this paper, we will focus only on data for 2005‐07.The results are presented in Figure 2. The options of the questions (see graphic 1) are not stated the same way the Design Ladder displays it. The correspondence between the two was defined as follows:

Non‐existent activity Æ Non Design;

Occasional activity/activity of modeling/shaping the product Æ Design as styling;

Design as a competitive factor of business/core competence integrating each of the firm’s decision Æ Design as a process;

Design as a catalyses of permanent innovation Æ Design as innovation.

15,2

Catalyzer of permanent Innovation Core Competence integrating each of the firm's decision

4,0 38,4

Competitive factor of the business

12,1

Activity of modeling and shaping of the product

16,2

Occasional Activity

14,1

Non Existent Activity ,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

40,0

45,0

50,0

Source: DeSID Project (2011) Figure 2: Characterization of design activity (2005 to 2007) Figure 2 shows us that 42,4% of the firms indicate to be on Step 3 of the Design Ladder; 28,3% state to be on Step 2 and 15,2% indicates being on Step 4 of the Ladder. However, evidence after data analysis shows that, in general, firms indicate a level of maturity that is higher than what exists in reality. The most evident result is the great centrality given to design as a “competitive factor of the firm’s business” (38,4%), as well as the evident relationship between design and innovation dynamics (Monteiro‐Barata, J., 1995; Roy and Riedel, 1997; Kyffin and Gardien, 2009).

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José Monteiro‐Barata

4. Design and innovation in the Portuguese manufacturing industry: An exploratory empirical analysis Among the various multivariate statistical methods for the analysis of data from the main survey, the paper includes an exploratory factorial analysis on determinants of design in the Portuguese manufacturing industry (perceptions and determinants of design) (Topic 4.1). Afterwards, we continued the analysis, using discriminant analysis, with two main objectives: firstly, to identify the main reasons that can explain, largely, the “execution” of design activities versus "non‐execution" of design activities; secondly, after the exclusion of companies that do not perform design activities (i.e., the first level of design "ladder"), we will determine the underlying reasons behind the positioning of the companies in the other three levels of design "ladder” (i.e., reasons that discriminate the different positioning) (Topic 4.2).

4.1 Perceptions and determinants of design The first dimension of the model for “perceptions” (first principal component) shows the strong opposition between the brand building process (and marketing) and an important but “ordinary” design task: functionality. Levels of differentiation and innovation did not get any relevance within this first component. They are the main reference for the second component, in strong opposition to cost reduction, setting the supremacy of differentiation as a generic strategy, removing the undesirabe positioning of "stuck in the middle" (Porter, 1980) (Table 1). For more detailed analysis see Annex 1. Table 1: Perceptions of the importance of design use – descriptive statistics and rotated component matrix

Mean

Std. Deviation

N

2,026 1,930 1,490 0,757 1,242 1,958 2,050 2,061 0,794 1,484 1,233 2,120

94 94 94 94 94 94 71 94 94 94 94 94

C1 (16,4%)

Brand building* Marketing* Trends* Process* Levels of differentiation** Innovation* Aesthetics* Quality* Sustainability* Cost reduction* Research* Functionality*

1,64 1,32 0,73 0,17 1,24 2,40 1,54 1,89 0,16 0,77 0,49 1,90

0,649 0,632 0,144 0,077 0,045 0,003 ‐0,036 ‐0,065 ‐0,115 ‐0,172 ‐0,205 ‐0,784

Components C2 C3 (12,6%) (11,8%) 0,282 0,170 ‐0,228 0,320 0,054 0,158 ‐0,194 ‐0,786 0,728 0,021 0,680 0,018 ‐0,002 0,416 0,210 0,171 0,076 0,002 ‐0,479 0,116 0,184 ‐0,652 ‐0,090 0,263

Source: Author computation based on DeSID (2011) * 1=minimum; 5=maximum; ** Only on product development versus using, additionally, industrial property instruments: licensing, trademarks and patents. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. In this analysis on general determinants of design, the variables “intensity in design”, “design people”, “graduated and post‐graduated in design” were added. These variables would be, in a standard causal analysis, considered as independent or dependent variables. All other ones (competitive variables) would be explanatory variables. The variable “top management involvement” in design activities and the “turnover” and “exports” (economic variables) were further added. Firstly, within first component, it should be noted the opposition (no association) between the main economic variables defined (“turnover”, which reflects the size of the companies, and “exports”, which defines the degree of internationalization) and the most direct indicators of the importance of design in companies: the intensity in design (financial resources) and, mainly, design people (human resources). However, we discover another variable, within human resources management, that shows different behavior: “graduated and post‐ graduated in overall design people” (%). Rather, this indicator is moderately associated with turnover (size) and exports level (see, in general, Bhattacharya and Bloch, 2004). This last indicator can be considered more

445


José Monteiro‐Barata demanding and sophisticated in the context of human resources indicators in design activities and is related to immaterial vectors of business (image/reputation) (2nd component). We can also say that the variables “intensity in design” and “design people” are associated with “top management involvement” in design activities (same signal) (Table 2). Table 2: General determinants of design – descriptive statistics and rotated component matrix

Mean

Std. Deviation

N

4,618 25,719 34,880

49 49 49

Components C2 C3 (23,1%) (13,9%) (12,8%) ‐0,644 0,030 0,421 ‐0,812 ‐0,053 ‐0,144 0,231 0,416 0,262

0,504 0,504 0,497 0,487 0,487 0,504 0,497 0,777 1,699 1,881

49 49 49 49 49 49 49 49 49 49

0,037 0,047 ‐0,015 0,497 ‐0,181 ‐0,036 0,134 ‐0,472 0,805 0,780

Intensity in design (2005/07) (%) 2,06 Design people/employees (%) 15,49 Graduated/Post‐graduated in design in total 30,47 design people (%) Firm: image/ reputation* 0,47 Firm: product* 0,53 Industry: market power of clients* 0,41 Clients: customer sophistication* 0,37 Competition: innovation capability* 0,63 Strategy: differentiation* 0,53 Strategy: market niches* 0,41 Top management involvement (4 levels) 3,02 Turnover (average 2005/2007) (ln) (€) 15,42 Exports/Turnover (5 levels), 2007 2,59

C1

0,765 ‐0,808 ‐0,015 ‐0,064 0,015 0,011 0,078 ‐0,281 0,218 ‐0,158

‐0,230 ‐0,288 ‐0,070 0,415 0,656 0,051 0,715 ‐0,077 ‐0,089 ‐0,046

Source: Author computation based on DeSID (2011) * Selected from a list of items. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. The new variables in the last exploration on determinants of design are selected from items for “investments”, “external entities” and other “information sources” for design. We add also a variable on the existence or not of an in‐house department of design (Table 3). Table 3: Specific determinants of design – descriptive statistics and rotated component matrix

Investments: Acquisition of tools, other equipment and software Investments: External knowledge acquisition Investments: Supporting marketing Investments: Vocational training External entities: Technological Centres External entities: Research Centres External entities: Clients External entities: Suppliers External entities: Universities Information sources: analysis of competitor's products. Information sources: consumer’s research Information sources: specific market research Information sources: sales force information Information sources: international fair’s visits Information sources: national fair’s visits In‐house department of design (Y/N)

Mean

Std. N Deviation

Components C2 (22,4%) (10,8%)

(9,7%)

C1

C3

0,51 0,36 0,39 0,32 0,29 0,19 0,47 0,37 0,25

0,503 0,483 0,490 0,470 0,458 0,392 0,502 0,487 0,438

75 75 75 75 75 75 75 75 75

0,479 0,716 0,422 0,637 0,274 0,216 0,073 ‐0,023 0,051

0,163 0,048 0,289 0,164 0,741 0,803 0,154 ‐0,088 0,669

0,621 0,234 0,196 0,318 0,016 0,013 0,815 0,587 0,396

3,53 2,89 3,07 3,81 3,61 2,33 0,53

1,298 1,530 1,464 1,074 1,335 1,359 0,502

75 75 75 75 75 75 75

‐0,226 0,017 ‐0,074 0,230 0,195 ‐0,297 0,664

0,495 ‐0,046 0,060 0,074 0,130 ‐0,090 0,178

0,033 ‐0,144 0,116 ‐0,046 ‐0,025 ‐0,072 ‐0,151

Source: Author computation based on DeSID (2011) Investments: (0‐1); External entities: (0‐1); Information sources: (1‐5) Extraction Method: Principal Component Analysis.

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José Monteiro‐Barata Rotation Method: Varimax with Kaiser Normalization. The first dimension shows the importance of investments, mostly immaterial. The existence of an in‐house department of design seems to be important for the achievement of such investments. The second dimension displays the ability of companies to establish relationships with the scientific and technological context (system of design): technological centers, research centers and universities. Finally, it is possible to realize a strong inter‐relationship in the value chain (suppliers and customers). These contacts appear associated with physical investments (“acquisition of tools, other equipment and software”).

4.2 The design "ladder” The next and final step is the discovery of the explanatory variables that lead firms to different levels of the design ladder. Firstly, we will try to advance the basic explanatory factors for the "non‐design" (status mentioned by the companies in the survey) versus the performance of design activities. Should be noted that firms "non‐design" answered a very limited number of questions. This greatly reduced the number of variables available for analysis. This will be an important reason for the failure of discriminant analysis essayed (statistical tests not significant). See Annex II.A. The explanatory variables essayed were: year of activity start (longevity), employees (2005/07 average, natural logarithm ‐ ln), foreign capital (Yes/No), company's exports in % of turnover (2007) and barriers to design (Yes/No). 93 valid cases were utilized. Wilks' Lambda=0,981; Sig.=0,890. The second analysis ‐ most promising ‐ focused on the most significant levels of design ladder (levels 2, 3 and 4). The variables were the following: employees (2005/07 average ‐ ln), foreign capital (Yes/No), graduated and post‐graduated in design in total design people (%), intensity in design (2005/07) (%) (insourced) and levels of differentiation. 48 valid cases were utilized. (For the first function: Wilks' Lambda=0,435; Sig.=0,000). 70,6% of original grouped cases were correctly classified. See Annex II.B. Very significantly, the differentiation strategy, preferably supported by industrial property instruments, was the highlighted variable in the discrimination of different levels of design ladder. Secondly, is the presence of foreign capital in companies, adversely affecting the advancement in ladder design. The expenditure in design (internal) and the presence of human resources with advanced training in design are also important, but did not reach statistical relevance. Table 4: Design ladder (by variables) ‐ tests of equality of group means and classification function coefficients (Fisher's linear discriminant functions)

Employees (2005/07) (ln) Foreign capital (Y/N) Graduated/Post‐graduated in design in total design people (%) Intensity in design (2005/07) (%) (insourced) Levels of differentiation (Industrial Property) (Constant)

Design_Ladder Design as Design Design styling as as (2) process innovation (3) (4) 2,968 3,164 3,491 1,935 ‐0,745 ‐1,609

Wilks' Lambda

F

0,949 0,876

1,28 3,40

2 2

48 48

0,287 0,042

0,948

1,32

2

48

0,276

0,008

‐0,005

0,005

0,931

1,79

2

48

0,178

0,628

0,618

0,882

0,551

19,53

2

48

0,000

‐0,254 ‐7,758

1,681 ‐10,151

2,507 ‐14,631

df1 df2

Sig.

Source: Author computation based on DeSID (2011)

Finally, taking into account the above factor analysis, we used the first components of each analysis as explanatory variables of the levels of design ladder: perceptions factor, general determinants factor and specific determinants factor. 48 valid cases were utilized. For the first function: Wilks' Lambda=0,665; Sig.=0,006. 62,5% of original grouped cases were correctly classified. See Annex II.C.

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José Monteiro‐Barata The sole statistically significant factor was the one related to “specific determinants”. This factor, as mentioned, is associated to investments (equipment and software, external knowledge, marketing, vocational training) and to in‐house department of design. Table 8: Design ladder (by factors) ‐ tests of equality of group means and classification function coefficients (Fisher's linear discriminant functions)

Tests of Equality of Group Means

Design_Ladder

Perceptions factor General determinants factor Specific determinants factor (Constant)

Wilks' Lambda F df1 df2 Sig. 0,899 2,52 2 45 0,092 0,973 0,64 2 45 0,535 0,747 7,61 2 45 0,001

Design as styling (2) ‐0,401 0,041 ‐0,805 ‐1,464

Design as Design as innovation process (3) (4) 0,114 ‐0,551 0,086 ‐0,639 0,165 1,526 ‐1,127 ‐1,775

Source: Author computation based on DeSID (2011)

5. Conclusive notes DeSID survey allowed us to understand in broaden terms the way business field evaluates the role of design. It is important to underline that the use of design in more than about 66% of the respondent firms has a history of less than 19 years. This survey is also helpful in the way it sheds light to firm’s perception of design in general and and the way it can be measured. The relationship of design and innovation is also relevant since for the majority of firms the first mental association with design is precisely ‘innovation’. An upgrade in employees’ qualifications could be an important step to boost design inside firms as a more valuable resource similarly to what happens in the North European countries (DDC, 2003; and Designium, 2005 studies). Indeed, an important result of this study was the detection of significant and positive relationships between the more qualified human resources (graduates and postgraduates in design) and business performance, namely dynamic factors of competitiveness. It is confirmed in general terms – see factor analysis carried out ‐ the complex and interactive character of the design that, to be successful, calls for considerable levels of organization, training, capture and circulation of information inside the firm (organization/value chain – investments, differentiation strategies) (Mozota, 2003) and in its relationship with the technical business environment (inter‐organizational relationships/value system – clients, suppliers, technological centres). Design is a fundamental driver of the innovation dynamics. The Portuguese design development sooner or later will claim a notion and development of a “National System of Design” (Raulik‐Murphy, 2008), setting new challenges to the public policies and to the business practices.

6. Annexe 1 Source: Author computation based on DeSID (2011) A. Perceptions of the Importance of Design Use. KMO and Bartlett's Test Kaiser‐Meyer‐Olkin Measure of Sampling Adequacy. Approx. Chi‐Square Bartlett's Test of Sphericity

Component

1 2 3

0,533 103,338

66 df Sig. 0,002 Total Variance Explained

Initial Eigenvalues

Extraction Sums of Squared Loadings Total % of Cumulative Total % of Cumulative Variance % Variance % 1,97 16,407 16,407 1,97 16,407 16,407 1,51 12,605 29,012 1,51 12,605 29,012 1,42 11,803 40,815 1,42 11,803 40,815

Rotation Sums of Squared Loadings Total % of Cumulative Variance % 1,55 12,949 12,949 1,49 12,379 25,329 1,49 12,371 37,700

Extraction Method: Principal Component Analysis.

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José Monteiro‐Barata B. General Determinants of Design KMO and Bartlett's Test Kaiser‐Meyer‐Olkin Measure of Sampling Adequacy. Approx. Chi‐Square Bartlett's Test of Sphericity df Sig.

0,539 155,806 78 0,000

Total Variance Explained Extraction Sums of Squared Rotation Sums of Squared Initial Eigenvalues Loadings Loadings % of Cumulative % of Cumulative % of Cumulative Component Total Variance % Total Variance % Total Variance % 1 3,008 23,137 23,137 3,008 23,137 23,137 2,909 22,377 22,377 2 1,803 13,869 37,006 1,803 13,869 37,006 1,578 12,141 34,518 3 1,668 12,830 49,835 1,668 12,830 49,835 1,539 11,840 46,358 Extraction Method: Principal Component Analysis.

C. Specific Determinants of Design KMO and Bartlett's Test Kaiser‐Meyer‐Olkin Measure of Sampling Adequacy. Approx. Chi‐Square Bartlett's Test of Sphericity df Sig.

0,635 271,251 120 0,000

Total Variance Explained

Component 1 2 3

Extraction Sums of Squared Rotation Sums of Squared Initial Eigenvalues Loadings Loadings % of Cumulative % of Cumulative % of Cumulative Total Variance % Total Variance % Total Variance % 3,583 22,395 22,395 3,583 22,395 22,395 2,131 13,321 13,321 1,720 10,751 33,146 1,720 10,751 33,146 2,127 13,293 26,614 1,554 9,710 42,856 1,554 9,710 42,856 1,812 11,324 37,938 Extraction Method: Principal Component Analysis.

7. Annexe 2 Source: Author computation based on DeSID (2011)

A. Discriminant Analysis: Non‐Design versus Design Group Statistics Design 0 Non‐ Design 1 Design

Total

Year of activity start Employees (2005_07) (ln)

Mean

Std. Deviation

1974,078 4,125 0,077

13,943 1,561 0,277

Foreign capital (Y/N) 2,692 Company's exports in % of turnover, 2007 Barriers to Design (Y/N) 0,385 1971,075 Year of activity start Employees (2005_07) (ln) 4,365 0,125 Foreign capital (Y/N)

2,323 0,506 32,530 1,385 0,333

2,625 Company's exports in % of turnover, 2007 Barriers to Design (Y/N) 0,280 1971,450 Year of activity start Employees (2005_07) (ln) 4,331 0,118 Foreign capital (Y/N)

1,858 0,449 30,580 1,405 0,325

2,634 Company's exports in % of turnover, 2007 Barriers to Design (Y/N) 0,290

1,916 0,456

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José Monteiro‐Barata Eigenvalues % of Cumulative Canonical Function Eigenvalue Variance % Correlation 1 ,019a 100,000 100,000 0,138 a. First 1 canonical discriminant functions were used in the analysis. Wilks' Lambda Test of Function(s) 1

Wilks' Chi‐ Lambda square 0,981 1,692

df 5

Sig. 0,890 Tests of Equality of Group Means

Year of activity start Employees (2005_07) (ln) Foreign capital (Y/N) Company's exports in % of turnover, 2007 Barriers to Design (Y/N)

Wilks' Lambda 0,999 0,996 0,997 1,000 0,993

F df1 0,107 1 0,323 1 0,243 1

df2 91 91 91

Sig. 0,745 0,571 0,623

0,014 0,643

91 91

0,907 0,425

1 1

Standardized Canonical Discriminant Function Coefficients Function 1 0,129 ‐0,818 ‐0,364 0,602 0,710

Year of activity start Employees (2005_07) (ln) Foreign capital (Y/N) Company's exports in % of turnover, 2007 Barriers to Design (Y/N) Structure Matrix

Function 1 0,605 ‐0,429 ‐0,372 0,246 0,088

Barriers to Design (Y/N) Employees (2005_07) (ln) Foreign capital (Y/N) Year of activity start Company's exports in % of turnover, 2007 Classification Function Coefficients Barriers to Design (Y/N) Employees (2005_07) (ln) Foreign capital (Y/N) Year of activity start Company's exports in % of turnover, 2007 (Constant) Fisher's linear discriminant functions

Non‐ Design 2,794 35,996 ‐38,034 ‐10,461 17,999 ‐2820,859

Design 2,793 36,226 ‐37,592 ‐10,584 17,384 ‐2818,071

B. Discriminant Analysis: Design as styling, design as process and design as innovation (by selected variables) Eigenvalues % of Cumulative Canonical Function Eigenvalue Variance % Correlation 1 1,078a 91,033 91,033 0,720 2 0,106a 8,967 100,000 0,310 a. First 2 canonical discriminant functions were used in the analysis.

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José Monteiro‐Barata Wilks' Lambda Test of Function(s) 1 through 2 2

Wilks' Lambda 0,435 0,904

Chi‐ square 38,278 4,641

df 10 4

Sig. 0,000 0,326 Group Statistics

Design as styling

Design as process

Design as innovation

Design_Ladder Employees (2005_07) (ln) Foreign capital (Y/N) Graduated/Post‐graduated in design in total design people (%) Intensity in design (2005/07) (%) (insourced) Levels of differentiation (Industrial Property) Employees (2005_07) (ln) Foreign capital (Y/N) Graduated/Post‐graduated in design in total design people (%) Intensity in design (2005/07) (%) (insourced) Levels of differentiation (Industrial Property) Employees (2005_07) (ln) Foreign capital (Y/N) Graduated/Post‐graduated in design in total design people (%) Intensity in design (2005/07) (%) (insourced) Levels of differentiation (Industrial Property)

Mean 3,955 0,313

Std. Deviation 1,339 0,479

25,848

37,107

1,467 0,563 4,558 0,074

3,284 0,964 1,415 0,267

29,145

34,700

0,958 1,963 4,727 0,000

1,937 0,898 1,137 0,000

49,792

34,852

3,867 2,750

7,965 0,707

Standardized Canonical Discriminant Function Coefficients Employees (2005_07) (ln) Foreign capital (Y/N) Graduated/Post‐graduated in design in total design people (%) Intensity in design (2005/07) (%) (insourced) Levels of differentiation (Industrial Property)

Function 1 2 0,212 0,268 ‐0,447 0,196 ‐0,117 0,574 0,206 0,945 0,909 ‐0,217

Structure Matrix Function 1 2 Levels of differentiation (Industrial Property) 0,869* ‐0,002 Foreign capital (Y/N) ‐0,359* 0,166 Employees (2005_07) (ln) 0,220* ‐0,115 Intensity in design (2005/07) (%) (insourced) 0,110 0,762* Graduated/Post‐graduated in design in total design people (%) 0,168 0,483* *Largest absolute correlation between each variable and any discriminant function Classification Resultsa

Original

Predicted Group Membership Design as Design as Design as Design_Ladder_4 styling process innovation Count Design as styling 13 3 0 Design as process 5 17 5 Design as innovation 0 2 6 Design as styling 81,3 18,8 0,0 % Design as process 18,5 63,0 18,5 Design as innovation 0,0 25,0 75,0 a. 70,6% of original grouped cases correctly classified.

451

Total 16 27 8 100,0 100,0 100,0


José Monteiro‐Barata C. Discriminant Analysis: Design ladder by design dimensions (by “Factors” – 1st component) Group Statistics

Design as styling

Design as process

Design as innovation

Design_Ladder_4 Perceptions factor General determinants factor Specific determinants factor Perceptions factor General determinants factor Specific determinants factor Perceptions factor General determinants factor Specific determinants factor

Mean ‐0,575 ‐0,201 ‐0,633 0,148 0,137 0,166 ‐0,204 ‐0,175 0,740

Std. Deviation 0,718 1,188 0,608 1,085 0,954 0,929 1,156 0,788 0,864

Eigenvalues % of Canonical Function Eigenvalue Variance Cumulative % Correlation 1 0,365a 78,390 78,390 0,517 2 0,101a 21,610 100,000 0,303 a. First 2 canonical discriminant functions were used in the analysis. Wilks' Lambda Test of Function(s) 1 through 2 2

Wilks' Lambda 0,665 0,908

Chi‐square 17,930 4,224

df 6 2

Sig. 0,006 0,121

Standardized Canonical Discriminant Function Coefficients Perceptions factor General determinants factor Specific determinants factor

Function 1 2 ,095 ,903 ‐,266 ,654 1,034 ‐,426

Structure Matrix Specific determinants factor Perceptions factor

Function 1 2 0,962* 0,052 *

0,372 0,781

*Largest absolute correlation between each variable and any discriminant function

Original

Predicted Group Membership Design as Design as Design as Design_Ladder_4 styling process innovation Count Design as styling 10 2 3 Design as process 8 14 4 Design as innovation 1 0 6 Design as styling 66,7 13,3 20,0 % Design as process 30,8 53,8 15,4 Design as innovation 14,3 0,0 85,7 a. 62,5% of original grouped cases correctly classified.

Total 15 26 7 100,0 100,0 100,0

References Bhattacharya, M. and H. Bloch (2004). Determinants of innovation. Small Business Economics, Vol. 22, No. 2, 155‐162. Brown, T. (2009). Change by Design: How Design Thinking Transforms Organizations and Inspires Innovation. HarperCollins, New York. DDC (Danish Design Centre) (2003). The Economic Effects of Design. NAEH, Copenhagen. DeSID (2011). Design as a Company’s Strategic Resource: a Study of the Impacts of Design. Project FCT no. PTDC/AUR/70607/2006, FCT, Lisbon. Designium (2005). Modelling the Strategic Impacts of Design in Businesses. Final Report, Helsinki. Hayes, R. (1990). Design: Putting Class into ‘World Class. Design Management Journal, Vol. 1, No. 2, pp. 8‐14.

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José Monteiro‐Barata Kyffin, S. and Gardien, P. (2009). Navigating the innovation matrix: An approach to design‐led innovation. International Journal of Design, Vol 3, No. 1, pp.57‐69. Monteiro‐Barata, J. (1995). Inovação, Captura de Valor e Vantagem Competitiva: a Formulação de Estratégias Tecnológicas, Mestrado em Desenvolvimento e Cooperação Internacional, ISEG/UTL, Texto de Apoio n.º 13. Mozota, B. (2002). Design and competitive edge: A model for design management excellence in European SMEs. Design Management Journal Academic Review, Vol. 2, pp. 88‐103. Mozota, B. (2003). Design management: using design to build brand value and corporate innovation. Allworth Press, New York. Porter, M. (1980). Competitive Strategy. Techniques for Analysing Industries and Competitors. The Free Press, New York, Potter, S., Roy, R., Capon, C., Bruce, M., Walsh, V. and Lewis, J. (1991). The Benefits and Costs of Investment in Design, The Open University/UMIST, Report Dig‐03, Design Innovation Group, September. Raulik‐Murphy, G. (2008). An International Perspective, Paper Dylunium Cyrum, Design, Wales, Marseille, 26‐27, June 2008. Romão, L., Almendra, R., Dias, E., Monteiro‐Barata, J., Nevado, P., Urbano, P., Marcelino, J. Dias, J. and Gomes, F. (2007). An online survey’s design to capture Portuguese companies’ perspective of Design, Proceedings of the 2007 Conference of Defsa International Design Education, 3‐5 October, Cape Town. Roy, R. and Riedel, J.C. (1997). Design and Innovation in Successful Product Competition. Technovation, Vol 17, No. 10, pp. 537‐548. Teece, D. J. (1986). Profiting from technological innovation–implications for integration, collaboration, licensing and public‐ policy. Research Policy, Vol. 15 No. 6, 285–305. Verganti, R. (2009). Design Driven Innovation: Changing the Rules of Competition by Radically Innovating What Things Mean. Harvard Business Press, Boston.

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Using Strategic Alliances to Facilitate Community Based new Venture Creation Peter Moroz1, Bob Kayseas2 and Robert Anderson1 1 Hill/Levene Schools of Business, University of Regina, Regina, Canada 2 School of Business and Public Administration, First Nations University of Canada, Regina, Canada peter.moroz@uregina.ca bkayseas@fnuniv.ca Robert.Anderson@uregina.ca Abstract: In this essay we explore how strategic alliances (SA) between organizations and communities can be used to develop opportunities that are advantageous for both the corporation and the community venturer. In particular, Indigenous communities have access to significant amounts of natural resources and corporations need access to these. Thus, there is an urgent need to discover the factors that drive the creation of successful corporate/community alliances and how these may be used to create sustainable new ventures that serve both economic and social value creation. To do this we review theory through the lens of three distinct but interrelated perspectives: strategic alliances, entrepreneurship and community. We argue that a sufficient framework for informing corporate/community based ventures has not yet been devised. The article concludes with discussion concerning the potential for the weaving of factors/issues identified in the reviewed literature into a framework that will guide future research. Keywords: strategic alliances, partnerships, aboriginal entrepreneurship, community development, natural resources

1. Introduction How may strategic alliances (SA) between organizations and indigenous communities be used to develop the entrepreneurial capacity necessary for creating and exploiting economic opportunities for growth around the world? This is an interesting and relevant question considering the failure of market and government based actions to foster development in some of the world’s poorest communities (Stiglitz, 2012). It is also a question of great importance to key economic actors due to the observation that even as the global economies of nations become increasingly integrated, actors within the capitalist market system that drive growth are highly dependent upon localized processes and community structures when considering both supply and demand equations (Anderson, 1997 Beamish, 1997). Strategic alliances amongst firms, governments, NGO’s, supranational organizations and communities are identified as a vital means for addressing problems and/or challenges standing in the way of sustainable development (Anderson, 1997). Moreover, strategic alliances are one of the key preferred methods of community owned Aboriginal development corporations to gain access to human and material resources, expertise and specialized knowledge. A 2011 survey of Canadian community‐owned development corporations by the Canadian Council of Aboriginal Business found eighty‐ percent had at least one joint venture (CCAB, no date). There is an urgent need to discover the factors that drive the creation of successful corporate/community alliances and how these alliances may be used in the creation of sustainable new ventures that create both economic and social value. Entrepreneurship and the creation of sustainable new businesses are argued to be a great force for the creation of wealth and social justice. But this has not proven to be so among the poor of the world where market paradigms, theories and policies have failed resulting in a widening gap between the rich and the poor, not only between first world and third world nations, but also within the core of both (Stiglitz, 2012). The world faces new challenges that include, first and foremost, the need to find sustainable growth models that are effective for first world economies while improving the development vector of the majority of the human populations that dwell in depressed populations, regions and countries. Entrepreneurship that works for both is required. Second, as part of this transition from a Fordist paradigm to new forms of contingency based versions of capitalism, corporations are ascendant in filling the void previously left to other stakeholders. In order to successfully solve economic problems while sustaining growth, corporations (both profit and not for profit)

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Peter Moroz, Bob Kayseas and Robert Anderson must place new emphasis on the recognition of bridging and bonding capital amongst economic stakeholders at the community level. This requirement offers new opportunities for communities to engage in development activities that align with their particular needs through emerging market mechanisms. Alliances between communities and corporations show potential as vehicles for sharing the resources and experience through networks that are critical to developing the capacity necessary for facilitating entrepreneurship. But corporations must be aware of the nature and cohesiveness of existing community social capital to do so effectively. Understanding how to best exploit opportunity is an important issue to resolve especially as it relates to Indigenous communities with access or ownership of natural resources. The “reality today is that indigenous peoples still live upon some of the world’s most resource intensive lands” (Davis, 2012). The Assembly of First Nations (AFN) estimates that there is approximately $400 billion of “resource‐based economic activity across territorial lands in the coming years” and argues that building partnerships between First Nations, industry and government with tangible social and economic benefits flowing to First Nations communities will assist in eliminating the gap between First Nations people and other Canadians (2013). Outside of Canada, Sawyer and Gomez, (2012) and Langton and Longbottom (2012) have compiled detailed examples of cases that illustrate that resource extraction across the globe through multinational corporations is moving forward at a similar pace and scale. And the World is increasing recognizing the Indigenous right to participate meaningfully in the development of resources in traditional territories (Anderson and Barnet, 2006). Indigenous communities stand on the periphery of billions of dollars in investment with growing access to opportunities flowing from this massive expenditure. Our approach to answering the question how may strategic alliances (SA) between organizations and indigenous communities be used to develop the entrepreneurial capacity necessary for creating and exploiting economic opportunities is to explore it using three distinct but interrelated perspectives: strategic alliances, entrepreneurship and community. In this article we use a definition of strategic alliances put forth by Keasler and Denning (2009). Strategic alliances are “contractual business arrangements to pool resources and engage in a new business venture with or without equity investment”. Also, two other research paradigms that have been developed for understanding and guiding community based venture development are reviewed and critiqued. We argue that a sufficient framework for informing corporate/community‐based ventures has not yet been devised – specifically within the context of the indigenous community. Through review and analysis of these three perspectives we propose a framework for future research.

2. Understanding strategic alliances 2.1 Overview of strategic alliances Strategic alliances among firms pursuing a variety of global economic objectives have produced a growing interest in the phenomenon (Beamish and Delios 1997; Hagedoorn and Schakenraad 1993, 1994). At its most general theoretical level, research on SA may be summarized as the investigation of how firms gain competitive advantages through collaborations with external organizations. Scholars argue that SAs are characterized by the paradoxical situation in which a firm hold a particular resource the development of which dependent upon external cooperation. The scholarly work on SA’s extends the resource based view of the firm from an internally focused organizational perspective to one that regards strategy and decision making behaviour as embedded within a wider social structure developed gradually over time: a process that provides a barrier to imitation (Barney, 1996). Central to this stream is the concept of social networks and the inter‐ organizational relationships that they represent. The literature is diffuse covering a wide range of areas inclusive of but not limited to international business, technology/innovation and foreign market entry. Due to the distinct nature of alliances (and their diverse set of objectives), evaluation of performance is not easily undertaken (Anderson, 1990). Issues such as control, cost reduction, bargaining power, knowledge absorption/leadership/exploitation, instability and exit are prominent areas of inquiry. Typically, SAs have been analyzed from either an economic or organizational perspective, but as noted above, ontology’s that involve the study of social network ties have arisen as a dominant theoretical viewpoint. Despite the growing interest in development and the significance of

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Peter Moroz, Bob Kayseas and Robert Anderson entrepreneurship to growth and renewal, the relationship between it and strategic alliances has received little research attention. While inter‐organizational studies involving firms are by far the most prevalent, there is a small but growing set of scholarly works that does look at the impact of SA, partnerships and joint/new ventures arising from interactions between corporations and communities. To date, much of the work on community/corporate interactions has focused on corporate social responsibility and environmental sustainability. For communities, alliances with corporations can be a means for acquiring necessary resources, capacity building, ensuring environmental protection, jobs and new venture creation. Partner selection, power structures/control, governance structures, institutional development and learning/knowledge transfer/knowledge protection have been staked out as significant requiring further study (Peredo and Chrisman, 2006). For corporations, alliances with communities may provide access to rare resources, new markets (sustainable business), supply chains/labour and critical licenses to operate through corporate responsibility measures and local investment (Walters et al. 1994; Newman & Chaharbaghi 1996; Varadarajan & Cunningham, 1995; Anderson, 1997). Issues identified as significant to the establishment and operation of strategic alliances from the corporate side include but are not limited to, cultural boundary spanning, establishment of trust, CSR, community investment, capacity building, social capital generation and corporate motivation (Kapelas, 2002; Loza, 2004; Seitanidi & Ryan, 2007). Definitions of strategic alliances are abundant and varied (Tsang, 1998; Takec and Singh, 1992). Gulati (1998: 293) provides one of the most cited definitions stating that SA are “voluntary arrangements [amongst two or more organizations] involving the exchange of products, technologies or services.” He goes on to state that SAs “can occur as a result of a wide range of motives and goals, take a variety of forms and occur across vertical and horizontal boundaries.”

2.2 Types of strategic alliances Barney (1996) groups strategic alliances into three categories: non‐equity alliances, equity alliances and joint ventures. A non–equity alliance develops a cooperative arrangement between organizations through contracts not the creation of independent organizations or cross‐equity positions. Equity agreements involve an equity investment made by one organization in the other organization, in addition to on‐going activity involving shared risks and rewards. Finally, a joint venture is developed when two or more organizations invest individually to create an independent organization. The investing partners are compensated by the profits of the independent organization. Lorange and Roos (1992) group alliances into five categories: informal agreements, contractual agreements, equity agreements, joint ownership and mergers and acquisitions. Informal agreements allow each organization to control its own activities without shared control, ownership or risk. Contractual agreements are legally documented alliances of shared risk and return with stated conditions and expectations. Mergers and acquisitions occur when one organization buys another.

3. Entrepreneurship: Process and context 3.1 Does entrepreneurship theory inform corporate/community alliances? Entrepreneurship researchers tend to focus on certain areas of the entrepreneurship phenomenon, for example, the characteristics of the entrepreneur, opportunities they respond to, the strategies they form, or their resource acquisition and organizing processes (Busenitz, et al., 2003). While research in these areas has contributed to the knowledge base on the entrepreneurship phenomenon (Bull and Willard, 1993; Low and MacMillan, 1988; Low, 2001), the rather narrow focus has resulted in a lack of a widely accepted general theoretical framework for entrepreneurship (Hindle, 2010). Moreover, an important aspect of choosing one theoretical framework from another involves the level of analysis under scrutiny. Two points made by Davidsson and Wiklund (2001) concerning entrepreneurship research are critical to the discussion within this paper. First, entrepreneurship research is dominated by micro‐level of analysis, predominantly using the firm or the individual as the level of analysis. Secondly, Low and McMillan (1988) suggest that approaches to researching the entrepreneurship phenomenon should incorporate both the micro and macro levels of analyses because of the complexity of the entrepreneurship phenomenon – it takes place and has effects on different levels of societal levels simultaneously. However, their recommendation “seems to have received limited following” (Davidsson and Wiklund, 2001). The inability of scholars to better marry the individual and

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Peter Moroz, Bob Kayseas and Robert Anderson environmental approaches to entrepreneurship is particularly relevant to research focussed on the intersection of community/corporate alliances and entrepreneurship. In a book edited by Schoonhoven and Romanelli two questions were posed. The first was, ‘what are the conditions, including economic, cultural, and even personal situations and proclivities that prompt the founding of new organizations?’ The second was, ‘what are the real and important outcomes of entrepreneurial activity?’ (Schoonhoven and Romanelli, 2001). These questions lie at the heart of our paper. Greater understanding of the conditions that are conducive to the birth of new ventures is vital to understanding what factors within communities affect any entrepreneurial process no matter the progenitor. The context under observation should not be limited to reductionist tendencies to focus specifically upon a narrow level of analysis, but as informed as possible by including individuals, groups within communities and entire communities acting through their governing bodies and the social, market and political environments in which they exist. Additionally, in a study outlining the ‘issues and processes’ involved in the creation of an infrastructure that facilitates and constrains entrepreneurship, Van de Ven pointed out deficiencies in entrepreneurship research exist when its study only focuses on the characteristics or behaviors of an individual entrepreneur and it treats the ‘social, economic, and political infrastructure for entrepreneurship as externalities’ (Van de Ven, 1993). Steyaert and Katz (2004) offered their insights into the implications of conceiving entrepreneurship as a social rather than economic phenomenon. Three key points raised by the authors are pertinent to this discussion. First, to fully appreciate entrepreneurship as practiced in our societies and communities, entrepreneurship researchers need to think more broadly and sample more diversely among people and organizations. Studies such as the Global Entrepreneurship Monitor (GEM 2001) capture only one type or situation of entrepreneurship. Second, entrepreneurship as a process or interaction is far more widespread and ubiquitous than current approaches to research suggest. Current measures of entrepreneurship are too coarse grained, looking only at business creation or even just high growth business creation, and missing the myriad fine‐ grained forms of entrepreneurial interaction taking place in society (Steyaert and Katz, 2004). The fundamental issue of locality, that is that entrepreneurship has a spatial characteristic has not yet been fully appreciated (Steyaert, 2007). Third, entrepreneurs do not operate in a vacuum (Gartner, 1985) they are in constant ‘dialogic’ ‘within an ongoing process and within an environment that has specific characteristics’ (Bruyat & Julien, 2000). The phenomenon of entrepreneurial behaviors cannot be ‘meaningfully separated from the social and economic context in which those behaviors occurred’…a new venture in the United States involves a very different set of dynamics than does the creation of a new venture in China or in Kenya’ (Bloodgood, Sapienza, Carsrud, 1995). It seems reasonable to assume that in order to understand the factors that drive the creation of successful corporate/community alliances and the potential for new enterprise creation, we need modes of analysis that conceptualize, articulate and operationalize different levels of analysis, i.e. the individual and the firm. These broader units of analysis must be understood within a range of contextual factors that are, in effect, structurally intertwined with the overarching environments in which social communities exist. We argue no such framework exists, which is adequate for exploring entrepreneurial opportunities and activities borne from community/corporate partnerships.

4. Communities 4.1 The concept of community The core conceptual idea of community is intuitive. Communities consist of people within a delimited boundary (not necessarily spatial), who share common beliefs and values. Community members adhere to commonly agreed to behavioral constraints, have direct and many‐sided relations (not mediated by institutions), and have an obligation of loyalty and reciprocity (Taylor in Lorenz, 1992). Another important aspect of ‘community’ is related to its literal meaning – and is expressed well by Plant (1974) using the German language: Gemeinde and Gemeinschaft. Gemeinde refers explicitly to the local community – a place or locality. The other term, gemeinschaft has a much broader meaning – it refers to the ‘quality of the relationship of people in a particular place or locality or belonging to a particular group’.

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Peter Moroz, Bob Kayseas and Robert Anderson Therefore, residence community = Gemeinde, and moral community = Gemeinschaft (Plant, 38). Understanding community in the first sense recognizes the spaces in which people interact, as in community school, community centre, and community church. While the conception of these facilities does denote a locality, they also convey a sense of the moral character of the concept of community. This moral aspect of community is integral to understanding the identity of communities around the world, especially those of Indigenous people. Indigenous writers have expressed the ‘multiple identities’ of Indigenous people that are formed around the concept of community – both residence and moral. For example, Smith (1999) described the manner in which the Maori create identities by naming ‘the mountain, the river, the tribal ancestor, the tribe, and the family’. In this manner the Maori locate themselves geographically, politically, and genealogically. Gerald Taiaiake Alfred, a Mohawk from Kahnawake, Quebec, characterized the Mohawk identity as, ‘localised Kahnawake, national Mohawk, broader Iroquois, and pan‐ Native’. He elaborated by stating, ‘Thus people of Mohawk descent who live in Kahnawake have a multi‐ layered identity which incorporates each one of the ‘communities’ he or she has inherited, and which also includes the broader Native – or the more common ‘Indian’ – identity flowing from their racial affiliation and identification as the indigenous peoples of North America’ (Alfred in Smith, 1999, 126). The identities that Indigenous people assume incorporate all aspects of both the ‘residence’ and ‘moral’ characterizations of the concept of ‘community’. These are important issues – not only because of the collective nature of Indigenous communities – but also because of its delimiting and boundary defining nature. As strategic alliances by their very nature seek to implement processes or activities pursued by individuals or groups that bridge, link, or potentially even blur the nature of two or more separate boundaries (Aldrich and Herker 1977), the concept of community ‐ shared sets of mental models that represent a group of peoples’ culture, goals, language and interests and that localizes the way that problems are defined ‐ is highly significant to how novelty is processed and entrepreneurial opportunities viewed and seized (Tushman 1977; Weick 1995; Carlile 2002).

5. A framework for corporate / community entrepreneurship 5.1 Approaches to community based entrepreneurship The development of a theoretical model focused on the community as a unit of analysis has been performed by a variety of scholars for a variety of purposes (Hindle, 2010; Johannisson & Nilsson, 1989; Johnstone & Lionais, 2004; Peredo & Chrisman, 2006) and has been pointed to as an area of important future research (Steyaert & Katz, 2004). Two key ‘models’ are presented in this section as a means of emphasizing 1) the importance of studying the community’s potential as a centre for entrepreneurial activity, and 2) identifying the processes best suited to the context of corporate/community entrepreneurship through exploration of the extant conceptual domain(s). Through analysis of these models and the strategic alliance literature, propositions for advancing a framework for alliance based community entrepreneurship are advanced.

5.2 Macro perspectives of community entrepreneurship Regulation theory has been specifically linked to indigenous community context and the pursuit of entrepreneurial ventures within the works of Anderson (1995, 97). Regulation theory, a contingency perspective, was propagated in response to the failure of modernization and dependency theories to explain the ‘actual outcomes’ in real world situations. It emphasizes a growing recognition of contingency and human agency in theories of capitalist development that had before been unrecognized (Anderson, 1995, 97). The attractiveness of the contingency perspective of development is explicitly different than both the modernization and dependency perspectives in two ways. First, the outcome of development efforts depends on the circumstances and actions of the parties involved ‐ it is not preordained by some ‘fundamental’ law of capitalism (Anderson, 1997, 1488). Secondly, contingency approaches emphasize the existence of multiple and diverse pathways to development (Wiarda in Anderson, 1997). A people’s culture, values, history, and resources shape pathways to development that are not totally dependent on the ‘centre’ or on a unilinear path already trod by developed countries. Thus, regulation theory is a new approach to understanding development that is respectful of the notion that local development can integrate into the global economy while maintaining unique characteristics of particular regions (Anderson, Dana, Dana, 2006).

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Peter Moroz, Bob Kayseas and Robert Anderson Anderson, (1995) describes three central concepts of regulation theory – regime of accumulation (RA), modes of social regulation (MSR) and modes of development (MD). Quoting Peck and Tickell, Anderson defines RA as; The dominant mode of economic growth and distribution. Elements of the accumulation system include the conditions of production (such as the amount of capital invested, the distribution of capital among the various branches and the norms of production) and the conditions of consumption (Anderson, 1995, 4). Thus the RA describes how capital moves through various stages, from production, circulation, consumption and distribution. MSR emerge in the context of the RA, currently the merging flexible regime. Modes of social regulation provide the structure, laws, policies, institutions (with their own sets of rules and regulations), and norms that allow RA to grow and expand. MSR are made up of ‘a series of formal and informal structures of governance and stabilization ranging from the state through business and labor associations, to modes of socialization which create ingrained habits of behavior’ (Anderson, 1995). Community culture, values, practices and goals impact the nature of an MSR meaning that they can and do vary by community, so long as they are still responsive to (by accommodating, modifying or resisting) the overarching RA The third concept, modes of development, is essentially the ‘coupling’ of the regime of accumulation (RA) and a MSR. MD may differ from community to community within a dominant RA as they are dependent upon localized MSRs. The biggest challenge with adopting regulation theory as a theoretical framework is the lack of clear means of operationalizing a research program within the tenets of the paradigm. The framework is simply much too broadly focused and without specificity that allows for a finer grained examination of community and corporate contexts. The strength of Anderson’s model, one that is specifically germane to corporate/community entrepreneurship, is that boundary spanning is found to be an underlying theme. We believe that he implies that boundary spanning is a potential mechanism for operationalizing how social modes of regulation may interface with the dominant regimes of accumulation so that “economic value” is properly defined, articulated and understood amongst community and corporate stakeholders in order to better reach a socially acceptable market for exchange. This is an Indigenous community specific concern. A number of authors have contributed to understanding the range of factors that have resulted in indigenous community social modes of regulation that are in conflict with the dominant regime of accumulation in Canada (Boldt, 1993; Helin, 2006, RCAP, 1996). For example, Canadian government policy that led to legislation, like the 1876 Indian Act formally acknowledged the intent to remove the cultural identity of Indigenous people and communities. There was no room for traditional societies beliefs and values in the modern world. The means to achieve the removal of the “Indian” from indigenous peoples involved the institutionalization of laws and policies like residential schools, ban on practicing traditional ceremonies, and the banning of selling goods off‐ reserve (RCAP, 1996). Contemporary Indigenous communities now contend with low rates of human capital (primarily due to low education attainments and high unemployment) and very few entrepreneurs. In addition, after years of suppression under the passive welfare system, entrepreneurs represent a new phenomenon in many Indigenous communities. They have often no role models or older generation entrepreneurs to facilitate the generation of the entrepreneurial spirit (Cachon, 2000). Thus boundary spanning provides an opportunity for linkages to be created between indigenous communities and corporations, as well as supra‐national organizations, the state, and the civil sector.

5.3 Meso perspectives of community entrepreneurship In a recent article, Hindle (2010) suggests and implements a ‘diagnostic system for assessing the influence of community factors’ on the ‘conduct and outcome of any proposed entrepreneurial venture’ (599). It is designed to provide to a researcher a tool to conduct a general assessment of the entrepreneurial potential of the whole community in its current state. Hindle’s model contains six principal domains: three under the headings of “generic structural factors” and three under the heading “generic human factors.” These form the two pillars that hold up the bridge: a metaphorical pathway(s) for movement between understanding the specific factors that define the community context and the entrepreneurial process(es) emphasizing that success is contextually grounded to that community. The cross braces of the model strengthening the pillars of the structure are programs and facilitation exercises designed to strengthen human resources, and tools needed to augment required physical resources. Hindle specifies the nature of the entrepreneurial process being contemplated within the community and proceeds across 11 stages and then provides a highly structured method of analytical procedure (please see Hindle, 2010 for a full accounting).

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Peter Moroz, Bob Kayseas and Robert Anderson Although Hindle provides a means for conducting a dispassionate evaluation of the aspects of community context germane to new venture creation, there are theoretical, conceptual and structural issues that dismiss it as an adequate framework for viewing corporate/community entrepreneurship. First, Hindle foregoes the prescription of any ontological conditions or theoretical foundations but instead chooses to set general categorizations of his domains of evaluation with no real hierarchy, classification (distinctness) or statement of relations among concepts within a set of boundary assumptions and constraints (Bacharach, 1989). This results in a model that is only an approximation of theory, and not theory itself (Merton, 1967). Additionally, the specificity and focus of Hindle’s Bridge removes the marketplace from the examination of the community/corporate context. One cannot examine entrepreneurship within the context of strategic alliances made between corporations and communities without taking into account the multitude of marketplace factors that can impinge or facilitate successful alliance outcomes. Although ‘Hindle’s Bridge’ is thus found to be inappropriate for building a framework for the exploration of community/corporate entrepreneurship, it does provide a conceptual touchstone for aligning it with Anderson’s development framework: boundary spanning. Hindle goes so far in emphasizing the importance of boundary spanning that he states that it is the key analytical prescription of the entire diagnostic system being proposed” (Hindle, 2010). At its simplest, boundary spanning has ‘emerged as a tool by which to establish the identity of an organization, determine its interaction with the environment, and understand the way in which knowledge is acquired, transferred and utilized’ (Hindle, 2010). Aldrich and Herker (1977) defined two primary roles of boundary spanners, information processing and external representation (218). Information enters the organization from the external environment through boundary roles and the boundary roles than link the organization to ‘environmental elements’ (Aldrich and Herker, 218). Leifer and Delbeqc (1978) define a boundary as, ‘demarcation line or region between one system and another, that protects the members of the system from extra‐systemic influences and that regulates the flow of information, material and people into or out of the system.’ The concept of boundary spanning is an important one given the nature of relationships to ‘outsiders’ within Canadian Indigenous bands. However, it is a concept that has not been examined in the Indigenous context as yet. Also, there is little explicit reference to boundary spanning in the extant entrepreneurship literature. The scholarly treatment of the concept in entrepreneurship related articles often assume that entrepreneurs automatically engage in boundary spanning activities thus the term gets confused with ‘closely related but distinguishable concepts’ (Granovetter, 1979; Aldrich and Zimmer, 1986 – both in Hindle, 2010). While the extant entrepreneurship does not make explicit references to boundary spanning several authors describe processes that are closely linked (for example, Gartner, 1985; Steyaert, 2007). There is ‘growing tentacles’ from organizational research into the entrepreneurship discipline with direct reference to boundary spanning as a recognized and useful concept (Hindle, 2010). One manner organizations maintain legitimacy in the external environment is through the information provided by boundary spanners to important ‘client groups’ (Aldrich and Herker, 1977, 220). That concept in isolation of other boundary role functions is a valuable asset given the often‐conflicting nature of the relationship between Indigenous bands and corporations, the Canadian government and society. A boundary spanner that can achieve fruitful relationships with external stakeholders may lead to opportunities that otherwise may not exist. As boundary spanning is directly and indirectly prominent in both scholarly works, its eminence to the development of a framework for explaining corporate/community entrepreneurship is readily observed.

6. Discussion The review of the extant literature on strategic alliances, entrepreneurship and community form the basis of a research agenda focused on answering the question, “How may strategic alliances (SA) between organizations and indigenous communities be used to develop the entrepreneurial capacity necessary for creating and exploiting economic opportunities for growth around the world?” The search for existing theoretical frameworks that might offer insight into how best to pursue answers to this question – answers that can contribute to both the academy and the indigenous community – led the authors to review Regulation Theory (Anderson; 1997, 2006) and Hindle’s Bridge (Hindle, 2010). Both theoretical frameworks make valuable contributions to the knowledge base of regional development (regulation theory) and community entrepreneurship (Hindle’s Bridge). However, taken in isolation each does not facilitate the operationalization of a research program that is articulated within this article. However, the analysis within each, regulation theory and Hindle’s Bridge, has drawn forward a set of beginning conceptual points with which we can begin charting an informed research path. Paired with the findings from a high level review of literature of strategic alliances, entrepreneurship and community, the conceptual domain defined as boundary spanning stands as a

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Peter Moroz, Bob Kayseas and Robert Anderson potentially profitable means for distinguishing a critical component of the process of new venture creation from within a community/corporate alliance context. This is particularly apparent when examined within the specific and rather unique context of the Canadian indigenous community. Distinct from the conceptual domain of social networks, which focuses more so on the precise nature of personal relationships and the value/resources derived from them, boundary spanning appears to be a means for understanding community like processes of production and/or market processes of exchange (Levina and Vaast, 2006) while still retaining an interrelationship required for theory building.

7. Conclusion Busenitz et al., (2003) argue that moving entrepreneurship research into the study of interrelated dimensions represented by the individual, opportunity, modes of organizing and the environment will define the field and enhance its legitimacy. With respect to new venture creation derived from a community/corporate alliance context, the concept of boundary spanning is posited as a means for achieving this synthesis through the activities of boundary spanners, governed by the very core concepts relevant to both alliances and entrepreneurship: resource flows, information flows and the management of uncertainty through the establishment of trust amongst groups and organizations with well defined identities and diverse systems of beliefs and values. How individuals and teams within communities and corporations work to span boundaries across markets, suppliers, competitors and the environment in general to establish new ventures may provide a better understanding of the entrepreneurial process (Gartner 1985) and better frame its importance to developmental economics as a socially enacted and inherently human activity.

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Senior‐ & Juniorpreneurship: An Intergenerational Approach in Engineering and Entrepreneurship for Value Creation Bernd Neutschel1, Olaf Gaus2, Matthias Raith2 and Sándor Vajna1 1 Institute for Machine Design, Chair of Information Technologies in Mechanical Engineering, Otto‐von‐Guericke University of Magdeburg, Germany 2 Faculty of Economics and Management, Chair of Entrepreneurship, Otto‐von‐Guericke University of Magdeburg, Germany bernd.neutschel@ovgu.de gaus@ovgu.de raith@ovgu.de vajna@ovgu.de Abstract: This paper examines how the generation of entrepreneurs 50+ should be addressed in order to raise their interest for improving their skills, and how young entrepreneurs and students can profit from the seniorpreneurs’ expertise in production processes and market knowledge as well as from their networks. To promote the promising synergies arising from the collaboration of young and elderly entrepreneurs a project was initiated that combines an integrated product development with business plan design support. Prospective entrepreneurs with industrial experience (seniorpreneurs) and innovative product ideas are matched with multidisciplinary student teams to generate a going‐to‐market prototype as a basis for starting new businesses. From the standpoint of research and development the balance is excellent with several promising product innovations and business plans for entrepreneurial implementation. The perspective of science and technology transfer demands an urgent desideratum to bring the accumulated value potential into the market. Accordingly, one can identify initial trends that illustrate and underline the growing social as well as economic importance of seniorpreneurs. Already one third of the newly formed companies is currently built on the initiative of 50+ entrepreneurs, i.e., founders who are 50 years and older. If one tries to weight the start‐up‐relevant profile characteristics that have high relevance for successful entrepreneurial acting, it becomes evident that the level of individual education and training plays a crucial role. As a consequence, one can expect future academics to be not only of great importance for research and development, but that they will also play a crucial role later on in their career as high‐expectation entrepreneurs. These resources provide both general entrepreneurial know‐how as well as specific methods and tools to determine the prospective success of a strategically planned entrepreneurial start‐up. This aspect is crucial, as older entrepreneurs often tend to cancel the creation process, if the performance targets are in question (Werner et al, 2008). Moreover, they will wish to make this decision as early as possible before starting a business. Keywords: value creation, product development, entrepreneurship, process engineering

1. Parallelizing product development and business planning ‘SeJu’ (Senior‐ & Juniorpreneurship) is a university‐based project that facilitates technically oriented start‐ups of founders with a professional, yet non‐entrepreneurial background. Specifically, SeJu offers the possibility to develop product ideas technically while, at the same time, constructing a business plan for a firm to successfully implement a mature product on the market. The project extends the intensive collaboration since the year 2005 at the University of Magdeburg in Germany between the chair of Information Technologies in Mechanical Engineering of the Faculty of Mechanical Engineering and the chair of Entrepreneurship of the Faculty of Economics. Taking advantage of the synergies already mentioned, participants obtain the opportunity of learning how to create high‐growth start‐ups (Neutschel et al, 2013). The design of the ‘SeJu’ project is inspired by the so called ‘Clinic Program’, developed by the Harvey Mudd College in the U.S. It’s considered to be an “extraordinary program of collaboration between industry and Harvey Mudd College that has been a hallmark of this institution for close to 50 years, engages juniors and seniors in the solution of real‐world, technical problems for industrial clients.” Even the organizational teaching and learning process as well as research and transfer are designed quite similar although both initiatives were raised independently from each other (HMC, 2012). Also to mention in this context is the ‘Partnerships for Innovation Program’ which has been started and funded by the National Science Foundation. Although in the meanwhile the program has been discontinued it serves pretty well as another model for how to “stimulate the transformation of knowledge created by the research

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Bernd Neutschel et al. and education enterprise into innovations that create new wealth; build strong local, regional, and national economies; and improve the national well‐being” (NSF, 2011). To get the process started a seniorpreneur actively has to be determined by acquisition who offers a technical based product idea to SeJu that is going to be proved, as well as assessed by the project team concerning it’s implementation options. Once the test results confirmes a high level of technical and economic quality of the idea it comes to a procedural process that helps to consider whether one may expect an entrepreneurial opportunity in case of a product launch. In order to get an idea of how the development process proceeds at SeJu, it can be briefly described as follows (Figure 1):

A seniorpreneur is applying with a technical product idea.

The idea is evaluated with the knowledge of the participating science departments and checked for viability.

After having accepted the project an interdisciplinary team of students is put together and joined with a seniorpreneur.

Technical product development and business plan design are running in parallel.

The involved seniorpreneur monitors the progress of the project as an expert.

Product concept and business plan are developed.

Results are evaluated by members of the academic staff.

By working together on a development task that is meant to be technically and economically realized, participants grow as an entrepreneurial team despite the differences in knowledge and age.

In addition to business plans and product prototype a multi‐disciplinary entrepreneurial team has been built, ready to start a well planned and promising product‐to‐market strategy.

Figure 1: The SeJu project process in general at a glance The product creation process is based on the principles of Integrated Product Development (IPD), (Vajna and Naumann, 2001). IPD requires a consistent vision of the entire product life cycle, meaning that the interaction between product and process is paramount. As a consequence, the product developer is faced with the task to synchronize the creation of a product with the production process all in one. The derived goal is to create a consistent product, while ensuring a demand‐oriented production, use and disposal. These principals are based on different views on the product to be developed. This allows the creation of all the essential features of the product and its required forms. On the functional sector all key items are permanently controlled with a view to criteria like form, function, performance, manageability, reliability and security, value for money, manufacturing ability, maintainability and sustainability.

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Bernd Neutschel et al. This necessarily requires engineering design methods and tools as Blanchard (Blanchard et al, 2004) describes it with special reference to its integration in process simulation. The embedded process was generally described by Clark, Fujimoto (Clark and Fujimoto, 1991) by regarding four major stages of development: concept development, product planning, product engineering, and process engineering as well as the critical linkages within and across them. The special feature of SeJu is that the process just described is duplicated and connected in parallel in terms of running the product and business development at the same time taking into account the critical linkages. A prerequisite for being able to capture the high‐growth potential of promising start‐ups was a prior, completed R&D project with the title “High‐Expectation Entrepreneurship” (funded by the German Ministry for Education and Research from 2008‐2010). The exploration and simultaneous implementation in cooperation with actual start‐up projects and early stage companies was aimed at bringing the latter into a high‐growth phase right from the outset. One of the most important results of this project was to trim start‐up enterprises already in the phase of business planning to consequently exploit all analyzable entrepreneurial opportunities (Raith, 2011). Nevertheless, even if a start‐up company succeeds in bringing an innovative product to the market, there still remains the question regarding its profitability. On the one hand, “under modern conditions of competition, it is becoming increasingly hazardous not to innovate. The firm that does not maintain a program of managed innovation can quickly find itself behind competition” (Yoon and Lilien, 1985). On the other hand, the same authors point out that “a survey of 148 companies... indicates that only half of the companies have achieved successful performance in two thirds or more of their new industrial products. In a study of 122 industrial product innovations... of every 100 products that are fully developed, only 60 become a commercial success.” This describes a fundamental dilemma that “New Product Development speed is critical, because product life cycles are shrinking and because obsolescence is occuring more quickly than in the past, while competition also has intensified“ (Langerak and Hultink, 2006). This finding calls for clarification. What are the reasons that 40% of the already developed products do gain acceptance in the market? Initial findings from SeJu suggest that it often concerns an optimization problem on the side of product development. This problem can be handled when the described process of “different perspectives” are integrated into the product development. On the other hand, a product’s success not only depends on communicating the unique selling point to the right audience but also on expanding the market to increase the number of potential customers. These two aspects have to be regarded simultaneously in order not to enter a hard‐fought contest with a new product but a still untapped market. This argument follows the idea of a “Blue Ocean Strategy” (Kim and Mauborgne, 2005) to which we refer to in the following. Previously must be noted, that as a consequence, sales numbers are increasing including the return on sales when using the right pricing strategy. The increase of yield is a condition for the continued success of the company. Only in case of sufficiently large corporate profits investments research and development can be made for the successful development of new products. To achieve this goal an establishment of a parallel development of the product and the market is helpful (Figure 2). This advantage also applies to the investment protection because this process of creating a product makes the product‐to‐market process calculable.

Figure 2: Parallelizing the IPD and business plan design process

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Bernd Neutschel et al. However, turning a concept into a profitable product is a challenging issue for all involved “and requires people from multiple disciplines to work together. New Product Development is a complex, collaborative process that requires coordinating the innovation efforts of many to meet a common goal“ (Brown, 2005). In order to find a reliable approach to implementation in practice, Aberdeen’s Product Innovation Agenda stands out as particularly important by emphasizing that “companies that are best‐in‐class at new product development and introduction tend to have (...) a senior manager (who) is directly responsible for overseeing the full process of identifying innovation, opportunities, engineering them, developing them into products, and bringing them to market.“ As a head of team this “senior“ is a necessary “coxswain“, who steers a project through the technical as well as the entrepreneurial process, while realizing the strategic and tactical success criteria that have been earlier developed in the business plan with the participation of the entire team. This is where business‐plan design comes into play. The finding that both an innovative product as well as the targeted market must perfectly fit together is insufficient. A third and mission‐critical component is the strategic positioning of the company itself. For a start‐up company, this implies that market, competition, customer, price and product distribution concepts already have to be worked out before communication on the product begins between the company and the market. This is essential, because strategic errors that are made at this stage of development like in the earlier stages of the product development cannot be reversed without large losses. On the other hand, in the strategic development of the relationship between company, product, and market there lies a business opportunity to transform a product innovation into a high yield value. To achieve this, business planning has to be taken seriously: it is always in reference to a future reality. Just as the creation of a new and innovative product design benefits from a view what future demands will be, entrepreneurs also should create new needs of tomorrow’s consumers. These are crucial aspects for the design of the company. A central question is, therefore, if the economic success of a company that comes with a new product can be achieved by business planning and whether this success is scalable? As the practical and theoretical support for start‐up companies in the previously mentioned project “High‐Expectation Entrepreneurship” revealed, entrepreneurial success can be designed and does not necessarily occur accidentally.

2. Start‐Ups without entrepreneurs If one views the combination of Integrated Product Development (IPD) and growth‐oriented business planning as a “recipe” for the success of start‐up companies, the question arises why start‐ups are not continuously being initiated through this approach. By taking a look back at the cooperation between IPD and business planning at the University of Magdeburg, one recognizes that the successful implementation of the concept requires a crucial “ingredient”, which all to often is missing at universities: The entrepreneur. The reason for this is known and, therefore, not surprising. Universities are excellent breeding grounds for new product ideas and their transformation into innovative products as well as their profitable commercialization through start‐ ups. Yet, to deliver products to the market, one must also have entrepreneurs. The people at universities mainly involved in innovation through research are students, graduates, and professors. Students generally have the primary interest to successfully finish their studies. They also argue that they lack the professional experience to establish a firm. “Not yet“ is an often‐heard response to the question whether they can imagine starting a business with a promising product idea. Academic staff, which includes graduates and professors, often has the preference to do research on other or further going innovations, rather than bringing them to the market by establishing a company. Overall, the result is that there is a significant lack of suitable entrepreneurs at universities. This does not necessarily mean that scientists should always develop into entrepreneurs. However, it would be useful to the intensification of good research and development projects if scientists are sensitized and trained for the identification of opportunities for value creation in science. Leaving aside the programmatic approach to such training at the moment, it is understandable that it requires appropriate incentives to bring a scientist to think about the possible economic value of his or her own research. Of course, at this point is the university itself into play because a successful implementation of incentive structures is very much dependent on what resources are available. It turns out more and more that among many reasonable resources two are most important. On the one hand, an entrepreneurial unit is needed to offer opportunity analysis for knowing whether a product‐to‐market project is commercially promising. On the other hand there have to be reliable contracts between the university and the scientists to determine to what extent scientists are involved in the

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Bernd Neutschel et al. transfer process of their research. But that does still not solve the problem that the implementation of a knowledge‐based project always needs an entrepreneur, which mostly has to be found outside the university. This topic, which recommends the creation of a Transfer Unit for Universities, requires a description of the reasons why universities should be entrepreneurially active at all and what strategic role knowledge transfer has as a ‘third mission’ in addition to research and teaching.

3. Professionalizing science transfer – universities’ third mission Since the beginning of the new millennium knowledge institutions are increasingly focusing on the utilization of scientific knowledge as a third mission. Particularly in European countries transfer processes of science‐ based knowledge, which provide the economy with innovations and capitalize generated know‐how of verifiable excellence, are progressively seen as an entrepreneurial challenge, especially for technical universities and research institutions. Funding options for entrepreneurial start‐ups as well as entrepreneurial growth are currently hard to tap. Firstly, scientists generally lack the necessary entrepreneurial interest in starting an own knowledge‐based company. Secondly, the majority of European universities today typically do not offer standardized equity instruments for university start‐ups. This not only describes a knowledge‐based start‐up problem, but also a not yet captured opportunity for universities to refinance their primary missions of research and teaching, enabling them to achieve a higher level of excellence. Therefore, we see the need for a new design of a transfer strategy that better fits the recommendations of scientists, research institutions, and firms. Our objective is to develop a proactive science transfer process that interacts directly with established firms in the market. This variation of knowledge transfer requires a strategic screening process to identify both economically utilizable science based innovations and the appropriate partner companies, in order to jointly develop and commercialize the entrepreneurial outcome. Utilization as a form of proactive recovery through knowledge transfer is of particular interest to universities in regions characterized by a fragmented economic structure, e.g. in the new German states. We find evidence that firms situated in this region often do not execute the entire R&D in‐house value chain, because of missing financial and human resources. As a consequence, the regional universities and research institutions are faced with the task of performing basic as well as applied research, in order to successfully initiate R&D processes. Hence, there is apparently a strong need for intensifying the approach of proactive recovery. A concept that helps reap the entrepreneurial benefits in this context very much depends on the screening and identification of qualified firms, which are equipped with a knowledge interface to be R&D compatible, and which are situated in the regional environment of a university. The relevance as well as the empirical based proofs are taken from a research study that focuses on the economic region of Magdeburg, located in the State of Saxony‐Anhalt in Germany, as an example for a fragmented economic structure (Proto et al, 2012). The survey examines three regional key industries and is divided into two phases. Phase one consists of face to face interviews with 37 experts in total. The selection of experts results from a previous analysis of relevant key players due to their active role in knowledge transfer processes that are relevant for the addressed key industries. After completion of phase one, the 330 most relevant regional companies were selected to participate in an online questionnaire. Within the framework of an efficient knowledge transfer in small‐scale economic regions knowledge networks are able to optimize the quality of R&D processes, which means that interacting network firms have a stronger access to research based innovations. On the other hand, research driven firms or company networks are more open towards science‐based knowledge offered by universities and research institutions. Since these company networks are often „invisible“, especially for universities, it is of great importance to systematically open up the network structures. In a next step, universities have the opportunity not only to become a part of regional economic network structures but also to set up project‐driven networks themselves.

4. R&D drives the science&technology transfer process Against this background and the will to develop a kind of transfer‐unit, one of the fundamental motivations for the development of the SeJu project was to firstly implement a suitable science‐transfer‐process and then to find individuals who would actually implement an entrepreneurial idea and who also had the appropriate skills. Over the years, sophisticated design and business plans had been accumulated in the archives of the

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Bernd Neutschel et al. cooperating academic chairs at the University of Magdeburg, waiting for their implementation. Once the idea was born to look for entrepreneurs outside the university, it developed into an agenda to implement already developed products and create further business plans. After this intellectual step was taken, one could not only imagine a business founder outside the university, but the idea of addressing existing businesses also evolved. Specifically, this meant that existing companies could integrate a new project in collaboration with the SeJu project in the form of a profit center, in order to take it further – as in an incubator – to market. Given this interaction between research & development on the university’s side and profitable product selling on the business side, there remains the question of who should receive the return on investment at the end? How could the yield be divided fairly among the interacting partners? And how would the university handle its share internally? For private research institutions, the incentive for their transfer activities is given, because it usually involves contract research from industry. Actors in public research institutions, however, are committed to their research and teaching and do not have the task to exploit their work economically, neither for themselves nor for their academic institution. However, the situation in the increasingly knowledge‐based society has changed: because new knowledge has become an asset and must be used as a resource in the value‐creation process of economies. It is, therefore, not surprising that politicians and business leaders are recently speaking of the “entrepreneurial university”. This term primarily means that, in particular, universities and research institutions are asked to find efficient ways to make research results available for economic use. Since public science in Germany is publicly funded, additional benefits should make such a transfer attractive for appropriate scientific institutions. In practice, universities and, specifically, faculties and scientists, must be able to draw their own benefit from scientific transfer. Moreover, they must be allowed to use the gained benefits (e. g., money) according to their own preferences. To initialize this function, two important requirements must be met: It is a necessary condition for any research transfer of public scientific research institutions to examine and to assess the value of innovation. The resulting knowledge concerning the extent and quality of the determined transfer potential can be made available for different utilizations in a next step. Possible transfer partners can be start‐ups from universities and research institutions, start‐up managers from the outside of universities and already existing companies interested in intrapreneurial opportunities, or third parties engaged in buying and selling research with high economic value on the world‐wide market.

5. Initiating value innovation by integrated product development Any successful utilization depends on the communication with transfer partners. Innovative products or services are not taken up by companies without reason. Promising co‐operations have to be analyzed in advance, especially regarding the willingness and the ability of a product‐to‐market strategy. This is important because not only a product has to be innovative in order to be successful, but also the market. In other words, the customer wants to understand why a product innovation is a value innovation (is a buy worth the money?). Indeed, it is necessary to evaluate the degree of innovation of a new or established product. This task has to be executed by the management of a company in order to assess technical risks. In terms of market success by differentiating a product by its novelty, however, the customers’ perception is relevant. As a consequence, the company‐specific perception of the degree of innovation of a new product has to be separated strictly from the customer’s perception. This makes sense particularly in such cases when entrepreneurial opportunities results from using familiar technology in new products, brought to selected markets where this technology is still unknown (Pahl et al, 2005). This idea was a significantly important basis for the development of what we later on consider to be an entrepreneurial „Blue Ocean Strategy“ as a method for sustainable development of profitable business models from the field of strategic marketing. The basic idea of the methodology is that sustainable success can only be achieved by the development of innovative new markets that offer the broad masses of customers and non‐customers truly differentiating and relevant benefits (Kim and Mauborgne, 2005). If these conditions are fulfilled for the customer, a carefully selected transfer partner would be able to use his company’s resources, e. g., production, sales and marketing, to realize a value creation process in short time.

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Bernd Neutschel et al. Regardless of which form of transfer is chosen, an experienced entrepreneur or manager is always required to design and implement the described process of value‐adding support (Figure 3).

Figure 3: Various methods of utilization of technology transfer

6. Mastering complexity in entrepreneurial decision making Considering the conditions for a successful transfer of science and technology, the complexity of the issue becomes visible. One of the most significant barriers to change public research institutions into a concept of entrepreneurial science is the necessary inertia concerning decisions (Warren et al, 2008). In this context, it is perhaps easier to understand why even young, capable, and well‐qualified students and researchers can be overwhelmed by the role of the entrepreneur in a science‐based start‐up company. Nevertheless, these concerns should be taken seriously, since they point to an interesting constellation. The experience in the SeJu project at the University of Magdeburg shows that product developers, economists, engineers, designers, or even psychologists, who are part of an interdisciplinary team (Figure 4) like to put their work under the guidance of an experienced seniorpreneur. Looking at the history of cooperation between the two involved university chairs, the balance can be described as outstanding and frustrating at the same time. From the standpoint of research and development, the balance is excellent with over 20 product innovations and business plans for entrepreneurial implementation. From the perspective of science and technology transfer, the net result is an urgent request to implement the accumulated value creation potential into the market.

Figure 4: Interacting SeJu team chart Can this unsatisfactory state of a science and technology transfer be improved by the integration of experienced seniorpreneurs? Recent experience arising from the SeJu project supports this assumption. Having managed to inspire an active entrepreneur for a start‐up idea, he integrated himself as „Head of Team“ and the „Decision Maker“ into the process of product and start‐up design. Right from the start of this project, it became evident that all people involved experienced a boost of motivation for their work. A major reason for this was that all parties realized that their development work went into an actual business establishment. A significant side effect is that students and staff learned about entrepreneurial thinking and acting for practice.

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Bernd Neutschel et al. One must not underestimate this aspect, because these experiences trigger in all people involved an ongoing process of reflection about whether they themselves could be future entrepreneurs. A project such as SeJu invites young and intelligent people from nearly all scientific disciplines to study the stresses and rewards of entrepreneurs, to become familiar with risks and threats, but also with the strengths and opportunities of entrepreneurial ideas.

7. Conclusion To become an entrepreneur or not equally depends on environmental influences and individual decisions. To make decisions is the high art that an entrepreneur needs to dominate and to exercise. The resulting experiences of good decisons in practise, together with the necessary knowledge of the theoretical foundations characterize the type of entrepreneur that is able to establish a concept of an “entrepreneurial university.” The evaluation results proof that the combination of elementary properties of seniorpreneurs on the one hand, in the form of entrepreneurial drive and experience, as well as science‐based knowledge on the other hand, controlled by a value‐oriented process, finally is able to lead to innovative entrepreneurial potential that is appropriate to create marketable products and to sell them profitably, whether in the form of start‐ups, profit centers or value transfers.

Acknowledgements The project „Senior‐ & Juniorpreneurship“ (SeJu) is funded by the European Social Fonds (ESF) and the Ministry of Science and Economics of the State of Saxony‐Anhalt, Germany. Key considerations on the issue of a “Entrepreneurial University” are due to the cooperation with the project “Universities as Enterprises” (Uni:prise) funded by the Ministry for Education and Research of the Federal Republic of Germany.

References Blanchard, B.S. (2004) System Engineering Management, Wiley, Hoboken, 3rd Edition, pp. 201‐206. Brown, J. (2005) New Product Development: Profiting from Innovation, Aberdeen Group (Business Value Research Series), pp. 1‐15. Clark, K.B. and Fujimoto, T. (1991) Product Development Performance: Strategy, Organization, and Management in the World Auto Industry, Harvard Business, Cambridge, pp. 101‐104. HMC, Harvey Mudd College (2012), [online], http://www.hmc.edu/clinic. Kim, W.C. and Mauborgne, R. (2005) Blue Ocean Strategy, Harvard Business School Publishing Corporation, Boston. Langerak, F. and Hultink, J.E. (2006) “The Impact of Product Innovativeness on the Link between Development Speed and New Product Profitability”, Journal of Product Innovation Management, Vol. 23, No. 3, pp. 203‐214. Neutschel, B., Gaus, O., Raith, M.G. and Vajna, S. (2013) “Value‐Focused Thinking – Combining Product Development and Entrepreneurial Product‐to‐Market Strategies”, Proceedings of the ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Chicago, Illinois, August 12‐15, 2012, Vol. 7, 9th International Conference on Design Education, ASME 2013, DETC2012‐70925. NSF, National Science Foundation (2012), [online], http://www.nsf.gov/funding/pgm_summ.jsp?pims_ id=5261. Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.H. (2005) Konstruktionslehre, Springer, Berlin. Proto, A., Tani, S., Bühnemann, J., Gaus, O. and Raith, M.G. (2012) "Knowledge Networks and Their Impact on New and Small Firms in Local Economies", OECD Local Economic and Employment Development (LEED) Working Papers, OECD Publishing. Raith, M., Staak, T. and Wilker, H. (2011) “High‐Expectation Entrepreneurship ‐ Strategic Planning for High‐Growth Start‐ Ups”, von Kortzfleisch, H.F.O. (ed.), Scientific Entrepreneurship ‐ Reflections on Success of 10 Years EXIST, EUL Verlag, pp. 305‐322. Vajna, S. and Naumann, T. (2001) “Implementation of the New IPD Study Course at the Otto‐von‐Guericke University Magdeburg”, Design Applications in Industry and Education, Proceedings of the 13th International Conference on Engineering Design (ICED 01) Glasgow, pp 277‐284. Warren, A., Hanke, R. and Trotzer, D. (2008) “Models for University Technology Transfer: Resolving Conflicts between Mission and Methods and the Dependency on Geographic Location”, Cambridge Journal Regions, Economics and Society, pp. 219‐232. Werner, A., Faulenbach, N. and Brockmeyer, A. (2008) Das Gründungsverhalten Älterer. Eine empirische Analyse mit den Daten des Gründerpanels des IfM Bonn, Institut f. Mittelstandsforschung Bonn (ed.), IfM‐Materialien Nr. 184, Bonn. Yoon, E. and Lilien, G.L. (1985) “New Industrial Product Performance: The Effects of Market Characteristics and Strategy”, Journal of Product Innovation Management, Vol 3, pp. 134‐144.

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Cooperation Activities for Innovation: An Empirical Analysis Applied to Iberian Countries Sandra Nunes1, Teresa Costa1 and Luísa Carvalho2 1 Economics and Management Department, Business School, Setúbal Polytechnic Institute, Portugal and CMA/FCT/UNL 2 CEFAGE‐ University of Évora, Portugal and Economics and Management Department, Business School, Setúbal Polytechnic Institute, Portugal sandra.nunes@esce.ips.pt teresa.costa@esce.ips.pt luisa.carvalho@esce.ips.p Abstract: The entrepreneurial structure of Iberian countries is mainly composed by small and medium enterprises (SME). To overpass the actual economic crises it is important to innovate in order to add value to products and services. In this context, innovation can help these firms to become more competitive and cooperation for innovation activities could be a key factor, for instance, to gain economies of scale, share the risk and to achieve new knowledge. This paper studies the cooperation for innovation activities in Portugal and Spain, analysing how several variables, such as R&D intensity, firm size, marketing and sector can contribute to cooperative activities of firms. The research uses Community Innovation Survey (CIS 2008, micro‐data) to Iberian countries and applied a logistic regression to study cooperation activities for innovation. We believe that the results obtained for these two countries provide important clues concerning different arrangements of cooperation activities and highlight some innovation patterns. Keywords: innovation; cooperation; CIS; Iberian countries

1. Literature review 1.1 Cooperation for innovation According to Tether (2002:949), “Innovation cooperation means active participation in joint R&D and other technological innovation projects with other organizations. It does not necessarily imply that both partners derive immediate commercial benefits from the venture. Pure contracting out work, where there is no active participation is not regarded as co‐operation.” Several studies point out the positive economic impact of cooperation on the competitiveness of firms (Powell et al, 1999; Hagedoorn et al, 2000; Cassiman and Veugelers, 2002), as well on performance and knowledge spillover and on success in the development of new products (Miotti and Sachwald, 2003; Sivadas and Dwyer, 2000). Cooperation for innovation must assure absorptive capacity in order to firms’ benefits from external spillovers and increase the profitability of R&D cooperation (Cohen and Levinthal, 1990; Cassiman and Veugelers, 2002). Cooperation activities also contribute to increase firm’s capability and their ability to benefit from future cooperative R&D projects (Mark and Graversen, 2004). 1.1.1 Cooperation for innovation in Iberian countries The outbreak of the global economic crisis changed the performance of modern economies. Some of the effects of the crisis are the production decline, bankruptcy of many financial intermediaries and a huge fall of turnover in financial markets. The consequences for the firms are: profit decline and a lack of financial funds that affects the systems of innovation in different countries. This subject, innovation and cooperation for innovation remains understudied. Most of the literature on innovation and empirical studies fail to carry out sufficiently in‐depth investigations to examine innovation, particularly in Iberian Peninsula. During the period 2008‐2010 Portugal was one of the countries with higher propensity to develop innovation activities (60% of firms). Concerning product and process innovation the countries with higher propensity to develop product and process innovation were Cyprus (62% of all product and process innovative firms), Austria

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Sandra Nunes, Teresa Costa and Luísa Carvalho (51%), Slovenia (45%), Lithuania and Hungary (both 43%). Portugal and Spain revealed lowest propensity to develop this type of innovation. In Portugal, 20% of firms developed product and process innovation and in Spain 22% of firms developed this type of innovation. Table 1: Innovation activity and co‐operation during 2008‐2010

EU27 Belgium Bulgaria C. Republic Denmark Germany Estonia Ireland Greece Spain France Italy Cyprus Latvia Lithuania Luxembourg Hungary Malta Netherlands Austria Poland Portugal Romania Slovenia Slovakia Finland Sweden U. Kingdom Iceland Norway Croatia Serbia Turkey

Cooperation partners Enterprises with All types of From another From the United From China or innovation innovation EU27 Member States India activity, % of all cooperation with State, EFTA or enterprises other enterprises or Candidate institutions country % of all product and process innovative enterprises 52.9 26.5 11.4 3.1 2.0 60.9 42.3 23.4 7.1 3.2 27.1 22.4 12.8 3.0 1.8 51.7 34.2 20.9 3.8 2.8 54.7 39.7 : : : 79.3 24.3 8.2 2.2 1.5 56.8 42.1 30.0 3.0 1.8 59.5 28.5 17.6 6.9 3.0 : : : : : 41.4 22.3 5.3 1.1 0.5 53.5 36.1 16.2 6.4 3.7 56.3 12.1 4.0 1.0 0.8 46.2 62.3 37.8 7.3 5.5 29.9 29.1 20.6 5.1 4.4 34.5 43.3 25.6 3.9 3.9 68.1 32.2 27.2 7.0 6.0 31.1 43.2 17.0 2.2 1.9 41.5 18.5 13.1 4.5 2.7 56.7 33.5 13.2 3.2 2.5 56.5 51.0 30.1 5.5 2.9 28.1 33.5 15.6 3.0 1.9 60.3 19.5 8.7 1.8 0.8 30.8 24.1 : : : 49.4 44.7 34.8 7.6 6.0 35.6 34.7 30.0 4.8 3.4 56.2 39.8 27.5 12.2 8.9 59.6 38.8 22.2 10.6 6.8 44.2 : : : : 63.8 32.2 13.1 4.2 : 43.5 30.6 16.4 5.9 3.4 42.4 32.6 19.9 3.9 2.8 51.7 24.9 14.4 3.1 2.9 51.4 18.7 5.5 2.1 1.9

Source: Eurostat, 2013

1.2 Factors that affect cooperation for innovation 1.2.1 R&D intensity and cooperation for innovation R&D is an important input used to study occurrence of innovation activities (Cohen and Klepper, 1991, 1992; Unger, 2005; Okamuro et al, 2011). The intensity of R&D can result in different performance. For example, a large sector can achieve a certain amount of R&D with an average intensity and a small sector can achieve the same contribution of R&D with a high intensity. Usually the measure of R&D intensity is the ratio of R&D

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Sandra Nunes, Teresa Costa and Luísa Carvalho investment and sales or revenue, so the percentage of revenue that is reinvested (Nunes et al, 2012). In a managerial perspective, R&D intensity is recognized as a robust phenomenon linked with resource allocation and new product development (NPD) portfolio strategies (Freyre, 2006; Kloeber, 2007). In academic view, several researchers, primarily in the domain of economics, highlight the consistency of R&D intensity. This research focuses on the industry as a unit of analysis and made an effort to prove that R&D intensity exhibits less variance within an industry then between industries. The majority of these efforts are based on analytic models of R&D spending (Kamien and Schwartz 1978, Nelson 1988, Cohen and Klepper, 1996). 1.2.2 Firm size and cooperation for innovation The size is also a central factor in the study of innovation (Pires et al 2008; Carvalho, 2010; Nunes et al, 2012). Acs and Audretsch (2003) identify five factors which facilitate innovation in large firms: 1) the innovation process absorbs high fixed costs (Galbraith, 1956; Comanor, 1987); 2) only the large firms with market power can appropriate the economic return of R&D (Levin et al, 1987; Cohen and Levin, 1989; Cohen and Klepper, 1991, 1992); 3) investment in R&D is very risky; when small and medium size firms invest a high proportion of their resources in R&D they are vulnerable to the outcome of the R&D process. Furthermore, larger firms can maintain a diversified portfolio of innovation projects in order to reduce their overall risks of performing innovative activities (Pires et al, 2008); 4) scale economies in production may produce economies of scope for R&D and 5) innovation costs are higher, in relative terms, for a small firm than for a larger firm. Financing costs may be higher for smaller firms due to capital market imperfections. Other studies relate firm size with the number of patents confirmation that the number of patents raises with the size of the firm (Bound et al, 1984; Scherer, 1984). Additionally, some studies propose that the relative contribution of small and large firms to innovation depends on industry conditions and, such as, market structure (Acs and Audretsch, 1987; Dorfman, 1987). Attending to cooperation for innovation, some studies refer differences in size. Large firms frequently have an R&D department with an important role in product innovations, in internal and external cooperation. Small firms prefer partnerships and networks to overcome limitations such as the lack of R&D department and resources (Zakic et al, 2008). 1.2.3 Sector and cooperation for innovation There are some differences between manufacturing and the services (Pires et al, 2008, Sarkar et al 2008). The absence of homogeneity inside the sector justifies the division of sector according to the technology intensity (Tether, 2001, 2002; Pires et al, 2008). Manufacturing firms are divided into four sub‐sectors: high technology, medium high technology, medium low technology and low technology. The classification of the services firms considers both the nature of the technology used and the services that each subgroup provides to the market (Miles, 1994; Tether, 2002): Knowledge intensive and less knowledge intensive services (OECD, 2009). Concerning the relation of sector and cooperation for innovation, cooperation with external partners assume an important role specially, in the case of highly R&D intense sectors and for innovations that are radical or imply knowledge and skills that firms’ don’t hold internally domain (Bayona et al., 2001; Miotti and Sachwald, 2003). 1.2.4 Marketing factors and cooperation for innovation Attending to the competitiveness factors that affect market performance, this study consider as marketing factors: increase or maintain market share, introduce products to new customer groups and introduction of the products into new geographic markets. 1.2.5 Increase or maintain market share The firm’s propensity to innovate depends on several internal and external factors that include aspects such as research, information search activities, and methods to protect the inventions, design, production, distribution and marketing.

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Sandra Nunes, Teresa Costa and Luísa Carvalho Concerning the innovation effects of demand factors it can be assumed that high export shares of sales and degree of diversification stimulate the development of innovation activities (Felder et al., 1996; Kamien and Schwartz, 1982; Nelson, 1959; Wakelin, 1998). Since firm size is not uniform within an industry, the market share is also an important indicator of market structure. Similarly to what happens with the market concentration, the intensity of R&D tends to increase market share, however, can reduce dramatically when a firm captures the entire market monopoly. Some studies point out that innovating firms are more likely to collaborate compared to non‐innovating firms. The one exception is to help keep current customers, suggesting that non‐innovators are more defensive concerning the maintenance of market share. Additionally, the collaboration for non‐innovators are linked with sharing of R&D (Kitson et al, 2001). 1.2.6 Introduce products to new customer groups The development of new products is an exigent task. The teams involved in the development of new products are permanently seeking out external resources to overcome the learning curves related to new technologies and new markets (Schilling and Hill, 1998). Several authors studied the participation of the customers in development of products (Leonard‐Barton, 1995; Rothwell, Freeman and Townsend, 1974; Von Hippel, 1988). For Brown and Eisenhardt (1995) customer involvement in this development has given important contributes to enhance product concept effectiveness. However, other author’s don’t agree with this perspective (Wayland and Cole, 1997). For them one of the most important factors that limited the participation of customer in product development is related to the poor connectivity between customers and producers. Nevertheless, only some innovations create new costumers. Literature frequently refers to radical innovations as innovations that represent a new technology that result in a new market infrastructure. According to Garcia and Galantone (2002) when an innovation causes discontinuity at industry or market level it also causes discontinuities on the firm and customer level. When a radical innovation causes the appearance of a new industry, new firms and new customers also emerge for that innovation. So, radical innovations usually create a new demand that encourage new industries with new firms, competitors, distribution channels, and new marketing activities. Additionally, cooperation for innovation is a key variable to the success of the product innovation, and implies both internally cooperation between different functions (forming of teams of inter‐crossed functions) and external cooperation with other stakeholders (customers, suppliers, business partners, innovators, institutes, faculties, government, standardizing bodies, independent experts, etc.) (Zakic et al, 2008). 1.2.7 Introduction of the products into new geographic markets In a first phase firm recognizes that can be profitably sell a product in a new geographic market. Products for exports typically follow a similar pattern (Wells, 1971; Feenstra and Rose, 2000). Lin (2000) proposes a positive correlation between the decision of one firm to export and the export trend of neighbor firms. Additionally Bedi and Cieslik (2000) point out a relation between export concentrations of foreign industries and export volumes of local firms. Analyzing the relationship between cooperation for innovation and introduction of the products into new geographic markets, Tether (2002) argue that from a subjective firm perspective most firms still develop their new products, processes and services without developing formal cooperative arrangements for innovation with other organizations. Nevertheless, firms that engage in R&D and that are trying to introduce higher level innovations, such as, new products or services new to the market or to the firm, are more likely to engage in cooperative arrangements for innovation.

2. Hypothesis The literature review presented aims to explain the cooperation for innovation activities regarding, R&D intensity, firm size (size 08), marketing innovations (OMKTS, OMKTCG, OMKTGM) and sector. The research hypotheses are as follows:

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Sandra Nunes, Teresa Costa and Luísa Carvalho H1:

R&D intensity is positively related to co‐operative activities for innovation;

H2:

Firm size is positively related to cooperation activities for innovation;

H3:

Sector is positively related to cooperation activities for innovation;

H4:

Marketing is positively related to cooperation activities for innovation.

3. Data and methodology 3.1 Database and descriptive statistics The data source is the Community Innovation Survey (CIS 2008) for Portugal and Spain. The CIS takes place every four years in European countries in order to examine innovative activities in firms. The CIS is based on a harmonized questionnaire and survey methodology monitored by Eurostat. The harmonized CIS 2008 questionnaire (based on Oslo Manual, 1997) focuses on product and process innovation and looks mainly at the effects of innovation, sources of information about innovation activities and innovation expenditures. In line with our main goal, an analysis of factors that positively influence cooperation for innovation was made in Spain and Portugal. The study defines firms that undertake cooperative innovative activities using the following question from CIS 2008: During the three years 2006 to 2008, did your firm co‐operate on any of your innovation activities with other firms or institutions? This question allows for a yes or no answer. The selected sub‐samples are presented in table 2. Table 2: Samples by countries Sample (N)

Spain 5112

Portugal 2039

Table 3 presents the variables description. The dummies variables considered assume value 1 to the answers yes and 0 to answers no. In the case of the sector, the codification 1 refers to firms in manufacturing sectors and 0 refers to firms in services sectors. Table 3: Variables description Variable name Co

R&D intensity Size 08 Sector OMKTS OMKTCG OMKTGM

Description Dependent variable Dummy – firms that co‐operated with other firms or organizations in innovation activities Independent variables Ratio of intramural R&D expenditure in 2008 over Turnover in 2008 Qualitative ordinal with 3 categories (small, medium and large) Dummy – firms in manufacturing sectors Importance of increase or maintain market share – qualitative ordinal with 4 categories (not relevant, low, medium and high) Importance of introduce products to new customer groups – qualitative ordinal with 4 categories (not relevant, low, medium and high) Importance of introduce products to new geographic markets – qualitative ordinal with 4 categories (not relevant, low, medium and high)

Table 4 allows understanding the distribution of sectors in the samples. The manufacturing sector is, for both countries, the most representative, in Spain goes beyond 60%. Table 4: Sector classification by country Sector classification Manufacturing sectors Service sectors

Spain 3167 1945

Portugal 1130 909

Table 5 reveals the distribution of firms according to their size. Portugal and Spain present a high preponderance of small firms in the sample. In Spain, we have 56% of small firms versus 12% of large and in Portugal the percentage is 57% compared to 11%, as we can see the distribution is similar. Figures 1 and 2, present the information of tables 4 and 5, considering the relation between the variables observed.

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Sandra Nunes, Teresa Costa and Luísa Carvalho Table 5: Firm size classification by country Firm Dimension (size08) Small (=<50) Medium (>50 and =<249) Large (>=250)

Spain 2864 1622 626

Portugal 1161 647 231

Figure 1: Firm size vs Sector in Portugal

Figure 2: Firm size vs Sector in Spain

4. Empirical results The empirical study used a logistic regression to investigate the effects of a number of explanatory variables on a binary response variable (a variable which can take only two values, 0/1 or no/yes). In the present study, this response variable represents the presence or absence of cooperation in the innovation process. Logistic regression relies on maximum likelihood estimation rather than OLS estimation and is generally used to study this type of model. Tables 6 and 7 presents the model including all variables identified in literature reviewed for Portugal and Spain, respectively. Table 6: Logistic regression identifying co‐operators for innovation in Portugal Variable Firm Size

Constant R&D intensity Sector Small Medium High

Coef.

Wald

Sig

Odds‐ratio

1,113 ‐,146 ,036 ‐1,426 ‐,995 ‐‐

46,504 1,145 ,141 80,666 35,748 ‐‐

,000 ,285 ,707 ,000 ,000 ‐‐

3,044 ,864 1,037 ,240 ,370 ‐‐

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Sandra Nunes, Teresa Costa and Luísa Carvalho Variable

OMKTS

OMKTCG

OMKTGM

Not relevant Low Medium High Not relevant Low Medium High Not relevant Low Medium High

Coef.

Wald

Sig

Odds‐ratio

,087 ‐,540 ‐,344 ‐‐ ‐,272 ‐,425 ‐,186 ‐‐ ‐,145 ‐,008 ‐,265 ‐‐

,061 3,899 8,165 ‐‐ ,968 3,825 2,385 ‐‐ ,646 ,002 4,555 ‐‐

,804 ,048 ,004 ‐‐ ,325 ,050 ,123 ‐‐ ,422 ,960 ,033 ‐‐

1,091 ,583 ,709 ‐‐ ,762 ,653 ,830 ‐‐ ,865 ,992 ,767 ‐‐

According to results presented in Table 6 some variables not present significance at least 10%, to improve the model these variables were removed from the model. Table 7: Logistic regression identifying co‐operators for innovation in Spain Variable Firm Size

OMKTS

OMKTCG

OMKTGM

Constant R&D intensity Sector Small Medium High Not relevant Low Medium High Not relevant Low Medium High No relevant Low Medium High

Coef.

Wald

Sig

Odds‐ratio

,203 ,001 ,210 ‐1,020 ‐,529 ‐‐ ,416 ,076 ,114 ‐‐ ‐,132 ,028 ‐,025 ‐‐ ‐,740 ‐,495 ‐,321 ‐‐

4,273 ,030 11,250 124,364 30,326 ‐‐ 4,032 ,492 2,471 ‐‐ ,521 ,059 ,089 ‐‐ 24,107 22,485 13,144 ‐‐

,039 ,862 ,001 ,000 ,000 ‐‐ ,045 ,483 ,116 ‐‐ ,470 ,807 ,766 ‐‐ ,000 ,000 ,000 ‐‐

1,225 1,001 1,234 ,360 ,589 ‐‐ 1,516 1,079 1,121 ‐‐ ,876 1,029 ,975 ‐‐ ,477 ,609 ,726 ‐‐

Once again also for Spain (Table 7) there are some variables that are not significant at a level of at least 10%. In order to improve the quality of the model it was used the forward logistic regression method that allowed obtaining the final model present in Tables 8 and 9. Table 8: Final logistic regression model for Portugal Variable Firm Size (Sig. 0,000) OMKTS (Sig. 0,000)

OMKTGM (Sig. 0,029)

Constant Small Medium High Not relevant Low Medium High Not relevant Low Medium High

Coef. 1,133 ‐1,461 ‐1,026 ‐‐ ‐,011 ‐,703 ‐,419 ‐‐ ‐,255 ‐,106 ‐,335 ‐‐

Wald 51,449 85,348 38,360 ‐‐ ,001 7,115 13,493 ‐‐ 2,509 ,540 8,329 ‐‐

Sig ,000 ,000 ,000 ‐‐ ,975 ,008 ,000 ‐‐ ,113 ,463 ,004 ‐‐

Odds‐ratio 3,105 ,232 ,358 ‐‐ ,990 ,495 ,658 ‐‐ ,775 ,900 ,715 ‐‐

It was possible to observe (Tables 8 and 9) that the final model is slightly different for Portugal and Spain. In both models all variables are significant at a 5% level. The variables “Firm size” and the “Importance of introduces products to new geographic markets” are common to both countries, indicating that the size of the

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Sandra Nunes, Teresa Costa and Luísa Carvalho firm and the increase in exports are the biggest innovation indicators. Furthermore, it is noted that the variable “Sector” is significant in Spain but not in Portugal, and exactly the opposite regarding the variable “Importance of increase or maintain market share”. Table 9: Final logistic regression model for Spain Variable Firm Size (Sig. 0,000) OMKTGM (Sig. 0,000)

Constant Sector Small Medium High Not relevant Low Medium High

Coef.

Wald

Sig

Odds‐ratio

,232 ,200 ‐1,015 ‐,526 ‐‐ ‐,722 ‐,445 ‐,290 ‐‐

5,889 10,291 123,862 29,973 ‐‐ 36,164 28,774 16,474 ‐‐

,015 ,001 ,000 ,000 ‐‐ ,000 ,000 ,000 ‐‐

1,262 1,221 ,363 ,591 ‐‐ ,486 ,641 ,748 ‐‐

Table 8 reveals that the odds ratio for cooperation for innovation decreases when comparing companies with high importance of increase or maintain market share to all other classes. Similar results are possible to find for the importance of introduce products to new geographic markets and also for the firm size. It is possible to conclude that in Portugal in all cases the upper classes has a higher probability of cooperation for innovation. Regarding the results for Spain, Table 9, allows similar conclusion for the two common variables (firm size and importance of introduce products to new geographic markets). Finally, the results showed that the odds ratio of a firm that cooperates for innovation increases in firms from services sector. Table 10: Model adjustment quality Cases correctly classified Hosmer and Lemeshow Test Qui‐Square (sig.) Omnibus test Qui‐Square (sig.)

Portugal 62,4%

Spain 66,4%

9,898 0,194

8,605 0,377

142,999 0,000

196,725 0,000

The adjusted model quality (Table 10), allowed observing that the percentage of correctly classified cases is in both cases over to 60%. The chi‐square statistics indicates, for both countries, that the independent variables are relevant in explaining the dependent one, the results of Hosmer and Lemeshow test confirms the overall quality adjustment.

5. Discussion of results and concluding remarks This paper examines the cooperation activities for innovation in Iberian countries. The entrepreneurial structure of Iberian countries is mainly composed by SME. This kind of cooperation could be a key factor, for instance, to gain economies of scale, share the risk and to increase knowledge. The empirical model allows highlight some particular aspects and also validate the hypotheses. Regarding the first hypothesis (H1: R&D intensity is positively related with co‐operative activities for innovation); since this variable was excluded from the final model (denoting non‐significance) nothing can be concluded about this relationship. The results tend to confirm that R&D intensity cannot be considered a perfect indicator to measure the cooperation for innovation in Portugal and Spain. The results also suggest that data are particularly composed by SME and some approaches refer a lack of studies applied to SME (Bayona et al, 2001; Fontana et al, 2006). Concerning the second hypothesis (H2: Firm size is positively related to cooperation activities for innovation), it is significant in both countries and the odds‐ratio between the different classes has the expected relationship. The results suggest that the relationship established have negative effects. These results are counter‐intuitive as expected, therefore, an issue that requires further investigation.

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Sandra Nunes, Teresa Costa and Luísa Carvalho With reference to the third hypothesis (H3: Sector is positively related to cooperation activities for innovation); the obtained results also allow confirming the results for Spain. In Portugal, this variable was not significant and was excluded from the final model. This indicates a positive effect in the cooperation for innovation that increases when the company belongs to the service sector. Cooperation with external partners assumes an important role especially in services, in radical innovations or in innovations that imply knowledge and skills not available internally (Bayona et al, 2001; Miotti and Sachwald, 2003). Concerning to the last hypothesis (H4: Marketing is positively related to cooperation activities for innovation), only the variable “Importance of introduce products to new geographic markets” was considered significant for both countries. The odds‐ratio between the different classes suggests that the relationship established have negative effects. These results are counter‐intuitive as expected. Also, this issue requires further research. The variable “Importance of increase or maintain market share” appears only for Portugal, and once again the effects have negative sign. Finally, the variable “Importance of introduce products to new customer groups” was not significant for both countries. An analysis of the results suggests the following remarks:

R&D intensity is not an appropriate variable, maybe because the economic structure of these economies are mostly services and the percentage of cooperation for innovation in these cases are lowest than the EU average.

Size influences positively cooperation for innovation in both countries confirming other studies cited in literature review.

Sector influences positively cooperation for innovation in Spain. However, the empirical study point out a different result to Portugal. Portugal has an economic structure where 99% correspond to SME and more than 70% of the firms belongs to service sector. In service sector the cooperation for innovation assume a more tacit profile instead of a formal cooperation.

Marketing factors reveal different behaviours. The factor introduces products to new geographic markets are significant to booth countries. Concerning the literature review the cooperative arrangements assume fundamental importance in both cases due to the reduction of the risk associated to internationalization process mainly in the case of more peripheral countries. Market share appear significant only to Portugal, suggesting that some marketing strategies are linked to market dimension, in the case of Portugal to a small market. Finally, the factor introduce products to new customer groups, are not significant in booth countries, the results could be related with economic structure of Iberian countries mainly composed by SME. The economic structures are predominantly composed by structures of perfect competition and monopolistic competition. This kind of economic structures don’t promote cooperation arrangements in the markets.

This study is mainly exploratory and provides clues for further investigation in order to understand and detail the behaviour of cooperation activities for innovation. Further research should aim to overtake the limitations in the present work such as: identifying other relevant variables that influence cooperation for innovation in southern countries.

Acknowledgements The authors would like to thank the Statistical Office of European Union for making European CIS data available for their research. This research was partially supported by national funds through FCT, Foundation for Science and Technology, projects Pest‐OE/MAT/UI0297/2011 (CMA/FCT/UNL).

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Organizational Innovation – can job Enrichment Enhance Employee? Morena Paulišić, Tea Golja and Barbara Unković Juraj Dobrila University of Pula, Pula, Croatia mpauli@unipu.hr tgolja@unipu.hr barbara.unkovic@unipu.hr Abstract: Recently, an assistant manager of the biggest hospital complex in Croatia gave a statement on organizational culture claiming it is much more likely that an environment favourable to innovation will be more responsive to innovation stimulating the flow of the idea. This creates a particular culture of innovation where those who do not innovate are the outsiders. So, innovative capability is perceived to be important asset for sustainable competitiveness and this was a “push” to our research. According to Carroll (1973) humanistic management is often called job enrichment and today humanistic management is every day more important in service industry and often connected with companies’ success. In accordance with previous studies which stressed the role of job design for employee innovativeness in the paper we observe the concept of organizational innovation and the variety of job enrichment strategies as basic ingredients of employee motivation to create new values. The paper starts by defining theoretical approach of job enrichment as HR strategy to enhance innovative behaviour at work place. The aim of this paper was to investigate the implications of changing role of HRM on organisational innovation with the focus on job enrichment. The authors’ purpose was to describe actual business situation of HRM on five biggest hotels in Croatia and to examine what determine the extent to which HR strategies in form of job enrichment can persuade innovation. A field research has been carried out in 2012 through semi‐ structural interview in which our theoretical hypotheses were discussed trying to find a pattern of HR strategies enabling innovation. Results are reported as descriptive observations and implications. Comparison of companies showed the differences between organisation of HRM unit; HR managers’ expertise; job descriptions; job enrichment; innovativeness and companies’ success. Research results showed that in case of Croatia, as expected because of political history individualism is contrasted with collectivism as a characteristic of an organization's culture inclined to innovation. Hotel companies which overcome traditional approach to HRM and included in job redesigning different HR strategies as job enrichment, performance management, and multi‐tasking … are more successful. Therefore we argue that the data support job enrichment strategies in reaching organisational innovativeness. Keywords: organizational innovativeness; workplace; job enrichment, hotel industry; Croatia

1. Introduction There are wide array of possibilities which strongly influence the innovation process ‐ from organizational culture, social responsibility, business ethics, to innovative human resource management. Our intention was to detect what human resource management (HRM) does in order to enhance organisational innovativeness with hypothesis that job enrichment strategies can enhance employee to create added value for the organization. The reason for such hypothesis is in theory that workplace innovations provide competitive advantage to organizations and the main goal of human resources management should be to answer a question: How can employees be motivated to give more and can we contribute to organizational innovativeness all in order to give an added value to organisation? One of possible answer could be job enrichment because it involves new ways of thinking and motivating employees. The vision of organizational innovativeness (Gjerding & Rasmussen, 2007) is a phenomenon that occurs through a combination of institutional management (organization, job design), group management (cooperation, team work), and self‐management (task, work environment). Innovative working is a key challenge for many organisations; although complex we believe that the right combination of different job enrichment strategies can create a formula for success. Encouraging innovation as an outcome poses a major challenge for human resource management, to guide and develop leadership, policy, knowledge creation, information systems, practices, processes, and strategy that support the creativity and implementation of innovation (Rose, 2005, 85) and for entire company. But, we have to bear in mind, innovation is not just a question of the employees becoming open‐minded and creative; it involves interdependencies that play out at the organizational level and beyond (Evans, 2012). So if workplace innovations provide competitive advantage to organizations, companies must put effort to ensure employee driven innovation (EDI), especially in service sector. It refers to daily review of organisational processes and practices often across internal boundaries and among employees not assigned directly to the task. But as Evans (2012) said understanding of the dynamics of organizations is crucial to the development of EDI, not just a backcloth but as constitutive of the ways in which activities are structured and how employees act. Therefore, changes are required in job design which should incorporate environmental dynamics, the

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Morena Paulišić, Tea Golja and Barbara Unković organization’s resources, and individual preferences (Kamery 2004, p.141). One method that can be used in the process of designing motivating jobs (Kamery 2004, p.141 according to Robbins and Coulter 1996) is job enrichment.

2. Discussion 2.1 Preconditions for innovative organization In today world innovation seek to drive economic growth and to assure organizational success. Often innovation is not radical, it is incremental based on constant improvements. Innovation is not always a question of product / service it is also a question of better internal processes which assure work well‐ being, commitment to work, job satisfaction influence on clients and stakeholders. In deep, it is a question of overall job enrichment. Increasingly, research on motivation is focused on approaches that link motivational concepts to changes in the way work is structured (Robbins et al., 2010, 173). Modern managers are interested in theories of motivation as sources of alternative methods for encouraging motivation, innovation and high performance. As Torrington et al. (2009, 255) stated: if organisational strategy is innovation; HRM policies must: assure interaction and coordination among groups and individuals; performance appraisal must reflect longer‐term and group based achievements; job must allow employees to develop skills that can be used in other positions in the firm; compensation system that emphasize internal equity; allow employee to be stockholders and have more freedom to choose the mix of components that make up their pay package; broad career paths to reinforce the development of a broad range of skills. Other words job enrichment. Nedelko & Potocan (2012, 37) suggested that thinking in innovative environment means: interdependency, partial harmony / partial diversity, constant change and radical change. The way in which the job is designed determines also the additional accessorizes available for stimulating the full potential of enrichment. Job sharing is believed to broaden the depth of organizational knowledge, bringing two diverse sets of skills, experiences, and perspectives to a position that would traditionally be occupied by only one person. With such arrangements both can benefit, the organization and the job‐sharing partners (Hunter, 2000). Job rotation policies by their observation should also generate new ideas how the company could operate better. Ichniowski and Shaw (2003) used an “insider” approach to understand how human resource management practices affect performance effects. Innovative HR practices, and their common objectives, include problem‐ solving teams aiming at involving in solving production problems, rotation of workers across jobs to increase worker flexibility and teamwork, careful screening and selection of workers in order to identify those who have both high‐level job and task‐related skills and broad job definitions. On the other hand innovations in HR practices produce tangible performance gained by reinforcing productive working behaviour (Ichniowski and Shaw, 2009). Today’s jobs are really complex and often employees’ expectations are motivating jobs. Most employees seek – because of motivational factors – autonomy, responsibility, and their own control. In return, they are committed, innovative, and overall interested in the work they do (Gonan Božac et al, 2012). For HR managers it is important to design motivating jobs in order to be competitive through innovations. Generally people are interested to “be involved”. So job enrichment arises as possible HR strategy.

2.2 Job enrichment as HR strategy Job enrichment is an intra‐organizational, procedural method to enhance organizational innovativeness and it is based on people’s expectations. Job enrichment (Accel Team 2005) is one of main tools in the managers’ kitbag for motivating the team among approval, praise and recognition; financial initiatives; good communications etc. Most important it allows the individual in organisation to grow, to be important, to give suggestions, to organise, to take responsibility, to use its skills and competences. Job enrichment (Robbins et al. 2010, Kamery 2004) refers to the vertical expansion of jobs that provides increased worker responsibility (i.e. planning and evaluating duties; etc.). Job enrichment could be a mixture of empowerment upgraded with responsibility in order to oversee the whole process of a certain role. Job should be organized in a way to allow the employee to do a complete activity. An enriched job organizes task so as to allow the worker to do a complete activity, increases the employee’s freedom and independence, increases responsibility and provides feedback so individuals will be able to assess and correct their own performance (Robbins et al. 2010, p.176). Job enrichment offers great opportunities for change, with improvement in staff morale, greater utilization of personnel, and improved services as the result (Grose, 1976), so it can enhance innovative work. Drucker (1974, 2001) points out that experiment in job enrichment have so far been confined to cleric operations, but that it seems particularly applicable to knowledgeable work positions. Job enrichment offers a solution to the «donkey work» (Grose, 1976). Job enrichment increases complexity of the work (Mullins 2010), giving

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Morena Paulišić, Tea Golja and Barbara Unković employee responsibilities normally allocated to supervisors offers to individuals more autonomy, by removing supervisory role, or redesigning it to involve other activities more in line with their talent and offering greater opportunities for psychological growth. This has more recently been linked to the related concept of employee engagement, employee empowerment and high performance working system (Buchanan & Huczynski 2011.) When employees take accountability for their own actions or duties it generates a sense of ownership directing them to think logically and responsibly. Considering a certain level of role clarity managers can influence situational‐level motivation by empowering employees to choose to act (Cadwallader et al., 2010). Then employee becomes a better judge of its own actions striving for an active participation and innovative thinking towards betterment of the organization and personal growth. Having more control over a task the employee is more disposed and more open to innovativeness (Saavedra & Kwun 2000, Dodd & Ganster 1996). Those intangible resources that firms employ in order to increase their profit and boost innovativeness are seemly protected 'magical potions'. People’s attitudes and behaviour regarding their job can be shaped as much by the structure of the company within which they work, as by the personalities that they possess and the groups and teams of which they are a part (Buchanan & Huczynski, 2011). So the question is: What kinds of strategies spur innovations? Different authors give different strategies for job enrichment. Mohr and Zoghi (2006) suggest job rotation, information sharing, teams, quality circles and classroom training. While Robbins et al. (2010, 177) explain that actions for enriching a job are: combining tasks, form natural work units, establish client relationship, expand jobs vertically and open feedback channels. But for success of suggested actions have to be supported by job dimensions as: skill variety, task identity, task significance, autonomy and feedback (Robbins et al. 2010, p.177). For McShane and Von Glinow (2005) there are two ways to enrich jobs: clustering task into natural groups (stitches highly interdependent tasks into one job) and establishing client relationship (involves putting employees in direct contact with their clients rather than using the supervisor as a go‐between). Dauda (2010, according to Blauner, 1972) focuses on self‐teams; engagement; and feedback (open communication). While Oladele et al. (2010) in detail suggest the utilization of the following job enrichment techniques: removal of control of a subordinate; assign a complete unit of work that can be done by a subordinate without following job procedure; provision of feedback directly to employee by supervisor; assignment of new or specialized tasks; rotating assignments or job schedules; implementing participative management; removal of difficult section of assignments; adjusting performance target; reduction of control of a subordinate; provision of additional authority to subordinates; increasing the degree of decision making of subordinates; encouraging increased use of techniques; increasing the amount of recognition for a job well done; involvement of subordinates in the identification and solution of problems that affect them and the organization; provision of employees with the feelings of belongingness; and combination and /or rearrangement of tasks to be more challenging. Or simply job enrichment (Gonan Božac et al., 2012) stresses the humanizing and self‐fulfilling potential of an expanded organizational role, including: scheduling (when you do what during the day); decision making (meaningful involvement in the decisions that affect your tasks, your job, and your role); meaning (who does your work help and how important does it seem to you); and feedback (the information that you receive on how your efforts contribute to the goals of your unit, users, etc.).

3. Research results 3.1 Methodology A field research has been carried out in 2012 through semi‐structural interview in which our theoretical hypothesis were discussed trying to find a pattern of HR strategies enabling innovation. Semi‐ structural interviews were conducted with HR managers of the five biggest hotels in Croatia. Framework of themes of job enrichment strategies in enhancing organisational innovativeness were formalised to be explored. The topics covered within the interview were cautiously defined. Among the authors of this article, one had a relevant previous working experience in employment agency and also as HR director, so we avoided the two main biases – untrained interviewer with low motivation (Shoughnessy et al., 2012). The interview was designed as face – to – face coffee table talk with visit of the workplace. Interview lasted approximately 45 minutes. Semi‐ structured interviews had a list of topics in the same order with the possibility to use probes judiciously in order to get the respondents to elaborate further on ambiguous or incomplete answers. The advantages of a free‐response question are that they offer to a respondent greater flexibility. However difficulties arise in recording and scoring responses to open‐ended questions. So, after investigating we agreed to provide the results in a form of ‘candidate profiles type of document’ in grid, as it is used as part of selection procedure in

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Morena Paulišić, Tea Golja and Barbara Unković order to keep the quality of the gathered data and relief the understanding of the matter. The structure of the topics and its order followed a planned scenario. In general, interview design was: after a brief introduction the HR manager was asked to present its working experience in short in order to get a profile overview and skip the initial spurious interpretation from our side. However the ability to generalize from a single case depends on the degree of variability in the population from which the case is selected, psychologists have agreed that with visual perception study is possible to generalize, even based on one individual (Shoughnessy et al., 2012). Afterwards each interview started with the HR department scanning so to get the scheme of it and gain access to real processes. Here open questions were posed for an insight of the processes blueprint. Following the line of topics to discover we skipped into job enrichment field and asked closed questions on its familiarity with used methods, if in use an open question was served to find out the practice. Job descriptions and process mapping question was a chronological step further in revealing the internal organisation issues while focusing on innovative traces in the system. In fact important fragments came out as direct evidence of past company behaviour as a result of selective wear of the one being interviewed. A closed question on internal culture was on turn, and for performance management an open one enabling HR managers to explain and combine previously mentioned topics. Two short closed questions for finalising the interview were asked at the end regarding international management and staff members, and self‐perception and success. The conclusion drawn by both sides were ‘it was a dialogue that both sides could benefit from’. Results are provided in a form of ‘candidate profiles type of document’ in grid, as it is used as part of selection procedure in order to keep the quality of the gathered data and relief the understanding of the matter.

3.2 Findings Comparison of companies showed the differences between organisation of HRM unit; HR managers’ expertise; job descriptions; job enrichment; innovativeness; internal culture; performance management and companies’ success (table 1.). Table 1: Companies’ profile document Topics HR manager expertise overview

Company A Lawyer, 20 years working in the same unit of the Company

Company B Economist. Experienced various job positions from low operative jobs in hotels, marketing unit until HR manager.

HR unit constituent parts

Personnel unit with composition: Employment, Education (just for low level workers), Payroll, and Employee administration.

Human Potential Unit with composition: Employee administration, Payroll, and Training and Development. Part of a bigger business group but can operate independently.

JOB ENRICHMENT

Never heard. They use

Yes, they use job rotations,

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Company C Lawyer; have changed several companies in the same industry. Similar internal cultures. Being an independent consultant for a while and came back. Human Potential Unit with composition: Search and selection, Training and Development and Employee administration.

Company D Lawyer, recently joined the Company. Most working experience gained in government public institutions.

Company E Psychologist, before had own consultancy company for a relevant amount of time.

Till recently a Personnel unit, but firmly on the way to became Human Potential Unit. Composition at the moment: Employee administration, Search and selection and Organizational affairs (job descriptions and workplace systematization).

Yes, they do job rotations but

Never heard. But their management

Human Resources Unit with composition: Employee administration affairs (including Search and selection) and Training and development (carrier planning, succession and performance management). Yes, job rotation


Morena Paulišić, Tea Golja and Barbara Unković Topics methods

Company A evaluation once a year. Do not wider jobs neither systematically move employees.

Company B and they use interdisciplinary teams among business functions.

Company C there is no systematic approach. No carrier planning or promotion process.

Process blueprint and Job descriptions

They have it, but very old dated, need refreshments.

Have process blueprints but no job descriptions.

They have it, but very old dated, need refreshments.

Encourage improvement and employee participation. During off pick period they hold workshops were everybody in the Profit Centre is invited to give a suggestion. Then their operations present the new planning for the next year. They think they are on the border between individualist and collectivist society (‘when somebody fails they think a lot about that person and what to do’). They manage performance by yearly valuation for middle and high management. Low level employees have stimulation fee

Not focused on innovativeness. Mentioned that middle and top management exchange opinions on trainings. They ‘do not expect suggestions from maids’.

Do not think about it.

Collectivists, but getting better, they said.

They think they are individualist with a huge collectivist heritage.

Collectivists.

Recently established a Performance management system. Structured in 3 levels: for administration and general

Do not manage it; they plan to introduce a performance management system in 2014. But still they have appraisals; For low level employees

Very structured, for middle and top management consist of yearly bonus. Several criteria within

INNOVATIVENESS They are not and motivation focused on it, for it do not motivate it.

Internal culture – Individualist or Collectivist

They think they are on the border between collectivists with social system heritage and western culture.

Performance management – measuring?

Do not motivate performance, but have variable element of pay (till 30%). Chief decides on it, mostly for an

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Company D (international) company does lead the HR strategy. After explaining the possible methods he said: that the management Company does trainings and development, job rotations, carrier programmes. Recently started to communicate in between, before there was no link at all. No process mapping, but working on Job description preparation, old dated.

Company E system (structured approach depending of type of rotation), widening jobs through increased complexity of jobs, change of vocation/job procedure, succession programme, and carrier plan. Have all processes mapped, and designed Job description based on them. Yes, they have a tailored programme for improvement suggestions at all employee levels.


Morena Paulišić, Tea Golja and Barbara Unković Topics

Company A extraordinary effort, but there are no transparent or clear criteria.

Company B for season picks. Have clear criteria and percentage.

Self‐perception and success

Successful. Employees work there until retirements. Exceptions are seasonal workers. Recently established an interdisciplinary team to prepare an Action plan for HR till 2014. (Haven’t mentioned until being asked about future plans). 549 32.146.281

Successful, everybody stay till retirements. The same seasonal workers every year. Use internal audit and mystery shoppers.

1353 81.621.895

922 60.334.946

869 55.110.371

1625 71.963.291

(‐2.521.995)

(‐1.116.597)

7.110.138

2.985.200

(‐4.051.179)

2.521.995

32.938.666

10.006.727

7.992.000

8.337.333

Other remarks

No. employees Revenue 2011 (EUR) Profit 2011 (EUR) Long term investments 2011 (EUR)

Company C Company D affairs, heads of quantitative production units criteria, and for and low level middle and top employees. management KPIs Measuring and (criteria based on rewarding cost of work and performance is subjective based on BARS measure of or Behaviourally ‘respecting’ the anchored rating job). They set scales. goals and projects Descriptive but with no categories and framework, and goal setting. no guidelines. There is no punishment, neither appraisal. During the seasonal pick two months in a row the stimulation part is shared among employees based on numbers of nights. Successful, even They perceive seasonal themselves as workers the successful. Do not same. Every few conduct internal years they climate check the questionnaires. internal climate. Recently have They do not have introduced vision, mission and ‘Talent corporate culture management strategy. program’. They have freshmen program (3 years long) and a Introduction programme for new employees.

Company E thematic topics, clear set of guidelines, in Company framework.

Successful, even very low percentage of sickness (in seasonal picks). Matured process operations, process grid in line and well combined horizontally and vertically.

Due to differences in strategic approach in analysed hotel companies we can identify that most successful in leading HRM is company E. Although the company with most value added in 2011 (added value of 26.190. 000 EUR) was Company C. Company E, is on second place with value added of 19.572.000 EUR. This company is “new” company integrated in September 2010 from three different hotel companies, so they are still in

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Morena Paulišić, Tea Golja and Barbara Unković alignment phase but huge attention was given to HRM. Company is using interdisciplinary approach in HRM function, the manager is psychologist with experience in human resources; the department is organised in two main parts with focus on: Employee administration affairs (including search and selection processes) and Training and development section (including carrier planning, succession and performance management). From all job enrichment techniques that are available, company is using: job rotation system; widening jobs through increased complexity of jobs, change of vocation/job procedure, succession programme, and carrier plan. Specific is also that they have all processes mapped and job description based on them. Also they enhance innovativeness with tailored made programme for improvement, suggestions for all employees’ level. The companies’ orientation is on matured process operations, process grid in line and well combined horizontally and vertically. The company also have own human resource academy. At this point we need to consider also the value orientation of the individual and company too because all companies are struggling with the problem of internal culture as well as culture of people in Croatia (with the collectivistic culture). The problem arising because collectivism is the idea that a group’s well being is more important then the individual, while individualistic value structure emphasize personal identity, uniqueness, freedom, worth of individuals as core value, all mechanism to enhance organisational innovativeness. If we consider rewards, employees working in a collectivistic culture primarily employ the norm of equality to determine how rewards should be doled out, regardless their competence and success. Although, there is a change in reward management, for example Company E has structured performance measurement ‐ for middle and top management consist of yearly bonus and several criteria within thematic topics, clear set of guidelines, in Company framework. But employees working in individualistic companies tend to distribute rewards to a norm of equity, based on the amount of contribution someone has made or the quality of their performance, and this is quality improvement in our value system which has to be done. Collectivism makes also difficulties because companies often have international management and staff , in case of Company E ‐ board members, and specialists and international staff, English language is commonly used and having an impact as cultural intervention, as well as higher expectations from international superior toward local staff members. Due to huge difference in public perception as well in organisation functionality, revenue, investments (in people and assets) of the analysed companies it is interesting point of interview: self‐perception of companies in which all said that they are successful!?

4. Conclusion The company E with most comprehensive human resource management (HRM) using job enrichment techniques stimulates innovativeness and motivation for it. From the research is evident that companies are not using all possible job enrichment techniques. But those companies which reorganised their HRM and are using job enrichment strategies encourage innovations. Innovative Human Resource practices include: job rotation system; widening jobs through increased complexity of jobs, change of vocation/job procedure, succession programme, and carrier plan. In future job enrichment strategies must be observed because innovations in HR practices produce intangible assets – sustainable competitive advantage gained from working behaviour so role and functions must be maintained. The ultimate goal of such strategy or HR programme is to provide sufficient enrichment and acceleration to the gifted ones to allow their talents to flourish and increase the likelihood that they will reach an innovative concept of a company product, service or procedure. In organisational context we must be aware of the role of culture in enhancing organisational innovativeness. Research results also showed that in case of Croatia, as expected, because of political history individualism is contrasted with collectivism as a characteristic of an organization's culture inclined to innovation. Hotel companies which overcome traditional approach to HRM and included in job redesigning different HR strategies as job enrichment, performance management, and multi‐tasking … are more successful (highest revenue and high investments in long term assets). Therefore we argue that the data support job enrichment strategies in reaching organisational innovativeness.

References Accel Team (2005) Aplication of employee motivation theory to the workplace, [online] http://www.accel‐ team.com/motivation/practice_oo.html Buchanan,D.A. & Huczynski, A.A.(2010) Organizational Behavior (7th ed.), Pearson Education Ltd., Essex. Cadwallader, S., Burke Jarvis, C., Bitner, M.J. and Ostrom, A.L. (2010) “Frontline employee motivation to participate in service innovation implementation”, Journal of the Academy of Marketing Science, No 38, pp 219–239. Dauda, Y.A. (2010). Managing Global Technology Innovation and Work System Dynamics: Implication for employment relations in Nigeria. Retrieved July 21, 2011 from www.ilera‐ online.org/15thworldcongress/files/.../CS1W_34_DAUDA.pdf

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Morena Paulišić, Tea Golja and Barbara Unković Dodd, N. G. and Ganster, D. C. (1996) “The interactive effects of variety, autonomy, and feedback on attitudes and performance”, Journal of Organizational Behaviour, No.17, pp 329–347. Drucker P. F. (2001) Management‐ an abridged and revised version of Management: Tasks, Responsibilities, Practices (Drucker series, 1974), Butterworth Heinemann, Oxford. Evans, K. (2012) Employee‐driven innovation and workplace learning: Exploring present realities, future possibilities and enduring changes, 4 [online] http://www.lline.fi/en/article//karen/employee‐driven‐innovation‐and‐workplace‐ learning‐exploring‐present‐realities‐future‐possibilities‐and‐enduring‐challenges. Gjerding, A.N. & Rasmussen, J.G. (2007). Organizational innovation and how it challenges management theory, Working paper measuring the dynamics of organisations and work. Retrieved July 30, 2011 from http://vbn.aau.dk/files/12716320/Organisational_level_‐_WP_2_‐_ANG.pdf Gonan Božac, M., Prester, J. and Paulišić, M. (2012) Job Enrichment – A pattern for Innovative SMEs. In M. Dabić and V.Potocan (Eds.),Entrepreneurship and Innovation (pp.177‐201) University of Zagreb and University of Maribor, Maribor. Grose, B.D. (1976). “Donkey Work” and Job Enrichment in the Academic Library. The Journal of Academic Librarianship. [online]http://www.mendeley.com/research/on‐my‐mind‐donkey‐work‐and‐job‐enrichment‐in‐the‐academic‐ library/ Hunter, L.W. (2000) “The adoption of innovative work practices in service establishments”, The International Journal of Human Resource Management, Vol 11, No. 3, June, pp 477 – 496. Ichniowski, C. and Shaw, K.L. (2003) “Beyond Incentive Pay: Insiders’ Estimates of the Value of Complementary Human Resource Management Practices”, Journal of Economic Perspective, Vol 17, No. 1, winter, pp 155‐180. Ichniowski, C. and Shaw, K.L. (2009) Insider Econometrics: Empirical Studies Of How Management Matters, Working Paper 15618, December. Kamery, R.H (2004) “Employee motivation as it relates to effectiveness, efficiency, productivity, and performance”, Proceedings of the Academy of Legal, Ethical and Regulatory Issues, Vol.8, No.2, pp 139‐144. Mc Shane, S.L. and Von Glinow, M.A. (2005) Organisational behavior: emerging realities for the workplace revolution (3rd ed), McGraw Hill, New York. Mohr, R.D. & Zoghi, C. (2006) Is Job Enrichment Really Enriching? US Department of Labor Statistics, BLS Working paper 389. [online] http://www.bls.gov/osmr/pdf/ec060010.pdf Mullins, L.J. (2010) Management & Organizational behavior, FT Prentice Hall, Essex. Nedelko, Z. and Potocan, V. (2012) Employees Innovativeness and Personal Value: A Case of Slovenia. In M. Dabić and V.Potocan (Eds.) Entrepreneurship and Innovation (pp 35‐55), University of Zagreb and University of Maribor, Maribor. Oladele, O.I., Subair, S.K., and Sebina, N.V. (2010) “Knowledge and utilization of job enrichment techniques among district agricultural officers in Botswana”, African Journal of Agricultural Research, Vol 5, No. 21, pp 2918‐2924. th Robbins, S.P., Judge, T.A. and Campbell, T.T. (2010). Organizational Behavior (13 Ed). USA:Pearson Education Ltd., Essex. Rose, D. (2005) Human Resources, High Involvement Work Processes, and Work Outcomes: An Exploratory Study. Unpublished doctoral dissertation.School of Management, Queensland University of Technology, Queensland. Saavedra, R. and Kwun, S. K. (2000) ”Affective states in job characteristics theory”, Journal of Organizational Behavior, No. 21, pp 131–146. Shaughnessy, J., Zechmeister,E. and Zechmeister J. (2012) Research Methods in Psychology. (9th ed), McGrow‐Hill Higher Education, New York. Van Praag, C.M. and Versloot, P.H. (2008) “The Economic Benefits and Costs of Entrepreneurship: A Review of the Research”, Foundations and Trends in Entrepreneurship, Vol 4, No. 2, pp 65–154. Torrington, D., Hall, L., Taylor, S. and Atkinson, C. (2009) Fundamentals of human resource management, Prentice Hall, Essex.

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The Institutions of Social Entrepreneurship in the USA, UK and Germany Within a Context of Market‐Based vs. Bank‐Based Systems Ruslan Pavlov Central Economics and Mathematics Institute, Russian Academy of Sciences, Moscow, Russia pavlovru@mail.ru Abstract: Since the beginning of the world economic crisis the level of unemployment across different countries increased significantly and so did social and welfare polarization of people. Under these conditions the emergence of social entrepreneurship could be viewed as an additional opportunity for the disadvantaged people to enhance their welfare and improve their living quality. As all the phenomena of such kind its activity should be coordinated by some special institutions in order to develop successfully, thus enhancing its aggregate performance. According to the rating of the Global Entrepreneurial Monitor (GEM), the United States have the highest rank in the growth rate of social enterprises for a short‐time perspective, which can be determined by the effect of such factors as Community Development Financial Institutions (CDFI), which provide some incentives for the business as well as for the communities to take part in the social projects. The paper reviews different kinds of economic systems inherent to certain types of integration between financial and industrial resources. So, the system of industrial development of the USA relies in most part on the stock market, while that of several European countries, such as the United Kingdom and Germany prefer to use credit resources, or the loan capital. In contrast to that, the financial systems of the developing economies, such as the Russian one, present to use both types of the financial systems aforementioned and combine the microcredit institutions with those of fundraising. The paper contains some implications for such countries suggesting them to consider some opportunities of evolving their market‐based institutions and bank sector to create a more suitable institutional system to support the development of social entrepreneurship. Keywords: social entrepreneurship, institutions, market‐based systems, ethical markets

1. Introduction Social entrepreneurship has become a very popular phenomenon among different scholars nowadays. It presents a great interest not only because of its extraordinary nature, but also due to the paradigm crisis of the neo‐liberal economic model, whose features are becoming increasingly evident for the recent times. The events which happened on 17 September 2011, when the protest movement ‘Occupy Wall Street’ began in Zuccotti Park, were impressionable by their scale and impact. The wave of protest movements all over the world that followed this action showed that the social discontent with economic inequality of people has been growing. According to the U.S. Census Bureau data, the proportion of overall wealth—a measure that includes home equity, stocks and bonds and the value of jewelry, furniture and other possessions—held by the top 10% of the population increased from 49% in 2005 to 56% in 2009 (Morin, 2012). At the same time the share of economically excluded people is growing steadily, which is evidenced by the recent data on the high rates of unemployment in Portugal and Spain. It is interesting to note that the left movement ideology has attracted lots of new followers which reflects, in particular, in the Marxism revival. ‘Why Marx was right?’ by T. Iglton proved to be a bestseller since lots of problems, connected with the system peculiarities of the paradigm being criticized by the contemporary scholars, were efficiently elaborated in the Marxist’ terms and some disturbances in the social and economic system resulted from the current trends of the mainstream policy were emphasized against the same disturbances the world economy faced more than a century ago (Eagleton, 2011). Such analogies have become of a great importance allowing for the crisis of methodological tools in the modern economics. Besides, the legitimacy of the left political movement in Europe is increasing, which is evidenced by the victory of the social‐democrats at the last parliamentary elections in Italy and the presidential in France. These are, in turn, the signs of poverty growth, labor migration, social exclusion and the failure to solve such problems by means of traditional ways of applying market mechanisms. Such challenge suggests to think about social entrepreneurship as a possible way to mitigate the distortions stated above. It can be viewed not only as an economic or social phenomenon, but also as a political movement, as it challenges the dominating paradigm at all the levels of its pervasion, forcing the governments to introduce some important measures aimed at supporting its development.

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2. Hierarchy of social entrepreneurship institutions The available literature on social entrepreneurship allows us to argue that there were several attempts to classify this phenomenon, though they were based upon a certain criterion, regardless of the fact that it might have different scales of development. In this context the classification provided by Nicholls (2007) seems to be successful, as it challenges the dominant paradigm at different dimensions. According to it, social enterprises challenge the dominant paradigm at three levels, micro (the enterprises), meso (new markets; intermediaries) and macro (socio‐economic impact; policy implications). These refer to social enterprises that (1) respond to market failure and/or “institutional void” by developing new products and services, (2) contribute to the reconfiguration of markets to generate new or increased social value and (3) challenge institutional arrangements through political action. From Nicholls' point of view, the third level of institutions should be presented by social enterprises. Though it is rather an excessive assumption, as in addition to social enterprises should also involve the ways of mitigating social problems at the micro‐level, which become embedded into an original institutional form. Thus, in order to enable an adequate reflection at micro‐level, different ways of eliminating social cataclysms within a given micro‐environment should be included into this concept, which don’t not necessarily have the form of social enterprises. Thus, if we imagine the hierarchy of social entrepreneurship institutions, we’ll get the picture as that presented in Figure 1. It’s an improved version of Nicholls’ classification as a pyramid with three levels, the first of which should present the macro‐ level institutions, the second deals with the activities of intermediaries and markets, e.g. social capital markets, and the third one presents the myriad of the local country‐ and region‐specific institutions which are inherent to the particular place shaping its origins and nature, while contributing in some way to forming the relative institutions at the meso‐level. The intermediaries presenting a nexus of some financial institutions designed to support social enterprises can be viewed as meso‐level structures coordinating the activities of those from the bottom level. So, Community Development Financial Institutions (CDFIs) in the United States can exemplify this kind of institutions, as they present a network of special innovative financial mechanisms embedded in the current institutional structure surrounding communities. The macro‐level institutions are those which influence much the dynamics of social entrepreneurship as a socio‐economic phenomenon in the given country or worldwide. They can be embedded in certain regulations, laws, policies or some original institutions, which are capable to change the existing status quo at the level of a given country, not within certain communities or districts.

Government and local authorities

Large‐scale institutions set up by individuals

Macro‐level Social Stock Financial Market Intermediaries Meso‐level Matched Micro‐ Industrial and Public bargain finance Provident Limited market Institution Society Company Micro‐level Figure 1: Three levels of social entrepreneurship institutions

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2.1 Social reforms as macro‐level institutions The macro‐level institutions are hard to specify, as the impact executed by a politician or a public figure, can be formalized into the system of certain institutions, as well as be realized within a certain political strategy. The first case can be exemplified by a famous public figure Elena Panaritis, who initiated the property rights reform in Peru, which improved significantly the life quality not only of the residents, but of the immigrants as well. Allowing for that the system of regulating property rights was rather disorderly and hazardous in this country, as the houses of people were not secured properly against any fraud, she undertook a special reform designed to improve the situation in this area and to fill the institutional gap with a special agency called “Registro Predial”. It was a special registry designed to refine the property rights system. In 1996 Peru’s government agreed to extend the property rights reforms nationwide, with funding from the World Bank. The government created a new commission, Cofopri, which would work in tandem with “Registro Predial”, sharing the process of transforming Peru’s property market, which Panaritis called transforming the “Unreal” to Real. The reform did more than change perceptions, however. The security created by the new property rights system generated tangible social and economic benefits for formal property owners that were not available to informal owners and the formal property rights spurred investment in property. Finally, the formal documentation enabled significant increasing in private‐sector loans (Panaritis, 2007). It is not surprisingly that due to such action Panaritis has got a title of social entrepreneur. Another case of social entrepreneurship, implying the adherence to a specific strategy that modifies greatly the position of certain local communities, but at the same time has a nationwide effect, is connected with some political measures introduced by the former US president Bill Clinton. As Figure 2 shows, the rank of early stage social entrepreneurial activity (SEA) in the United States is the highest, as compared to those of other countries, according to the data provided by the Global Entrepreneurship Monitor (2009). SEA is the social equivalent of the total early‐stage entrepreneurial activity index (TEA) which is measured as the percentage of a country’s working‐age population who are actively trying to start a new business (nascent entrepreneurs) and those who at least partially own and manage a business less than 3.5 years old (a baby business). Its highest rate in most part can be explained by the longevity of charity traditions in the United States which would be of the same force as the entrepreneurship ones. Numerous examples mentioned by Clinton (2009) in his book “Giving/How Each of Us Can Change the World” suggest that. Besides, he is known as a person launching several charity initiatives, but he should be called “social entrepreneur” not only for that reason. He managed to force the financial institutions to provide loans for the low‐income communities, while most of them refused to do that before. According to the amendment of 1995 to the Community Reinvestment Act of 1933, they might be closed in the case of refusal. Such measure can be treated not only as social, but also as entrepreneurial, as it had the same effect as that implemented by Panaritis. The highest rate of early stage entrepreneurial development can be explained in part by the environment inspiring people to engage in business of such kind, that was formed under the period of Clinton’s presidency. We can’t help but mention emergence of the Community Development Financial Institutions which shaped greatly the institutional structure to support social entrepreneurship at that time. 4.50% 4.00% 3.50% 3.00% 2.50% 2.00% 1.50% 1.00% 0.50%

a

na Ch i

l

Ru ss i

Br az i

US A

it a ly

Fr an ce G er m an y

UK

0.00%

Figure 2: Early‐stage social entrepreneurial activity (SEA) rate in different countries, 2009

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2.2 Social stock market and loan stock institutions at the meso‐level The meso‐level institutions present the intermediary level in this structure. Marking this group of institutions as a specific category is of great importance because it is not only a superstucture over that beneath, but also a factor which shapes ant determines the behavior and performance of the micro‐level institutions. So, for instance, the social capital market which is coordinated by a network of international financial organizations, such as the International Association of Investors in the Social Economy which was thoroughly investigated by Mendell and Nogales (2009), can be viewed as a cluster which began to grow from the bottom of this pyramid, but it can influence significantly the subsequent trends of development of micro‐institutions worldwide. In this context the emergence of a social stock market should be mentioned. For the recent decade there were several attempts in the world aimed at constructing some mechanisms to enable social enterprises to act as conventional business enterprises – that is to provide them with the opportunity to issue shares, but allowing for the high‐level risk connected with their trading at an ordinary stock exchange, it should be advisable to let them trade at a special stock exchange designed for that. So, the United Kingdom and Germany begin to play a pivotal role in installation and deployment of such mechanisms. Whereas the former belongs to the market‐ based countries range, the latter belongs to another group, consisting of bank‐based countries, but it didn’t miss the chance of adopting such mechanisms which seem to be effective. A special meso‐institution, such as Social Stock Exchange Association (SSEA), has been operating in Germany for the recent 5 years. It is designed not only to ensure forming the social stock market within this country, but also expands its influence abroad to help other countries which are engaging in this difficult and controversial process. Besides implementing a pilot project in Germany, SSEA is engaged in similar activities in Portugal, where the processes of launching a social stock exchange are underway. Moreover, it organizes different events for similar initiatives to get involved, collaborate and learn from each other’s experience (SSEA, 2013). The initiators of such project are deemed to be aware of the financial risk connected with the assets of social enterprises, implying the low return rate on the capital invested. The main task of SSEA project in Germany is to create a platform that will offer investors comparability on the social and technological impact on their investments, which will yield a slightly lower (single digit) financial return). Though this platform is not launched yet, it has a preliminary stage which expressed in the meeting which was held on 25 March 2011. At this meeting five social ventures were pitching to a dozen investors for a financing volume of roughly € 20 million (Kuhlemann, 2011). We should think that taken such event as the first indicator characterizing the activity of social stock market in Germany nowadays, we can make a conclusion that in any case Germany leaves behind the UK where the total sum raised from the ethical issue shares amounted £ 50.1 million by 2005 (Hartzell, 2007) that equals € 58.6 million which is about three times as many as this value. Table 1: Number of ethical share issues and total raised in the UK Period 1984‐1990 1991‐1995 1996‐2000 2001‐2005 Total

Number of issues 6 8 13 16 43

Total raised (£ million) 3.35 4.17 10.55 32.03 50.1

The process of launching the social stock exchange is also still ongoing, as in Germany. Nevertheless there are several ways of executing such operations beyond such exchange. Such operations are possible due to a three‐ step system of ethical share investment in the UK which presents a way for social enterprises to adopt their abilities within a less stringent environment than that for the existing business enterprises. So, these steps are: the Off‐Exchange (OFEX), the Alternative Investment Market (AIM) and the London Stock Exchange (LSE). All of them can be considered as a hierarchical tree, in which companies graduate from one level to the next as they grow in size. Indeed, AIM was established by the LSE for companies at an earlier stage of development. The markets higher up the tree offer greater liquidity, but are more expensive to list on and the listing requirements more stringent in terms of disclosure of the price sensitive information. Thus a company might first choose to list on OFEX, where the cost of listing is only around £ 10,000 a year or less, but trading there can be deceptive, as some OFEX shares are not traded at all for long periods. The share price then remains static and may not reflect the value that a share might achieve in a more liquid market. The lack of competition and the absence of due confidence among investors cause the fall in the share price. Although many companies go straight to AIM, a listing on OFEX is often a first step towards an AIM listing, as it is a chance for them to attract major institutional investors and to increase their reputation. However, fees for listing on AIM are likely to be between £ 300,000 and £ 500,000 even before marketing costs (Hartzell, 2007). For a social

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Ruslan Pavlov enterprises, where a high profit level is not to be expected, share issues therefore need to be in the £ 10 to £ 20 million range to stand a chance of covering the costs of fees. Raising this level of investment is often unrealistic, allowing for the financial condition of social enterprises. The larger of the AIM companies move to the London Stock Exchange. Some of them have a balance sheet as small as £ 10 million, but most are much larger. However there is a threat of a hostile takeover for the enterprises seeking to attract large amounts from the institutional investors or venture capitalists. That is also the reason which prevents social businesses from being the participants of the mainstream market. While the UK demonstrates an example of enhanced activity in the field of social stock operations, Germany appears to be one of the leaders on the development rate of microfinance institutions (see Table 2) and in this sense matches its position as a bank‐based country absolutely. In most part Germany’s successes in the development of microcredit system can be explained by the effective performance of such meso‐institution as the German Microfinance Institute, as it provides a wide range of different services, in particular, counselling and training for MFIs (e.g. their loan officers), designing electronic loan processing tools and accrediting MFIs for the risk capital fund which is called “Microfinanzfonds Deutschland” (El‐Zoghby, Gähwiler, Lauer, 2011). Table 2: Main microfinance indicators in selected European countries Country Germany Italy Spain UK Romania Bulgaria Czech Republic Slovakia France Poland Netherlands Hungary

Number of loans disbursed 4,625 3,223 8,773 1,252 2,496 68,348 ‐ 982 121,000 130,888 43,508 104,754

Microfinance Indicators Total value of loans Average Loan Size disbursed (EUR M) (EUR) 52,276,375 11,303 22,451,418 6,966 97,800,000 9,943 13,420,000 10,718 18,847,296 7,551 432,890 6,334 ‐ 4,500 155,000,000 157,841 852,500,500 7,045 ‐ 2,024 739,636,000 17,000 371,876,700 3,550

Average Interest Rate (%) 6.92 5.80 5.00 13.40 ‐ ‐ ‐ 6.50 0.5 11.00 ‐ ‐

2.3 Matched bargain market in the UK as an example of micro‐level institutions As in the United States and Germany the social capital market is only at the stage of installation, while in the United Kingdom it is at the stage of deployment yet, we’ll focus only on the English institutions as having settled fundamentally and providing a very valuable experience on this point. In this country a company a company not listed on the mainstream markets can usually only trade its shares through a matched bargain market. This is usually run by a broker or a recognized financial institution, and involves holding a list of buyers and sellers of the shares and matching them at the price they both wish to pay. So the matched bargain market for a certain enterprise can be viewed as a micro‐level institution. Matched bargain markets usually operate for one company in isolation rather than for several companies. Moreover, the Financial Services and Markets Act limits the extent to which the investment can be marketed. Price‐setting on a matched bargain market is usually a haphazard affair. Quite often it is left to buyer and seller to agree, but if any price at all is recommended, it is usually the broker running the market who would recommend a price, based on information provided by the company. Thus in a matched bargain market, the company itself has much more control over the share price. This is usually regarded as an unsatisfactory situation open to abuse, as two conditions necessary for an efficient stock market are not met. The first one is that the market is sufficiently liquid for expectation of value to be quickly reflected in the current price. The second is that investors have all and equal information available to them surrounding the situation of a company. When these conditions are not met, anomalies occur and some individuals can benefit over others due to the drop in the share price as stated in the previous subsection. Speaking about matched bargain markets, it’s interesting to note that those companies which didn’t list on OFEX and AIM have achieved wonderful results. To approve our suggestion derived in the previous section that the division of countries according to the criteria, whether it is a market‐ or a bank‐based system, coincides with the development of the same kind institutions for social enterprises in these countries, we’ll

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Ruslan Pavlov provide some data concerning the growth of capital amount raised as a result of share issues by three most successful social enterprises of the United Kingdom: Ttaidcraft, Shared Interest and Wind Fund. Table 3: Three leading social enterprises in the amount of shares issued Company

Year

Legal form

Type of investment

Traidcraft

1984

PLC

Share

Amount raised (£M) 0.3

1986 1991 2002

PLC PLC PLC

Share Share Share

1 0.4 3.25

Shared Interest

1995 1996 1997

IPS IPS IPS

5 Year Loan stock 5 Year Loan stock 5 Year Loan stock

0.65 0.85 1.2

Wind Fund

1995 1998 2005

PLC PLC PLC

Share Share Share

1 1.3 4.75

Thus, according to these indicators, we can conclude that all the three companies achieved such great results, having issued their shares beyond the mainstream market, but whereas Traidcraft and Wind Fund are public limited companies (PLCs), Shared Interest is an industrial and provident society (IPS) which has a limited ability to attract funds. Moreover, the redemption period for the bonds issued by IPSs is rather short. So, the investors usually have less opportunities to buy and sell such bonds, as they would have dealing with bonds issued by a conventional business enterprise. Wind Fund happened to be the most successful among these companies, as it managed to raise its capital from £ 1 million in 1995 to £ 4.75 million в 2005, which is comparable with AIM in its scale. Though Traidcraft managed to have even 2,400 shareholders, while the average number of the AIM company’ shareholders is around 800 (Hartzell, 2007). This fact suggests that a matched bargain system presents something like an economic miracle which is developing along with its immanent laws and has an ability to outachieve the existing formal markets.

3. The system of microcredit institutions and social stock exchange in the USA, Germany and the UK The model of institutions presented here is a sophisticated version of Nicholls’ classification which enables us to make it clear what kind of financial institutions are best developed in a particular country at the particular level. So we can compare the respective institutions of social entrepreneurship in these countries with their profiles – whether it is a market‐based or a bank‐based system, according to the classification presented by Demirguc‐Kunt and Levine (2003). In bank‐based financial systems such as Germany and Japan, banks play a leading role in mobilizing savings, allocating capital, overseeing the investment decisions of corporate managers, and in providing risk‐management vehicles. In market‐based financial systems such as England and the United States, securities markets share center stage with banks in terms of getting society’s savings to firms, exerting corporate control, and easing risk‐management. Table 3 presents three countries, two of which are market‐based (the United States and the United Kingdom) and the third is bank‐based (Germany). The distribution of the respective institutions for social entrepreneurship looks like that for the commercial sector in these countries. Different laws, regulations and standards coordinating the activity of the respective fields of social investment systems presented here are treated as macro‐institutions. Community Reinvestment Act of 1977 with the amendment of 1995 which resulted in increasing the opportunity window for the low‐income households is worth mentioning first. The Act amending the German Investment Act of 2003 (also known as the Amendment Act of 2007 played a major role in forming an environment for the development of microfinance institutions in Germany. It enabled the emergence of two meso‐institutions in microfinance area: the German Microfinance Institute and the Microfinance Fund “Germany”. As for the system of regulating social stock exchange, it should be stressed once more that the most successful pattern of it is represented by the UK financial system which is, in turn, a market‐based country. Maybe that is the reason of its leadership among all the other European countries. In addition, the system of regulating transactions in AIM is simplified so that AIM companies are supervised by a nominated adviser (referred to as a “nomad”) rather than by a securities regulator (in the UK, this is the Financial Services Authority (FSA). All the transactions of AIM companies are

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Ruslan Pavlov subject to the AIM Rules for Companies (AIM Rules). AIM’s simplified admission procedures generally result in savings in time and cost for an AIM admission as compared to a main market or other listing. In most part the creation of such institution was predetermined by the increased activity of matched bargains, which was, in turn, caused by the traditions of using stock exchange as a leading mechanism to support industrial development in this country. Table 3: The loan capital and social stock institutions in the USA, Germany and the United Kingdom

USA

Germany

Loan Capital Institutions Community Reinvestmen t Act of 1977 as amended further

Social Stock Institutions The United States Securities Act of 1933

Meso‐ institutions

Community Developmen t Financial Institutions

Green Stock Exchange (launch in 2014)

Micro‐ institutions

Web‐ resource ‘www.kiva.o rg’

New York Stock Exchange

Macro‐ institutions

Loan Capital Institutions The Act amending the German Investment Act of 2003 (the Amendment Act, 2007) The German Microfinance Institute (Deutsches Microfinanz Institut); The Microfinance Fund Germany (Microfinanzfo nds Deutchland) GLS Bank

Social Stock Institutions The Stock Exchange Act of 1896 as amended further

United Kingdom Loan Capital Social Stock Institutions Institutions Community Financial Investment Services and Tax Relief, Markets Act; Credit AIM Rules Unions Act for Companies

Social Stock Exchange (launch in 2013)

Community Developmen t Loan Funds

OFEX, AIM, LSE, Social Stock Exchange (launch in 2013)

NExT SSE

FINCA UK

Triodos mathed bargain market

4. In conclusion The main result of the paper is a modified version of Nicholls’ classification of challenges against the dominant neo‐liberal paradigm. It is modified so that it might include the main institutions orienting the activities of social enterprises which proved to be effective. Such model would help us to assess the completeness of coverage of the relevant aspects in the system of institutional regulation of the subject in issue. Its application allowed us to answer the question, what institutions are more developed in the countries observed and whether it matches the widespread opinion on the separation of countries between market‐based and bank‐ based. The result is that such trends hold rather true for the financial streams of social enterprises in the UK and Germany. Consequently, it should be advisable to recommend those countries having strong traditions of stock market development to put a special emphasis on the development of relative financial institutions to support social enterprises, whereas those relying upon a strong system of bank institutions would be reasonable to develop the microfinance sector to achieve the competitive advantage for their social enterprises. Besides, one should say some words about the way of attributing these implications to the analysis of the situation in developing countries. For instance, Russia might be subsumed under the group of bank‐based, rather that market‐based countries because of its path dependence connected with long traditions of bank monitoring system which originated in the Soviet Union and was performed by the State Bank. To speak about Russia as a market‐based country presents a great difficulty, because it lacks the established class of social investors which is well represented in such countries as USA and UK thereby contributing to their image as market‐based countries. Moreover, Russia has one of the lowest positions in the ranking of social th responsibility of business across different countries, occupying the 37 place (Belova, 2011). Only Turkey has a worse position being at the bottom of the list. The implications derived in the paper could be valuable when planning the strategy of development for different countries. The link between the kind of economic system and the respective institutions of supporting social entrepreneurship should be taken into account when

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Ruslan Pavlov projecting the strategy of development of financial mechanisms for social enterprises in the respective countries. As the amount of the paper is rather limited we hadn’t the opportunity to reinforce our implications by an empirical research. This task faces a problem of collecting data on the development rates of bank and market institutions in the respective countries, but it seems rather realistic to perform. So, maybe further it would be possible to construct a regression model showing the link between the level of development of market‐ and bank‐based economies and the respective rates of social entrepreneurship’ institutions in those countries.

References Belova T. (2011) “The most socially responsible countries”, [online] RBK Rating, http://rating.rbc.ru/article.shtml?2011/06/09/33318359 Clinton, W.J. (2007) Giving: How Each of Us Can Change the World, Alfred A. Knopf, New York. Demirguc‐Kunt, A., Levine R. (2003) “Bank‐based and market‐based financial systems: cross‐country comparisons”, [online] World Bank, www‐wds.worldbank.org/external/default/WDS ContentServer/WDSP/IB/1999/09/14/000094946_99072307505320/additional/126526322_200411172106.pdf. Eagleton T. (2011) Why Marx was right, Yale University Press, London. El‐Zoghby, M., Gähwiler, B., Lauer, K. (2011) Cross‐border funding of microfinance, Focus Note, No. 70, April, pp. 1‐3. GEM (2009) “United Kingdom 2009 Monitoring Report”, [online] Global Entrepreneurship Monitor, http://strath.ac.uk/media/departments/huntercentre/research/gem/GEM_UK_2009.pdf. Hartzell J. (2007) “Creating an ethical stock exchange”, [online] Skoll Centre for Social Entrepreneurship, www.sbs.ox.ac.uk/Skoll/Ethical_Stock_Exchange.pdf. Kuhlemann, A.‐K. (2011) “NExT SSE to promote ‘crowd investing’ in Germany”, Alliance, Vol. 16, No. 2, 2 June, p. 10. Mendell M., Nogales, R. (2009) “Social entrepreneurs in OECD member countries: what are the financial streams?” in The changing boundaries of social enterprises. Ed. A. Noya, Seoul, Work Together Foundation. Morin, R. (2012) “Rising share of Americans see conflict between rich and poor”, [online], Pew Social & Demographic Trends, www.pewsocialtrends.org/2012/01/11/rising‐share‐of‐americans‐see‐conflict‐between‐rich‐and‐poor/. Nicholls, A. (2007), What is the Future of Social Enterprise in Ethical Markets?, Office of The Third Sector, London. Panaritis, E. (2007) Prosperity Unbound. Building Property Markets with Trust, Palgrave Macmillan, New York. SSEA (2013) “Two major lines of SSEA work”, [online], Social Stock Exchange Association, www.socialstock.eu/what/

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Collaborative Strategies for Innovation Capacity‐Building: A Study of MIT’s International Partnerships Sebastian Pfotenhauer, Dan Roos, and Dava Newman Massachusetts Institute of Technology, Cambridge, USA

pfotenh@mit.edu roos@mit.edu dnewman@mit.edu Abstract: Over the past two decades, the key role of universities for innovation and economic development has become a central concern of policy‐makers and researchers alike. This paper discusses international university collaborations as a deliberate strategy in national and regional innovation policy to build innovation capacity through universities in transitioning economies. Using four of MIT’s major international partnerships as case studies – the Cambridge‐MIT Institute, the MIT‐Portugal Program, and the Masdar Institute of Science and Technology, and a suite of relationships between MIT and Singapore – this paper aims to provide a first analysis of this increasingly popular policy instrument. We will first develop a policy rationale for why countries seek to engage in such a collaborative, university‐centred strategy. Using a systems architecture approach, we will then analyse the different collaborative models employed in the four case studies and discuss how they address specific country needs and contexts. Our findings reject simplistic, quasi‐mechanistic notions of emulation and best‐practice transfer, and instead underscore the specific national character of each collaboration and the flexibility of the collaborations as a policy instrument. To illuminate how these questions of systemic embedding translate into program design, governance, and evolution, we further present a collaboration lifecycle model that can help inform policy decisions and program management for these collaborations in the future. We believe that MIT’s collaborations are no isolated occurrences, but spearheading a paradigm shift in international innovation policy whereby purposeful linkages to eminent entrepreneurial universities may become key instruments in innovation capacity building, thus redefining the role of leading universities in global economic development. Keywords: innovation policy, university collaborations, capacity building, collaboration models, systems architecture

1. Introduction For many years now, policy‐makers and researchers alike have stressed the idea that universities are the key to innovation and economic growth in the 21st century (OECD 2010; Goldin & Katz 2009). For many years, too, this assertion has usually been qualified by the observation that only a handful of universities – such as MIT, Stanford, or Caltech – are truly able to live up to this promise and excel at university‐driven innovation and entrepreneurship. Left with this troubling dual insight, governments around the globe have increasingly begun to look beyond their own borders for effective strategies, models and global “best‐practices” to turn their universities into innovation hubs and facilitate their country’s transition into a knowledge economy. Arguably, the successes of such emulation endeavours have been very mixed. What, then, if countries or institutions were to emulate “best practices” in innovation and entrepreneurship with the help of the sources of these very practices? Over the past 15 years, the Massachusetts Institute of Technology (MIT) has entered into a number of large‐scale international collaborations designed to foster university‐based innovation in the respective partner countries. Sponsored by the foreign governments, these collaborations go beyond traditional notions of emulation by directly linking one eminent entrepreneurial university – MIT – with several institutions abroad. From an innovation policy standpoint, MIT’s international collaborations are interesting for several reasons. First, they are all concerned, in one way or another, with the development of innovation capacity as embodied by the MIT model. Yet, the innovation needs of countries as different as Portugal, Singapore, Abu Dhabi or the UK differ immensely, and it is hence interesting to study how these collaborations differ in their design and objectives. Secondly, these collaborations are complex; that is, they address innovation capacity through a variety of levers, including human capital development, scientific and technological development, institutional and ecosystem development, as well as through national and international linkages across institutions. Thirdly, they are comparably large in scale and scope, involving typically hundreds of people, multiple institutions and scientific areas, and several tens to hundreds of million dollars of investment. Thus, they go significantly beyond traditional international university activities such as study abroad programs, dual degrees, or research partnerships. Furthermore, the intensive, limited‐ time collaborative model pursued by MIT and its partners differs markedly from the recent trend of international branch campuses, focusing primarily on the strengthening of regional partners, not spawning

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman branches. Fourth, all the collaborations are public‐private partnerships, driven mostly by public sector interests and investment, but involving a considerable number of industry partners as well. This paper analyses four of MIT’s recent international partnerships as a policy instrument for national and regional innovation policy in transitioning economies. In the following, we will discuss the motivations why countries seek to pursue such collaborative strategies with an institution like MIT, analyse different collaborative models with a view towards more general questions of collaboration design and systemic embedding, and discuss the collaboration lifecycle to highlight more practical questions of program governance and implementation, which can help to inform future projects of this kind.

2. Policy rationales for university partnerships as innovation strategies 2.1 The role of universities for innovation and the knowledge economy Universities have boldly moved to the centre stage of innovation policy (Thorp & Goldstein 2010; Berman 2011). Governments around the globe are focusing increasingly on the role of universities at the heart of the “knowledge triangle” – education, research, and innovation – capable of catering simultaneously to human capital formation, the creation of new knowledge, and the translation of this knowledge into innovation and technological advancement (Winckler 2010). Universities have also become major economic actors themselves. With the rise of “entrepreneurial university” models, they increasingly engage in the creation of proprietary knowledge, the commercialization of research through spin‐offs or licensing, and are measured not only by their intellectual but also their economic impact (Slaughter & Leslie 1997; Etzkowitz 2002). MIT, one of the standard bearers of university entrepreneurship, creates about $100M annual revenues through its Technology Licensing Office, and the revenues of companies founded by MIT graduates would, if gathered into an independent nation, make up the 11th‐largest economy comparable in the world, comparable to Russia and India (Roberts & Eesley 2009). The recent focus on universities in the economy is underwritten by decades worth of theoretical development in endogenous growth (Romer 1990; Aghion & Howitt 1998) and innovation, most prominently the theory of innovation systems (Lundvall, Bengt‐Åke 1992; Nelson, Richard 1993).

2.2 Collaboration, networks, and technological learning Theories of economic development have long emphasized the important role of international linkages. For decades, the prevailing development narrative has been one of technology transfer and gradual convergence to the innovation frontier, whereby less developed nations start out as adopters, gain expertise through imitation and import substitution, and eventually start innovating themselves (Kim 1997; Lall 1992). Yet, many countries struggle to close persistent gaps in scientific, technological, and innovation performance despite technology transfer, which has spurred new scholarship such as technological learning (Fransman et al. 1984; Kim 1997; Mani & Romijn 2004), which links opportunities to benefit from technology in the long run to the ability to build local capability (individual, organizational and systemic) and to adapt technologies as part of a local context; systems research, which underscores the interrelatedness of actors, institutions, regulatory frameworks, and policy sub‐sectors such as education, research, finance; and immigration; and the emergence of the “knowledge economy,” where access to knowledge hubs, rapid learning, human capital, communication and networks under conditions of increasing globalization are becoming the cornerstones of growth and competitiveness (Conceição & Heitor 1999; Archibugi & Lundvall 2001).

2.3 International higher education A third main policy rationale is the increasing internationalization of higher education (Knight 2007; Altbach 2007). Internationalization has been acknowledged as important instrument for capacity building in higher education, particularly for advanced science or other specialized degrees that might not available in the sending countries; for the cross‐border flow of skills and knowledge; research productivity; and labor force development. The number of internationally mobile students is estimated to triple to 8 million in 2025 (Bhandari 2009). As a consquence, many countries are at present trying to re‐set their international strategy to meet this “international imperative” and make a transition from a net‐sending to a net‐receiving country, which will allow them to benefit from these bright young individuals in their universities and labour market.

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2.4 Expertise, legitimacy, institutional reform and global visibility A fourth policy rationale can be found in the social interplay between expertise and legitimacy: Critical changes in an institution or system are often hard, if not impossible, to achieve from inside the institution or system alone. On the one hand, critical expertise and the means for change might not be readily available. Expertise on how to implement a successful innovation and entrepreneurship ecosystem around a university is, arguably, limited to a handful of universities, and foreign institutions might reason that they stand a better chance emulating this success models if they team up with these very universities. On the other hand, universities are comparabely inert and conservative institutions, embedded in a system deeply resistant to change because of hard legal structure, diverse political stakeholdership, and strong traditionalist‐type opposition. Partnering with an authoritative international brand institutions like MIT may put sufficient legitimacy behind institutional and systemic changes that might otherwise receive little support in the host country (Pfotenhauer et al. 2012). Moreover, the impact of research and innovation today is closely to visibility and participation key actor networks. Access to the MIT brand is also a means to increase the visibility of research and education activities, and to attract the attention of other player (e.g. industries).

3. Cases Our paper uses a case‐study approach to analyse strategic university collaborations as a policy instrument, using obtained through interviews, document analysis, extended periods of observation, and validation and triangulation through multiple sources. The case study approach is adequate for a number or reasons. First, it allows us to pursue an in‐depth investigation into a situation that has many of variables of interest while retaining a holistic perspective on a complex, systems‐specific instrument (Yin 1994). Second, our case study approach enables comparison between different manifestations of more general underlying phenomenon, i.e. international university collaborations as (specifically with MIT), and explore structural aspects across contexts and the flexibility of the instrument. Third, as suggested by (Siggelkow 2007), our cases have been selected with a view towards persuasiveness and generalizability. MIT has been a trendsetter in the domain of international university partnerships for technology development since the 60s and, arguably, it epitomizes the very innovation practices other countries and institutions seeks to “import.”

3.1 The Cambridge‐MIT Institute (CMI) CMI was launched in 1999 between MIT and the University of Cambridge, UK, to “enhance the country’s competitiveness and innovation by improving knowledge exchange between university and industry” (CMI 2008). Amidst a fierce public debate about the future and finances of British universities, Gordon Brown – then Chancellor of the Exchequer – became a strong advocate of the idea that British universities weren’t contributing enough to the economy and contemplated CMI as a possible solution. Although initial negotiations considered the possibility of creating a new university or partnering with a more Engineering‐type university, Cambridge was chosen for its high quality research and reputation, reaffirming the proud Oxbridge tradition of academic leadership in the UK. CMI ran for 6 years and involved a total of 43 faculty members (175 PIs) and 350 students on both sides of the Atlantic. CMI created 6 innovation‐oriented Master’s programs at Cambridge (Technology Policy, Micro‐ and Nanotechnology Enterprise, Engineering for Sustainable Development, Computational Biology, and Bioscience Enterprise, and Advanced Chemical Engineering), modelled largely after existing MIT programs, and engaged primarily in four domains of research (Energy and the Environment, Communications and Networks, Healthcare and Biotechnology, and Tomorrows Technology), all of which were chose because of their potential to attract industry collaboration, In addition, it introduced a number of ecosystem activities to foster innovation, such as “Knowledge Integration Communities,” the “consideration of use” principle to guide research activities, or “undergraduate research opportunities” for students.

3.2 The MIT‐Portugal program (MPP) In 2006, MPP was launched as a “strategic investment in people, knowledge, and ideas [that] can have a positive, lasting impact on the economy” (MIT 2005). MPP was conceived at the apogee of European university reforms surrounding the Bologna Process and the Lisbon Agenda, and reiterated the strong support for science in Portugal since the late nineties. MPP was designed to address several long‐standing systemic challenges: A “delayed” system due to the dictatorship until 1974, Portugal long focused on domestic access and massification, and only recently shifted discourses towards strong national research universities and international benchmarking (Heitor & Horta 2011). Despite an impressive catching‐up trajectory, the system

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman transition into a knowledge economy is far from complete and faces many challenges, such as limited university‐industry interaction, as underscored by the recent economic woes. MPP tried to strengthen excellence and critical mass in select focus areas by bringing together as a consortium 8 universities, 20 national research labs, and industry. The program focuses on four areas: Sustainable Energy Systems, Bioengineering Systems, Transportation Systems, and Engineering Design and Advanced Manufacturing, all of which are centred on an engineering systems core combining engineering with economics, management, policy, and social science. The program created 4 American‐style PhDs and 3 professional Master’s programs, which strongly focussed on innovation and entrepreneurship and radically broke with existing education traditions in Portuguese engineering. AS of today, MPP has gathered 214 Portuguese faculty and 70 faculty from MIT, and has thus far enrolled 452 graduate students at Portuguese institutions and 140 graduate students at MIT. The program has been renewed for another 5 years in 2013.

3.3 The Masdar Institute of Science and Technology (MI) In 2006, MIT signed an agreement with the government of Abu Dhabi to help establish a new research university – MI – as the centrepiece of the ambitious Masdar City project. Masdar City is spearheading the UAE’s socioeconomic transition from a booming oil‐based economy to a more diversified economy based on sustainable energy research and innovation, with the city itself acting as a test‐bed for technology and innovative urban design under desert conditions. It is at once also a touchstone for the future of the whole region. MI was conceived to develop the necessary local human resources, locally relevant research, and ecosystem to fuel this transformative vision. The MI‐MIT partnerships literally began by building MI from scratch, including faculty and student recruitment, the definition of a research agenda and educational programs, the design of physical infrastructure (including lab space) institute as well as the administrative, legal and virtual infrastructure. MI started out with a variety of research programs, which were later consolidated into three main research thrusts: Water, Environment and Health; Future Energy Systems; and Microsystems and Advanced Materials. As of today, MI’s offers 8 Master’s degrees related to the abovementioned areas, and added Interdisciplinary Doctoral Degree Program. MI has grown to a body of 86 faculty, and currently has 336 students of 52 different nationalities. The MI‐MIT collaboration has recently (2012) entered into its second phase.

3.4 MIT‐Singapore (SMA/SMART/SUTD) MIT’s longstanding collaboration with Singapore spans several programs. The Singapore‐MIT Alliance (SMA) was launched in 1998 primarily as an educational collaboration based on conventional distance education models with student rotation and a dual degree option, featuring a strong focus on research training. In collaboration with the National University of Singapore and Nanyang Technological University, SMA offered five educational tracks: Advanced Materials for Micro‐ and Nano‐Systems, Chemical and Pharmaceutical Engineering, Computation and Systems Biology, Computational Engineering, and Manufacturing Systems and Technology. SMA was complemented in 2007 by the Singapore‐MIT Alliance for Research and Technology (SMART), which added an explicit research dimensions to partnership and further jumpstarted the SMART Center as the first entity in the new Singaporian Campus for Research Excellence and Technological Enterprise. SMART aimed to attract MIT faculty for extended periods to Singapore (e.g. sabbaticals), where they would received their own laboratories and students, and collaborate with researchers from regional universities. SMART focuses on five research thrusts: BioSystems and Micromechanics, Environmental Sensing and Modelling, Future Urban Mobility, Infectious Diseases, and Low Energy Electronic Systems. In addition, SMART launched the Innovation Center, a translational unit modelled after MIT’s Deshpande Center to shepherd nascent technologies into commercialization. Finally, Singapore and MIT recently announced the joint creation of the Singapore University of Technology and Design (SUTD), which notably adds an undergraduate component to the suite MIT‐Singapore relationships and emphasises creative design thinking in engineering education. SUTD further offers Master’s degrees and an interdisciplinary PhD program.

4. Different collaboration models In the following, we will discuss selected key findings of a systems architecture analysis of the four MIT collaborations. Systems architecting is an approach to understand, design, and manage complex systems (Maier & Rechtin 2000). It allows us to understand how the components, or forms, of a system relate to certain systems functions, and shows how alternative architectures align or conflict with the stakeholder objectives. The goal of architectural analysis is not to assess the success of the collaboration according to some

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman external criteria. Rather, it is to understand the complex interrelation between multiple goals and activities (e.g. education, research, commercialization, ecosystem development) and the resulting trade‐offs in performance, as well as how systems constraints (e.g. political preferences or structural constraints) allow only certain architectures to materialize. For reasons of space constraints, the full architecture analysis will be detailed elsewhere. The analysis revealed four distinct models for collaboration (Fig. 1). CMI, first, follows a bilateral model. From the earliest stages, CMI was not conceived as MIT “helping” Cambridge, but as a symmetric “joint venture” between two institutions of equal standing, building on the “complementary strengths” of each institution and effecting “cultural change in both” (CMI 2008). This bilateral model was possible because the UK did actually have universities that were comparable in research and educational quality to MIT (though with significant cultural differences), and the idea that Cambridge was not on par with any other university in the world was politically not viable. From this bilateral core, the vision and effects of the collaborations were supposed to radiate outward into an affiliated network of universities in a hub‐and‐spokes fashion. This network further fostered the absorption and rapid dissemination of research in through a knowledge integration community model (Acworth 2008). Cambridge‐MIT Institute Bilateral Model

MIT‐Portugal Program Network Model

Masdar Institute of S&T Institution‐building Model

Singapore MIT Alliance Singapore University of Tech. & Design Functional Expansion Model

Figure 1: Different collaboration models identified by systems architecture analysis MPP, secondly, follows a network model. Portugal did not possess a single eminent university of the calibre of Cambridge, which made the bilateral model unlikely. Moreover, given the historical emphasis on social equity rooted in the post‐dictatorship era, a broad institutional base was politically preferable. Finally, one of the central intentions behind MPP was the creation of critical mass. In the network configuration, MIT served as a catalyst to incentivize intra‐Portuguese collaboration spanning research (e.g. all funded projects involved multiple Portuguese universities), education (e.g. by joint degrees between several Portuguese universities and student rotations between them), and innovation (e.g. national innovation events like venture competitions). The network approach carries even further: Parallel to MPP, the Portuguese government created similar partnerships with Carnegie Mellon, UT Austin, Harvard Medical School and the German Fraunhofer Society, which allowed Portugal to pool expertise from multiple domains.

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman MI, thirdly, can be best characterized as an institution‐building model. Rather than strengthening an existing university within an existing context, MIT was asked to assist with creation of the first graduate research university of the country in the proverbial middle of the desert. Therefore, the MIT‐MI partnership encountered a lot of “firsts” – for the institution, the ecosystem and the nation. For example, MI developed the first clean room of the country, was the first to import certain research equipment into the country, solve certain supply chains issues, safety standards (e.g. for hazardous waste management), and regulatory questions (e.g. questions of IP or human subjects research), and stimulate the creation of the UAE innovation ecosystem, which is still lacking multiple core components, from a research funding agency to a mature venture industry. While this institution‐building meant many hurdles for the MIT collaboration, it broke ground for future research in the UAE as a whole. Fourth, MIT‐Singapore follows a functional expansion model: Different functions have been successively added through new forms of collaboration. While SMA was focused on (Master’s level) education, it was later complemented by SMART, which added an (institutionalized) research component and an innovation center, and the launching of SUTD as a full‐fledged university with undergraduate focus. In contrast, CMI, MPP, and MI each simultaneously addressed education, research, and innovation through one collaborative arrangement. Fundamentally, the interactions between Singapore and MIT cover the same functions as the previous three archetypes, and comprise the same elements: bilateral interaction (MIT‐SMART), network (MIT‐NUS‐NTU), and institution‐building (MIT‐SUTD). What is different, though, is the separation and gradual roll‐out of functionality, which arguably speaks to the technocratic, highly planned systems management style that Singapore is known for. The four different models identified here are quite heterogeneous. Yet, their structural analysis holds some generalizable insights. First, it is striking that “one” instrument – a collaboration with MIT with the purpose of emulating innovation practices – takes a radically different forms in each case, which contradicts the widespread simplistic, quasi‐mechanistic understanding of “best‐practice transfer.” Looking at different architectures and their genesis in a comparative way provides an entry point to systematically account for, and theorize, cross‐national differences in ostensibly identical policy instruments, which is something that the innovation policy literature has sometimes struggled with in the past. Our analysis reveals how different architectures are shaped by different systems constraints and their socio‐political embedding, each idiosyncratic for a particular country (e.g. the elitist tradition of the UK university system leading up to a bilateral model of “equal standing”). Second, while we do not claim to provide an exhaustive description of all possible collaboration models, our analysis points out important building blocks and archetypes that underwrite different collaboration architectures. The Singapore case stands witness to how the three other models (bilateral, network, institution‐building) can be juxtaposed to render a distinct nation‐specific configuration.

5. Collaboration lifecycle To cast some more light on when and how these systems constraints affect the design and implementation of these international collaborations, the next part of our paper will discuss the “collaboration lifecycle.” This more process‐ and management‐oriented angle complements our architectural analysis by connecting the systems level to program level. By highlighting different collaboration phases and challenges in each phase, we hope to provide some strategic guidance for policy‐makers who wish to implement such programs in the future. Like the above architecture analysis, this lifecycle analysis is based on our in‐depth case studies with a view towards synthesis‐oriented comparison.

5.1 Collaboration initiation and design Our research finds three major collaboration phases, which are depicted in Fig. 2. In the program initiation phase, three factors must typically come together for a collaboration to happen. First, the program must fit into the larger systems context, defined by the recent trajectory of the national STI system, on‐going reforms efforts, or extraordinary challenges. Second, the collaborations typically needs a political champion, i.e. a government leader who is convinced of its strategic importance, can mobilize the necessary financial and political resources, and is able to shield the program from attacks. Third, the collaboration must be attractive to MIT, including faculty interest (e.g. unique research opportunities) and institutional interest (e.g. access to good students, sufficient funding).

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman The initiation phase is followed by a more formalized phase of program design that defines program objectives, assembles the program’s functional components, and articulates a legal (contractual) framework. All three tasks are subject to complex negotiation processes between the initiating key stakeholders, which primarily include representatives of the national governments (or sometimes a subsidiary organization) and senior leadership from MIT. In many ways, the touchstone of the program design phase is its translation into a contract. Three main issues frequently arise in the process. First, Intellectual Property (IP): Typically, the participating partners (institutions, countries) have very different (and at times outright incompatible) IP frameworks. Second, the partnerships are “hybrid” arrangements that fall in between traditional research collaboration and a consulting arrangement. That is, while part of the collaboration employs traditional academic collaboration models (e.g. joint research projects or student mobility), MIT typically also takes an advisory role on institutional models, curriculum design, faculty hiring, legal frameworks, infrastructure development etc. Third, contracts need to consider accountability and liability, both in terms of key performance indicators (KPIs) and reporting requirements. Discussions around KPIs are often fierce and almost always sawn with unrealistic expectations (e.g. the number start‐ups to be expected); similarly, different cultures and requirements for reporting may cause friction. The program design phase overlaps with what one could call a “year 0” before the official launch of the program. During this “year 0,” faculty members from both sides are brought together to explore areas of common interest and potential collaboration (e.g. through workshops), often facilitated through preliminary seed grants. The “year 0” also allows for the hiring of staff and ramping up educational programs. Experience shows that the “Year 0” is extremely important to set the stage wisely for a successful collaboration; once the program has been launched, performance pressure, standard operating procedures, political pressure and media attention may undermine easy adjustment along the way.

Figure 2: Collaboration lifecycle

5.2 Collaboration execution Program execution entails program governance on multiple levels. At the top level, the collaboration is typically run jointly by one collaboration lead on each side. These leads also members of a joint governing/steering committee that also includes a high‐level government representatives and MIT senior leadership. On an operational level, leads are typically supported by a operating committee with broader stakeholder representation. At the content level, each scientific area typically has “focus area leads” on both sides that oversee activities in this domain (both research and education). Frequently, purpose‐specific management positions are created such as a Director of Innovation or Director for Education. The collaborations typically also feature scientific advisory boards and/or external review boards, with representation of key national and international leaders. It comes as no surprise that the learning curve for collaboration of this magnitude and complexity is steep and long, and many initial decisions are being revised as the program evolves. The changes may include for

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman example consolidation or diversification of research projects or educational programs, implementation of new processes (e.g. a shift from discretionary funding to research calls), new program members, new activities (e.g. the addition of a venture competition), political intervention and budget adjustments, and many more. Typically, programs undergo at least one major revision during its lifetime, often associated to leadership change. Closely related to program governance is the establishment of adequate program evaluation structures. Program evaluation fulfils a dual role of demonstrating impact to donors, which is particularly important during program renewal negotiations, and facilitating real‐time program learning to adjust program performance over time. Performance assessment typically proofs extremely difficult: All collaboration pursue multiple goals and activities, and program impacts are often visible only with a lag of several years (e.g. publications, patents, economic stimulus, exports). Moreover, the program goals are typically inherently sociotechnical and targeted cultural change rather than a marginal publication increase. Therefore, the collaborations withstand attempts to impose simplistic measures of “success.”

5.3 Collaboration completion Completion of the initial program typically results in one of three scenarios: program termination (e.g. CMI), program continuation into a phase 2 (MPP, MI), or the creation of a new program (SMA/SMART/SUTD). The different scenarios are not necessarily a measure of program success; rather, they point to different functions of the programs in the respective national innovation systems, which may require longer or shorter activity. Different completion scenarios call for different transition strategies. Termination requires a smooth winding down of program activities to prevent shocks, including thinking about students in the pipeline, the identification of alternative funding sources, or a handover of all teaching responsibilities to the local universities. Program continuation may call for a strategic revision of program goals and activities, including the discontinuation or addition of certain elements. A new partnership starts the lifecycle from the beginning.

6. Conclusion In this paper, we discussed international collaborations as a novel policy instrument by way of which countries, regions or institutions can build innovation capacity through strategic interaction with eminent global research universities. Based on a comparative study of four of MIT’s recent major international engagements, we presented several models of how these partnerships can be set up (bilateral, network, institution‐building, functional expansion), and analysed how different configurations aligned with the particular innovation needs, systems constraints, and cultural norms of the partner country. Our findings suggest that international university collaborations of the type described here are a powerful and flexible policy instrument for countries seeking to enhance their innovation capabilities. We demonstrated how in each case the emulation efforts underlying these collaboration lead to very different manifestation, contradicting the prevalent notion of “best‐practice transfer” as something quasi‐mechanistic and uniform across contexts. Our comparative architecture analysis provides an entry point for how to theorize cross‐ national systemic differences in the context of university collaborations, and how certain systems constraints give rise to (or inhibit) certain collaboration architectures. While our case studies are far exhaustive, the models discussed here may hold some generalizable lessons facing a specific set of systems constraints may go about building innovation capacity in a collaborative fashion. They further provide a set of building blocks and archetypes from which one can begin thinking about design principles. For example, the case study of Singapore illustrates applied elements of all three other cases (UK, Portugal and Abu Dhabi), such that the latter can be seen as a sort of toolbox for other possible configuration. We further analysed the collaboration lifecycle in its various stages – initiation/design, execution, and completion – highlighting specific implementation challenges (e.g. contract design) for each stage. The lessons learned from the set of collaborations studied in this paper may prove useful for governments or institutions seeking to enter in a similar collaborative arrangement. We believe that MIT’s collaborations are no isolated occurrences, but spearheading a broader policy trend and possible paradigm shift in international innovation policy whereby governments and institutions increasingly seek strategic linkages to globally leading universities. The recent “recruitment” of Cornell University to build an engineering school in New York underlines the potential of this policy instrument also on a national level. This trend may, in the long run, redefine the already central role of eminent research universities in global

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Sebastian Pfotenhauer, Dan Roos, and Dava Newman economic development, moving closer to an active facilitation model for capacity building in science, technology, and innovation. More work needs to fully extract the lessons from these rich case studies, to broaden the empirical base, and to build a theory on complex international innovation partnerships that enables strategic architecting of such collaborations in the future.

References Acworth, E.B., 2008. University–industry engagement: The formation of the Knowledge Integration Community (KIC) model at the Cambridge‐MIT Institute. Research Policy, 37, pp.241–254. Aghion, P. & Howitt, P., 1998. Endogenous Growth Theory, MIT press. Altbach, P., 2007. Tradition and Transition: The International Imperative in Higher Education, Chestnut Hill, MA: CIHE Publishing. Archibugi, D. & Lundvall, B.‐Å. eds., 2001. The Globalizing Learning Economy, New York: Oxford University Press. Berman, E.P., 2011. Creating the Market University: How Academic Science Became an Economic Engine, Princeton University Press. Bhandari, R., 2009. Changes in International Mobility, Los Angeles, CA: NAFSA. CMI, 2008. Accelerating Innovation by Crossing Boundaries: The Cambridge MIT Institute 2000‐2006, Available at: http://www.regionalinnovation.org.uk/object/download/2302/doc/CMI%20Final%20Report‐web.pdf. Conceição, P. & Heitor, M., 1999. On the role of the university in the knowledge economy. Science and Public Policy, 26(1), pp.37–51. Etzkowitz, H., 2002. MIT and the Rise of Entrepreneurial Science, New York: Routledge. Florida, R., 2005. The World is Spiky. The Atlantic, Oct. Available at: http://www.theatlantic.com/past/docs/images/issues/200510/world‐is‐spiky.pdf. Fransman, M., King, K. & Bell, M. eds., 1984. “Learning” and the accumulation of industrial technological capacity in developing countries. In Technological capability in the Third World. Macmillan, pp. 187–209. Goldin, C. & Katz, L., 2009. The race between education and technology, Belknap Harvard. Heitor, M. & Horta, H., 2011. Science and Technology in Portugal: From Late Awakening to the Challenge of Knowledge‐ Integrated Communities. In G. Neave & A. Amaral, eds. Higher Education in Portugal 1974‐2009. Dordrecht: Springer Netherlands, pp. 179–226. Kim, L., 1997. Imitation to Innovation: The Dynamics of Korea’s Technological Learning, Boston, MA: Harvard Business School Press. Knight, J., 2007. Cross‐border Tertiary Education: An Introduction. In Cross‐border Tertiary Education: A Way towards Capacity Development. Paris: OECD, pp. 21–46. Lall, S., 1992. Technological capabilities and industrialization. World Development, 20(2), pp.165–186. Lundvall, Bengt‐Åke, 1992. National Innovation Systems: Towards a Theory of Innovation and Interactive Learning, London: Pinter. Maier, M.W. & Rechtin, E., 2000. The Art of Systems Architecting, Second Edition 2nd ed., CRC Press. Mani, S. & Romijn, H. eds., 2004. Innovation, Learning, and Technological Dynamism of Developing Countries, United Nations. MIT, 2005. Program Overview Brochure, MIT Portugal Program, http://www.mitportugal.org/index.php?option=com_docman&task=doc_download&gid=3&Itemid=383. Nelson, Richard ed., 1993. National Innovation Systems. A Comparative Analysis, New York/Oxford: Oxford University Press. OECD, 2010. The OECD Innovation Strategy, Paris: OECD. Pfotenhauer, S.M. et al., 2012. Seeding Change through International University Partnerships: The MIT‐Portugal Program as a Driver of Internationalization, Networking, and Innovation. Higher Education Policy. Roberts, E.B. & Eesley, C., 2009. Entrepreneurial Impact: The Role of MIT, The Kauffman Foundation and MIT Sloan School of Management. Romer, P., 1990. Endogenous Technological Change. Journal of Political Economy, 98(5), pp.71–102. Siggelkow, N., 2007. Persuasion with Case Studies. Academy of Management Journal, 50(1), pp.20‐24. Slaughter, S. & Leslie, L.L., 1997. Academic Capitalism: Politics, Policies and the Entrepreneurial University, John Hopkins University Press. Thorp, H.H. & Goldstein, B., 2010. Engines of Innovation: The Entrepreneurial University in the Twenty‐First Century, Chapel Hill, NC: University of North Carolina Press. Winckler, G., 2010. Innovation Strategies of Europeam Universities in the Triangle of Education, Research, and Innovation. In L. E. Weber & J. J. Duderstadt, eds. University Research for Innovation. Glion Colloquium. Economica, pp. 107–124. Yin, R.K., 1994. Case Study Research: Design and Methods. Thousand Oaks, CA: Sage Publications

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The Internationalization Process of German High‐Tech SMEs: An Empirical Analysis Andreas Pinkwart and Dorian Proksch HHL Leipzig Graduate School of Management, Leipzig, Germany pinkwart@hhl.de dorian.proksch@hhl.de Abstract: Much research has been done about the internationalization process of companies since the 1970s. However, only few studies applied the findings to high‐tech SMEs and different researchers have pointed out this lack of research (see e.g. Rialp and Knight 2005 and Kriedrich and Kraus 2009). Our contribution attempts to fill in the previous research gap using a longitudinal study to analyze the internationalization process of German high‐tech startups. Our data set consists of 120 venture‐capital‐financed German high‐tech SMEs of which 41.6 per cent of them went international. The data was collected directly from the original transaction documents at the venture capital companies. This enabled us to collect reliable quantitative (e.g. the financial figures) and qualitative data (e.g. the market entry strategy). We showed that the companies followed a structured process for going international which mainly consists of the following four parts: Early Planning, Protecting IP, Raising Funds and Building Networks. The German high‐tech SMEs plan for their internationalization within their business plan and then stick to the plan. They analyze the patent situation and file international patents if possible. In addition, they sometimes have to seek for a way to finance their internationalization. Furthermore, they actively work on expanding their international network, most using trade fairs as a first step. Comparing the national with the international group we were able to quantitatively verify this process. In addition, we enhanced our process model by findings derived from our qualitative data. We used investigator triangulation to ensure the reliability of our approach. Our findings are contrary to the international new venture theory currently discussed in literature and support the process theory of internationalization. Keywords: internationalization, German high‐tech SME, internationalization process, venture capital, longitudinal empirical study

1. Introduction The research area of internationalization evolved in the 1970s and 1980s and most of the existing theories were developed during that time (Rialp et al 2005). Three main models were built to describe the internationalization process: the Uppsala internationalization process model (Johanson and Vahlne 2005), the born‐global model (Madsen and Servais 1997) and the born‐again global model (Bell et al 2003). The first model assumes that companies go through a step‐by‐step approach while becoming international so as to minimize risks as much as possible. Therefore, they try to use strategies, which were proven correct in the domestic market. This model is referred to in literature as Process Theories of Internationalization (PTI). The born global approach describes that new ventures may go international right or shortly after founding without following a structured process. Similarly, the born‐again global model states that a company goes international quickly following a specific event like being taken over by another company or experiencing a change in management. These two models are referred to in literature as International New Venture Theory (INVT). We analyzed the internationalization process of German high‐tech SMEs. The particular lack of research in the field of high‐tech SMEs was pointed out by Rialp et al (2005) and Kriedrich and Kraus (2009). In addition, Johnson (2004) and Crick and Spence (2005) stated that high‐tech SMEs should be analyzed separately because they internationalize more rapidly and use different market entry strategies. Burgel and Murray (2000) reported that technology firms in particular follow a rapid internationalization approach. Schweins and Kabst (2011) confirmed this by analyzing German high‐tech SMEs and added that although they internationalized quickly, these firms used an incremental approach. George et al (1999) showed that a systematic internationalization approach lead to better results. On the other hand, Bürgel et al. (2000) showed that internationalization that occurs quickly leads to faster growth. By using longitudinal empirical data we were able to analyze the internationalization process of German high‐tech SME’s in detail and derive a more specialized model.

2. Theoretical framework Current models of the internationalization process give an abstract description about the factors and steps in internationalization. However, Jones (2001) stated that these comprehensive theories might not be applicable

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Andreas Pinkwart and Dorian Proksch for small high‐technology firms and that rather a series of sub models should be used to explain the internationalization process. We therefore try to connect different models used in current research and apply them to an empirical data set. We thereby combine the theories of technology, financing and networking in internationalization and add a rarely discussed point in the literature ‐ the planning of the internationalization. Table 1: A summary of current literature in the five research fields of internationalization Dimension Early Planning

Authors Cieslik and Kaciak (2009) Fletcher (2007) Burgel and Fier (2000)

Protecting IP

Autio et al (2000) Zou et al (2010) Saarenketo et al (2004)

Raising funds

Westhead (2001) Fernharber (2007) Lutostarinen and Gabrielson (2006) Sharma and Blomstermo (2003) Zaig and NG (2006) Ojala (2009)

Building Networks

Results New ventures internationalize either right from the beginning or not at all Preparation of an international business plan predicts internationalization International sales in the business plan increases the likelihood of internationalization An imitable technology positively influences the international growth Technology capability (including IP protection) is one of the main drivers of international growth Patents have an emerging role as being a determinant for internationalization The ability to acquire financing does not predict the propensity to export The level of venture capital in an industry correlates with the likelihood to internationalize A shortage of financing is a significant challenge for early internationalization Born global firms built their international network early on Networks can be an effective way to penetrate international markets Companies build strategic relationships to internationalize

Current research results were described in table 1. These led us to four steps in an internationalization process. For each step of the internationalization process we were able to derive a hypothesis, which we will describe in the following parts.

2.1 Planning of internationalization Cieslik and Kaciak (2009) argue that start‐ups that focus initially on the domestic market are less likely to export their products. That can lead to the counter hypothesis that ventures which already plan to internationalize in their business plan are much more likely to go global. This was supported by Fletcher (2007) who described writing an international business plan as a main determinant of internationalization. Burgel and Fier (2000) found that the plan for international sales in the business plan increased the likelihood to contract an international distributor. We want to find out if this is also the case for German high‐tech SMEs: H1: International operating German high‐tech SMEs planned their internationalization already in their business plan.

2.2 IP protection To shield themselves from competitors the high‐tech SMEs can file patents for their technologies. Saarenketo et al (2004) state that patents have an emerging role as becoming a determinant for internationalization. That can especially be the case for SMEs because they lack the resources for a fast and aggressive market entry. Zou et al (2010) mentioned that the technology capability (consisting of patents and explicit knowledge) is one of the main drivers of international growth. In contrary, Autio et al (2000) argue that an imitable technology positively influences the international growth. It forces the company to act faster. We want to find out the IP protection strategy by German high‐tech SMEs: H2: International‐operating German high‐tech SMEs filed international patents upon internationalization.

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Andreas Pinkwart and Dorian Proksch

2.3 Financing The internationalization process can create additional costs. These may include travel expenses, costs for new staff members or translation services. Therefore, a company would want to seek new financing upon internationalization. Westhead (2001) surprisingly found that the ability to acquire financing does not predict the propensity to export. However, more recent results state the opposite. Lutostarinen and Gabrielsons (2006) argued that a shortage of financing is an important challenge for early internationalization. Fernharber (2007) described that the likelihood to internationalize rises when more venture capital financing is available within an industry. We want to find out if German high‐tech SMEs try to acquire new financing upon internationalizing. H3: German high‐tech SMEs acquire a new financial investment round prior to their internationalization.

2.4 Network building Various studies stress the importance of an international network. For example, Sharma and Blomstemo (2003) describe how born global firms build their international network very early to enable quick integration into other networks. Zaig and NG (2006) describe that network relationships can be an active way to penetrate international markets. These international networks are actively built and strategically chosen as described by Ojala (2009). High‐tech SMEs often use the possibility to present their products in trade fairs to build their international network. We want to find out if German high‐tech SMEs actively build their networks before internationalizing. H4: High‐technology SMEs build an international network prior to internationalizing.

3. Methodology 3.1 Sample We carried out a survey with 120 high‐tech SMEs. We collected the data from eight different public venture capital funds (VCF) in Germany, which financed these companies. They were financed within 18 months upon being founded and their business models were built on technical innovations. We collected the data directly from the VCF and had access to the original documents. That enabled us to collect reliable, longitudinal data. We had access to the decision files (business plan, due diligence, investment committee paper) and the continuous reporting (qualitative and quantitative reporting, milestone reports, board meetings). That gave us a broad perspective about the development of SMEs. We were able to collect quantitative data (e.g. the financial figures) and qualitative data (e.g. the market entry strategy). An already carried‐out pretest with eight high‐tech SMEs showed the feasibility of this approach. We used a codebook to be able to transform the qualitative data. The codes were derived from literature and were adjusted based on the result of the pretest. We used investigator triangulation to ensure the reliability of our approach. One of the authors and an assistant coded the data. We looked at high‐tech SMEs, which were initially financed between 2005 and 2011; the average age was 5.1 years. SMEs from the following industries were included: information technology, life science, material science, energy and telecommunication. Of the 120 companies in our sample 50 went international. Therefore, the internationalization ratio is 41.6 per cent. Table 2 shows a description of our sample. Table 2: Overview of our sample Variable Number of international cases Number of national cases Number of all cases Number of cases which planned for internationalization in their business plan Internationalization ratio Average age of firms

We state a company as being international if it:

509

Value 50 70 120 48 41.6 % 5.1 years


Andreas Pinkwart and Dorian Proksch

founded a branch in a foreign country;

built a joint‐venture with an international company; or

initiated international sales activity e.g. indicated through meetings with international clients.

3.2 Measures and variables To test our hypothesis in the area of planning we looked at the business plans and the decision files of the SMEs to find out if a possible internationalization was already mentioned. We therefore coded it binary, 1 for mentioned and 0 for not mentioned. We then looked at the text, where there was mentioning of internationalization and searched for patterns. To verify our hypothesis in the area of IP protection we looked at whether international patents were filed. We found this data in the business plans, the decision files and the qualitative monthly reporting. We coded 1 if international patents were filed and 0 if not. We then looked at text, where there was mentioning of IP protection and possible problems in dealing with it. For testing our hypothesis in the area of financing we looked at how many financing rounds the companies have gone through. We can state this by the number of term sheets available. We also looked at the qualitative reporting to find out if the SMEs mentioned that they need more capital for the internationalization. To verify our hypothesis about the international network we looked at the business plans, the decision files and the qualitative reporting. We coded 1 if an international network was mentioned and 0 if not. We then looked at the textual phrases containing any information about the international network. Table 3 shows the descriptive statistics of our variables for our total data set, as well as for the national and international group separately. Table 3: Average values of the variables for the international groups of German high‐tech SMEs Variable General Age of firm Planning Planning in the BP IP protection International patent filed Financing Number of financial rounds Network International network building

International Group Mean/ Share Std. Dev.

National Group Mean/ Share Std. Dev 5.75 1.606 0.404 0.494

5.068

2.508

0.595

0.497

0.380

0.490

0.129

2.040

1.009

1.814

0.548

0.503

0.211

Total Mean/ Share Std. Dev 5.510

3.354

0.484

0.502

0.337

0.233

0.424

1.386

1.908

1.243

0.411

0.353

0.480

To encode our qualitative data we used a codebook with codes derived from literature. After conducting a pretest with eight high‐tech SMEs we adjusted our codebook to get a better fit to our available data. We used investigator triangulation to ensure the reliability of our approach and encoded the variables “Planning in the BP” and “International network built”. Currently, more than 50 intercoder reliability measures are used. However, only Scott’s Pi, Cohen’s Kappa and Krippendorff’s alpha are widely accepted in literature (Lombard et al, 2002). We calculated the values for all three intercoder reliability indicators. After two rounds of encoding the data we received a Cohen’s Kappa larger than 0.81 for all of our variables. Landis and Koch (1977) stated that this value can been interpreted as nearly perfect. In addition, we calculated the values for Scott’s Pi. It’s higher than 0.9 and therefore can be interpreted as excellent (Lombard et al, 2002). Finally, we calculated Krippendorff’s alpha. The value is higher than 0.8 and can be interpreted as acceptable

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Andreas Pinkwart and Dorian Proksch (Krippendorff, 2004). In summary, we have an excellent intercoder reliability for all our variables. Table 3 summarizes the intercoder reliability measures. Table 4: Intercoder reliability for the encoding of our qualitative data Planning in the BP International network built

Percent agreement 97 %

Scott’s Pi

Krippendorff’s Alpha 0.937

N agreement

N disagreements

0.936

Cohen’s Kappa 0.936

96

3

97 %

0.934

0.934

0.934

96

3

4. Results We used One‐Way ANOVA to test if the identified variables were related to going international. The binary measurement of the internationalization (yes or no) attributed to the choice. Using ANOVA, we could identify if the variables had a significant difference in the national and in the international group. To test if the results were significant we provided the F‐value and the P‐value. The results are summarized in table 5. In addition, we enhanced our results with examples of our findings from the qualitative data. Looking at the planning we can state that this variable is significant. High‐tech companies, which go international, planned that within their business plan. We can accept H1. Looking at the qualitative data we found that the business plans often included an analysis of international competitors, a market assessment and a market entry strategy. In view of the intellectual property protection, we can state that this variable is highly significant. High‐tech companies protect their technologies with international patents upon entering international markets. We can accept H2. Looking at the qualitative data we found that the high‐tech SMEs often consult patent lawyers to analyze the patent situation or see if regulations apply. Some high‐tech SMEs say that they want to remain in the European market because the patent situation there is easier to manage. With regards to financing, we have to reject H3. The number of financial rounds doesn’t differ significantly between the national and international group. However, we found examples from the qualitative data that German high‐tech SMEs do seek additional funding to finance the internationalization process. Regarding the international network, we can state that the variable is highly significant and we can accept H4. High‐tech SMEs built international networks upon internationalizing. From our qualitative data, we see that they visit international trade fairs to build up their networks. Also, they use their own international networks and the networks of their investors. Scientific based high‐tech SMEs plan to publish their results in international journals to attract attention and increase their network with people in the field. Table 5: Results of the one‐way ANOVA for each tested variable Variable Planning Planning in the BP IP protection International patent filed Financing Number of financial rounds Network International network built

Degrees of freedom 98 119

F‐value 3.617 11.088

P‐value 0.060 0.001

Sig. S S

119

0.961

0.329

NS

98

13.408

0.000

S

5. Discussions In this section we discuss our results in the four areas of: Planning of internationalization, IP protection, Financing and Network building. Firstly, we analyzed the role of planning in the internationalization process. We found that German high‐tech SMEs make the decision early whether to internationalize or not on and stay with that decision. Our results are in line with the research by Fletcher (2007), Burgel and Fier (2000). Cieslik

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Andreas Pinkwart and Dorian Proksch and Kaciak (2009) stated that new ventures internationalize right from the beginning or not at all. We can’t confirm that statement but argue instead that the decision of German high‐tech SMEs to internationalize is made at the beginning. The planning process includes analyzing international competitors, the assessment of the market potential and the planning of the market strategy. Secondly, we analyzed the role of IP protection and found this to be highly relevant. German high‐tech SMEs first check the patenting situation and then file international patents. They don’t want to risk violating other patents and they want to protect their IP in foreign markets. This confirms the results of Saarenketo et al (2004) and Zou et al (2010). We can state that German high‐tech SMEs are following a risk adverse patent strategy. Thirdly, we looked at the role of financing. We found that German high‐tech SMEs don’t have more financing rounds. This can be due to the young age of 5.1 years in average of the companies in our data set. Possibly, the number of financing rounds differs significantly from each other between national and international high‐tech SMEs if we were to compare them at a later stage. Another reason could be that the number of financing rounds is not higher but the amount of capital raised is more. We were able to show that the international high‐tech SMEs were significantly able to raise more capital in a previous study. This is in line with our results from H1 that the companies already plan for their internationalization from the beginning. Also, our qualitative results showed that some high‐tech SMEs were seeking new funds to finance their internationalization approach. Fourthly, we looked at the creation of international networks and showed that this is highly relevant. This supports the results of Zaig and NG (2006) who describe that building networks is a way to penetrate a market and Ojala (2009) who describes that the international networks are often strategically chosen. Our qualitative results confirm that German high‐tech SMEs are strongly aware of the importance of networks and actively build them. They mainly use trade fairs to first present their products to international buyers. They also use their already established networks and if possible the networks of the VCF. In addition, they use scientific publications to extend their international research network. German high‐tech SMEs don’t seem to simply follow a very structured internationalization approach in whole but also follow a structured networking approach. This could be an area for further research.

Figure 1: The steps of the internationalization process of a German high‐tech SME Figure 1 summarizes our results. Our research showed that the internationalization approach of German high‐ tech SMEs is similar to the Uppsala model developed 40 years ago. German high‐tech SMEs are using a highly structured approach. These findings are also consistent with the results of Schweins and Kabst (2011) who found that SMEs internationalize quickly but in a structured way. A reason for that may be that bringing high‐ tech products or services to the market itself requires a complex and structured approach. The founders may therefore be accustomed to a structured process and therefore tackle the internationalization with the same approach. We were able to create a detailed model of the internationalization steps by enhancing our quantitative results with qualitative findings. 6 Limitations, implications and outlook Our study has the following limitations:

Our research method allowed us to identify and examine the steps German high‐tech SMEs take while going international. However, our research approach doesn’t allow for building conclusions as to the order of these steps. That’s an area for further research.

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We included companies, which were founded between 2003 and 2011 with an average age of 5.1 years. Therefore, we may have more born‐global SMEs in our data set and would have seen a higher internationalization rate if we conducted our study on a set of longer existing businesses. However, we found that most companies already mention their intention to internationalize in their first business plan. Only few companies were included which mentioned their willingness to internationalize and haven’t done so yet.

Our data set only includes data from German companies. It would be interesting to conduct a comparative study to see if the identified internationalization of high‐tech SMEs can also be found in other countries or if it is biased within the German culture.

Our research showed that German high‐tech SMEs follow a highly structured process when internationalizing. That is contrary to the results of the born‐globals. Our results may be attributed to the way high‐tech SMEs work. To develop their products for market‐readiness they have to follow a highly structured approach. That’s why they may be inclined to work in a structured way in general. We encourage further research in this area to verify this. Our results enable researchers to have a better understanding of the internationalization process of German high‐tech SMEs. Combining quantitative and qualitative research we were able to verify our suggested process model and enhance it with actual examples. This can also help high‐tech SMEs to better structure their internationalization process and investors to better support them. In the future, we plan to conduct a survey with the investment managers of the examined VCFs to prove our findings. Also, we plan to build a study comparing the group of high‐tech SMEs, which already internationalized with those that are still planning internationalization.

References Agarwal, S. and Ramaswami, S. (1992) ‘Choice of foreign market entry mode: Impact of ownership, location and internalization factors‘, Journal of International business studies, Vol. 23, No. 1, pp.1–27. Autio, E., Sapienza, H.J. and Almeida, J.G. (2000) ‘Effects of age at entry knowledge intensity, and imitability on international Growth‘, Academy of Management Journal, Vol. 43, pp.909–24. Bell, J. et al. (2003) ‘Towards an Integrative Model of Small Firm Internationalisation‘, Journal of International Entrepreneurship, Vol. 1, pp.339–363. Burgel, O. and Murray, G.C. (2000) ‘The International Market Entry Choices of Start‐Up Companies in High‐Technology Industries‘, Journal Of International Marketing, Vol. 8, No. 2, pp.33–62. Bürgel, O. et al. (2000) ‘Internationalisation of high‐tech start‐ ups and fast growth‐evidence for UK and Germany‘, ZEW Discussion Papers, No. 00‐35, pp.1–27. Cieslik, J. and Kaciak, E. (2009) ‘The Speed of Internationalization of Entrepreneurial Start‐Ups in a Transition Environment‘, Journal of Developmental Entrepreneurship, Vol. 14, No. 4, pp.375–392. Crick, D. and Spence, M. (2005) ‘The internationalisation of “high performing” UK high‐tech SMEs: a study of planned and unplanned strategies‘, International Business Review, Vol. 14, No. 2 pp.167–185. Fernhaber, S.A. McDougall, P.P. and Oviatt, B.M. (2007) ‘Exploring the Role of Industry Structure in New Venture Internationalization‘, Entrepreneurship: Theory & Practice, Vol. 31, No. 4, pp.517–543. Fletcher, R. (2007) ‘A holistic approach to internationalisation‘, International Business Review, Vol. 10, 2001, pp.25–49. George, S., Biscarri, G. and Monti, J.A. (1999) ‘The Role of the Internationalization Process in the Performance of Newly Internationalizing Firms‘, Journal of International Management, Vol 8., December, pp.10–36. Jones, M. V. (2000) ‘First steps in internationalisation Concepts and evidence from a sample of small high‐technology firms‘, Journal of International Management, Vol. 7, pp.191–210. Johanson, J. and Vahlne, J.‐E. (2009) ‘The Uppsala internationalization process model revisited: From liability of foreignness to liability of outsidership‘, Journal of International Business Studies, Vol. 40, No. 9, pp.1411–1431. Johnson, J.E. (2004) ‘Factors Influencing the Early Internationalization of High Technology Start‐ups : US and UK Evidence‘, Journal of International Entrepreneurship, Vol. 2, 1999, pp.139–154. Kiederich, Andreas and Kraus, S. (2009) ‘Investigating new technology‐based firm internationalization: the impact on performance, the process and the antecedents‘, International Journal of Business Research, Vol. 9, No. 2, pp.1–13. Krippendorff, K. (2004) ‘Reliability in Content Analysis‘, Human Communication Research, Vol. 30, No. 3, pp.411–433. Landis, J. R. and Koch, Gary G. (1977) ‘The Measurement of Observer Agreement for Categorical Data‘, Biometrics, Vol. 33, No. 1, pp.159‐174 Lombard, M., Snyder‐duch, J. and Bracken, C.C. (2002) ‘Content Analysis in Mass Communication‘, Human Communication Research, Vol. 28, No. 4, pp.587–604. Luostarinen, R. and Gabrielsson, M. (2006) ‘Globalization and Marketing Strategies of Born Globals in SMOPECs‘, Thunderbird International Business Review, Vol. 48, No. 6, pp.773–801.

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Andreas Pinkwart and Dorian Proksch Madsen, T.K. and Servais, P. (1977) ‘The Internationalization of Born Globals: an Evolutinary Process?‘, International Business Review, Vol. 6, No. 6, pp.561–583. Ojala, A. and Tyrväinen, P. (2007) ‘Market Entry and Priority of Small and Medium‐Sized Enterprises in the Software Industry: An Empirical Analysis of Cultural Distance, Geographic Distance, and Market Size‘, Journal of International Marketing, Vol. 15. No. 3, pp.50‐59. Ojala, A. (2009) ‘Internationalization of knowledge‐intensive SMEs: The role of network relationships in the entry to a psychically distant market‘, International Business Review, Vol. 18, No. 1, pp. 50–59. Rialp, A., Rialp, J. and Knight, G. a. (2005) ‘The phenomenon of early internationalizing firms: what do we know after a decade (1993–2003) of scientific inquiry?‘, International Business Review, Vol. 14, No. 2, pp.147–166. Saarenketo, S. et al. (2004) ‘Dynamic knowledge‐related learning processes in internationalizing high‐tech SMEs‘, International Journal of Production Economics, 89(3), pp.363–378. Schwens, C. and Kabst, R. (2011) ‘Internationalization of young technology firms: A complementary perspective on antecedents of foreign market familiarity‘, International Business Review, Vol. 20, No. 1, pp.60–74. Sharma, D.D. and Blomstermo, A. (2003) ‘The internationalization process of Born Globals: a network view‘, International Business Review, Vol. 12, No. 6, pp.739–753. Westhead, P., Wright, M. and Ucbasaran, D. (2001) ‘The internationalization of new and small firms: A resource‐based view‘, Journal of business venturing, Vol. 16, pp.333–358. Zain, M. and Ng, S.I. (2006) ‘The impacts of network relationships on SMEs’ internationalization process‘, Thunderbird International Business Review, Vol. 48, No. 2, pp.183–205. Zou, H., Liu, X. and Ghauri, P. (2010) ‘Technology capability and the internationalization strategies of new ventures‘, Organizations & Markets in Emerging Economies, Vol. 1, No. 1, pp.100–120.

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Entrepreneurship ‐ Successes and Failures of Start‐Up SMEs on Regional and International Markets Aneta Ptak‐Chmielewska Institute of Statistics and Demography, Warsaw School of Economics, Poland aptak@sgh.waw.pl Abstract: In this paper we analyse the basic characteristics of start‐ups: the winner and the loser. Above 90% of new enterprises are sole‐traders. The support of entrepreneurship needs research such as firms survival in the context of business demography. This information type is crucial for developing a good policy supporting the enterprise survival. Simultaneously, supplying such information is insufficient. New survey types are needed. Recently the interest in firms survival in Poland has increased significantly. To cover the need for more detailed data there was panel database used. The survey covers the five‐year history of enterprises’ activity and the sample covers only enterprises employing initially fewer than 50 workers. In this paper only the sample of 2349 enterprises established in 2004 was selected. In results we can point out that micro enterprises were mostly self‐employed owners. With at least one worker, the survival chances were higher compared to self‐employed owners. Enterprises operating on local or regional markets had lower survival chances compared to enterprises operating nationwide or internationally. Expanding outside regional and local markets offers lower liquidation risk. The effect of places of activities is stronger with time, which means that expanding activities decreases the liquidation probability , and increases the existence time. Expansion is significant with regard to number of employees. The most crucial factor was the first‐ year profits. First‐year profits meant lower liquidation risk compared to enterprises making a loss or suspending their activity. Regarding demographic characteristics of the main owner a conclusion may be drawn, that an enterprise with a highly educated owner experienced in management had a lower liquidation risk. First‐year investments increased the survival chances. The first year was the most important because at that time the main drive for being on the market was observed. Keywords: entrepreneurship, SME and Microfirms, enterprises survival, Cox regression model

1. Introduction Demographic analysis regarding human population can be adopted to the analysis of entrepreneurs population. In business demography an entrepreneur is the research object, whereas processes characteristic of the population of enterprises such as the birth process, death process and population dynamics are the subject. Business demography analysis explains processes in the enterprises population using macro and micro determinants. Above 90% of new enterprises are sole‐traders (including self‐employment). Micro (demographic characteristics of entrepreneurs) and macro factors (basic macro indicators) influencing the business success can be analysed. The development of enterprises and entrepreneurships creates new employment possibilities. The support of entrepreneurship needs research such as business demography in the context of population dynamics. The increase in this field raises the demand for databases consisting of data on newly established enterprises (births) and enterprises exiting market (deaths) and their activity time (survival). This information type is crucial for developing a good policy supporting the enterprises survival. The supply of such information is insufficient. The analysis of the birth and death rates is a starting point for an analysis and research on stimulants of new enterprises establishment, barriers enterprises report and the basis for analysing bankruptcy and liquidation reasons. There is an urgent need for new type of surveys, retrospective surveys and panel surveys. Recently the interest in business demography in Poland has increased significantly. A relevant source of data regarding micro and small (up to 50 workers) enterprises is a panel survey that has been conducted by CSO since 2002. “Creation and operation conditions, development prospects of Polish enterprises established in the years …” is a publication regarding the results of this CSO research. The data th regard results of research on the sample of enterprises in annual periods. Enterprises are followed up to 5 year of the activity. The panel survey can be a source for assessing the enterprise survival but it does not constitute information about population necessary to indicate demographic ratios for the whole population of enterprises. For this paper and survival analysis a panel of SMEs (up to 50 workers) established in 2004 was selected. The sample consists of 2349 enterprises with information of their five‐year activity covering years 2004 ‐2009. All enterprises active in 2009 were censored.

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Aneta Ptak‐Chmielewska

2. Theoretical aspects In theories connected with enterprise management (Poznańska, 2008): “Liability of Smallness”, “Liability of Newness” and “Ecological Economy”, the position of a small enterprise on the competitive market is much weaker. They are put at a disadvantage with regard to economy of scale, distribution chains, market research. However, according to the market niche theory, a small size can create many opportunities (Caves, Porter, 1979), such enterprises are able to reach market niches inaccessible for large companies. Liability of Newness links the success with the time the enterprise operates on the market. The probability of market exit is much higher for new enterprises than for those surviving at least one year. Ecological economy refers to biological theories (Hannan, Freeman, 1989; Carroll, Hannan, 2000) focusing on three enterprise groups: new, developing and shrinking. The ecological theory is focused on the enterprise life cycle: birth, survival and death determinants. In this context “business demography” serves as a tool to measure life cycle, the length of subsequent stages of existence and their determinants on the micro level. The growing interest in theories connected with institutional aspect of enterprise development is also quite important (Gruszecki 2008). Often in “business demography” papers (Scarpetta et al. 2000) and the enterprise life cycle papers, theory of creative destruction by Schumpeter can be found (Schumpeter, 1934). According to this theory, creating new enterprises and liquidating existing ones are key elements of general dynamics of the economy. It also triggers the learning process which affects the enterprise life cycle (Jovanovic 1982). Companies learn about their potential and survival opportunities by generating profits. To minimise the uncertainty risk connected with lack of information at start, companies try to enter the market as small entities thus lowering potential losses if they fail. The enterprise may actively influence its profitability by observing its situation after entering the market and also by taking actions to increase income and profits (Ericsson, Pakes, 1995). The U‐shape of the hazard function confirms such an influence of active and passive enterprise learning. New companies need time to assess their efficiency. Such a behaviour is known as “liability of the adolescence” in contrast to “liability of the newness” (Bruderl, Schussler, 1990; Fichman, Levinthal, 1998). Recently we noted dynamic growth in using statistical and econometric models and analysis regarding firm survival. Both cross‐sectional and longitudinal models and analysis are applied. A very detailed review of literature and research was presented in “Firm survival: methods and evidence” by Miguel C. Manjo´n‐Antolı´n and Josep‐Maria Arauzo‐Carod (Empirica (2008) 35; pp. 1–24). Basic factors influencing firm’s survival are: internal factors specific for an enterprise and external factors connected with macroeconomic situation and the environment. External factors are connected with sector, geographical space and business cycle. External factors are connected with the concept of market “pull” and “push” factors affecting the entry and exit . The market‐pull hypothesis states that greater demand creates more opportunities for starting companies due to greater market absorption. Market push hypothesis assumes that high unemployment level may contribute to self‐employment and opening own business activity. Freedom to enter and exit the market constitutes the main mechanism of functioning a competitive market economy (Balcerowicz, 1999). If there is no such freedom or when this freedom is limited, the economy starts to be uncompetitive, which leads to inefficient allocation of resources. Regarding enterprises population dynamics, three aspects and areas must be considered: entry, exit and survival. Entry may be motivated by higher earnings as self‐employed (Creedy and Johnson 1983, Audretsch 1995, Geroski 1995, Vivarelli 2004) as well as escape from unemployment as push factor. Entry barriers like financial constraints (Evans and Jovanovic 1989, Cabral and Mata 2003) are significant. Some entrepreneur characteristics may be important: self‐realisation, fulfillment of aspiration, better social status (Creedy and Johnson 1983, Vivarelli 2004). Market exit shows that more than 50% of new firms exit within first 5 years (Geroski 1995, Mata, Portugal and Guimaraes 1995, Johnson 2005), which is due to just mistake according to true Schumpeterian displacement‐ replacement effect (Geroski and Mazzucato 2001).

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Aneta Ptak‐Chmielewska Survival success is the effect of self‐decisions or due to financial difficulties. Big role is played by loan constraints (Becchetti and Trovato 2002, Hurst and Lusardi 2004). The internal factor is human capital of entrepreneur workforce and skills (Lazear 2004, Silva 2006), and also sex, but this is mixed effect (Cooper et al. 1994), not confirmed. The sector heterogeneity of survival (Audretsch 1991, Marsili 2002) is also significant. Initial papers regarding the enterprise survival have appeared recently in Poland. Markowicz (2012) applies Cox model analysing enterprises from Szczecin region based on REGON register. Dehnel (2011) applies small area estimation techniques for basic business demography ratios for SMEs in Poland. Some works of Ptak‐ Chmielewska (2011, 2012d) apply non‐parametric (Kaplan‐Meier) and semi‐parametric (Cox regression) methods for retrospective data for one region in Poland.

3. Background situation in Poland Regarding external factors we describe basic figures of macroeconomic situation in Poland in 2004. In 2004 the GDP level was high on the increasing turn. Inflation (CPI) was generally low but at the local peack. Unemployment was high (c.a. 18%) but decreasing. Years 2004‐2005 were good to start a business, the economy was in the up‐turn cycle. Local crises were observed in 2001‐2002 and again in 2009. As pointed in Ptak‐Chmielewska (2012c) the survival and enterprises’ population dynamics are not fully correlated with macroeconomic factors. 25 20

in %

15 10 5 0 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 GDP

CPI

Unemployment

Source: CSO (Central Statistical Office) Database. (GDP – Gross Domestic Product, CPI – Consumer Price Index). Figure 1: Macroeconomic situation in Poland in years 1998‐2012

4. Methods Event history analysis is defined as the set of different statistical techniques used for description and analysing life course of the individual. This process is described by survival time defining the time from the start of observation till the moment of the end or the moment of survey if it happens before the end of the process. Comparing event history analysis with traditional cross‐sectional research one must stress that the biggest advantage of the first is supplying information about the process dynamics. In recent years methods of failure time analysis started to be used in social sciences. The event of liquidation eliminates the enterprise from the observation and is treated as the ending event in the single episode model. According to number of categories the distinction is made between single‐events and multiple‐events models. Methods of estimation (Frątczak, 2005) distinguish between parametric and non‐parametric methods. This is based on assumptions about the functional form of time distribution (T). If there are no such assumptions, non‐parametrical methods are applied with classical example of life table models. Non‐parametric analysis

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Aneta Ptak‐Chmielewska gives information about changes of individual behaviours schemes in time. In parametric approach the time between events is assumed to be random variable with specific distribution. The most frequently used distributions are: exponential, Weibull, Gompertz. In parametric analysis regression methods are used including the influence of time on hazard rate and the inclusion of explanatory variables and heterogeneity of the population. The combination of two approaches is named semi‐parametric approach (Cox regression model). The parametric component is based on specified influence of explanatory variables on the hazard rate, but non‐parametric component does not specify functional distribution of the time. Censoring is very characteristic for event history data. If information is not available then it is censored. The most typical is right censoring when the time till event is not known but it is longer than observation period. Take the interval variable T as the time till event occurrence since the time t0. Distribution of variable T may be described in a few different ways apart from density and cumulative function also by survival and hazard functions.

survival function

S(t ) = P (T > t ) where S(t) means unconditional probability that event occurs after time t, so the enterprise will survive at least till time t. This function describes the survival pattern in the population.

hazard function

h (t ) = lim

Δt → 0

P (t ≤ T < t + Δt | T ≥ t ) Δt

where h(t) is conditional density of time to event occurrence (conditional that the event did not occur till time t), so h(t)Δt means (approximately) probability that the event occurs in a very short period of time (t, t+Δt), conditional that the individual survived at least till time t. The most frequently used model is semi‐parametric proportional hazards Cox regression model. For Cox regression model the hazard function is given by: h(t | x1 ,..., x k ) = h0 (t ) exp(α1x1 + ... + α k x k ) , where: h0 (t ) ‐ means base hazard, parametrically non‐specified function of time and X1,X2,…Xk‐ means explanatory variables (including time dependent variables). Cox proposed also the special type of estimation method called pseudo‐likelihood (Cox, 1972). It divides the likelihood function for proportional hazards model into two parts: first including only information about parameters α i and second, including information about parameters α i , and hazard function. Division into two components is justified because first depends only on sequence of events occurrence, does not depend on exact time of occurrence, and the second is 0 and is omitted. Main advantage of Cox model is assessment of many variables influence on the process without necessity of base hazard h0(t) specification. The main disadvantage of Cox model is hazard proportionality assumption. This assumption imposes that for each pair of individuals in any time the hazard rate is fixed. Despite this limitation of Cox model, it is attractive for researchers in case of (Blossfeld and Rohwer 2002): unknown shape of hazard in time, no theoretical bases for parameterization or no possibility of functional shape of hazard specification and when the main interest is focused on explanatory variables influence on hazard. The only disadvantage of Cox model is proportionality assumption which implies fixed proportion of hazard for individuals during the observation time period. This problem may be solved by including additional time dependent variables. For checking the proportionality assumption the easy way is to include the interaction with time, the significance of these parameters confirms that the proportionality assumption is violated. In this case the model is named non‐proportional hazards Cox regression model. Results of Cox model estimation are parameters describing the influence of explanatory variables on the probability of event occurrence and on the base hazard.

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5. Empirical results Analysis of enterprises’ survival requires information about exact dates of starting and ending activities. Data available in registers like REGON (Register of Business Activities), covering all enterprises are not up‐to‐date and are useless in enterprises’ survival analysis. KRS (National Court Register) or VAT (Value Added Tax System), Central Statistical Office data (SP– annual questionnaire for enterprises and F‐02 statistical financial statement) do not cover all enterprises. This situation requires representative surveys. Panel representative survey on micro and small enterprises sample conducted by CSO since 2002 is a good source of data. More about data sources is available in Ptak‐Chmielewska (2012a). The sample of 2349 enterprises established in 2004 was selected consisting of 2/3 of enterprises with below 10 workers and 1/3 of enterprises with 10‐49 workers, representative for a whole country separately for micro and small enterprises. Basic characteristics are enclosed in table 1. 43.6% of enterprises were still active after 5 years and those enterprises were censored. Table 1: Enterprises characteristics Variable name legal form area of activity (2005) export (2005) places of activity (2005) number of workers (1) 2005 number of workers (2) 2005 number of workers (3) 2005 type of activity profit/loss (2005) owner’s sex owner’s age owner’s education owner’s type of previous work owner’s source of maintenance way of start loan for a start investments (2005) barriers (demand) 2005 barriers (supply) 2005

Description 1=’company with and without legal personality’ 0=’sole‐trader’; 1=’domestic or international market’ 0=’local or regional market/no information’; 1='exporting' 0=’non exporting/no information; 1=’several locations’ 0=’single location/no information’; 1=’employer’ 0=’only owners/no information’; 1=’10 and more workers’ 0=’0‐9 workers/no information’; 1=’5 and more workers’ 0=’0‐4 workers/no information’; 1=’production’ 0=’non‐production/no information’; 1=’profit’ 0=’loss/no information; 1=’male or company’ 0=’female’; 1=35 and older or company’ 0=’below 35’; 1=’higher, post‐secondary or company’ 0=’lower’'; 1=’private, state company manager or company’ 0=’other/no information’; 1=’main source of maintenance or company’ 0=’not a main source of maintenance/no information’; 1=’as new’ 0=’other: take‐overs, mergers etc/no information’; 1=’at least 50% from credit’ 0=’below 50% from credit/no information’; 1=’investing’ 0=’non investing’/no information’; 1=’demand barriers’/ no information’ 0=’no barriers’; 1=’supply barriers/no information’; 0=’no barriers’;

Sources: own elaboration. Registration as a company should provide higher survival chances due to share capital required by law at start compared to sole traders who are not expected to contribute any capital. Companies appear more frequently in the production sector, sole traders in services. Enterprises which expanded above regional market or

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Aneta Ptak‐Chmielewska succeeded in exporting are more successful. Enterprises with at least one worker are more successful than sole traders. First year is crucial and only profitable enterprises have more survival chances. Some barriers reported determine the entrepreneur profile. Some demographic entrepreneur characteristics also matter due to internal factors and human capital. Older, experienced and educated entrepreneurs are expected to succeed, however this effect is not confirmed in literature. The effect of main owner’s sex is not definitely confirmed. More successful are enterprises started as a result of mergers or take‐overs rather than new start‐ups. If a start‐up succeeded in getting the loan it proves owner’s management abilities. Investments and external financing mean that management skills are confirmed and chances for a success are increased. As dependent variable the time from registration to failure was adopted. Multivariate method, the Cox regression model, was applied. Interactions with time were analysed to check proportionality assumptions and time varying effects. Table 2: Results of Cox regression estimation Variable legal form area of activity export places of activity number of workers (1) number of workers (2) number of workers (3) type of activity profit/loss owner’s sex owner’s age owner’s education owner’s type of previous work owner’s source of maintenance way of start loan for a start investments barriers (demand) barriers (supply)

DF 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Parameter ‐0.14125 ‐0.14559* 0.07626 ‐0.32811* ‐0.22225* ‐0.07662 ‐0.24477 ‐0.33619* ‐0.69099* 0.12738* 0.15579 ‐0.37099* ‐0.34568* ‐0.07858 0.14753 ‐0.28944* ‐0.51306* ‐0.00551 0.41703*

Hazard Ratio 0.868 0.865 1.079 0.720 0.801 0.926 0.783 0.714 0.501 1.136 1.169 0.690 0.708 0.924 1.159 0.749 0.599 0.995 1.517

Interaction with time ‐0.13698 ‐0.08292 0.19325 ‐0.30514* ‐0.15200* 0.04572 ‐0.20668 ‐0.06916 ‐0.39946* 0.07583 ‐1.46489* ‐0.04692 0.24287* ‐0.00201 ‐5.67596* ‐0.16965 ‐0.24327* ‐0.41107* ‐1.02238*

*significant at 0.05 level. Source: own elaboration. 11 from 19 included effects were significant at level 0.05. Operating nationwide or internationally means 13.5% lower liquidation risk than operating regionally and locally. This is connected to places of activity. More than one unit gives 18% less liquidation chances . Expansion is evident in case of exporting but this effect was not significant. The enterprise size matters. At least one worker decreases the liquidation threat. More successful are companies in production sector, liquidation chances are 29% lower. Regarding entrepreneur’s demographic profile the effect of sex is not obvious. It was expected that male ownership increases the survival, but the effect is opposite. Education increases survival chances. Owners with managerial experience have 30% lower chances of failure. The motivation can be different but the effect is confirmed. Managerial abilities confirm the ability to convince a bank to grant a loan. First‐year investments in assets are also important, survival chances are increased and this effect accelerates with time. Regarding first‐year supply barriers, this effect is positive, means liquidation chances are increased if the enterprise reports barriers, but the acceleration with time is in opposite direction. Supply barriers matter but at the beginning, their effect is not so important in subsequent years. Only interactions with time for places of activity, number of workers (1), profit/loss, owner’s age, owner’s type of work, the way of start, sources for investments, barriers were significant at level 0.05. Those results confirm the time varying character of the influence of those variables on liquidation process. All significant effects were negative, which means they accelerate the effect of the main variable in negative direction. The more places of

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Aneta Ptak‐Chmielewska activities, the smaller liquidation chances, and this effect is stronger with time. Expansion is also significant in case of employees. First‐year profit is important, because a loss at start means 50% higher liquidation chances. This effect accelerates with time. Owner’s age being first the positive effect, diminishes with time. Age 35 and over is not high enough to start a business because the difference between younger under 35 and older over 35 is not significant, but the interaction with time is significant.

6. Conclusions and discussion Summarising results of semi‐parametric Cox regression model we point out that:

predominantly micro enterprises were self‐employed owners. With at least one worker, chances of survival were higher compared to self‐employed owners.

operating locally or regionally gives lower survival chances than operating nationwide or internationally. Expansion outside regional and local markets meant lower liquidation risk.

First‐year profit is crucial. It meant lower liquidation risk compared to enterprises reporting a loss or suspending activities.

Owner’s education and management experience prove a lower liquidation risk. Conditions of activity and barriers are important. First‐year investments increase survival chances. The effect of places of activities is stronger with time, which means that expanding activity decreases the liquidation probability, and increases the time of existence. Expansion is significant in case of number of employees. First‐year profit is important, loss at start means 50% higher liquidation chances. This effect accelerates with time. According to theories proposed and classifications used to explain the enterprise survival we proposed to distinguish between internal and external factors. Internal factors The first internal factor is the size and age, numerous investigations have found that larger and older firms have lower hazard rates than smaller and younger ones. However, this effect is not uniform. The effect of size is not linear however decreasing (Mata and Portugal 1994, Esteve et al. 2004, Strotmann 2007), but the age effect is more often U‐shaped (Agarwal and Gort 2002, Esteve and Man˜ez 2007). The effect of size and age is different for countries and type of activities ( Lo´pez‐Garcı´a and Puente 2007, Ptak‐Chmielewska 2010). The size‐age effects are only significant for single‐person firms, and there is no size effect in new branches and subsidiaries (Audretsch and Mahmood 1994, Mahmood 2000). This means that the effect of ‘‘liability of adolescence’’ differs across different types and sectors. According to the ecological theory (Hannan 2005), smaller firms have a higher risk of failure ‐ ‘‘liability of smallness’’ (Freeman et al. 1983) and younger firms have higher risk of failure ‐ ‘‘liability of newness’’ (Stinchcombe 1965). In our sample most micro enterprises were self‐employed owners. Company with at least one worker, gives more survival chances compared to self‐employed owners. The second factor, i.e. ownership, is also significant in firms survival. New plants have higher hazard rates than new branches or just diversifying firms (Audretsch and Mahmood 1995, Agarwal and Gort 2002, Kimura and Fujii 2003, Mata and Portugal 1994). In our sample new companies had higher liquidation risk however this effect was not statistically significant. Multi‐plant firms have more chances to survive than single‐plant firms (Mata et al. 1995). This effect was confirmed for Polish SMEs, in our model this effect was significant. Multi locations meant lower liquidation risk. There are studies focusing on differences in firm’s legal structure (Mata and Portugal 2002, Esteve et al. 2004; Esteve and Man˜ez 2007). Evidence from Germany finds that limited liability companies are more likely to exit than sole proprietorships (Harhoff et al. 1998). For one region in Poland the evidence shows that sole traders are the most risky group, and any form of partnership decreases the risk of failure (Ptak‐Chmielewska 2010). However in our model for the whole sample for Poland it was not significant.

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Aneta Ptak‐Chmielewska Other strategic activities are advertising and exporting (Kimura and Fujii 2003; Esteve et al. 2004; Esteve and Man˜ez 2007). Such firms have lower hazard rates of exit (Mata and Portugal 2002). In our sample we considered dummy: exported in first year or not exported, but this effect was not significant. Considering the socio‐demographic profile of an entrepreneur as the most deterministic in enterprise failure we describe below the owner’s demography. In 29% of enterprises the owner was a woman, in 35% ‐ a man and the rest was without the main owner. In 55% of enterprises the owner was younger than 35 and in 13% ‐ younger than 25 when starting the business in 2004. Main owners have at least secondary education (78%), 35% declared tertiary. 12% of owners were unemployed before starting their business, which means that influence of market “push factor” was insignificant (see also Ptak‐Chmielewska 2012c). In 55% of cases employment in own enterprise is the main source of owner’s maintenance. In our model effects of owner’s sex (but opposite), education, type of experience were significant. The evaluation of situation and conditions helping or disturbing enterprises’ development was focused on the environment and barriers. 50% of enterprises did not invest during first year. Almost 48% of enterprises used own funds, only 9.25% used loans or subsidies. With time, share of non‐investing entrepreneurs slightly increased but financing structure changes were rather small. Half of entrepreneurs did not report any barriers in sales and production development. In subsequent years the share of enterprises not reporting barriers decreased slightly. First year was most important to make a decision whether to stay on the market. 26% of enterprises reported too high competition, other barriers were not significant. External factors Industry, geographical space, business cycle play most important role (Manjo´n‐Antolı´n and Arauzo‐Carod 2008). First, industry‐specific characteristics such as technology, entry rates and scale economies seem to explain differences in survival rates across firms. High‐tech industry firms have lower survival probability (Audretsch 1995; Agarwal et al. 2002, Esteve and Man˜ez 2007). This sector is very monopolized and this factor plays a key role in ability of start‐ups to enter the market and influences their ability to survive. Higher hazard rates may be interpreted as the result of barriers in the initial firm’s activity typically occurring in highly innovative industries (Agarwal and Gort 2002). High entry rates have a positive effect on the probability of failure for entrants and existing firms (Segarra and Callejo´n 2002; Mata and Portugal 2002; Honjo 2000; Lo´pez‐Garcı´a and Puente 2007; Mata et al. 1995). Survival is higher in industries with low entry barriers and low minimum efficient scale (Audretsch and Mahmood 1995; Strotmann 2007). The smaller the minimum efficient scale the easier for new firms is to reach a competitive size of activity, but this effect is not obvious for high technology sectors and new units (Mata and Portugal 1994; Audretsch and Mahmood 1994). In our research we controlled for type of activity and reported barriers. Production enterprises have higher survival chances, however the effect of high‐tech sector could not be confirmed due to lack of data. The second, the geographical space, according to New Economic Geography factors, such as, agglomeration economies, affects performance (Fujita et al. 1999). Empirical evidence is inconclusive, some authors find that rural areas represent higher survival chances but some neglect it (Strotmann 2007; Honjo 2000; Fotopoulos and Louri 2000). In Poland urban enterprises have higher survival chances (Ptak‐Chmielewska 2010). According to our results enterprises operating locally or regionally had lower survival chances than enterprises operating nationwide or internationally. The situation varies by regions in Poland (Ptak‐Chmielewska 2012b). The third, the business cycle, survival chances are related to business cycle, higher in the upswings and lower in the downturns. Business cycle upturn, shows negative and statistically significant coefficients in most results with evidence that firms founded in periods of low unemployment have longer survival time (Audretsch and Mahmood 1995; Mahmood 2000; Disney et al. 2003; Go¨rg and Strobl 2003; Ptak‐Chmielewska 2012c). Macroeconomic conditions at the time of entry determine the survival probability (Mata et al. 1995). Concluding, we found that internal factors like socio‐demographic owner’s characteristics: education, previous experience, motivation are significant for a success. External situation and barriers matter considerably. Some results confirmed basic previous research findings but some detailed results gave new insight into start‐ups failure or success. Expanding activities nationwide and internationally is important and increases the survival probability. First‐year survival is crucial, however strongly connected with profits, investing in assets and barriers (demand side). Those effects accelerate in time. Research in this area including methods with time varying effect of characteristics was very rare and our work gives more light into this area.

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Entrepreneurship Education: A View Across Outcome Expectations and Antecedents in Students of Higher Education Augusto de Castro Rocha1, Maria José Aguilar Madeira Silva2 and Julia Discacciati1 Master in Entrepreneurship and Business Creation, University of Beira Interior, Portugal 2 Research Centre for Spatial and Organizational Dynamics (CIEO), University of Beira Interior, Portugal

1

gutorocha@gmail.com msilva@ubi.pt judiscacciati@hotmail.com Abstract: This research aims to identify aspects associated to the outcome expectations and entrepreneurial antecedents that are predicted to influence Portuguese students to follow entrepreneurial career. To empirically test the hypothesis, we used secondary data taken from the survey EEP (Entrepreneurship Education Project) applied in Portugal. It is an approach that reviews the education directed to entrepreneurship and a theoretical approach about the outcome expectations and entrepreneurial antecedents. After this theoretical approach, it´s made a statistical study of the results of the EEP questionnaire ‐ Portugal and then the results are discussed. The sample was considered for result analysis of this study included a total universe of 2054 responses from Portuguese Universities EEP project. To this tests, we used the logistic regression for the outcome expectations and to antecedents, we used first a factor analysis and after a nonparametric test for comparison of means of two independent samples. It can be seen that the look on the expected results Autonomy, may have a relevant impact when we analyze the outcome expectations by the Portuguese students of higher education. May also be conclude that aspects such as family members who have created a business project, previous work experience and previous work experience that failed may affect the propensity to create and manage a new business project. Keywords: entrepreneurship education, outcome expectations, entrepreneurial antecedents, EEP, entrepreneurship

1. Introduction The entrepreneurship education has developed over time several lines of approach to set theory in order to contribute to the development of the business profile in higher education students (Franco et al. 2010) and identify factors that may influence the creation of their own business by college students (Rodrigues et al. 2010). The theme of entrepreneurship education has become so important, that there is indications that this type of practice in education should also expand to secondary school (Marques et al. 2012). There are studies regarding entrepreneurship teaching in Portugal for higher education (Redford 2006; Franco et al. 2010; Teixeira & Davey 2008; Rodrigues et al. 2010; Davey et al. 2011), however it is still a subject that need to be developed. As this is seen as a very important issue in the hole world, a global study has emerged which aims to measure various constructs relating to entrepreneurship teaching. This study is called EEP (Entrepreneurship Education Project) and it is a joint project conducted in over 800 countries with coverage of more than 400 universities. This work performs an analysis of data of this questionnaire applied in Portugal, with a specificity regarding the outcome expectations and entrepreneurial antecedents. In summary, this study aims to identify components of the process of entrepreneurship teaching and the way that those components can influence and lead to a more structured and efficient teaching of this subject.

2. Theoretical framework 2.1 Concepts about entrepreneurship education Entrepreneurship has developed positive effect in previous generations and has key role in economy of countries. It helps in the development of a nation, and also generates a series of contributions to that population. It is through these gains that can be emphasized that the teaching of entrepreneurship has a key role in the educational formation (Rodrigues et al. 2010) and a positive impact in the approach towards entrepreneurship (Packham et al. 2010). The teaching of entrepreneurship is not only aimed on individuals that want to develop new companies, because, as Pittaway & Cope (2007) say, it should cover the following

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Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati interests: employability skills, social enterprise, self‐employment, employment in small businesses, small business management and management of high‐growth ventures. In Portugal, students have certain indecision about following with their own jobs or be employed on behalf of others (Davey et al. 2011), despite knowing that the example provided during the school plays a key role in shaping the entrepreneurial profile (Teixeira & Davey 2008). The entrepreneurship education, in this case Portugal, happens to be a reality because it is a response to intrinsic needs of the market (Redford 2006) and probably is crucial to introduce innovation processes in the market by having more students prepared for their careers (Wilson 2008). Several studies approve of entrepreneurship development policies implemented by governments in the education system, help to include entrepreneurial attitudes and values in students (Audretsch & Beckmann 2007; Parker 2007; Stevenson & Lundström 2007; F. J. Greene & Storey 2007). The importance of these policies is mainly to promote a strong educational system in teaching entrepreneurship, aimed at encouraging constant innovation (Acs & Szerb 2006). In order to create those policies, Thomas & Kelley (2012) suggest a pattern of actions aiming to transform the educational system of the countries that want to introduce their students in entrepreneurial activities. Among the items that are suggested by the authors are: Develop national plans for entrepreneurship education; Create interministerial working groups (education, economics, research and technology, etc.); Creating public or private agencies to promote entrepreneurial education; Working with leaders in educational institutions, and Reassessing rules and regulations of the University.

2.2 Outcome expectations The anticipation of favorable results gives the individual a sense of satisfaction (Lent et al. 2009). Expectations for results are important factors in determining whether an individual can pursue an entrepreneur career. Studies such as Townsend, Busenitz, & Arthurs (2010) indicate that with the growth of the phases of business plans analysis, those entrepreneurs with high expectations result can have a more practical view of his own business and not choose a certain path only for their expectations. However there are also studies such as Cassar (2010) which indicates that entrepreneurs overestimate the results of their projects, so you can hide some failure. This brings the importance of entrepreneurship education adequately, because there are indications that the quality of education directed to entrepreneurship may have an impact on the results that a company may have (Zhao et al. 2005), although more tests are needed to ascertain this fact. An entrepreneur aims to search for positive results from their entrepreneurial activity. Entrepreneurs have in essence a pursuit for independence, self‐fulfillment and financial success when they decide to start a new business (Carter et al. 2003). One explanation for the entry of an individual into a new business venture has a direct link with the expectation of having a good financial result (Cassar 2007; Shepherd & Patzelt 2011) and such good financial results can be guaranteed to provide an adequate family safety (Edelman et al. 2010). H1: The need for financial success is positively and significantly associated with the outcome expectations in the implementation of a new business project for Portuguese university students. H2: The family safety is positively and significantly associated with the outcome expectations in the implementation of a new business project for Portuguese university students. Autonomy represents an achievement of objectives that can be targeted and endorsed by the individuals themselves, since they are responsible for their consequences. There is also a study of Gelderen (2010) which proves that autonomy during the entrepreneurship education in order to discuss individual circumstances, better prepares individuals to practice entrepreneurial activity more autonomously. Individuals who have autonomy at work, both working on their own or others, are most benefited (Prottas 2008). H3: Autonomy is positively and significantly associated with the outcome expectations in the implementation of a new business project for Portuguese university students. When individuals seek entrepreneurial activity as a follow up of their careers, they may be seeking a personal development greater than if they had continued to work for others (Guzmán & Santos 2001). The choice of an entrepreneurial career has an intrinsic motivation for self‐realization / personal gain (Tyszka et al. 2011) seeking flexibility and the use of time itself through independence (Carter et al. 2003). For example, in the area of technologically innovative companies, personal gain through self‐realization is a great reason to start a new

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Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati business (BarNir 2012). The expectation of self‐realization (Carter et al. 2003; Cassar 2007; Edelman et al. 2010) is an expected result for those seeking an entrepreneurial career. H4: Personal gains (self‐realization) are positive and significantly associated with the outcome expectations in the implementation of a new business project for Portuguese university students.

2.3 Antecedents Future entrepreneurs who have family members who have started a business project are more likely to pursue an entrepreneurial career (Delmar & Davidsson 2000), confirming that positive models are important for this (Davidsson 1995), including the family ones. (Altinay et al. 2012). Building on the basis of what is reported above that family members can influence the possibility of someone starting a new business project. H5a: Family who created a business project, influences the confidence to successfully build and manage a new business project by Portuguese university students H5b: Family who created a business project that failed, influences the confidence to successfully build and manage a new business project by Portuguese university students Previous experience of an administrator / manager has a direct link to the success of a new undertaking that he participate (West & Noel 2009). Several companies are conceived during previous working experiences (Bhide 1994; Terjesen & Sullivan 2011). And the growth of these new companies may be intrinsically linked to the fact that the entrepreneur was employed or not before taking new business project (Capelleras et al. 2010). H6a: The previous professional experience on a new enterprise influences the confidence to create and successfully manage a new business project by Portuguese university students H6b: The previous professional experience on a new enterprise that has failed influences the confidence to create and successfully manage a new business project by Portuguese university students

3. Methodology In this context, after what was seen during the literature review, it comes to the conclusion that the literature little addresses the expected results by the Portuguese higher education students wishing to participate in the creation of a new business project. It follows that this study will be exploratory, because according to George (2002), an exploratory study is useful for the construction of new knowledge in a particular area, thus maximizing the information that may be collected in a given sample (Tukey 1977).

3.1 Database The data used to make this research work were collected through a survey that was submitted to the Portuguese higher education students, the project participants EEP. The EEP is designed to be a project with a global reach, with defined objectives to realize the impact that the entrepreneurship education will have on college students, through knowledge of motivational processes related to who intends to pursue a career and entrepreneurial transformation of a student in an entrepreneur (Liguori et al. 2011).

3.2 Method used To review the Outcome Expectations, found that the logistic regression method would be most appropriate. Since the dependent variable is analyzed qualitatively and fits as nominal dichotomous (yes / no) (Menard 2002), tells us the use of a regression method categorical this case, logistic regression (Maroco 2007; Harrell 2001). Furthermore, the variable indicates participation or not in a given occurrence (Bethlehem 2008), therefore another indication that the most appropriate method is logistic regression. When the analysis is performed with respect to Antecedents, first performed a factor analysis to determine a measurement scale (Maroco 2007) for determining degrees of confidence to create and successfully manage a new business project. To evaluate which tests are used, you should consider whether these factors follow a normal distribution. It is then used nonparametric Mann Whitney test for comparison of means of two independent samples.

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4. Analysis and discussion of results 4.1 Sample characterization Gender is used in this work in order to characterize the sample at a level of knowledge of the rate of entrepreneurial expectation for each sex. Gender is addressed in several studies on entrepreneurship (BarNir 2012; Terjesen & Sullivan 2011; Carter et al. 2003; Teixeira & Davey 2008), with a variable positioning, very dependent of the sample used. Even the genre may have a greater effect not on actually entrepreneurs, but those who have the expectation of being entrepreneurs in the future (Zhao et al. 2005). Among respondents who were asked which their gender was identified as 44.16% are male while 55.84% are female. Another interesting aspect to see the group answered the questionnaire EEP Portugal is in relation to Family Wealth. This analysis is that the families of the respondents are mostly middle class (83% of respondents), while 8.18% are considered poor and 8.82% identify themselves as upper class. It is known that the family can have some influence on the entrepreneurial intention of an individual (Dyer 1994; Franco et al. 2010; Rodrigues et al. 2010) and financial level this family can influence this intention through due support.

4.2 Analysis and discussion of results 4.2.1 Factorial analysis Before testing the model with the application of logistic regression, we performed a factor analysis process to determine the factors related to confidence in the ability to successfully create and manage a new business project. To validate the factor analysis would be valid for the proposed model, we used the criterion measure of sampling adequacy Kaiser‐Meyer‐Olkin (KMO), which resulted in a KMO value = 0.590. As the value found is greater than 0.5, the adequacy of the sample is acceptable. To understand if the variables are significantly correlated, we resort to the Bartlett Sphericity test. As the p‐value <0.001, reject the hypothesis that the covariance matrix is proportional to the identity matrix, so variables are correlated significantly (Maroco 2007). Using the rule of eigenvalue with value greater than 1, it was decided to extract two latent factors. On Table 1 shows a summary of the factorial weights of each item analyzed for each of the two factors, the values of its eigenvalues, and the percentage of variance explained by each factor. Table 1: Presentation of setting values of the factors of factor analysis, Eigenvalues and Variance Explained Factor Item

Description

Parents have created business projects that affect the confidence to successfully build and manage a new business project Brothers or sisters have created business projects that affect the 2 confidence to successfully create and manage a new business project Grandparents create business projects that affect the confidence 3 to successfully build and manage a new business project Paid professional experience interferes confidence to successfully 4 create and manage a new business project Unpaid work experience interferes with the confidence to 5 successfully build and manage a new business project Eigenvalue Variance Explained 1

Familiar Confidence (CF)

Professional Confidence (CEP)

0,734

0,104

0,769

0,057

0,683

0,104

0,266

0,773

‐0,031

0,866

1,917 38,3%

1,122 22,4%

The first factor retrieved from factorial analysis shows high weights for items 1, 2 and 3 respectively and explained 38.3% of the total variance. For a clearer representation, the first factor is called Familiar Confidence (CF). The second factor which was extracted latent has higher values for Items 4 and 5 and explained 22.4% respectively of the total variance. To better understand this second factor is called Professional Confidence (CEP). In general, these two factors are responsible for explaining 60.7% of the total variance. 4.2.2 Logistic regression After defining the assumptions in the preceding paragraphs of this study, we constructed logistic regression

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Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati models able to test the proposed elements. It is tested a model of outcome expectations. For this feature toTable 2 which contains the OE Model (Outcome expectations). Table 2: Logistic regression of OE model ER Model Variable FUS FS Au PG

B S.E. p‐value Exp(B) 0,063 0,087 0,525 0,469 1,065 ‐0,011 0,059 0,035 0,853 0,989 0,234 0,090 6,670 0,010 1,263 0,083 0,071 1,385 0,239 1,087 Quality of the adjustment of the model Correctly predicted 65% Chi‐square

22,666; 0,000 (Sig)

‐2 Log likelihood

1497,662

The variable Autonomy (bAu=0,234; =6,670; p=0,010) showed a statistically significant effect on the Logit of the probability of participating in a new business project. In analyzing the quality of the adjustment related to the OE model, we can verify their predictive ability is 65%, which results from a comparison between the values of the response variable predicted by the model with those observed. The test indicates the ratio of likelihoods us G2(4)=22.666, p<0.001, concluding that there is at least one independent variable in the model with predictive power on our dependent variable. The statistical‐2LL (‐2 Log Likelihood) with the value of 1497.662 also corroborates to evaluate the goodness of fit and significance of OE model compared with the null model. To discuss the results, since they reject the hypotheses H1, H2 and H4, for not having been proven by model. But based on the number of results presented above, we can draw some interesting conclusions. When analyzing the OE Model, has an indication that the variable Autonomy can be identified with a statistically significant effect. So it was proven that Autonomy is positive and significantly associated with the expected results in the implementation of a new business project for Portuguese students (H3). 4.2.3 Test of factors To test the hypotheses H5a, H5B, H6a and H6B should be done statistical analysis on the factors derived from factor analysis: Familiar Confidence (CF) and Professional Confidence (CPE). To decide which test should be used, primarily has been used a normality test. The normality test can be seen in Table 3. Table 3: Normality test to analyze CF and CEP Familiar Confidence (CF) Professional Confidence (CEP)

Kolmogorov‐Smirnov Statistic df 0,193 157

Sig. 0,000

Shapiro‐Wilk Statistic df 0,917 157

Sig. 0,000

0,247

0,000

0,865

0,000

157

157

The assumptions of this statistical method, namely the normality of the distributions on both factors were evaluated, respectively, with the Kolmogorov‐Smirnov test with Lilliefors correction (KS(157)CF=0,193; p=0,000 e KS(157)CEP=0,247; p=0,000). With a probability of error of 5% could be concluded that the two factors do not follow normal distribution. The statistical software also provides the test results Shapiro‐Wilk, however the results of this test are best used when you have small samples. The factors CF and CEP do not follow normal distribution resort to non‐parametric tests in order to compare means. For the analysis we use the nonparametric Mann‐Whitney test as an alternative to t‐Student test to compare the means of two independent samples. This is "particularly when the assumptions of this test are not valid and is not possible, or desirable, to evoke the robustness of the test to violations of its assumptions" (Maroco, 2007, p.219). Notably in relation to family members who have created a business plan, it is possible to attempt for two analyzes of acceptance / rejection of the hypotheses. For these analyzes, we propose the analysis of Table 4 representing family that created a business project and Table 5 representing family that created a business project that failed.

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Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati Table 4: Mann Whitney´s non parametrical test representing family that created a business project Family No Yes Null Hypothesis The distribution of Familiar Confidence is the same across categories of Family

Mean ‐0,4592476 0,3600919 Test

N 69 88 Sig.

Std. Deviation 0,86915102 0,95090945 Decision

Independent‐Samples Mann Whitney U Test

0,000

Reject the null hypothesis

It appears that there are significant differences in the degree of confidence to create and manage successful business project in students that have family members who have created an enterprise project (p = 0.000). Therefore, this study confirms the hypothesis that family that created business project affects the confidence to successfully build and manage a new business project for Portuguese students (H5a). In this particular case until we can say that trust is higher in students who have family members who have created a business project. Table 5: Mann Whitney´s non parametrical test representing family that created a business project that failed Family (project that failed) No Yes Null Hypothesis The distribution of Familiar Confidence is the same across categories of Family_Failure

Mean ‐0,0692625 0,2983287 Test

N 124 26 Sig.

Std. Deviation 0,96281415 1,20824016 Decision

Independent‐Samples Mann Whitney U Test

0,054

Retain the null hypothesis

Considering those family projects that failed, there was no statistically significant differences for the significance level of 5% in average student confidence (Table 5). Therefore reject the hypothesis that family that created a failed business project affects the confidence to successfully build and manage a new business project for Portuguese students (H5B). Regarding hypotheses related work experience, make up two more analyzes related to confidence in creating and managing a new business project of whom have had previous professional experience (Table 6) and of those who have had previous professional experience that failed (Table 7). Table 6: Whitney´s non parametrical test representing those who have had professional experience Professional Experience No Yes

Mean ‐0,5752179 0,7931035

N 91 66

Std. Deviation 0,68474732 0,80552272

Null Hypothesis The distribution of Professional Confidence is the same across categories of Experience

Test

Sig.

Decision

Independent‐Samples Mann Whitney U Test

0,000

Reject the null hypothesis

For confidence to create and manage successful business project for students who have had previous experience is verified that there are statistically significant differences (p = 0.000). Thus, this study confirms the hypothesis that previous work experience in a new venture influences the confidence to create and successfully manage a new business project for Portuguese students (H6a). It can be argued, in the case relating to this sample, who had experience in a new business project has on average a higher degree of confidence compared to those who does not have experience. Watching professional experiences in previous projects that failed, there are statistically significant differences to the significance level of 5%. As the p‐value = 0.000, reject the null hypothesis of equality of means for the two groups. Thus, this study confirms the hypothesis that previous work experience in a new venture that failed influences the confidence to successfully build and manage a new business project for Portuguese students (H6B).

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Augusto de Castro Rocha, Maria José Aguilar Madeira Silva and Julia Discacciati Table 7: Whitney´s non parametrical test representing those who have had professional experience that failed Experiência Profissional (projeto que falhou) Não Sim Null Hypothesis The distribution of Professional Confidence is the same across categories of Falilure_Experience

Mean

N

Std. Deviation

‐0,0977659 0,8179307 Test

134 17 Sig.

0,97046272 1,01463835 Decision

Independent‐Samples Mann Whitney U Test

0,000

Reject the null hypothesis

5. Conclusion It can be seen that the look on the expected results Autonomy, may have a relevant impact when we analyze the outcome expectations by the Portuguese students of higher education. May also be conclude that aspects such as family members who have created a business project, previous work experience and previous work experience that failed may affect the propensity to create and manage a new business project. This last aspect is important above all because it is the influence for the positive direction, may indicate a possibility of learning from previous mistakes. Among the limitations of this study, we identify that the sample could be a wider scope, as it was applied in most schools of business. If it were a national sample for various courses and universities in Portugal, could reach more conclusive data to form a more robust model. Indication as to future lines of research, similar work could be done by analyzing the data in other ways. When considering entrepreneurship as a phenomenon, there is a more comprehensive perception of the real meaning of the term and it can be related to some phenomena of imbalance (microeconomic), such as technological breakthroughs, innovation, changes in the production process and pure profit and loss (Kirzner 2008). It is also indicated as future research line, perform the same study differentiating the employment situation of respondents, since that statement could influence the model. This could result in values of interest to analyze the results when the model has been unemployed, working full time or part time.

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Institutional Support Program for Entrepreneurship: The Experience of the University of Minho Cristina Rodrigues1 and Filipa Vieira2 1 Algoritmi R&D Centre, Departement of Production and Systems, University of Minho, Braga, Portugal 2 CGIT, Departement of Production and Systems, University of Minho, Guimarães, Portugal crodrigues@dps.uminho.pt filipadv@dps.uminho.pt Abstract: Entrepreneurship has a significant effect in promoting innovation, productivity, creating employment opportunities and economic development of a country. In many countries has been made a significant effort to promote entrepreneurship. An entrepreneur is someone who is able to develop new products and services, taking risks and identifying opportunities. The university programs have one important role in identifying business opportunities and support during the entrepreneurial process. Since Portugal has been particularly affected by the current crisis, with particular focus on the country's unemployment rate and economic operating conditions, which impact can have an academic initiative like the TecMinho’s IdeaLab of University of Minho? Since 2009, the University of Minho has in operation a business ideas laboratory, the TecMinho’s IdeaLab, which supports the generation and development of technology‐based and / or knowledge intensive business ideas. Having already completed eight editions, it is intended to support students and graduates of the University of Minho from any scientific area. In addition to testing the commercial potential of the ideas presented, evaluates the vocation and entrepreneurial skills of the participants through the various stages of the program. Besides presenting and discussing the results over time, the paper complements the analysis with a case study of participants and ideas that were selected to initiate the TecMinho’s IdeaLab workshop phase. Since its foundation, the TecMinho’s IdeaLab has supported the development of 126 business ideas and enabled for 291 entrepreneurs the acquisition of knowledge and skills in business development and business creation, regardless their training areas. In addition to the individual characteristics and skills of participants, we analyze the characteristics of the ideas presented, in order to contribute for the understanding of the evolution of the program. The presented results make a contribution in the Portuguese academic entrepreneurship theme and in particular in the University of Minho case. Keywords: entrepreneurship, support program, University of Minho, Portugal

1. Introduction The entrepreneurship origin lies in the recognition of an opportunity or a need, in meeting the necessary resources and the creation of a company. The universities, given their potential for knowledge and research, have been implementing programs to encourage entrepreneurship, particularly through the creation of technology transfer offices, incubators, entrepreneurship centers or establishing internal funds to stimulate the application of patents, revenue licensing and the creation of spin‐offs. Located in the northern region of the country, in a region of strong industrial implementation, the University of Minho created in 1990 the TecMinho, an interface with the peripheral business environment that provides a comprehensive set of services for managing innovations born at the University of Minho. TecMinho has three complementary departments, and beyond its technical and scientific component, has been developing initiatives to promote entrepreneurship such the creation in 2009 of TecMinho's IdeaLab, a program to support the generation and development of ideas for technology‐based business and / or knowledge intensive of students and graduates of the University of Minho from any scientific area. The present study aims to examine the TecMinho’s IdeaLab program to support entrepreneurship among University of Minho’s students and is organized into five sections, besides the introduction. Section 2 presents the importance of education in promoting entrepreneurship. Section 3 gives a brief summary of the Portuguese University of Minho’s program to support and promote entrepreneurship. Section 4 presents the case study of TecMinho’s IdeaLab with the analysis. Finally, Section 5 presents the main conclusions.

2. Entrepreneurs and education Entrepreneurship origin lies in the recognition of an opportunity or a need, in meeting the necessary resources and the creation of a company. Additionally it can be stated that, apart from putting the market in equilibrium,

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Cristina Rodrigues and Filipa Vieira entrepreneurs are individuals who are aware of the business opportunities and use the means at its disposal to make best use of these resources (Kirzner, 1997). The origin of the word "entrepreneur" resides in the French verb "entreprendre" which means “to undertake”. Entrepreneurs are held responsible for economic development, by introducing and implementing innovative ideas such as product innovation, process innovation, market innovation and organizational innovation. The implementation of these new ideas creates new companies which generate economic growth and supply new jobs for the working population (Van Praag, 1999). The work of Wong et al (2005) state that small businesses and newly formed firms create a substantial number of new jobs, with some studies showing that small and new firms are the source for the majority of new jobs created. Many countries have put policy priority on supporting entrepreneurship, but as Drucker (2006) said entrepreneurship is neither a science nor an art, it can be learned and should be practiced, because entrepreneurs are not born but are molded. Policy makers believe that increased levels of entrepreneurship can be attained through education and especially entrepreneurship education (Curteis, 1997). Several authors, such as Raijman (2001) and Askun and Yiidirim (2011) defend that education, by providing broad skills, training and knowledge facilitates the access to the business world through enabling individuals to assess the extent of the labor market, and the kind of goods customers demand, and to organize a business. For Carayannis et al (2003) there is no doubt that entrepreneurship education seeks to build knowledge and skills and also increases the likelihood of entrepreneurial success. Furthermore, Souitaris et al (2007) and Von Graevenitz (2010) added that entrepreneurship education increases the intention to start a new business. A key assumption underlying the entrepreneurship education is that entrepreneurship skills can be taught and are not fixed personal characteristics. Indeed, it has been shown that (1) the effect of general education as measured in years of schooling on entrepreneur performance is positive and (2) the business training is effective or the performance of people who applied for microfinance to start their own business (Oosterbeek et al, 2010).

3. Entrepreneurship at the University of Minho The spread of the negative effects of the international financial and economic crisis has significantly affected the activity of the Portuguese economy, with particular emphasis and impact on the unemployment rate of the country and the conditions of its economy. The emergence of entrepreneurs, able to identify and seize opportunities, invest and create wealth and jobs are critical to the recovery and development of national economy (GEM, 2010). A recent study confirms a new generation of Portuguese entrepreneurs with higher qualifications (LINI, 2009) but data from the GEM survey indicated in 2010 a score to Portugal of just 4.5% for the rate TEA (early‐stage activity entrepreneurship tax), a significant decrease of the value obtained in 2007. Regarding gender distribution of entrepreneurs in Portugal, the number of entrepreneurs male (5.9%) is equivalent to about twice the number of female’s entrepreneurs (3%) (GEM, 2010). At the academic level, the programs of institutional support for academic entrepreneurship are recent, but there is an increase in the last four years of individual initiatives of the various public universities. One of earlier examples was the University of Minho, a public university located at the north of Portugal. Established in 1973, began its teaching activity in 1975 and offers nowadays a portefólio with several courses at all levels of higher education whose quality has been evidenced by several national and international assessments. The scientific and academic activities of the University of Minho are organized into two separate campi. The Gualtar campus, located in the city of Braga, is where are the courses of exact and natural sciences, social sciences and humanities. The Azurém campus in the city of Guimarães, hosts the schools of architecture and engineering. At the human level, the university mobilizes 1100 teachers and 550 staff to cope with a diverse educational offer (total of 234 courses) and a student population of 18,700 students, of which approximately 4,300 are master's degree students and 1,900 are doctoral students. University of Minho believes that its mission is based on three projects: teaching, research and the provision of specialized services to the community. Thus, the organizational structure of the University is currently organized into eight schools and three institutes and is associated with 13 interface structures comprising:

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Cristina Rodrigues and Filipa Vieira

3 structures oriented to knowledge transfer (TecMinho the IDITE Minho and SpinValor),

1 Park of Science and Technology (The Ave Park),

1 business incubator (the Spinpark),

1 binding entity encompassing the outside (Foundation Carlos Lloyd Braga) and,

7 structures aimed at applied research interaction with the business sector.

The developed work has highlighted this University as an important agent of regional development. The University of Minho has created several centers of applied research and one interface structure, TecMinho, to respond to requests from the strong existing industrial park in the area where it is inserted. Founded in 1990 as a joint initiative of the University of Minho and the Association of Municipalities of the Ave Valley, TecMinho is the interface structure of the university in the scientific and technological aspects. During its early years, TecMinho guided primarily for projects of regional development but, from 1998, it began to focus increasingly on the enhancement of university knowledge by promoting entrepreneurship, protection of intellectual property rights, licensing and the creation of spin‐offs. The mission of TecMinho is defined in three main lines of action: 1) supporting the development of new technologies / products / processes and transfer to companies, 2) the design and implementation of activities in education and training (classroom and e‐learning), organizational development and transnational mobility of human resources, 3) support for university entrepreneurship and the creation of innovative firms with particular attention to the academic spin‐offs. TecMinho provides a comprehensive set of services for managing innovations born at the University of Minho and is structured in three complementary departments. The first, the Technology Transfer Department ensures the protection of new products or processes, the development of a portfolio of technologies and the commercialization of University assets. Second, the Department of Advanced Education aims to improve business competitiveness based on the qualification of human resources, by offering various training courses for individuals. Finally, the Department of Entrepreneurship encourages the formation of technology‐based companies, by encouraging an entrepreneurial culture and support for spin‐offs in the pre‐start and start‐up. Aiming to develop the entrepreneurial skills of students at the University of Minho, TecMinho has implemented several initiatives to foster an entrepreneurial culture in academia and promote entrepreneurship as a valid alternative career. The most recent initiative was the establishment in 2009 of a laboratory of ideas, TecMinho's IdeaLab, aimed at facilitating the generation and development of innovative business ideas by students from the University of Minho.

4. The TecMinho’s IdeaLab (University of Minho) 4.1 Methodology Ongoing research aims to examine the use and impact of programs of institutional support for entrepreneurship, in order to answer the research question: "What is the impact of initiatives such as the program to support entrepreneurship at the University of Minho?". Thus, at an early stage of the investigation, it was decided that the research strategy would be a case study of the University of Minho, in the particular case of TecMinho's IdeaLab. The methodology of case study consists of detailed research, based on data collected over a period of time, one or more organizations, in order to obtain an analysis of the problem to be studied. In the particular case of this work, it can be stated that this is a case study explaining why if you want to find relationships cause‐effect relationship between certain situations.

4.2 Presentation of the TecMinho’s IdeaLab programme The TecMinho's IdeaLab emerged under an application submitted by TecMinho to the contest "Promoting Entrepreneurship in Higher Education Students Portuguese" promoted in 2007 by COTEC Portugal. Supported by the University of Minho and subsequently approved and co‐financed by COTEC, the application was designed to define an integrated strategy to encourage entrepreneurship at the University of Minho and able to develop students entrepreneurial skills and promote entrepreneurship as an attractive alternative career. TecMinho’s IdeaLab was established at the beginning of 2009 after the establishment of a cooperation agreement between TecMinho and the Mälardalen University (Sweden) where this model was originally

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Cristina Rodrigues and Filipa Vieira implemented. The TecMinho’s IdeaLab provides hands‐on training and consultancy in order to help participants generate and develop innovative business ideas and also provides them access to the laboratory for a maximum period of 5 months in order to mature their business ideas. The TecMinho’s IdeaLab of University of Minho intends to support the generation and development of business ideas with a technological and/or intensive knowledge background of students or graduates of any scientific area. With this TecMinho's IdeaLab program, the University of Minho seeks:

Provide promoters of selected ideas with knowledge, methodologies and tools related to the creation and development of innovative businesses in order to facilitate analysis, planning and implementation of marketable products or services;

Encourage entrepreneurs attitudes, behaviors and values within the academic community (particularly the student community) and raise awareness of entrepreneurship as a valid career option;

Intensify the dynamic creation of innovative firms generated from the University of Minho (i.e., spin‐offs) to contribute to the renewal of the business in the region.

Besides testing the commercial potential of ideas presented, the TecMinho's IdeaLab evaluates the entrepreneurial vocation and competencies of its participants along three phases. The first phase, the receipt of business ideas, makes the analysis and selection of ideas presented by different promoter candidates. The second phase, start‐up workshops, allows the development of skills related to business creation and business development through the frequency of training workshops on creativity and innovation management, strategic analysis, market analysis, analysis financial and elevator pitch. The third and final phase, pre‐incubation is the individualized guidance by a “Business Coach” to allow the definition and implementation of business ideas.

4.3 Analysis of TecMinho’s IdeaLab’s editions Since 2009, the TecMinho's IdeaLab concluded a total of eight editions, two editions each year (April‐July and November‐March). This article focuses on data from phase start‐up workshops with a number of participants or promoters by year ranged from 62 participants (2010) and 82 participants (year 2011). With a total of 291 participants in this initiative is spreading across the University, and has a laboratory in the School of Engineering, Campus Azurém. In editions of TecMinh's IdeaLab there is a significant majority of male participants (72.9% versus 27.1% of females). However, throughout the editions, the gender distribution has been some variations (see Figure 1). Editions 5th, 6th and 7th showed a significant increase of female participants, with a peak of 45% in the 7th Edition. However, on 8th Edition the female participation decreased to 19%. Male

Female

1st edition

79%

21%

2nd edition

77%

23%

3rd edition

81%

19%

4th edition

83%

17%

5th edition

64% 69%

6th edition 7th edition 8th edition

36% 31%

55%

45% 81%

19%

Figure 1: Participants’ gender In turn, the analysis of the training participants distinguishing the engineering background of non‐engineering shows that most participants have training in engineering (55.7% versus 40.9% non‐engineering). By analyzing the formation of non‐engineering, it was possible to identify a variety of training areas from the sciences (13.4%), social sciences and humanities (12%) or architecture (see Figure 2).

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Cristina Rodrigues and Filipa Vieira

Missing 3,4% Economy and Business 9,3%

Social and Human Sciences 12,0% No Engineering 40,9%

Engineering 55,7%

Sciencies 13,4%

Education 3,8% Arquitecture and Arts 2,4%

Figure 2: Participants’ scientific background The ages of the participants range from 19 to 55 years, with an average of 27.68 years. The analysis was done according to the edition indicators median, minimum and maximum (see Figure 3). In the different editions median age records a minimum of 25.0 years (Editions 2nd, 4th and 5th) and a maximum of 28.0 years (8th and 3rd Editions), which is a good indicator of youth promoters. Already at the level of the range of ages, the highest amplitude recorded was the 2nd Edition (35 years) and lowest in the 3rd Edition (15 years) which marks this edition as the "youngest" of TecMinho’s IdeaLab. Maximum

55,0

50,0 43,0

44,0

43,0

25,0

25,0

26,0

Median

Minimum

50,0 41,0

36,0 28,0

26,0

25,0

21,0

20,0

21,0

21,0

21,0

21,0

1st edition

2nd edition

3rd edition

4th edition

5th edition

6th edition

27,0

28,0

23,0 19,0

7th edition

8th edition

Figure 3: Participants’ age by edition In addition to the individual characteristics of each participant, the team analysis was also made. During the eight editions were accepted 126 ideas that corresponded to 126 teams. The number of elements’ team varies from a minimum of 1 member and a maximum of 5 members, with an average of 2.32 members per team. Each team was further classified into a new variable "dimension" with three different classes depending on the number of member:

One member (small team);

Two or three members (average team size);

Four or five members (large team).

The Figure 4 illustrates the results for edition. It is noted that the teams with 2 or 3 members are those that have greater percentage participation. The exceptions are the 3rd edition with the same percentage for teams with 1 member and teams with 2 or 3 members (42.9%), and the 4th edition in which teams with one member dominated (55.6%). The teams with 4 or 5 members are less significant but in the 6th edition they accounted for a maximum of 37.5% of the teams.

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Cristina Rodrigues and Filipa Vieira 1 element

68,8%

2 or 3 elements

4 or 5 elements

62,5%

60,0%

56,3% 50,0%

55,6%

46,7% 42,9% 42,9% 31,3%

37,5% 27,8%

33,3%

25,0% 20,0% 14,3%

20,0% 20,0%

16,7%

18,8% 18,8% 0,0%

0,0%

1st edition

31,3%

2nd edition

3rd edition

4th edition

5th edition

6th edition

7th edition

8th edition

Figure 4: Team’s elements Following the analysis, we evaluated for each team the number of 1) members with engineering background, 2) female members and 3) members aged less than or equal to 25 years. Subsequently teams were classified according to three new variables:

At least one member with engineering background (by coding the "yes" answers the 1‐yes, 0‐no otherwise),

At least one member of the feminine gender (by coding the "yes" answers the 1‐yes, 0‐no otherwise),

At least one member aged less than or equal to 25 years (by coding the "yes" answers the 1‐yes, 0‐no otherwise).

The Table 1 summarizes the results obtained. Considering the team members with engineering background it is found that 62.7% of the teams have at least one member with engineering background. In the 3rd and 8th edition only half of the teams had at least one member with engineering background. If considering the feminine elements, 42.1% of teams had at least one female member and the exceptions are the 5th and 7th editions, with a majority of teams with female participation (respectively 53% and 56%). Finally, it was found that 52.3% of the teams have at least one member aged less than or equal to 25 years and that the issue of greater inequality was the 3rd edition, with 79% of the teams with all members over the age of 25 years. Table 1: Team characterization

1st edition

Eng. Elements

Fem. Elements

%No 31%

%No 56%

%Yes 69%

%Yes 44%

<=25 years Elements %No 44%

%Yes 56%

2nd edition

27%

73%

60%

40%

33%

67%

3rd edition

50%

50%

57%

43%

79%

21%

4th edition

22%

78%

67%

33%

44%

56%

5th edition

33%

67%

47%

53%

40%

60%

6th edition

44%

56%

50%

50%

31%

69%

7th edition

44%

56%

44%

56%

44%

56%

8th edition

50%

50%

81%

19%

63%

38%

N_Total

47

79

73

53

59

67

% Total

37,3%

62,7%

57,9%

42,1%

46,8%

53,2%

The Table 2 summarizes the percentage of incidence in each team. In the analysis of engineering background there are 47 teams (37.3%) with zero elements and 61 teams with all elements with engineering background. In terms of females, although there are 73 teams (59.3%) with zero elements, there are 22 teams with all elements of feminine gender, a result very promising. The analysis of the elements aged less than or equal to 25 years reveals that there are 59 teams (48.2%) with zero elements. The remaining results, including the 33 teams with all elements aged less or equal to 25 years, confirm the participation of young promoters among teams.

538


Cristina Rodrigues and Filipa Vieira Table 2: Teams’ indicators Eng. Elements

Fem. Elements

Team percentages

N_teams

Team percentages

N_teams

<=25 years Elements Team percentages

N_teams

0,00%

47

0,00%

73

0,00%

59

20,00%

1

20,00%

2

20,00%

1

25,00%

1

25,00%

2

25,00%

2

33,33%

3

33,33%

5

33,33%

5

-

-

40,00%

1

40,00%

1

50,00%

11

50,00%

19

50,00%

15 1

-

-

60,00%

1

60,00%

66,67%

2

-

-

66,67%

7

-

-

75,00%

1

75,00%

1

-

-

-

-

80,00%

1

100,00%

61

100,00%

22

100,00%

33

total

126

total

126

total

126

The analysis also included the 126 ideas accepted in the program TecMinh's IdeaLab. When each idea was classified according to the desired output (services or product), is perceived a strong component of ideas in services (66.7% against 33.3% of ideas into products). The Figure 5 examines the evolution over time, which is perceived a major trend of services ideas, with the products representing a small part of the ideas presented. The 7th Edition is the only exception with 56% of the ideas focus on products but, the 8th Edition corrected and reversed this situation by giving priority to services (56%). Services 1st edition

Product 31%

69%

2nd edition

33%

67%

3rd edition

29%

71%

4th edition

22%

78%

5th edition

73%

27%

6th edition

75%

25%

7th edition 8th edition

56%

44%

44%

56%

Figure 5: Ideas outputs by edition During the 8 issues, we identified nine different idea themes, with a significant amount of the information technologies ideas (35.7%) followed by the environment and energy (15.1%), consultancy (13.5%) and health care (11.9%) (see Table 3). The ideas in information technologies were most significant in the 5th, 4th and 8th edition (respectively 53.3%, 50.0% and 43.8%). Interesting to note that:

the themes with constant presence in the editions are the IT's and the Environment and Energy (E_Energy),

the environment and energy registered the highest importance in the 6th and 2nd editions (25.0% and 20.0% respectively),

the consultancy had greater importance in 1st and 6th edition (31.3% and 25.0% respectively),

the themes with less presence in the editions are the food industry (three editions), education (three editions) and Hotel & Catering (two editions).

To evaluate the incidence of dropouts, we analyzed the number of team members that dropped along the workshop phase. This enabled subsequent creation of a new variable to characterization of the teams:

At least one member quit the program (by coding the "yes" answers the 1‐yes, 0‐no otherwise)

539


Cristina Rodrigues and Filipa Vieira Table 3: Ideas’ theme by edition IT'S

E_Energy Consultancy Health Care Engineering

Industry

Food Industry Education Hotel & Catering N_Total

N_Total

45

19

17

15

10

9

5

3

3

126

% Total

35,7%

15,1%

13,5%

11,9%

7,9%

7,1%

4,0%

2,4%

2,4%

100,0%

1st edition

31,3%

18,8%

31,3%

6,3%

6,3%

-

-

6,3%

-

16

2nd edition

33,3%

20,0%

20,0%

6,7%

6,7%

13,3%

-

-

-

15

3rd edition

28,6%

14,3%

14,3%

7,1%

14,3%

21,4%

-

-

-

14

4th edition

50,0%

5,6%

5,6%

-

11,1%

5,6%

5,6%

5,6%

11,1%

18

5th edition

53,3%

13,3%

6,7%

20,0%

6,7%

-

-

-

-

15

6th edition

25,0%

25,0%

25,0%

18,8%

-

-

-

-

6,3%

16

7th edition

18,8%

12,5%

6,3%

18,8%

12,5%

6,3%

18,8%

6,3%

-

16

8th edition

43,8%

12,5%

-

18,8%

6,3%

12,5%

6,3%

-

-

16

During the 8 editions there were 47 teams (37.3%) with at least one member that quit the program. The results are illustrated in Figure 6. The editions that resulted in more teams with members that quit were the 2nd and 6th editions (53% for both). The editions with fewer quit teams were the last, i.e. the 8th edition with 13% and the 7th edition with 19%. % No quit 1st edition 2nd edition

53%

47%

3rd edition

5th edition 6th edition

44%

56%

64%

4th edition

% Quit

36%

61%

39%

47%

53%

56%

7th edition 8th edition

44% 81% 88%

19% 13%

Figure 6: Quit teams by edition Tests of independence were performed between the incidence of "quit the program team" and the characterization variables: edition number, size of the team (small / medium / large), team members with engineering background (yes / no), team with female members (yes / no) and team with members aged less than or equal to 25 years (yes / no). The results suggest dependency relationships between the incidence of quit and:

The edition number (χ2 (7) = 10,463, p <0.10);

The team age (Fisher’s exact test, p <0.05).

5. Conclusions The TecMinho’s IdeaLab of University of Minho test the commercial potential of the ideas presented and evaluates the vocation and entrepreneurial skills of its participants over three phases. The results analyzed in this paper are related to the start‐up and workshops phase and highlight the importance of male gender participants on the program. Female participation is still relatively low (27.1%), but when analyzed by team it is verified that 42.1% of teams had at least one female member and that 22 teams are all with female members. The evolution recorded over time may indicate a progressive increase in female participation but, as the

540


Cristina Rodrigues and Filipa Vieira selection for participation in the program is based on the ideas presented, it could be interesting in the future to create an edition fully dedicated to female entrepreneurs. In terms of training, most participants have background in engineering (55.7%) but there is a great diversity in the non‐engineering areas. Interestingly, 62.7% of teams had at least one member with engineering background and that there are 61 teams with all members from engineering. The question is whether this is a consequence of the fact that TecMinho's IdeaLab is located in the school of engineering or whether there will be greater potential entrepreneur by people with engineering background compared to non‐engineering. This should be explore in the future. It was interesting to recognize the degree of youth participants since the mean participant’s age was 27.68 years, and ranged from 19 to 55 years. The analysis of members aged less than or equal to 25 years concluded that 52.3% of the teams have at least one member aged less than or equal to 25 years and the existence of 33 teams (26.2%) with all members of age less or equal to 25. The classification of the outputs of the ideas in service or product resulted in a high incidence of the ideas of services (66.7%). Analysis over time not evidence significant changes, although it is acknowledged that the last two editions have been more balanced. Once the output is strongly dependent on the theme idea, the ideas were classified by theme. Results indicated that the themes that are present constantly in editions of TecMinho's IdeaLab are information technologies (IT's) and the Environment and Energy (respectively 35.7% and 15.1% of the ideas accepted in the program). This result may not be surprising given the high participation of background in engineering. The incidence of dropouts of the program was analyzed according to the number of team members who quit. Of the 126 teams accepted into the program, there were 47 teams with at least one member who quit (37.3%) and were confirmed relationships of dependence between incidence of quit members with the number of edition and team members age. Although preliminary, the results obtained are important to characterize and understand the evolution of the program TecMinho's IdeaLab. As it is a relatively new program, we believe that the current study may contribute to a better performance of the program (including the suggestion of an edition dedicated to the participation of females proponents) and to identify potentially critical phases for participants. Following the investigation will comprehend a phase of study of the specific reasons for leaving the program in the workshop phase, with the realization of interviews and a specific survey.

Acknowledgements The authors would like to thank the collaboration of TecMinho's IdeaLab into the research project. The authors also wish to acknowledge the support of CGIT and Algoritmi R&D Centre, two research centres at the University of Minho, Portugal. This work is supported by FEDER Funds through the Operational Programme Competitiveness Factors – COMPETE, and National Funds through FCT ‐ Foundation for Science and Technology under the Projects FCOMP‐01‐0124‐FEDER‐022674 and Pest‐OE/EME/UI0252/2012.

References Askun, B. and Yildirim, N. (2011) “Insights on entrepreneurship education in public universities in Turkey: creating entrepreneurs or not?”, Procedia Social and Behavioral Sciences, Vol 24, pp 663–676. Carayannis, E. G., Evans, D. and Hanson, M. (2003) “A cross‐cultural learning strategy for entrepreneurship education: outline of key concepts and lessons learned from a comparative study of entrepreneurship students in France and the US”, Technovation, Vol 23, pp 757–771. Curteis, H. (1997) “Entrepreneurship in a growth culture”, Long Range Planning, Vol 30, No. 2, pp 267‐155. Drucker, P.F. (2006) Innovation and Entrepreneurship, Harper Business. GEM (2010). GEM Portugal 2010 Report. INE (Instituto Nacional de Estatística) (National Statistics Institute of Portugal) (2012) Destaque ‐ Estatísticas do Emprego, 4º Trimestre de 2011, Lisboa, Portugal (in Portuguese). Kirzner, I. M. (1997) “Entrepreneurial discovery and the competitive market process: An Austrian approach”, Journal of Economic Literature, Vol 35, pp 60‐85. LINI (Lisbon Internet and Networks) (2009) Empreendorismo e Inovação nas PME'S em Portugal: a Rede PME Inovação COTEC, Lisboa, Portugal (in Portuguese).

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Factors Influencing Innovation and Competitiveness – a Comparative Analysis of Selected Economies Anna Sacio – Szymańska Institute for Sustainable Technologies – National Research Institute (ITeE – PIB), Radom, Poland anna.sacio@itee.radom.pl Abstract: The growing interdependencies between modern countries significantly influence the international competitiveness of a national economy. The impact, however, can have both a positive and a negative character. The advantages of globalisation are expressed in an easier access to international markets, capital, labour, and knowledge. Its drawbacks, on the other hand, are closely related to the issues of economics, and they can be particularly noticed when crisis hits a particular country (or region) and then spreads to other countries that are economically linked with it. This amplifies the already harsh market conditions stemming from the need to cope with global competitiveness. Taking into consideration both the dramatic intensification of integration processes all over the world and the shifting balance of power in the global economy, the ability to shape a country’s innovation policy seems to be of key importance. It is crucial to direct national innovation policy in a way that enables the exploitation of all development opportunities stemming from current and future competitive advantages of the economy. The paper analyses some of the factors influencing the creation of innovation and economic competitiveness, including the following: The level and structure of expenditure on R&D; Key national R&D priorities, which are supported by large public R&D programmes analysed in comparison to high‐ tech industries and sectors of the highest expenditures on innovation; and, The level of total entrepreneurial activity. The impact of policy measures related to science and technology for innovation is shown through the analysis of the following data: The dynamics of GDP and GDP per capita in the 2001‐2011 period, The position in Global Innovation Index ranking in the 2007 – 2012 period, The position in Global Competitiveness Index ranking in the 2007 – 2012 period and The position in Knowledge Economy Index ranking in 2012. The analyses include the following countries: Switzerland, Sweden, United States, Germany, United Kingdom, France, China, India, Russia, Czech Republic, and Poland. Keywords: innovativeness, competitiveness, public support measures, R&D, smart specialisation, foresight, knowledge economy

1. Innovativeness studies – analysis of the state‐of‐the‐art The issues of the competitiveness and innovativeness of the economy are a frequent subject of analysis. The forerunner in this field of study was Smith (1776), who analysed factors stimulating economic innovativeness. His followers were neoclassical economists, including Schumpeter (1941), Solow (1956), and Swan (1956). Contemporary analyses of innovativeness and competitiveness are conducted at numerous national and international research centres. Table 1 delineates the classification of research on innovativeness (with literature references), in which the following criteria were selected: the aim of the analysis, its subject, object, territorial scope, and means of data collection. Table 1: Classification of innovation research Classification criteria Aim of the analysis

Subject of the analysis

Type of research Analysis of the level of innovativeness and recommendations Development of research methodology Innovativeness of national economies Innovativeness of regions Innovativeness of economic entities

Object of the analysis

Innovation creation factors

Authors (selection) Sala‐i‐Martin (2004), Chen, Dahlman (2005), Hollanders, Tarantola (2010), Dutta (2011) Frascati Manual (1962‐2002), Oslo Manual (1997 – 2005) Frascati Manual (1962‐2002), Dutta (2011), Hollanders, Tarantola (2010), Archibugi, Denni, Filippetti (2008), Chen, Dahlman (2005), Sala‐i‐Martin (2004) Cooke (2001), Asheim, Coenen (2006), OECD Reviews.. (2011), Hollanders, Tarantola, Loschky (2009) Oslo Manual (1997 – 2005), Hagedoorn, Cloodt (2003), Jaruzelski et al. (2005‐2012), Baczko (2005‐2012), Chen, Sawhney (2012) M. Holland, W. Spraragen (1933), Bernal (1939), National Patterns of R&D Resources (1956 ‐ 2011), Frascati Manual (1962‐2002), McGraw‐Hill (1971), Godin (2003), Jaruzelski et al. (2005‐2012)

543


Anna Sacio – Szymańska Classification criteria

Territorial scope of the analysis

Type of research Effects of innovative activity Factors of innovative activity creation and its effects National analyses International analyses

Means of data collection

Primary data Secondary data Primary and secondary data

Authors (selection) Patent Manual (1994‐2009), Okubo (1997) Oslo Manual (1997–2005), Sala‐i‐Martin (2004), Chen, Dahlman (2005), Baczko (2005‐2012), Dutta (2011) Baczko (2005‐2012), ERAWATCH Annual Country Reports (2006‐2012) Hollanders, Tarantola (2010), Archibugi, Denni, Filippetti (2008), Chen, Dahlman (2005), Dutta (2005), Sala‐i‐Martin (2004) Oslo Manual (1997 – 2005), Baczko (2005‐2012) Hollanders, Tarantola (2010), Dutta (2005), Chen, Dahlman (2005), Jaruzelski et al. (2005‐2012) Sala‐i‐Martin (2004)

Source : Author The classification of innovation research enabled the identification of the main characteristics of analyses presented in the article, which include the following:

The aim of the study is to analyse the state of innovativeness and make recommendations,

The analyses are conducted on the macroeconomic level,

Selected factors of innovativeness creation are studied,

The analysis concerns the economies of countries selected with the use of criteria proposed in the original research methodology, and

Only secondary data were used in the analysis.

2. Selection of countries to be analysed It was assumed that OECD countries or countries cooperating with them within the Enhanced Engagement Programme (i.e. Brazil, India, China, South Africa and Russia) will be analysed, which helped to select an initial group of 39 economies. Due to a similar level of development of some of the selected countries, it was decided that the research sample would be narrowed down with the use of the following three‐stage methodology: 1) The analysis of the level of GDP and GDP per capita in the 2000‐2010 period, 2) The analysis of the dynamics of GDP and GDP per capita in the 2001‐2010 period, 3) The analysis of the position of selected countries in international innovation and competitiveness rankings in the 2007 – 2012 period including:

The Global Competitiveness Index‐GCI (Sala‐i‐Martin, Artadi 2004),

The Global Innovation Index‐GII (Dutta 2012).

As a result of the analyses, three groups of countries were singled out:

Countries with the highest level of GDP and GDP per capita,

Counties with the greatest dynamics of GDP and GDP per capita, and

Countries with the highest level of innovativeness and competitiveness.

Moreover, individual countries meeting all the above listed criteria were selected. These included the following: Sweden, Switzerland and the USA, Germany, the UK and France, China, India, Russia, the Czech Republic, and Poland.

3. Method of analyses The analysis of the dynamics of GDP and GDP per capita covering the 2007‐2010 period and the position of individual countries in the global innovation and competitiveness rankings (GCI, GII) covering the 2007‐2012 period called for an in‐depth analysis of the state and the condition of the countries’ innovation performance (see Tables. 2 and 3).

544


Anna Sacio – Szymańska Table 2: Dynamics of GDP and GDP per capita in the analysed countries in the 2001‐2010 period Country

Country

GDP per capita dynamics

Switzerland Sweden USA Germany UK France China India Russia Czech Rep. Poland

(2001‐2010) 103.0 103.7 103.0 103.2 103.1 102.8 112.2 108.2 107.7 105.3 106.3

GDP dynamics

Switzerland Sweden USA Germany UK France China India Russia Czech Rep. Poland

(2001‐2010) 103.8 104.2 104.0 103.2 103.7 103.4 112.9 109.9 107.2 105.5 106.2

Source: Author based on International Monetary Fund, World Economic Outlook Database, http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx The greatest dynamics of GDP and GDP per capita are observed for China, India and Russia (respectively a 12%, 9% and 7% growth in the analysed period). The dynamics of GDP and GDP per capita in the case of Poland and the Czech Republic is similar and amounts to 6% and 5%, whereas in the remaining countries to ca. 3%. Concurrently, countries with the highest dynamics of GDP and GDP per capita are characterised by the lowest level of GDP per capita, which in India comes to 3000 USD, China – 7000 USD, Russia – 15000 USD, Poland – 20000 USD, and the Czech Republic – 24000 USD; whereas, in the analysed Western European countries these figures vary between 34000 USD (France) and 41000 USD (Switzerland) (IMF World Economic Outlook Database). Table 3: Position of the analysed countries in innovativeness and competitiveness rankings in the 2010‐2012 period Analysed index

Global Competitiveness Index (GCI)

GCI trend

Global Innovativeness Index (GII)

GII trend

Analysed period

SUI

SWE

USA UK

GER

FRA

CZ

CHIN

RUS

2007‐2008

2

4

1

2008‐2009

2

4

1

2009‐2010

1

4

2

2010‐2011

1

2

2011‐2012

1

2012‐2013

1

2007‐2012 2007

IND POL

9

5

18

33

34

58

48

51

12

7

16

33

30

51

50

53

13

7

16

31

29

63

49

46

4

12

5

15

36

27

63

51

39

3

5

10

6

18

38

26

66

56

41

4

7

8

6

21

39

29

67

59

41

6

12

1

3

2

5

32

29

54

23

56

2008‐2009

7

3

1

4

2

19

33

37

68

41

56

2009‐2010

4

2

11

14

16

22

27

43

64

56

47

2011

1

2

7

10

12

22

27

29

56

62

43

2012 2007‐2012

1 ↑

2 ↑

10 5 ↓ ↓↑

15 ↓

24 ↓

27 ↑

34 ↓↑

51 ↑

64 ↓

44 ↑

Source: Author based on http://www.weforum.org/issues/global‐competitiveness and http://www.globalinnovationindex.org/gii The indisputable leaders in the rankings referred to in this article are Switzerland (first in both indices for 2012) and Sweden with 2nd (GII) and 4th (GCI) positions. In the analysed period, despite the negative influence of the global crisis, these countries either improved or maintained their position. Poland, the Czech Republic, and China also displayed growth tendencies in the area of economic competitiveness and innovativeness. More prone to the negative trends in a global economy were the USA, Germany, the UK, and France, which (apart from the UK) are ranked lower on both innovativeness and competitiveness. Similar downward tendencies are

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Anna Sacio – Szymańska displayed by India and Russia, which despite the high dynamics of their economic development, are ranked among the 5th and 6th ten in the 2011‐2012 period. It needs to be noted that the greater dynamics of changes in the GII index mainly results from methodological differences in both indices. Global Innovation Index was developed in 2007 by INSEAD economists (Fr. Institut européen d'administration des affaires). The factors included in GII are classified into two basic groups of indicators: innovation input and innovation output. Within the first of them the following categories were further distinguished: institutions, human capital and infrastructure, market sophistication and business sophistication. The innovation output sub‐Index, on the other hand, includes scientific outputs and creative outputs. The GII methodology distinguishes between 60 innovation measures, which are used for the assessment of the innovation performance of 125 countries (Dutta 2012). The methodology of economic competitiveness assessment by the Global Economic Forum has been developed since 1979. The approach concerns a wide scope of factors (117 altogether) that influence economic competitiveness and productiveness. The factors are grouped into 12 pillars of competitiveness including the following: (1) Institutions, (2) Infrastructures, (3) Macroeconomic environment, (4) Health and primary education, (5) Higher education and training, (6) Goods market efficiency, (7) Labour market efficiency, (8) Financial market development, (9) Technological readiness, (10) Market size, (11) Business sophistication, (12) Innovation. Analysis of competitiveness with the use of GCI index are conducted with reference to 144 countries (Sala‐i‐Martin, Artadi 2004).

When analysing such complex indicators as GII or GCI one must be aware that the characteristics of innovation systems in developing and in catching‐up economies (such as the analysed: China, India, Poland, the Czech Republic or Russia) differ significantly from the ones that gave rise to the current statistical standard (for example: the United Kingdom, the United States, Germany). Therefore, complex indicators should be cross‐ nationally comparable, and at the same time they should reflect the characteristics of the above mentioned groups of countries (Measuring R&D...2010). These criteria are met by the WEF’s Global Competitiveness Index, the method for calculation of which (contrary to the INSEAD’s Global Innovation Index) takes into account the differences in the level of the economic development between countries. The GCI separates countries into three specific stages, i.e. factor‐driven, efficiency‐driven, and innovation‐driven (Sala‐i‐Martin 2012). The division allows to differentiate factors that mostly contribute to the competitiveness of the analysed economies (tab. 4). Table 4: The factors of highest impact on a country’s competitiveness

Source: Author based on http://www.weforum.org/issues/global‐competitiveness The two countries, i.e. Poland and Russia, are in transition from the efficiency‐driven to the innovation‐driven stage, which means that current economic conditions still allow companies to exploit economies of scale, but there must be an increase in knowledge‐intensive activities resulting in the greater share of high value added industries in order to secure a future competitive position of these countries. As shown in the table 4, the ability to create, share and use knowledge is required in order to secure a country’s innovative position.

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Anna Sacio – Szymańska The Knowledge Assessment Methodology – KAM by the World Bank Institute (Chen, Dahlman 2005) is the metric, which is designed to measure a country’s preparedness to compete in the knowledge economy. An aggregate KEI index (based on a an average of four sub‐indexes) and the value of the four sub‐indexes by country is shown in table 5. Table 5: An aggregate KEI index and its sub‐indexes calculated for the analyzed economies in 2012 Country

Knowledge Economy Index (KEI)

Economic and institutional regime

Innovation system

Education system

ICT

Sweden

9.4

9.6

9.7

8.9

9.5

Germany

8.9

9.1

9.1

8.2

9.1

Switzerland

8.9

9.5

9.9

6.9

9.2

United States

8.8

8.4

9.5

8.7

8.5

United Kingdom

8.8

9.2

9.1

7.3

9.5

France

8.2

7.8

8.7

8.3

8.2

Czech Republic

8.1

8.5

7.9

8.2

7.9

Poland

7.4

8.1

7.2

7.6

6.7

Russia

5.8

2.2

6.9

6.8

7.2

China

4.4

3.8

6.0

4.0

3.8

India

3.1

3.6

4.5

2.3

2.0

Source: http://www.worldbank.org/kam In KAM 2012 the countries were ranked as follows: Sweden (1), Germany (8), Switzerland (10), the United States (12), the United Kingdom (14), France (24), the Czech Republic (26), Poland (38), Russia (55), China (84), India (110). The data, which resemble the ability to generate, diffuse and apply knowledge for innovation surge and economic development, are comparable in the majority of the analysed countries, except for China, Russia, and India. The main weaknesses of these countries relate to their educational systems and the economic regime. Interestingly, the education system of Switzerland might also call for improvement as its score does not differ much from the Russian one. Worth underlying is the fact that KEI reveals rather weak position of the Chinese economy compared to Poland and Russia, which were outperformed by China in GII and GCI rankings. In the light of the above stated, the factors which are associated with knowledge creation, diffusion and use need to be considered while analysing the achievements of selected countries in the area of innovativeness. 1 The following factors were analysed:

The level and the structure of expenditure on R&D;

The degree of interdependence between key national R&D priorities, industry sectors of highest expenditures on innovation, and high‐tech sectors; and,

The level of total entrepreneurial activity.

4. Results of analyses One of the most important and frequently quoted in literature innovation creation measures (Godin 2003) and (OECD Science…2011) is the level and the structure of R&D expenditure (Tab. 6) The highest R&D expenditure can be observed in Sweden (3.4% of GDP), Switzerland (3% of GDP), Germany and the USA (both 2.8% of GDP). Slightly lower spending on R&D is in France (ca. 2.3% of GDP) and the UK (ca. 1.8% of GDP). Russia, Poland and India are characterised by the lowest R&D expenditure, which is below 1% of GDP; whereas, China and the Czech Republic invest ca. 1.5% of GDP in their R&D activity. Along with the low 1

These factors were selected from more than a dozen measures covered by the analyses carried out by the author in the framework of the Innovative Systems of Technical Support for Sustainable Development of Economy Strategic Research Programme.

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Anna Sacio – Szymańska level of R&D expenditure, the structure of R&D spending is also unfavourable, which in the case of Poland (as well as India and Russia) significantly differs both from the structure characterising developed countries (e.g. Switzerland, Sweden, the USA, Germany, France and the UK) and also from the structure of R&D expenditure in the Czech Republic (which displays similar to Poland’s level of the economic development) and in China. In a vast majority of these countries, the private sector’s expenditure on R&D constitutes approximately 60‐70% of the total R&D spending, whereas in Poland (Russia and India alike), the trend is reverse. Table 6: Level and structure of R&D expenditure in the analysed countries in 2010 Analysed countries

Total R&D expenditure as % of GDP

Switzerland Sweden USA UK Germany France Czech Rep. China Russia India Poland

3.00 3.42 2.77 1.77 2.82 2.26 1.56 1.44 1.03 0.79 0.74

Private sector expenditure on R&D as % of GDP 2.21 2.35 1.86 1.08 1.90 1.38 0.97 1.04 0.30 0.23 0.20

Public sector expenditure on R&D as % of GDP 0.80 1.07 0.91 0.69 0.92 0.88 0.59 0.40 0.73 0.56 0.54

Source: http://erawatch.jrc.ec.europa.eu/erawatch/opencms/information/country_pages/ Due to the fact, that the growth of the level of innovativeness is not only dependent on the increased R&D expenditure (Jaruzelski, Dehoff 2010), the analysis also included the characteristics of key national R&D priorities in the countries selected for analysis. It should be stressed that the concept of the support of selected R&D priorities and areas (Mazurkiewicz, Poteralska, Sacio‐Szymańska 2011) with public funds is highly popular, particularly in Europe, where the policy of smart specialisation has recently been introduced (Foray, David, Hall 2011). The popularity of the smart specialisation policy has been boosted by the recent global crisis, which revealed a large asymmetry in the development of the EU economies and has caused a number of chronic problems. Good conditions facilitating the inclusion of intelligent specialisation into the Europe 2020 strategy ensured the advancement of the majority of the EU countries in the execution of foresight projects. This poses a question whether research directions indicated by foresight projects and included in the priority public support within strategic research programmes are actually connected with the branches of industry which practically apply latest technologies and actively participate in the creation of innovation in the analysed countries (Tab. 7). The analysis of data presented in Table 5 enables the conclusion that only companies operating in the area of ICT, healthcare and transportation (particularly automotive) widely apply advanced technologies and therefore contribute to the dynamic development of these sectors and, as a result, increase the level of the innovativeness of the national economy. The analysis of one of the priority areas is particularly interesting, i.e. the area of technologies of industrial production. Although the development of this area is essential in the case of only five of the analysed countries, it is included in the high‐tech sector and significantly contributes to innovation creation in these countries in a majority of economies. This mainly stems from the role of electronic technologies and precise and mechanical engineering technologies, which have an essential input in the dynamic development of the industrial production sector and facilitate the creation of innovations. In most of the analysed countries, these technologies are not incorporated into complex public support programmes, and their development is mainly triggered by intensified private investment. The influence of achievements in the remaining priority areas (i.e. nano‐ and biotechnologies, environmental protection, space, materials, defence, services) on the creation of market innovation in a majority of analysed countries is limited. On the one hand, this stems from the specificity of these areas (Tab. 8), and on the other

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Anna Sacio – Szymańska hand, it can be the effect of the application of a improper strategy for the determination of priority research directions. Table 7: The degree of interdependence between key national R&D priorities, high‐tech sectors and industry sectors of highest expenditures on innovation by country Country

SUI

SWE

USA

UK

High Inn High High Inno Inno High R&D priorities Tec o Tec Tech Inv Inv Tech h Inv h Nanosciences &        nanotechnolo gies 

Environment

Energy

Health Biotechnologi es

Aerospace

Transport

Materials

Security

g

CZ

CHIN

RUS

IND

POL

 

innovation Inn High Inn High Inn High Inn High High Inn High Inn High Inn Inno o Tec o Tec o Tec o Tec Tec o Tec o Tec o Inv Inv h Inv h Inv h Inv h h Inv h Inv h Inv

Manufacturin

Services

FRA

Correlation of national R&D priorities, high‐tech industries and sectors of highest expenditure on

ICT

GER

Legend to table 7 + ‐ +

National R&D priority, which is either on the list of a country’s high‐tech industries, or it is a sector of the highest expenditure on innovation National R&D priority, but it is neither on the list of a country’s high‐tech industries, nor it is a sector of the highest expenditure on innovation Not a national R&D priority Not a national R&D priority, but it is on the list of a country’s high‐tech industries and (or) it is a sector of the highest expenditure on innovation

Source: Author based on: INNO‐Policy... 2009; ERAWATCH Annual... 2010, Innovation Union... 2011 For R&D priorities to be triggers for innovation and economic growth, it is highly important to design the process of their determination according to the context (economic, environmental, cultural, social etc.) in order to exploit the best potential of a country, region, or organisation. Foray, David, Hall (2011) provide an important voice on the means and meaning of R&D priority setting as follows: Discovering the right domains is by no means trivial and technology foresight exercises ordered by administrations tend to produce the same ranking of priorities, without any consideration of specific conditions of the “client” for whom the exercise is carried out. Too many … have selected the same technology mix – a little bit of ICT, a little bit of nano and a little bit of bio – showing a lack of imagination, creativity and strategic vision. … The authors claim that an appropriate process of priority setting should not necessarily identify the hottest domains but rather the domains where new R&D and innovation projects will complement the country’s other

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Anna Sacio – Szymańska productive assets to create a future comparative advantage. And they add that “The main issue to be addressed by policy is not “what to do” but “how to help companies to discover what to do and how to implement the policy according to what has been discovered (stimulating entrepreneurship).” (Foray, David, Hall 2011). Table 8: Some factors that influence the limited contribution of selected research areas to the creation of market innovation

Source: Author Taking the above stated into consideration, it seems appropriate to describe the final factor that influences competitiveness and innovativeness of nations, namely, the level of entrepreneurship, which has been researched in the framework of the Global Entrepreneurship Monitor (GEM) project (Bosma, Wennekers, Amoros 2011). When comparing the level of entrepreneurship across nations, GEM, similarly to GCI, classifies countries into three groups by phases of economic development (Xavier et al 2012). In each of the three phases of economic development, the role of the country in supporting entrepreneurship and economic growth is different. In the case of factor‐oriented economies (India), the most significant is to develop institutions, infrastructure, macroeconomic stability, health, and primary education. In efficiency‐driven economies (China, Russia, Poland), the focus of governments should be on getting labour and capital markets working more efficiently, attracting foreign direct investments, and educating the workforce to successfully adopt technologies. In innovation‐driven economies (USA, Switzerland, Sweden, the United Kingdom, Germany, France, the Czech Republic), the key role of the country is to provide and commercialise knowledge (Zbierowski et al 2012). The paper analyses Total early‐stage Entrepreneurial Activity (TEA), which presents the percentage of working age population involved in establishing business activities or running a new enterprise (Fig. 1.). There are significant differences between countries worldwide in the level of early‐stage entrepreneurship. The lowest level of early‐stage entrepreneurship among countries analysed in the paper can be found in Russia (the second to last in TEA worldwide ranking). As few as 4.6% of people aged 18‐64 are involved in the establishment of business activity or the operation of young enterprises. The highest level of entrepreneurship was recorded in China (the second in TEA worldwide ranking), where 24% of the working age population establish or operate early‐stage businesses. The unweighted mean for all countries is 11.39%, and the median is 9%. The average for the factor‐driven economies is 16.14%. The average for the efficiency‐driven economies is 14.09%, and the average for the innovation‐driven countries is 6.92%. This reveals a particular correlation in the association between GDP per capita and the level and nature of entrepreneurial activity in an economy. In countries with low GDP per capita, TEA rates tend to be high. As per capita income increases, larger established firms play an increasingly important role in the economy. This provides an option for stable employment for a growing number of people, serving as a viable alternative to starting a business (Xavier et al 2012). Research on the extent to which entrepreneurship is a determinant of economic growth was done by van Stel, Carree, Thurik (2005) and others. Other researchers (Anokhin, Wincent 2012) analysed the relations between

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Anna Sacio – Szymańska the level of entrepreneurship and a country’s innovation position. Since the role of entrepreneurship for economic and innovation growth is considered positive, the extent to which it will boost innovation highly depends on the presence of the adequate framework conditions (e.g. high investment in R&D and education), which will make it possible for entrepreneurs to exploit technological advances created by research.

Source: own figure based on Bosma, Wennekers, Amoros 2011. Figure 1: TEA index in 2011 by country (%) Note: India was not covered in 2011 GEM research (the most recent data is for 2001).

5. Summary and recommendations The undertaken analyses made it possible to characterise selected economies in terms of their innovative and competitive achievements. In particular, the analyses revealed large disparities between highly innovative and competitive economies (e.g. Switzerland, Sweden, United States) and the still developing (in terms of innovation standing) countries (e.g. China, Russia, India, Czech Republic, Poland). Even though the aforementioned group outperforms the leaders of world rankings in terms of the dynamics of economic growth, there are areas that remain a challenge for policy makers and other actors involved in managing innovation processes in these countries. This refers to the following examples:

Allocating significantly more funds in the R&D sector (Russia, India, Poland, Czech Republic),

Increasing the contribution of the private sector in the operation and funding of research and innovation activities (Russia, India, Poland),

Strengthening internationalisation of business (Russia, India, Poland) and science (China, Russia, India, Poland, Czech Republic),

Strengthening economic and social freedom (China, Russia, India),

Strengthening educational system (China, India) and

Reforming the legal system and counteracting bureaucracy and corruption (China, Russia, India).

Taking the above into consideration, it seems appropriate to point out key challenges that need to be addressed while building (or sustaining) innovation potential of the economy. These are as follows: Challenges with regard to the level and the source of expenditure on R&D:

Ensuring the relatively high level expenditure on R&D, and

Ensuring the adequate structure of R&D financing where business contribution prevails over public financial engagement.

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Anna Sacio – Szymańska Challenges with regard to the degree of interdependence between key national R&D priorities, industry sectors of highest expenditures on innovation, and high‐tech sectors:

Directing public funds to R&D priorities, which best exploit the capabilities of a country or a region (smart specialisation);

Finding a balance between the need to determine key national (regional) R&D priorities and the need to encourage the bottom‐up approach in formulating the scope of innovation research projects;

Designing foresight projects in line with the strengths and weaknesses of beneficiaries;

Setting mechanisms and measures that would facilitate the Implementation of the results of foresight projects in the economy; and,

Invigorating the cooperation of science and industry in R&D.

Challenges with regard to the level of total entrepreneurial activity:

Creating conditions conductive to starting and operating a business,

Developing a strong entrepreneurial workforce,

Fostering an environment in which high‐tech companies can access the kinds of capital (human capital included) they need, and

Securing the effectiveness of economic, financial, or legal systems at the national level.

Challenges with regard to general innovation policy

Aligning the long‐term policies with the changing economic conditions (introducing changes to existing public measures supporting innovation and entrepreneurship); and,

Ensuring correlation between regional and national innovation, industrial, entrepreneurial and educational policies.

6. Conclusions and further research It should be underlined that it is very difficult to analyse the individual contribution of each of the analysed factors to innovation and competitiveness, as they are closely interlinked and dependent upon each other. For example (tab. 9), from the analyses presented in the paper, it is understood that in order maintain or improve its competitive position, a country needs to invest in R&D (factor 1a), but as the bulk of innovation originates from business, then the share of private sector’s expenditure on R&D should outperform the public sector contribution (factor 1b), this is where the increasing number of high‐growth entrepreneurial ventures becomes crucial (factor 3). Furthermore, as shown in the recent economic crisis that have left many countries with very few opportunities for economic recovery, and taking into account the capacity asymmetries between countries, the strategy of smart specialisation has become crucial (Foray et al 2011). The strategy implies that a country or a region should specialise in R&D and innovation related to those sectors, which complement the country’s other productive assets to create future comparative advantage (factor 2). Table 9: Selected links between the factors considered and the innovation and competitiveness

Source: Author

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Anna Sacio – Szymańska Equally, if not more challenging, is the effort to illustrate the link between the analysed factors and the innovation and competitiveness of each analysed country, as their impact varies across countries in function of their current stages of economic development. Therefore, in the light of the above, instead of direct answers, research questions could be formulated to promote further scientific discussion and research. And these include the following:

Is a country of low level of expenditure on R&D still able to innovate?

Does innovation appear in countries, where business expenditure on R&D is limited?

Is the innovation‐oriented smart specialisation policy able to bridge the “top‐down” (governmental decisions) versus “bottom‐up” (entrepreneurial decisions) dichotomy?

Acknowledgements Scientific work executed within the Strategic Programme “Innovative Systems of Technical Support for Sustainable Development of Economy, 2010‐2014” within “Innovative Economy Operational Programme”.

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INNO‐Policy TrendChart Mini Country Reports, (2011), [online], http://www.proinno‐europe.eu/inno‐policy‐ trendchart/repository/country‐specific‐trends

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Anna Sacio – Szymańska Innovation Union Competitiveness report, (2011). European Commission, Directorate General for Research and Innovation, Luxembourg: Publications Office of the European Union. International Monetary Fund, World Economic Outlook Database, http://www.imf.org/external/pubs/ft/weo/2013/01/weodata/index.aspx Jaruzelski B. Dehoff K., (2010), The Global Innovation 1000, How the Top Innovators Keep Winning, [online], strategy+business, ISSUE 61, http://www.booz.com/media/file/sb61_10408‐R.pdf Jaruzelski B., Loehr J., Holman R., (2012), The Global Innovation 1000, Making ideas work, [online], strategy+business, issue 69, http://www.strategy‐business.com/media/file/00140‐The‐Global‐Innovation‐1000‐Making‐Ideas‐Work.pdf Mazurkiewicz A., Poteralska B., Sacio‐Szymańska A. (2011), Foresight methods in supporting generation of strategic research directions, pp. 298‐315 in: Mazurkiewicz A. (edit.), Innovative Technological Solutions for Sustainable Development, ITeE‐ PIB Press, Radom‐Shanghai, ISBN 978‐83‐7204‐955‐1. McGraw‐Hill Survey (1971), Business Plans for Research and Development Expenditures, McGraw‐Hill Publications Company. Measuring R&D: challenges faced by developing countries, UNESCO Institute for Statistics, Montreal 2010. National Patterns of R&D Resources, (1956 – 2011), National Science Foundation, Washington. OECD Science, Technology and Industry Scoreboard 2011, OECD Publishing. OECD (2002),Frascati Manual 2002: Proposed Standard Practice for Surveys on Research and Experimental Development, The Measurement of Scientific and Technological Activities, OECD Publishing. OECD/Statistical Office of the European Communities, Luxembourg (2005),Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd Edition, The Measurement of Scientific and Technological Activities, OECD Publishing. OECD (1994‐2009), Patent Statistics Manual, OECD. OECD (2011) Reviews of Regional Innovation: Regions and Innovation Policy, OECD. Okubo Y., (1997), Bibliometric Idicators and Analysys of research Systems, Methods and Examples, STI Working Paper, OECD. Sala‐i‐Martin X., Artadi E.V., (2004), The Global Competitiveness Index, in: The Global Competitiveness Report 2004–2005, Palgrave Macmillan, Hampshire. Schumpeter, J. (1950), Capitalism, Socialism and Democracy. New York: Harper & Row; 3rd Edition. Smith A., (1776), An Inquiry into the Nature and Causes of the Wealth of Nations, W. Strahan and T. Cadell, London. Solow R., (1956), A Contribution to the Theory of Economic Growth, Quarterly Journal of Economics (70), pp. 65–94. Swan, T. W. (1956)., Economic Growth and Capital Accumulation, Economic Record 32 (2): 334–61. Van Stel A., Carree M., Thurik R., (2005), The effect of entrepreneurial activity on national economic growth, Small Business Economics 24 (3), 311‐321. Xavier S. R., Kelley D., Kew J., Herrington M., Vorderwülbecke A, (2012), Global Entrepreneurship Monitor, 2012, Global Report. Available at http://www.gemconsortium.org/docs/download/2645 Zbierowski P., Węcławska D., Tarnawa A., Zadura‐Lichota P., Bratnicki M., (2012), GEM Poland, 2012. Polish Agency of Entrepreneurship Development and University of Katowice, ITeE‐PIB Press.

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Experiential Entrepreneurship Education in Canada – new Venture Creation While Earning a Masters Degree Tarek Sadek1 and Rafik Loutfy2 Xerox Centre for Engineering Entrepreneurship & Innovation, McMaster University, Hamilton, Canada tarekss@mcmaster.ca loutfyr@mcmaster.ca Abstract: In the last 20 years, there has been a shift from studying entrepreneurship as a phenomenon to learning the skills needed to become an entrepreneur. More recently, there has been a shift towards teaching the skills in the context of starting an actual real business. This paper describes the results of an experiment that implemented an industry‐proven technology‐based new‐venture‐creation methodology into the academic environment in a Canadian university. It also describes the pedagogical design of the masters program that leveraged this methodology. First of its kind in Canada, The Xerox Centre for Engineering Entrepreneurship and Innovation (XCEEi) at McMaster University offers a masters program to students who want to pursue entrepreneurship as a career option. Students practice starting up their own businesses while they pursue their Masters degree. XCEEi students participate in commercializing technologies in real life situations. McMaster masters program is compared with the two‐year masters program offered by the Entrepreneurship school at Chalmers University of Technology, which is considered one of the most successful new‐venture‐creation Masters programs in the Sweden. It is believed that top four factors, influencing the success of such programs, are: Access to seed funding, involvement of seasoned entrepreneurs in program delivery, integration with an existing university commercialization ecosystem, and finally financial sustainability of the programs. Based on interviews and surveys, the paper concludes that the first two factors are the most influential in determining the quality of experiential education and the students’ learning experience. However, the commercial success of the students’ ventures depends on the quality of the ideas and students, access to follow‐on investment, and finally integration with the university commercialization ecosystem. Venture creation masters programs could be key tools in realizing economic value from universities research. Students should be perceived as crucial filters of ideas and human feeders for the different governmental and regional innovation centers. Keywords: new venture creation, experiential learning, entrepreneurship education, commercialization of research

1. Introduction The Xerox Centre for Engineering Entrepreneurship and Innovation (XCEEi) was founded in 2005, to respond to the increasing demand of students who want to pursue entrepreneurship as a career option. Students, participating in XCEEi, start up their businesses while they are pursuing their Masters degree. In the Master's of Engineering Entrepreneurship & Innovation (MEEI) program, students participate in commercializing technologies in real life situations. One of the most successful examples of entrepreneurship experiential learning is the masters program, offered by the Entrepreneurship School (E‐School), in Chalmers (Chalmers University of Technology is referred to as Chalmers in this paper). The success of the program in spinning out start‐ups is a clear manifestation of the potential of involving students in commercializing university research (E. Berggren, 2011; S. Olllila, 2011; M. Jacob et al, 2003). The core of the masters program is to give the students the mission of creating university spin‐offs using technologies developed at Chalmers laboratories (More recently inventions from outside the university have been included). This paper presents a case study and a comparative analysis of MEEI program. We begin with a review of the literature about the status and trends of entrepreneurship education in the world. We then discuss the design, operation and results of the MEEI program and compare it with the E‐School master program; both programs are based on the same experiential model, which is the integration of actual venture creation into the academic requirements. Finally, we discuss the key differences between offering entrepreneurial education programs within the Canadian and the Swedish education systems.

2. Literature review In the last 20 years, there has been a shift from studying entrepreneurship as a phenomenon to learning the skills needed to become an entrepreneur. It was found that graduates who had acquired an entrepreneurship

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Tarek Sadek and Rafik Loutfy education are more likely to start new businesses and go through the entrepreneurial processes repeatedly in their careers (Rasmussen & Soorheim, 2006). In Canada, a research study showed a significantly higher venturing rate among engineering students who took ONE course in entrepreneurship (48%) compared to students who did not take any (26%) (Menzis & Paradi, 2003). More interesting is the finding that students who took one course and did not start a business were significantly more likely to become CEOs of companies. More recently, there has been a significant shift towards teaching the skills in the context of starting an actual real business, i.e. experiential learning. Laukkanen (2000) called this model for teaching entrepreneurship the “Business Generation Model”. Its aim is to foster the necessary conditions for starting new ventures by students. This trend ranges from involving the students in working on real business cases, to involving the students in real start‐ups, and letting the students start their own companies (Fayolle & Gailly, 2012; Erikson & Gjellan, 2003). The way to measure the success of entrepreneurial education has also been subject of debate; should success be measured by the improvement in the entrepreneurial skills and capabilities of the students or by the performance of their new ventures, or both? In 2010, Industry Canada released a survey‐based report about the ways in which entrepreneurship education 1 is delivered within Canadian Higher Education Institutions . The report identifies 12 barriers, recognized by the universities, for entrepreneurship education. The top 4 barriers were:

Education depends on the effort of a single champion

No funding to support the activities needed to teach the required entrepreneurial skills.

No strategic integration with the university system.

Limited entrepreneurial experience among academic staff.

The focus of this paper is to compare the MEEI program and the E‐School Masters program in terms of these barriers.

3. Data collection methodology There have been many calls for more qualitative research in the field of entrepreneurship (Gartner and Birley 2002; Hindle 2004). We believe that such qualitative research may add new perspectives to the field of entrepreneurship education and may contribute to the advancement of the field. The data collected for this paper derive from qualitative research aimed at developing concepts/models that enhance our understanding of the entrepreneurial learning phenomenon, with emphasis on the experiences and views of involved stakeholders. A survey of 50 students’ perceptions of the MEEI program was carried out, by an independent third party, and is used in our analysis. In addition, face‐to‐face interviews were held with the different stakeholders of the Masters program including administrative leaders, faculty members, director, and McMaster university technology transfer officers. The interviews were semi‐structured. Each interview lasted between 60‐90 minutes. Information, about E‐School masters program, was collected from available online sources and the numerous papers that discussed the program (Jacob et al, 2003; Dahlstrand et al, 2003; Berggren, 2011; Olllila, 2011; Wallmark 1997).

4. McMaster Masters Program MEEI The MEEI program consists of three critical components:

The Engineering Enterprise Project: From their first day in the program, the students start working on their new venture ‘The Enterprise Project’. The students select their projects either from the opportunities scouted and mined by the XCEEi team or based on their own ideas.

Entrepreneurial & Innovation Skills Development Modules: Five compulsory enterprise modules focus on providing the student with the basic skills needed to select an idea with good potential, manage the innovation process, then create and manage the business outcome. The skills cover all the business life cycle from start to growth and sustainability. The modules develop an understanding of both the innovation and the entrepreneurial processes through lectures, workshops and hands‐on work.

1

http://www.ic.gc.ca/eic/site/061.nsf/eng/h_rd02541.html. Accessed 3rd July, 2013

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Tarek Sadek and Rafik Loutfy

Advanced Engineering Studies: The candidate is required to complete two graduate level engineering courses. The objective is to let the students acquire engineering skills and apply them to the enterprise project.

The MEEI program uses a 20‐month phase & gate commercialization. This process links the three critical components mentioned earlier. As shown in Figure 1, there are four primary phases in the new business creation process used by the MEEI program: Opportunity Scan, Technology & Market Development, Business Development, and the Start‐Up & Entry to Market Stage.

Figure 1: MEEI Tollgate Process The essence of this commercialization process is setting deliverables for each phase, and testing them at the three tollgates shown in the Figure. These deliverables describe what the student needs to know, master, and produce at each tollgate. At each of the three tollgates, the advisory committee evaluates the quality of the student’s analysis and his/her ability to achieve the deliverables for the phase. The Advisory Committee assesses whether or not the information describing the business case has been thoroughly researched, and whether or not the tools taught have been satisfactorily executed. The Advisory Committee consists of the student's business and technical mentors, an academic advisor who is assigned to the student at the beginning 2 of the program, and finally the business development manager . As the MEEI student moves his/her venture through the process, assumptions are tested for validity so that the information for each set of deliverables is refined and enhanced. Phase 1 (Opportunity Scan) establishes the value creation potential for the product or service under consideration. The student addresses the issue of the knowledge basis of the product, its value proposition and the market that he/she might enter. The student considers the demand issue: why the new product is in demand, what is its competition, how demand can be gauged objectively, and what price will the market bear and why. Then, the student addresses the intellectual property (IP) issues such as: IP uniqueness and IP protection. Finally, the student describes the technology development plan with a focus on the critical technological advances that need to be demonstrated to prove the core concept. At the end of the first phase, the student goes through he Concept Initiation Tollgate (Tollgate #1). Phase II (Technology & Market Development) is the formal commencement of both the R&D and market development phases. The budding entrepreneurs have to validate the assumptions they made at the first tollgate. On the market development side, it is expected that thorough primary market research will be carried out to explore different willing‐to‐pay customer groups, determine what the market size is, and who the main competitors are. From the technical perspective, the student is expected to prove that the core technology 2

The BDM helps all the teams in the program in their daily business activities

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Tarek Sadek and Rafik Loutfy works and that there is no further invention required. Moreover, using the voice of customer, customer requirements are mapped into technical specifications for the product/service. When the market development and the technical proof‐of‐concept (POC) activities are accomplished, a financial projection is developed. At the end of this phase the student goes through the Business Initiation Tollgate (Tollgate #2). Phase III (Business Development): The knowledge accumulated in the second phase provides the context for an analysis of potential business models and a selection of a business start‐up strategy. The remaining project assumptions are tested to formulate the tactical go‐to‐market approach. This enterprise investigation culminates in proposing a business strategy for the venture, specifying the path for the venture implementation and examining funding implications. The strategic decision process should lead to the development of a fully articulated business plan, the masters’ thesis. The expectation is that the business is ready for the fourth phase (Business Start‐Up), or the venture is terminated (Outside the program scope). At the conclusion of this phase, the student goes through the Business Startup Tollgate.

5. Program eesults Since its inception in 2005 till June 2013, the program graduated 100 students, and resulted in 32 start‐up companies and 14 patent applications. Table 1: MEEI program results Number of Graduates

100

HQP Retained in Ontario

79

Businesses & Services Created

32

Jobs Created in Ontario

77

Patents Applied

14

Patents Granted

7

XCEEi actively campaigns to raise capital for the MEEI students’ proof‐of‐concept activities. The introduction of the MEEI program was embraced by the federal and provincial government agencies and was successful in receiving in excess of $3.26 million in ‘seed’ funding to support the academic projects/business of the students. Students’ companies raised close to $30M in capital. XCEEi generated more than $4.5M in revenue from student’s fees over 8 years period.

6. The Chalmers University Masters of Entrepreneurship program The essence of the Masters program offered, by the E‐school at Chalmers, is to pair high‐quality students with inventions from Chalmers’ laboratories to create spin‐offs. Initially, the E‐school was designed to combine formal coursework with assigning students the task of creating real companies in a one‐year program; it was converted into a two‐year international master program in 2007. At Chalmers, students select projects and inventors select students. A contract is signed where the owner of the IP is left with one third ownership rights, students obtain one third conditional on continuing the project after graduation, and Chalmers obtains the remaining third. Each project has a seed fund of around $15,300 in cash (for patenting, legal and other costs), which is raised by the university from public sources. The inventor agrees in writing to provide support to the students’ commercialization efforts (T. Astebro et al.). The business ideas are scouted and recruited by Encubator. Encubator (Education + Incubator) is a Chalmers subsidiary. The main rationales behind Encubator were to professionalize the venture creation process linked to Chalmers E‐ School and attract more financial support and investments, while also improving the entrepreneurial learning. In 2005, the structure of Encubator changed from annual investment funds to a holding company and an incubation company in attempt to reach a balance between public grants and investment money. Encubator facilitates and supports business development by providing infrastructure, network, seed financing, and business advice. The E‐school produced two start‐ups in its first year of operations, which increased to six in 2007. These companies together had raised more than US$ 10 million, and created 136 new jobs (Jacob et al., 2003). The 2007 annual report from the E‐school claimed an accumulation of 32 started firms with 26 still operating and employing 220 (Chalmers School of Entrepreneurship, 2007). In 2012, when the program

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Tarek Sadek and Rafik Loutfy celebrated its 15th anniversary, 350 students had been trained, spinning off 51 companies. 42 companies are still running, raising more than 350 MSEK (around $53.5 millions) with 340 full‐time employees 3 .

7. Chalmers Masters of Entrepreneurship vs. McMaster MEEI program The focus of the comparison is on the key challenges facing entrepreneurship education as identified earlier. The basis of comparison will be:

Access to seed funding and follow‐on investment

Access and involvement of seasoned practitioners

Strategic integration with the university

Financial sustainability of the Masters program

8. Access to seed‐funding and follow‐on investment Both programs have managed to secure seed funding to support their students' venture creation. The key difference is that in the case of E‐School, the project is allocated the seed funding once the student/team starts working on the project. In the case of XCEEi, XCEEi manages the seed funding. Students have to apply for the seed funding after passing their first tollgate. The process of accessing seed funding is competitive; there is no guarantee that the student will obtain any funds. However, the MEEI program lacks an access to follow‐on investment, whereas E‐school has managed to secure an investment fund through Chalmersinvest. MEEI graduates go and seek investments through the connections they built through the entrepreneurship center and through other governmental funds such as the Market Readiness Program administered and offered by the Ontario Centre of Excellence OCE. In the last two years, XCEEi has managed to secure additional seed‐funding and incubation space for their graduates.

9. Access and involvement of entrepreneurial mentors/faculty Both programs clearly recognize the importance of involving seasoned entrepreneurs and experienced management in their offerings. In XCEEi, each student/team is assigned a business mentor and enterprise advisor as part of their advisory board. The business mentor is either in an executive position in a relevant existing company, an entrepreneur or a recognized market expert. The mentors are not compensated for their time and are usually alumni of McMaster University. As for the enterprise advisor, he/she is an XCEEi full‐time faculty member. All XCEEi faculty members have either significant new‐product‐development industrial or entrepreneurial experience. On the other hand, at Chalmers, the Encubator team provides the business and management support needed. Team Encubator shares office space with the faculty of the E‐School. Team Encubator consists of eight paid employees. All team members have considerable industrial/entrepreneurial experience. The team comprises experts in marketing, IP issues, sales, business strategists,.etc. There is a clear separation between theory and application. In the first year, the students acquire the needed tools through 4 the courses offered by the E‐School. In the second year, the students embark on starting their new ventures .

10. Strategic integration with the university There is evidence that both the E‐School and XCEEi have tried to integrate their programs with the overall university strategy. At McMaster University, in case the student decides to work on university‐owned IP, an IP policy was established to guide the relationship between the university (the owner of the IP), the inventor and the student. There is no mandate to formalize the relationship before the student starts working on the project. In the case of Chalmers University, a contract is signed between the three stakeholders (in this case, the university is an investor not the owner of the IP). It governs the relationships during the program and after the student’s graduation.

11. Financial sustainability of the Masters program Both McMaster and Chalmers are considered two of the top universities in their respective countries as well as worldwide. Swedish students do NOT have to pay tuition to attend the Masters program at Chalmers University, as the government covers the costs of the program. In Canada, students have to pay for both their 3

http://www.encubator.com/about/venture‐creation/. Accessed 3rd July, 2013 New venture creation is one track among four tracks offered after the first year. One of the other tracks focuses only on bioscience venture track creation.

4

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Tarek Sadek and Rafik Loutfy undergraduate and graduate studies. McMaster considers MEEI a professional degree. MEEI tuition is the highest among all Engineering programs, which provides for financial sustainability for XCEEi as a stand‐alone cost center.

12. Discussion and analysis In the previous section, a comparison between the entrepreneurship programs at Chalmers and McMaster Universities was carried out. The anchor of both programs is their dual focus on developing students' entrepreneurial skills and starting new ventures. In this section, the ways in which the previously identified factors impacted the commercialization success of the students’ ventures and the quality of education will be discussed.

13. Commercialization success of students’ ventures One of the most important factors in the success of this breed of programs is access to follow‐on investment. Even though Chalmers University is considered one of the top performing universities financially in Sweden, the university recognized that it could not rely solely on its revenues to support such programs. In their paper, Jacob et al. listed the entities that cover both the operational costs of the programs as well as the costs of the students’ commercialization activities. Chalmersinvest, a wholly Chalmers‐owned seed venture, provides funding for the early stage. Then, Innovationkapital, a venture capital company, partially owned by Chalmers, helps in funding the later stages of commercialization. The entrepreneurship program is treated as part of the university commercialization ecosystem not only as a revenue‐generating program. However, in the case of MEEI program, there are no secured funds to support students’ commercialization activities. The program depends on the availability of governmental funds programs focused on students’ professional training. Initially the MEEI program depended on the Talent Program delivered by Ontario Centre of Excellence OCE. After this program was terminated in 2009, the MEEI did not have any source of funds to support students’ commercialization activities. Luckily, in 2011, the Ontario government started a new two‐ years program called the Experiential Learning Program to replace the Talent Program. Currently, the only source of Governmental funds is the Scientists and Engineers program offered by the Federal Economic Development Agency for Southern Ontario (FedDev). However, this program requires securing matching funds for every dollar spent. XCEEi also has access to an endowment by one of McMaster alumni. However, the endowment is not under the discretion of the center. Another important factor is access to the university's high quality, high potential ideas/technologies. According to the Times Higher Education rankings of 56 2012/2013 McMaster ranks 88th while Chalmers University falls between 226th and 250th. The two universities score very close in research (McMaster scores 47.9 and Chalmers scores 41.5). However, in spite of having an IP agreement that governs the relationship between the university (as the owner of the IP) and the students, few McMaster students pursued that option. Several factors may account for this situation:

In Chalmers University, between 2009‐2012, only 37% of the Masters students admitted in the program were coming from outside the university. Clearly, there is an already established relationship between Chalmers faculty members and the students. Meanwhile, in the same period, at McMaster University, less than 5 % of the students are actually graduates of the university. Moreover, around 40% of the students are international students, funded by their governments, and required to go back home when they have completed their studies. According to the interviews conducted, McMaster faculty members stated that they feel more comfortable formalizing a relationship with their former graduate students. They are in a good position to estimate both the business and technical potential of the students. Under these conditions, it is very hard to effectively build a relationship or an agreement between the faculty members and the students during the program.

Contrary to McMaster, which has a university‐own policy, Chalmers adopts inventor‐own policy when it comes to IP. The E‐school requires all its students to sign contracts that govern the relationship with the inventors from the beginning. In the case of McMaster, which actually owns the IP, putting into effect formal agreements has not been an easy task. The students have to negotiate, case by case, a license agreement with both the inventors and the technology transfer officers of the university. The student has

5

http://www.timeshighereducation.co.uk/world‐university‐rankings/2012‐13/world‐ranking/institution/mcmaster‐university. Accessed 3rd July, 2013 6 http://www.timeshighereducation.co.uk/world‐university‐rankings/2012‐13/world‐ranking/institution/mcmaster‐university. Accessed 3rd July, 2013

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Tarek Sadek and Rafik Loutfy to convince the inventor and the technology transfer officers of his/her technical and entrepreneurial capabilities

In McMaster University, there is a strong focus on fundamental research rather than applied research. Even though McMaster has only 900 scholars (including faculty from the non‐technical departments), compared to Chalmers which has 1600 scientific and technological academics, McMaster's citations score is 81.7 compared to Chalmers' 47.7. Until 2009/2010, there was a joint tenure and promotion committee for both engineering and science faculties. The whole incentive systems for faculty members (research funds from the Federal Government and incentives at the university level) are based on the number of published peer‐reviewed papers and research grants raised from the industry to carry out fundamental research. These factors have affected the number of technologies ready to be commercialized and the entrepreneurial inclination of the faculty members themselves.

One of the key factors is the ability to attract talented students to work on high potential ideas. At Chalmers University, students do not have to pay university tuition, there is no financial burden associated with entering the program. On its part, E‐School does not need to increase enrollment to support its operating expenses. The number of students is capped to around 20 to guarantee the quality of both the students and the business ideas. In Canada, students have to pay for both their undergraduate and graduate studies. Even though there are usually scholarships available for students pursuing traditional research‐based Masters degrees, such support is almost non‐existent for the MEEI program. The Centre itself cannot offer scholarships unless the operating budget allows it (which draws from the tuition fee income). In addition, the university treats XCEEi as a cost recovery unit. The Centre has to cover all its salaries, marketing and operating costs from students’ tuition.

14. Quality of education/training In August 2011, XCEEI engaged a private company to conduct a comprehensive research survey to measure the effectiveness of the Centre’s programs in relation to its founding objectives. Fifty XCEEI graduates responded to the written survey (out of a total pool of 52). Twenty graduates made themselves available for 15‐20 minute telephone interviews. Summary of findings:

The experiential and hands‐on approach of the course was highly valued by all and was the big draw to the program.

90% of graduates would recommend the program to those interested in pursuing a business career.

Many felt that the XCEEI experience gave them a business advantage ahead of their peers (37%).

Most agreed that Mentorship was a key to success.

The survey also assessed graduates’ perceptions of the change in their abilities/skill level in essential program learning outcomes and how critical was this change in their preparedness for full‐time engagement in the business world. As an example, the change in the graduates’ ability to identify and assess business before and after the program is shown below as well as how essential this change was to their careers:

Figure 2: Students feedback about their abilities to identify business opportunities before and after the program

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Tarek Sadek and Rafik Loutfy As an example of the impact of the program, soft skills development and its importance to the graduates’ career, as reported in their answers, are shown below:

Figure 3: Students feedback about their interactive abilities before and after the program In the case of Chalmers, the Swedish National agency for higher education ranked Chalmers E‐School the best entrepreneurship education program in Sweden. We do not have access to the same detailed data from E‐ School's students’ perspective. However, the fact that approximately 80 percent of the businesses remain in the region, providing research contracts to the university, and the rate at which alumni return as guest speakers (T. Astebro et al., 2012) allow us to assume that the quality of the program is well perceived by the students. Also, the impressive survival rate of 82% of the start‐ups is a proof of the quality of the education offered.

15. Conclusion This case study of MEEI new‐venture creation masters program confirms that, regardless of the commercialization success of the ventures, students develop the set of skills required to start their own businesses and/or act as a growth catalyst in new or existing companies. However, the study confirms that achieving commercialization success cannot happen without the support and integration with the whole university system. The ability to attract governmental and private funds depends on the university commercialization ecosystem. Chalmers founded its own venture capital company Innovationskapital in 1994, its seed venture capital company in 1998, the Chalmers School of Entrepreneurship in 1997, an incubator in 1999, before starting the two‐years masters program in 2007. Venture creation masters programs could be key tools in realizing economic value from universities research. Students should be perceived as crucial filters of ideas and human feeders for the different governmental and regional innovation centers. In Canada, the Ontario Government realized the importance of such new venture‐ creation programs. Because of its notable success over the previous two years, in May 2013, the Ontario Government approved around $ 25 million to renew the OCE‐ELP program. The main objective is to help refine and polish the entrepreneurial skills of students, by supporting their early stage commercialization activities. In terms of their educational potential, they blur the line between formal and non‐formal learning environments, adding new sets of skills to their graduates, thus meeting the ever‐increasing demands of the labor market. Finally, one of the key factors in attracting entrepreneurially talented students, lies in alleviating the financial burden of joining the program. Canadian Universities should find their own balance of private and governmental funding to support the operational expenses of such programs, instead of depending on tuition funds.

References Åstebro, T., Bazzazian, N. And Braguinsky, S., 2012. Startups By Recent University Graduates And Their Faculty: Implications For University Entrepreneurship Policy. Research Policy, 41(4), Pp. 663‐677. Berggren, E., 2011. The Entrepreneurial University's Influence On Commercialisation Of Academic Research – The Illustrative Case Of Chalmers University Of Technology. Int.J.Of Entrepreneurship And Small Business, 12(4), Pp. 429; 429‐444; 444.

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Tarek Sadek and Rafik Loutfy Berggren, E. And Dahlstrand, A.L., 2009. Creating An Entrepreneurial Region: Two Waves Of Academic Spin‐Offs From Halmstad University. European Planning Studies, 17(8), Pp. 1171‐1189. Dahlstrand, Asa L. And Jacobsson, Staffan. Universities And Technology‐Based Entrepreneurship In The Gothenburg 2003. Local Economy,2003 18, 1, 89‐90 Erikson, T. And Gjellan, A., 2003. Training Programmes As Incubators. Journal Of European Industrial Training, 27(1), Pp. 36‐ 40. Fayolle, A. And Gailly, B., 2008. From Craft To Science. Journal Of European Industrial Training, 32(7), Pp. 569‐593. Gartner, W.B. And Birley, S., 2002. Introduction To The Special Issue On Qualitative Methods In Entrepreneurship Research. Journal Of Business Venturing, 17(5), Pp. 387‐395. Hindle, K., 2004. Choosing Qualitative Methods For Entrepreneurial Cognition Research: A Canonical Development Approach. Entrepreneurship Theory And Practice, 28(6), Pp. 575‐607. Jacob, M., Lundqvist, M. And Hellsmark, H., 2003. Entrepreneurial Transformations In The Swedish University System: The Case Of Chalmers University Of Technology. Research Policy, 32(9), Pp. 1555‐1568. Laukkanen, M., 2000. Exploring Alternative Approaches In High‐Level Entrepreneurship Education: Creating Micromechanisms For Endogenous Regional Growth. Entrepreneurship & Regional Development, 12(1), Pp. 25‐47. Menzies, T.V. And Paradi, J.C., 2003. Entrepreneurship Education And Engineering Students ‐ Career Path And Business Performance. International Journal Of Entrepreneurship & Innovation, 4(2), Pp. 121. Ollila, S., 2011. The Venture Creation Approach: Integrating Entrepreneurial Education And Incubation At The University. Int.J.Of Entrepreneurship And Innovation Management, 13(2), Pp. 161; 161‐178; 178. Rasmussen, E.A. And Sørheim, R., 2006. Action‐Based Entrepreneurship Education. Technovation, 26(2), Pp. 185‐194. Wallmark, J.T., 1997. Inventions And Patents At Universities: The Case Of Chalmers University Of Technology. Technovation, 17(3), Pp. 127‐164.

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Knowledge Sharing, Innovation Networks, and Innovation Capability: The Case of Uruguayan Software Firms Josune Sáenz1 and Andrea Pérez‐Bouvier2 1 Deusto Business School, University of Deusto, San Sebastián, Spain 2 Universidad Católica del Uruguay, Montevideo, Uruguay josune.saenz@deusto.es acperezbouvier@gmail.com Abstract: Knowledge sharing both within the firm and with external agents is considered a key ingredient for innovation to happen. In this paper, the focus will be on knowledge sharing with external agents. In particular, we argue that nurturing interaction with external agents (by means of participation in different events that allow face‐to‐face interaction, or through collaborative technology) positively affects the innovation capability of firms by allowing the development of innovation networks and making them run smoothly. In other words, we suggest that innovation networks (both their existence and operational performance) partially mediate the relationship between interaction with external agents and innovation capability (i.e. new idea generation, effective organization of innovation projects, and efficient use of resources). For this to be tested, an analysis has been carried out in Uruguayan software firms. A questionnaire was designed and addressed to the managers of the firms making up the target population (those companies belonging to the Uruguayan Chamber of Information Technologies). 105 firms out of 319 answered the questionnaire, which means a response rate of 33%. Structural equation modeling (SEM) based on partial least squares (PLS) was then applied in order to test the hypotheses drawn from the research. The results obtained show that nurturing interaction with external agents has a positive and significant influence both on the formation of innovation networks and on their operational performance. This influence is much stronger when it comes to ensuring the smooth operation of the network than when it comes to facilitating its formation. Moreover, innovation networks and their operational performance clearly mediate the relationship between interaction with external agents and innovation capability. Total mediation exists in the case of the generation of new ideas and efficient project management (i.e. fitting to costs and deadlines), whereas partial mediation applies in the case of effective organization of innovation projects (i.e. resource allocation, coordination, and knowledge leverage). Actually, additional analyses suggest that organizing innovation projects effectively fully mediates the relationship between interaction and network‐related constructs on the one hand, and the efficient use of resources (i.e. fitting to costs and deadlines) on the other hand. Keywords: knowledge sharing; interaction; innovation networks; innovation capability; software companies; Uruguay

1. Introduction and research purpose Increasingly, knowledge flows between firms are becoming crucial for many innovations (Simard and West, 2006; Bessant and Tidd, 2007). The increasing costs and complexity of R&D, the shortening of technology life cycles, the presence of increasingly knowledgeable suppliers and clients, the growth of venture capital, and the growing dissemination of cutting‐edge knowledge in universities and research laboratories call inevitably for inter‐organizational cooperation and the development of innovation networks (Vanhaberveke, 2006). Thus, there is a growing recognition of the importance of collaborative networks for innovation (Allen, 1977; Freeman, 1991; Burt, 1992; Hargadon and Sutton, 1997; Ahuja and Lampert, 2001; Schilling, 2011). This is especially important in high technology sectors (as is the case with the software industry), where it is unlikely that a single individual or organization will possess all of the resources and capabilities necessary to develop and implement a significant innovation (Hagedoorn, 2002; Schilling, 2011). As Henry Chesbrough (2006) points out, even the most capable and sophisticated R&D organizations need to be well connected to external sources of knowledge. Innovation networks involve partners sharing their respective knowledge resources, resulting in innovation and joint product development (Parise and Prusak, 2006). For knowledge to be shared, nurturing interaction with external agents is a key aspect. First of all, frequency of interaction can influence a firm’s willingness to exchange knowledge. When firms interact frequently, they develop greater knowledge of each other that could help them to build trust (Parise and Prusak, 2006; Schilling, 2011). Trust enables partners to collaborate, share critical knowledge, and debate without fear of opportunism or misappropriation (Parise and Prusak, 2006). Moreover, knowledge that is complex or tacit may require frequent and close interaction in order to be meaningfully exchanged (Bourdieu, 1986; Granovetter, 1992; Almeida and Kogut, 1999; Hansen, 1999; Schilling, 2011). Frequent interaction could help to develop common ways of understanding and articulating knowledge before partners are able to transfer it (Zander and Kogut, 1995; Szulanski, 1996; Schilling, 2011).

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Josune Sáenz and Andrea Pérez‐Bouvier Considering this, the aim of this paper is to analyze the influence of nurturing interaction with external agents on the formation of innovation networks and on their operational performance, as well as the influence of the latter two elements on the innovation capability of firms. The direct influence of interaction with external agents on innovation capability will also be tested, since it is believed that such interaction could have additional benefits for the innovation capability of companies. For instance, interacting with external agents (even though this interaction does not give rise to the establishment of cooperation agreements) could help to enhance the knowledge, skills, and experience of the company’s employees and, therefore, to increase the possibilities of innovating (Bessant and Tidd, 2007; Kaplan, 2007). In this paper, innovation will be conceptualized as a “dynamic capability”. This refers to the particular capacity business enterprises possess to shape, reshape, configure and reconfigure assets so as to respond to changing technologies and markets and escape the zero‐profit condition (i.e. a situation that occurs when there are no points of differentiation amongst firms with respect to technology, markets, information or skills, and which involves companies only making just enough to cover their cost of capital) (Teece and Augier, 2009). In particular, innovation allows the resource base of an organization to be shaped or reshaped by the addition of new knowledge embedded in new products, services, processes, technologies or business models. According to Teece (2007, 2009), this “dynamic capability” concept encompasses three first‐level (i.e. more simple) capacities. The first one is the capacity to sense and shape opportunities and threats. This can be related to the ideation stage of innovation processes (i.e. the generation of new ideas). The second one is the capacity to seize opportunities. This refers to the selection of the new ideas to be addressed and to their subsequent development and fulfillment (i.e. implementation of new ideas or innovation project management). Finally, the last first level capacity is the capacity to maintain competitiveness through enhancing, combining, protecting, and where necessary, reconfiguring the business enterprise’s tangible and intangible assets. This refers to the company’s capacity to reinvent/transform itself and not die because of unfavorable path dependencies generated by past success. In the case of this paper, the focus will be on the first two first‐level capacities – that is, on ideation and on innovation project management. As far as the latter is concerned, project management involves the process of leading and controlling a specific ongoing work program to ensure that it results in the creation of new or improved products or services (Jones, 2013). This requires allocating the right resources to each project; coordinating efforts between different organizational units, agents, and projects; and leveraging knowledge generated or acquired in the past (in other words, it involves organizing innovation projects effectively). It also requires launching products and services on time and within budget (i.e. efficient use of resources). As Jones (2013) points out, “In the race to produce advanced technological products, the issues of managing a project both to reduce the time it takes to bring a new product to market and to reduce the high costs of innovation are becoming increasingly important” (p. 396). Actually, organizing innovation projects effectively should facilitate fitting in with costs and deadlines, and launching products and services at the right time. Therefore, it could be expected that the benefits of interacting with external agents and those related to innovation networks would affect this second dimension of innovation project management mainly via the influence they exert on the first dimension (i.e. by means of their contribution to organizing innovation projects effectively). Consequently, this mediating effect will also be tested.

2. Conceptual framework and hypothesis development 2.1 Innovation, knowledge creation, knowledge sharing, and interaction According to Nonaka and Takeuchi (1995), “Knowledge creation fuels innovation” (p. 235). In other words, the process through which knowledge is created is the cornerstone of innovative activities. This process of knowledge creation involves both an epistemological and ontological dimension. From an epistemological perspective, knowledge creation involves the interaction between tacit and explicit knowledge. This interaction is called “knowledge conversion”. In the view of Nonaka and Takeuchi, tacit knowledge is the type of knowledge which is personal, context‐specific and, therefore, hard to formalize and communicate, whereas explicit or “codified” knowledge is the one that is transmittable in formal, systematic language. This tacit/explicit interaction is continuous and dynamic, and is shaped by shifts between the different modes of knowledge conversion (socialization, externalization, combination, and internalization),

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Josune Sáenz and Andrea Pérez‐Bouvier which gives rise to a “knowledge creation spiral”. More precisely, socialization involves the conversion of tacit knowledge into a tacit one. This can only be achieved by a process involving experience sharing. As a result of this, a set of shared mental models and technical skills will be obtained. In externalization, tacit knowledge is articulated into explicit concepts, using metaphors, analogies, hypotheses or models. This is triggered by dialogue or collective reflection. On the other hand, combination involves systemizing concepts into a knowledge system, which implies using different bodies of explicit knowledge. Documents, meetings, conversations or computerized communication networks could be used for this purpose. Lastly, internalization is closely related to the idea of “learning by doing”, and it means embodying explicit knowledge into a tacit one. “For explicit knowledge to become tacit, it helps if the knowledge is verbalized or diagrammed into documents, manuals or oral stories” (Nonaka and Takeuchi, 1995: 69). From an ontological perspective, knowledge creation involves a progressive move from knowledge created on an individual level, to knowledge amplified and crystallized on group, organizational, and inter‐organizational levels. Along these lines, knowledge creation involves a continuous process via which one overcomes the individual boundaries and constraints imposed by information and past learning by acquiring a new context, a new view of the world, and new knowledge. By interacting and sharing tacit and explicit knowledge with others, the individual enhances the capacity to define a situation or problem, and apply his or her knowledge so as to act and specifically solve the problem. In the case of organizational knowledge creation, this means making available and amplifying the knowledge created by individuals as well as crystallizing and connecting it with the organization’s knowledge system (Nonaka and Takeuchi 1995; Nonaka, et. al., 2006). Therefore, interacting and sharing ideas and experiences with other people is a key aspect to ensure that knowledge creation and subsequent innovation take place. This is even more relevant if we consider that innovation often involves a “recombinant search” (Fleming and Sorenson, 2001, 2004). As Fleming (2001) notes, inventions are fundamentally composed of combinations of prior existing components into new syntheses, or the recombining of existing combinations. In other words, a recombinant search involves combining specialized, differentiated, yet complementary knowledge (Tell, 2011). Such recombinations may result in completely new products and services, or in the application of existing products to new markets and uses (Fleming and Sorenson, 2004; Ahuja and Novelly, 2011). Interacting and sharing ideas and experiences may take place among individuals from the same organization or among individuals from different organizations. In this paper, the inter‐organizational perspective will be adopted. Thus, the following hypothesis has been formulated: H1: Nurturing interaction with external agents positively affects the innovation capability of firms and, more precisely:

The generation of new ideas.

The effective organization of innovation projects.

The efficient use of resources.

As we have argued in the Introduction section, this positive influence will partly take place through the beneficial effects of interaction on the formation of innovation networks and on their operational performance.

2.2 Interaction with external agents and innovation networks Firms often form alliances with different agents in order to cooperate on innovation projects. “Collaborators can pool resources such as knowledge and capital, and they can share the risk of a new product development project” (Schilling, 2011: 26). By providing access to a wider range of information and other resources than individual firms possess, inter‐organizational networks can enable firms to achieve much more than they could achieve individually (Liebeskind et al., 1996; Rosenkopf and Almeida, 2003; Schilling, 2011). In particular, collaboration can enable a firm to obtain necessary skills and resources more quickly than developing them in house, and reduce asset commitment and enhance flexibility, which may be of particular relevance in markets characterized by rapid technological change, as is the case with the software industry (Schilling, 2011). Along these lines, Simard and West (2006) argue that companies have to build ties that are both wide and deep. Deep ties (which strongly depend on trust between partners and require frequent interaction) enable a

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Josune Sáenz and Andrea Pérez‐Bouvier company to capitalize on its existing knowledge and resources (“exploitative innovation”), whereas wide ties (based on occasional rather than frequent interactions) enable a firm to find yet untapped technologies and markets (“exploratory search”). Of course, building ties is not enough. For innovation to succeed, ensuring the proper functioning of the network (i.e. operational performance) is also a necessary condition. Thus, seeing the potential benefits of collaborative networks for innovation, the following hypothesis has been formulated: H2: Innovation networks, both in terms of their (a) breadth and depth, and (b) operational performance have a positive influence on innovation capability, and more precisely on:

The generation of new ideas.

The effective organization of innovation projects.

The efficient use of resources.

As previously mentioned, and as recalled by Simard and West (2006), for innovation networks to emerge and function properly, nurturing interaction with external agents is a crucial issue. On the one hand, frequent interaction can influence a firm’s willingness to exchange knowledge by contributing to the generation of trust (Parise and Prusak, 2006; Schilling, 2011) and, on the other hand, it could develop common ways of understanding and articulating knowledge (Zander and Kogut, 1995; Szulanski, 1996; Schilling, 2011), something especially relevant when it comes to complex and tacit knowledge (Bourdieu, 1986; Granovetter, 1992; Almeida and Kogut, 1999; Hansen, 1999; Schilling, 2011). This interaction could take place both through face‐to‐face conversations and meetings (Wiig, 2004), and through collaborative technology (Cross et al., 2006). Nevertheless, knowing what someone else knows is a necessary precursor to seeking a specific person or agent out when we are faced with a problem or opportunity (Cross et al., 2006). In this respect, warning systems and mechanisms could be very helpful. Therefore, the following hypothesis has been formulated: H3: Nurturing interaction with external agents positively affects:

The generation of innovation networks.

Their operational performance.

This hypothesis together with hypothesis H1 means that innovation networks (both their breadth and depth, and their operational performance) mediate the relationship between the promotion of interaction with external agents and innovation capability. In particular, partial mediation applies, since it is believed that such interaction could have additional benefits for the innovation capability of companies beyond the promotion of collaborative networks. As Nonaka et al., (2006) point out, interaction (and, therefore, interaction with external agents as well) could help to enhance the knowledge, skills, and experience of the company’s employees and, therefore, to increase the possibilities of innovating (Bessant and Tidd, 2007; Kaplan, 2007). Finally, given that organizing innovation projects effectively (i.e. allocating the right resources to each project; coordinating efforts between different organizational units, agents, and projects; and leveraging knowledge generated or acquired in the past) should facilitate fitting in with costs and deadlines, and launching products and services at the right time, it is assumed that the benefits of interacting with external agents and those related to innovation networks would affect this second dimension of innovation project management mainly via the influence they exert on the first dimension (i.e. by means of their contribution to organizing innovation projects effectively). Consequently, the following hypothesis has been formulated: H4: Organizing innovation projects effectively totally mediates the relationship between (a) external interaction, (b) the generation of innovation networks, and (c) their operational performance on the one hand, and efficient project management on the other hand.

3. Research methods The population subject to study is made up of Uruguayan software firms. The software industry in Uruguay has reached a remarkable degree of development and is one of the strategic sectors in the country. A

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Josune Sáenz and Andrea Pérez‐Bouvier questionnaire was designed and addressed to the managers of the firms making up the target population (those companies belonging to the Uruguayan Chamber of Information Technologies). 105 firms out of 319 answered the questionnaire, which means a response rate of 33%. Structural equation modeling (SEM) based on partial least squares (PLS) was then applied in order to test the hypotheses drawn from the research. The PLS approach works in two stages:

The assessment of the reliability and validity of the measurement model.

The assessment of the structural model.

This sequence ensures that the constructs’ measures are valid and reliable before attempting to draw conclusions regarding relationships among constructs (Barclay et al., 1995). The sample size obtained is large enough to carry out a statistical study based on PLS structural equation modeling approach (Chin and Frye, 2003). According to the complexity level of the model to be tested, the minimum sample size required was calculated, and this was made up of 70 firms. As previously outlined, the research model encompasses several mediation relationships. For these to be checked, the following conditions must hold (Baron and Kenny, 1986):

First, independent variables must have a significant effect on the dependent ones in the absence of the mediators.

Second, independent variables must affect mediating variables significantly.

Third, in the full model (the one that encompasses all variables), mediators must have a significant effect on the dependent variables. If these conditions all hold in the predicted direction, then the effect of the independent variables on the dependent ones must be less than in the first model (the one in which mediating variables were omitted). Perfect mediation exists where in the final model the relationship between the independent variables and the dependent ones becomes non‐significant, whereas partial mediation applies when these relationships remain still significant, albeit less strong.

To verify such conditions, two models should be run: one which excludes mediating variables and that allows the first condition explained to be tested, and another one that includes all variables and that allows the second and third conditions to be tested. In our particular case, as two staggered sets of mediation relationships have been proposed, a third model will be necessary.

4. Research findings Following the sequence of analysis previously described, the main findings of the multivariate analysis carried out are as follows: As far as the measurement model evaluation is concerned, this differs depending on the nature of the construct being analyzed (reflective or formative). In the case of constructs made up of reflective indicators, individual item reliability, construct reliability, convergent validity, and discriminant validity should be checked. In the case of formative constructs, however, multicolinearity problems should be explored. In both cases, all the tests carried out have shown satisfactory results. Once the quality of the measurement model has been guaranteed, the quality of the structural model should then be assessed. This refers to the strength of the research hypotheses and to the amount of variance 2 explained (R ). In order to assess the research hypotheses, path coefficient levels should be examined, as well as their degree of significance, by means of bootstrapping techniques. Tables 1, 2, and 3 summarize the results obtained. In these tables, we can also see the contribution of each exogenous construct to the amount of variance explained. This has been obtained by multiplying the path coefficient and the correlation coefficient corresponding to each relationship. In the first model, given that each endogenous construct is explained by a single variable, path coefficients are equal to correlation coefficients. Model 1 shows that nurturing interaction with external agents has a positive and significant direct influence on each innovation capability dimension. Therefore, hypothesis H1 is fully supported, and the first condition for the first set of mediation effects to exist is also satisfied. In particular, organizing innovation projects effectively is the innovation capability dimension most benefited by the interaction with external agents

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Josune Sáenz and Andrea Pérez‐Bouvier (amount of variance explained: 18.92%). In the case of the other dimensions (new idea generation and efficient use of resources), the amount of variance explained is slightly lower: 11.36% and 10.05%, respectively. Table 1: Structural model evaluation – model 1

Endogenous constructs

Interaction with external agents Path Correlation 2 R Path Correlation 2 R Path Correlation R2

New idea generation Effective organization of innovation projects Efficient use of resources

0.337*** 0.337 11.36% 0.435*** 0.435 18.92% 0.317** 0.317 10.05%

Notes: ***p<0.001, **p<0.01, *p<0.05 (based on t499, one‐tailed test). Table 2: Structural model evaluation – model 2

Exogenous constructs Breadth and Interaction depth of the with external innovation agents network Breadth and depth of the innovation network

Path Correlation

Endogenous constructs

Total amount of variance explained

0.285

2

Contrib. to R 8.12%

8.12%

Ϯ

32.95%

Path

0.099

0.208

0.311*

Correlation

0.337

0.321

0.424

2 Contrib. to R 3.34%

6.68%

13.19%

23.20%

Ϯ

Ϯ

0.324*

Path 0.189 Effective organization of Correlation 0.424 innovation projects Contrib. to R2 8.01% Efficient use of resources

Operational performance of the network

0.285***

Path 0.574*** Operational performance of the Correlation 0.574 network Contrib. to R2 32.95% New idea generation

0.172 0.314

0.479

5.40%

15.52%

28.93%

0.119

0.199Ϯ

0.240Ϯ

0.313

0.298

0.362

Contrib. to R 3.72%

5.93%

8.69%

18.34%

Path Correlation 2

Notes: ***p<0.001, **p<0.01, *p<0.05 (based on t499, one‐tailed test). Table 3: Structural model evaluation – extract of model 3 Exogenous constructs Breadth and depth of the innovation network

Path

0.004

0.091

0.027

0.636***

Correlation

0.313

0.298

0.359

0.679

0.13%

2.71%

0.97%

43.18%

Efficient use of resources

Operational Effective Total amount performance organization of variance of the of innovation explained network projects

Interaction with external agents

2

Contrib. to R

Notes: ***p<.001, **p<0.01, *p<0.05 (based on t499, one‐tailed test).

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46.99%


Josune Sáenz and Andrea Pérez‐Bouvier The first part of the second model shows that nurturing interaction with external agents exerts a positive and significant influence both on the formation of innovation networks and on their operational performance. Actually, this influence is much stronger when it comes to contributing to the operational performance of the network (amount of variance explained: 32.95%) than when it comes to contributing to its formation (amount of variance explained: 8.12%). Hence, hypothesis H3 is fully supported, and the second condition for the first set of mediation effects to exist is also satisfied. Moving on now to innovation capability, in all cases, the breadth and depth of innovation networks and their operational performance exert a positive and significant influence on each first‐level capacity. Therefore, hypothesis H2 is fully supported and the third condition for mediation to exist is also verified. In particular, the operational performance of innovation networks accounts for the highest portion of variance explained in each dimension. On the other hand, it can be noticed that, when mediators are included in Model 2, the direct influence of nurturing interaction with external agents on innovation capability dimensions diminishes considerably (i.e. path coefficients are noticeably lower). More precisely, the direct effect on the generation of new ideas and on the efficient use of resources becomes non‐significant (thus, total mediation applies), whereas in the case of effective organization of innovation projects, it still remains significant (therefore, partial mediation applies). If the total amount of variance explained in Model 1 and Model 2 are compared, it could be observed that the inclusion of mediating variables significantly increases the amount of variance explained of each first‐level capacity. In the case of the generation of new ideas, the amount of variance explained increases from 11.36% in Model 1 to 23.20% in Model 2; in the case of the effective organization of innovation projects, from 18.92% to 28.93%; and in the case of the efficient use of resources (i.e. fitting to costs and deadlines), from 10.05% to 18.34%. Finally, Model 3 allows us to verify the last mediation effect. Table 3 only shows the relevant part for this purpose, as the rest is similar to Model 2. In Model 1 and Model 2, it was verified that nurturing interaction with external agents and innovation networks had a positive and significant effect on the efficient use of resources (i.e. the first condition for mediation to exist). Moreover, in the second model it could be seen that interaction with external agents and innovation networks had a significant a positive influence on the effective organization of innovation projects (i.e. the second condition for accepting mediation). Now, Table 3 shows that organizing innovation projects effectively plays an extremely important role when it comes to ensuring the efficient use of resources (i.e. the third condition for mediation to exist). Actually, when this mediating relationship is included, the direct influence of interaction with external agents and innovation networks becomes non‐significant and the total amount of variance explained rises from 18.34% in Model 2 to 46.99% in Model 3. Therefore, total mediation applies, which confirms hypothesis H4.

5. Conclusions The research carried out has helped to disentangle the interplay between nurturing interaction with external agents, innovation networks, and innovation capability in Uruguayan software firms. In particular, it has been demonstrated that, in the set of companies analyzed, fostering interaction with external agents by means of face‐to‐face meetings and conversations, and by means of collaborative technology is a crucial aspect in enhancing the innovation capability of firms. Moreover, it has been shown that, to a great extent, this positive influence is due to the role that interaction with external agents plays in the formation of innovation networks and in their operational performance. In the case of the generation of new ideas, the fact that innovation networks (both their breadth and depth, and their operational performance) fully mediate the relationship between interaction with external agents and this first level capacity means that all beneficial effects derived from the exchange of ideas and experiences with other people outside the company only take place through innovation networks. However, in the case of the effective organization of innovation projects (i.e. resource allocation, coordination, and knowledge leverage), nurturing interaction with external agents has additional benefits beyond those related to the formation of innovation networks and to guaranteeing their operational performance. Actually, this interaction with people outside the organization may improve employees’ knowledge, skills, and

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Josune Sáenz and Andrea Pérez‐Bouvier experience in a way that positively affects the management of innovation projects, even though cooperation agreements may have not been established. Finally, fitting in with costs and deadlines (i.e. the last dimension of innovation capability considered in this research) has proved to be completely dependent on the effective organization of innovation projects. Thus, everything that contributes to the latter will pay off in terms of guaranteeing an efficient use of resources. In particular, the research carried out shows that operational performance of innovation networks plays a substantial role in this respect. Consequently, efforts should be made in terms of planning, design of work methods, monitoring, and evaluation of network activities, as well as in terms of fostering continuous interaction with external agents. The study presented in this paper has some limitations that should be highlighted. The main one is that this is a cross‐sectional study and time lag effects are not considered. This could be especially relevant for the relationship between nurturing interaction with external agents and innovation networks, as the influence of the former on the generation of such networks may not be immediate. Similarly, the fact of having developed an innovation network may not have an instant influence on the identification of new opportunities for innovation. Therefore, future work should consider carrying out longitudinal studies, as well as expanding this research to different sectors and settings. In particular, it would be of particular interest to see whether nurturing interaction with external agents and innovation networks are equally relevant in low‐technology industries. Moreover, this study looked at only two of the three first‐level capacities that make up innovation capability (ideation – i.e. sensing and shaping opportunities and threats – and innovation project management – i.e. seizing opportunities, both in terms of effective organization and efficient use of resources). Therefore, it would be very interesting to analyze the influence of knowledge sharing on the third first‐level innovation capacity: the capacity of the firm to reinvent/transform itself rather than die because of unfavorable path dependencies generated by past success.

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IS Resilience in SMEs in Post‐Earthquake Christchurch Amitrajit Sarkar1 and Stephen Wingreen2 1 Department of Computing, Christchurch Polytechnic Institute of Technology, Christchurch, New Zealand 2 Department of Accounting and Information Systems, University of Canterbury, Christchurch, New Zealand Amitrajit.Sarkar@cpit.ac.nz stephen.wingreen@canterbury.ac.nz Abstract: Over recent years, the concept of resilience has gained increasing support within the academic community. Given the potentially devastating implications of disruptions, understanding the dynamics of successful adaption of Information Systems (IS) within organisations yields an important avenue for future research. Our business world is in need of adventurous thinkers and dynamic leaders to identify and follow through on the best methods of managing commercial challenges. This paper is an initial attempt to develop a conceptual framework for IS resilience, with regard to the factors that affect the decision‐making of IS managers and planners. Through this, a conceptual framework of an Information Systems resilient organisational response is presented. We adopt Agency theory to develop a conceptual framework, which supports decision making and planning for IS resilience. Concourse Theory and Q‐methodology are adopted to develop a Q‐sort questionnaire, which is refined by interviews with researchers, IS managers, and IS planners. The result is a 34‐item Q‐sample regarding IS resilience in SMEs. This research makes a methodological contribution by the development of a Q‐ sort questionnaire that may be used to study decision making and planning in the context of IS resilience. This methodological contribution will eventually enable theoretical contributions by establishing a framework that may be used to characterize planning and decision making in the context of IS resilience. Finally, conclusions are presented and attention is drawn to the implications of this instrument development for future research on IS resilience and planning. Keywords: information systems resilience; innovative decision making; uncertainty; disaster preparedness; business continuity; small medium enterprises

1. Introduction and background There is a longstanding worldwide recognition that Small and Medium Sized Enterprises (SMEs) make a significant contribution to employment generation and economic growth of a nation (Storey, 1994; OECD, 2010; Ministry of Economic Development, 2012). There are 474,415 small‐ and medium‐sized enterprises (SMEs) in New Zealand, representing 99 per cent of the business population (Ministry of Economic Development, 2012). It is therefore understandable that why the SME sector is often referred to as the backbone of the economy of a nation. Countries, communities, organisations and individuals are all subject to a diverse and ever changing environment. This occasionally tempestuous environment postures threats which can vary in severity, impact and frequency. An event in one area can often have disastrous effects in another in the current globally connected world. These events can take many forms including the 2010‐2011 Christchurch Earthquakes, the 2011 Japan Tsunami, the 2010 Haiti and Chile Earthquakes, the 2010 eruption of Icelandic volcano and the most recent Hurricane Sandy in East coast of US. Natural disasters, pandemic disease, terrorist attacks, Information Systems failure and human error can all pose both a potentially unpredictable and severe threat to the continuity of an organisation’s operation. Traditionally, SMEs have several advantages over a large company due to its size and flexibility in adapting to change. Despite their prominence and flexibility, SMEs are the most vulnerable and very susceptible to disasters. Disasters can cause challenges to organisations and it is essential that sufficient effort is directed into making small and medium enterprises (SMEs) robust and resilient to withstand these uncertainties and challenges. It is often only through hindsight that disasters look like the events that individuals, communities, organisations and countries should have prepared for. Agency theory predicts differences in management structure, leadership style, organisational culture, and the emphases placed on different dimensions of the strategy making process, barriers to the implementation of strategy and performance between SMEs and Large Organisations. An IBM study that investigates how

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Amitrajit Sarkar and Stephen Wingreen organizations are increasingly adopting integrated business resilience strategies in an uncertain environment narrates that large organisations lead the way in business and IS resilience and most studies of the IS resilience has been made in the context of big business, to best of our knowledge no attempts have been made to study small business in this regard (IBM, 2011). However, given the specificities of SMEs as organizations, research results obtained from the study of large enterprise IS cannot necessarily be generalized and transferred to SMEs (Thong, 1999).It is important to remember that a small firm is “not a little big business,” according to Welsh and White (1981), and there is a need to take off the big organization glasses when studying technology issues in small firms (Thong, 1999). In this paper the emphasis is on a relatively overlooked area of research; that is the people who own and operate these firms – the entrepreneurs or owner‐managers – and their effort to make their business resilient in terms of Information Systems. Much of the research to date has focused on identifying characteristics of the firm (e.g. size, sector, performance and practices, etc.), in an attempt to understand their survival, growth and failure (Massey, 2005). Yet the characteristics of the entrepreneur and owner/manager and how they make decision in time of crisis to ensure resilience of Information Systems of their business have attracted far less attention, which is surprising given that one of the defining characteristics of SMEs is their dependence on the entrepreneur or owner/manager as a leader, decision maker, manager and day‐to‐day operator of the firm (Storey and Greene, 2010) and IS plays a major role in SMEs today. As such, this article will focus on establishing a solid conceptual base for IS resilience upon which future empirical studies can be based. This article outlines the background literature relating to resilience and in particular focuses on Information Systems (IS) resilience and presents a working definition for Information Systems resilience. Our review of the literature suggests a paucity of empirical research on the relationship between ownership structure and culture, leadership, decision‐making skills attached to factors influencing strategy, barriers to implementation of strategy, and their effort to make their business resilient in terms of Information Systems. The purpose of this article is twofold: first, it seeks to fill the void in research on determinants of IS resilience in SMEs, and second, it seeks to understand the determinants of IS resilience in SMEs. One research question is proposed to better understand the Information Systems resilience in SMEs, as well as the factors that affect the Information Systems resilience in SMEs: What characterises resilient SMEs from non‐resilient SMEs within the context of Information Systems?

2. Literature review SMEs in the Context of Agency Theory Research and literature have highlighted that there is no precise definition of SMEs (Bhamra, Dani, and Burnard, 2011) (Storey D. J., 1994). As SMEs differ in size, location, business, financial performance, maturity and management style, the definition of SMEs varies from country to country. Government bodies and official statistics most commonly define SMEs as those having fewer than 20 full time equivalent employees (Ministry of Economic Development, 2012). Generalised characteristics of these firms are that they have limited access to resources, personalised management styles and little formal structure (Battisti, Lee, and Cameron, 2009). SMEs employ 30% of New Zealand’s working population and contribute an estimated 40% of the economy’s total value added output (Ministry of Economic Development, 2012). New Zealand has the highest number of businesses per head of population in the OECD (Ministry of Economic Development, 2012). More than 50% of these enterprises are family or owner‐operated businesses (Ministry for Economic Development, 2012). Even with this definition SMEs are diverse. Some firms are dynamic and flexible with a great power to innovate and a vast range of diversity. Some are based on family involvement and embedded in local business environments. Others may fall under the category of start‐ups: fragile organisations striving for survival. Due to lack of universally accepted definition of SME, in our research we will define SME as “privately owned, have personalised management styles, little formal structures and employ less than 50 full time staff members.”

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Amitrajit Sarkar and Stephen Wingreen It is well known that SMEs are different from large organisation in many respects, and organizational theories applicable to large firms may not be applicable to them (Bharati and Chaudhury, 2006; Dandridge, 1979; Senn and Gibson, 1981; Blili and Raymond, 1993). It is important to remember that a small firm is “not a little big business,” according to Welsh and White (1981), and there is a need to take off the big organization glasses when studying technology issues in small firms (Thong, 1999). There are significant differences between the large organisations and SMEs. We will elaborate and explain these differences using Agency Theory. Agency Theory Effects in SMEs Agency theory has its roots in economic theory and is based on the following principles. Agency theory is a contract under which one or more persons (the principals) engage another person (the agent) to perform some service on their behalf which includes delegating some decision making authority to the agent. “If both parties to the relationship are utility maximisers then there is good reason to believe the agent will not always act in the best interests of the princip al” (Jensen and Meckling, 1976). Agency theory predicts that the agency conflict may be reduced when the owner is involved in management (Fama and Jensen, 1983) (Jensen and Meckling, 1976). This theory is likely to hold more dominance in the case of smaller organisations where it is more likely for the principal and agent to develop a close relationship or even principal and agent is the same person. On the other hand, it is also true that managers in small firms may be more isolated from the market discipline due to a closer relationship with their principals. Such isolation may result in entrenchment. Entrenchment is in turn likely to have a negative impact on performance. Furthermore, isolation from market disciplines and entrenchment‐induced inertia is likely to encourage a weak culture and weak leadership as well as a myopic strategy (Ghobadian and O'Regan, 2006). However, in SMEs the CEO is usually the owner‐manager. Since CEO is the main decision maker hence personal traits of the CEO could potentially influence the culture, leadership and strategic planning processes of an SME (Ghobadian and O'Regan, 2006). Owner‐manager’s desire for autonomy and possible disposition towards social aspects of relationships should not be ignored when trying to better understand the dynamics of power within SMEs. Implementing change can be particularly problematic for organisations where power and authority are highly centralised (Paton, 2007). Competitor power is also of concern to SMEs, especially when buyers can at short notice switch suppliers. In this position dominant buyers are able to make demands, not only on the deliveries and quality of the product, but may in addition force weaker suppliers to manufacture unprofitable products (Saunders, 1997). In summary, based on the arguments and predictions of agency theory, SMEs and large organisations are likely to behave differently. Moreover, agency theory predicted differences in leadership style, culture, the emphases placed on different dimensions of the strategy making process, barriers to the implementation of strategy and performance between SMEs and Large Organisations. Transformational leadership style was more prevalent in SMEs, while transactional leadership style was more prevalent in large organisations. SMEs and large organisations also differed across a number of culture constructs. Literature reviews illustrate that large organisations are more likely to have formal strategic plans than SMEs. In addition, SMEs and large organisations place differing emphases on the attributes of strategic planning. Overall, large organisations place greater emphases on most dimensions of strategic planning. Also literature reviews suggested the differences in barriers to strategy implementation. SMEs would experience difficulties to a greater extent compared large organisations. Literatures also suggested that strategic planning for SMEs must be further developed and refined and SMEs should be encouraged to deploy it. Literature review findings suggest personal traits could potentially influence the culture, leadership and strategic planning processes of an SME. Thus, from the above discussions it is evident that research findings related to large organisations may not be directly applicable to the SMEs. However, these findings may provide useful insights towards SMEs. Roles and Impact of Information Systems in SMEs Carr (2003) was the first among many other researchers to turn the research focus by questioning the value gained from investments in IT, and now there is considerable literature on the IT productivity paradox that

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Amitrajit Sarkar and Stephen Wingreen examines “IT investment” and its relationship with firm performance. In the years of the dotcom hype many believed that IT would enable SMEs to compete with large companies. However a lack of readiness for networking with other enterprises and reluctance to use advanced IT proved otherwise. SMEs perceive little incentive to change business models when returns are unclear (OECD, 2004). Research also showed that SMEs do not excel in knowledge retention and obtaining a sustainable competitive advantage. There is a slower adoption of IT in SMEs than in large enterprises. The methodologies that lead to successful IS implementations in large organisations can therefore not be extrapolated to SMEs, since we are dealing with a completely different economic, cultural and managerial environment. Due to their small scale and hence a lack of in house IT‐skills, SMEs depend more on vendors than large companies (Thong, 1999). This does not mean that outsourcing is without risks or problems. Resilience of Organisations Resilience is the ability of an organisation to not only survives but to thrive, both in good times and in the face of adversity (Seville 2009). Vargo and Stephenson (2010) proposed that for organisations to invest in resilience, the business case for resilience investments has to go beyond insurance, and must be as good as the case for new equipment or new staff (Vargo and Stephenson, 2010). Gibson and Tarrant (2010) presented the integrated functions model which suggests that organisational resilience is a goal that results from a combination of other activities such as risk management and business continuity. Gibson and Tarrant (2010) also presented the herringbone resilience model shown as Figure 1. This model suggests that resilience is enhanced by a combination of organisations’ characteristics or attributes and their activities and capabilities, or who they are and what they do (Gibson and Tarrant, 2010). The herringbone model incorporates many of the factors considered as possible indicators of IS resilience in this article.

Figure 1: Herringbone resilience model (Gibson and Tarrant, 2010) Planning vs. Resilience Discussion on resilience is incomplete unless we explore planning. A central theme of resilience research is the question of anticipation vs. resilience, planning vs. adaptation. This section defines anticipation and resilience and discusses how these two approaches can be combined within organisations to address IS resilience in organisations. Anticipation involves predicting possible sources of failure or causes of crisis or disaster, so that they can be planned for, mitigated or avoided altogether. Weick and Sutcliffe (2007) refer to this as avoiding error by design whereby a system of controls, processes and checks is put in place to prevent possible crises from occurring. Valle (1999) further added that an anticipatory approach is more suited to environments characterised by stability and predictable outcomes.

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Amitrajit Sarkar and Stephen Wingreen In contrast resilience, involves adaptation to changing environments. Weick and Sutcliffe (2007) discuss the resilience approach and note that resilient organisations recognise that it is impossible to prevent all crises and disasters all of the time. Instead they monitor their organisation as a system with inputs and outputs, the characteristics of which can provide information about the health of the system. Researchers propose a balance between anticipation and resilience. Comfort (2001) argues that disaster management practices are moving towards a combination of anticipation and resilience strategies. She explained that “While we agree that resilience is the key to coping, it is necessary to organise for resilience”. Researchers suggest that the anticipatory approach, including planning, is used to enable organisations to be resilient. Planning and formalising response arrangements in advance means that the organisation is free, at the time of crisis, to be much more adaptive and resilient in its response (Hurley‐Hanson, 2006). Importance of IS Resilience in Organisations For most businesses today, a lot of business is done with vendors and customers on the Internet; they rely heavily on IT and data and operate 24/7. For this reason the line between business and information system is blurred (Sayana, 2005). In such cases, continued availability of information systems is a sine qua non for business. Such businesses do not have any other alternate means of recording transactions and other data, hence cannot afford to be without information systems for long. All businesses that use information systems and data in their operations have a need for business continuity and disaster recovery plan. Most large organisations, particularly all Fortune 1000 enterprises, conduct regular information systems audit to ensure confidentiality, integrity and continuous availability of information systems (Singleton, 2011). Hence, availability of information systems is one of the major criteria for IS resilience. However, a small enterprise that uses IT and whose business processes are reliant on IT is also at a high risk (Singleton, 2011). Studies have found that after London bombing incidence SMEs failed to plan for unexpected disruptions to their business (Goodwin, 2005). Goodwin (2005) mentioned that SMEs are particularly weak to demonstrate that they have planned about the business continuity of their IT systems. Goodwin (2005) predicted that SMEs will be under‐pressure from large businesses, regulators, investors, insurers and their suppliers and it will be hard for them to ignore business continuity in future. Unfortunately SMEs are much less likely to carry out such planning processes than larger organisations, and when they do, the planning is likely to be less disciplined (Berman et al. 1997). However, the good news is that when they do carry out structured planning processes, it is good for business (Cragg and King 1988). A review of literature on IT management in large organisations and SMEs identifies significant differences in the IT management processes between these two types of organisations. Literatures have acknowledged the involvement of top management in IT planning and decision making as an important factor that leads to success of information systems in organisations.

3. Research method Essentially, we are studying decision process of stakeholder decision priority in context to IS resilience. This involves the prioritisation of different decisions. Q‐methodology is capable of capturing the priorities. Therefore Q‐methodology was employed in accordance with the goals of this study to identify IS resilience planning priorities in SMEs. Utilizing the Q‐methodology entails the adoption of its guiding philosophy of preserving operant subjectivity, the guidelines for instrument development and measurement using the q‐sort, and a specialized centroid factor extraction technique known as “q‐factor analysis” (Brown, 1980). The preservation of operant subjectivity may be best described as the principle of allowing the subjects to speak for themselves in their own voice (Brown, 1980). In the context of this study the idiographic nature of the Q‐ methodology makes it appropriate for the identification and interpretation of the existing perspectives about IS resilience in SMES. The basic steps of the Q sorting procedure are as follows. A heterogeneous set of items (called a Q sample) is drawn from the concourse. A group of respondents (P set) is instructed to rank‐order (Q sort) the Q sample along a standardized continuum according to a specified condition of instruction. Participants do this according to their own 'psychological significance'. The resulting Q sorts are submitted to correlation and factor analysis. Interpreted results are factors of 'operant subjectivity' (Brown, 1980).

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Amitrajit Sarkar and Stephen Wingreen The definition of a concourse, development of the set of Q‐statements for IS resilience priorities, instrument development followed the recommendations of previous research on the subject (Brown, 1980). In order to achieve the highest probability of a representative sample of the concourse we have conducted extensive literature review, conversation with people who participate in the concourse, and input from the domain experts about the content of the sample of Q‐statements. The development process includes a series of deliberate steps to ensure content validity of the Q‐sort statements. The procedure of instrument development includes literature review, discussion with experts, and refinement of sample q‐statements with the help of domain experts and IS decision makers and planners. Feedback from the evaluators was then incorporated into the Q‐statement and Q‐Sort instrumentation. After several iterations the experts confirmed that the instrument is ready and should function as intended, and now the study could proceed to primary data collection. The result is a 34‐item Q‐sample regarding IS resilience in SMEs. This research makes a methodological contribution by the development of a Q‐sort questionnaire that may be used to study decision making and planning in the context of IS resilience.

4. Research model As mentioned before, the purpose of this article is twofold: first, it seeks to fill the void in research on determinants of IS resilience in SMEs, and second, it seeks to understand the determinants of IS resilience in SMEs. A conceptual framework of determinants of IS resilience is shown in Figure 2. After an extensive literature review we have not been able to find a definition of IS resilience. However, organisational resilience has been studied extensively by researchers (Vargo and Seville, 2011); (Hatton, Seville, and Vargo, 2012). A definition of Information Systems resilience is introduced for the purpose of our study, it is defined as: Information Systems resilience is a function of an organization’s overall situation awareness related to Information Systems, management of Information Systems vulnerabilities, and adaptive capacity of Information Systems in a complex, dynamic, and interconnected environment. A conceptual framework of IS resilience has also been developed.

Internal Factors

Information Systems Resilience External Factor

• • • • • • • •

IS-Business Continuity Plan IS-Disaster Recovery Plan Leadership Top Management Support CEO Characteristics CEO’s IS Knowledge Organisational Culture Decision Making

• • • •

Customer Pressure Supplier Pressure Competitor Pressure Situation Awareness

Figure 2: IS resilience conceptual framework

5. Conclusion Although SMEs are regarded as key drivers for economic growth, there is a lack of work on this subject matter. There is especially the need for empirical studies analysing key issues of Information Systems resilience in SMEs. Accordingly, an extensive literature review is conducted to identify differences between large‐scale enterprises and SMEs with respect to Information Systems resilience. We have used agency theory to establish the decision priority differences between the SMEs and large organisations. Also we have identified the gap in research related to information systems resilience in SMEs. To best of our knowledge this is the first attempt to create an IS resilience framework for SMEs. In particular, this paper examines Information Systems vulnerability; Information Systems risk management and propose a conceptual model for Information Systems resilience in SMEs. To test the conceptual model we have also created a valid and reliable instrument. It was

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Amitrajit Sarkar and Stephen Wingreen necessary to develop and validate an instrument to measure IS resilience priorities and factors. In this study, we have taken the first step towards fulfilling this objective. The individual prioritizes the Q‐Statements by sorting them into categories that approximate a normal distribution, with fewer statements sorted into the extreme categories and more in the central categories. Since all statements are sorted relative to one another, any given Q‐sort represents the person’s coherent point‐of‐view on the concourse. Every study has its limitations, and this one is no exception. The instrument we have developed as part of this research need to be tested with primary data. There are a number of avenues of future research. Future empirical research should attempt to understand the IS resilience priorities and characteristics of resilient organisations. Finally, results have implications both for researchers who are looking for theories that explain the importance of Information System resilience and business managers and owners who are challenged with decisions about how to design resilient Information System framework for their organisation.

Acknowledgements We are grateful to the anonymous reviewers for their insightful feedbacks.

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The Institutional Support as a Factor for Technology Internationalization From Developing Countries Viktor Stojmanovski1, Velimir Stojkovski2, Mijalce Santa3 and Beti Kostadinovska Dimitrovska2 1 Faculty of Mechanical Engineering, Ss. Cyril and Methodius University in Skopje, Skopje, Macedonia 2 Ss. Cyril and Methodius University in Skopje, Skopje, Macedonia 3 Faculty of Economics – Skopje, Ss. Cyril and Methodius University in Skopje, Skopje, Macedonia viktor.stojmanovski@mf.edu.mk velimir@ukim.edu.mk mijalce@eccf.ukim.edu.mk beti.kostadinovska@ukim.edu.mk Abstract: In the current global market economy, companies need to continuously innovate and create new products that satisfy unmet market needs. A major aspect of the innovation process is to market the new technologies on local and international markets. The internationalization of the technology and its distribution to larger number of partners and customers will ensure long‐term success of the company that invented the technology. However, the innovative entrepreneurs and SMEs face challenges in achieving internationalization of their technologies especially those from the developing countries. The obstacles that the SMEs are facing range from lack of information about the market opportunities, lack of knowledge of the process of commercialization of the innovative technology and lack of knowledge of the potential international customers and partners. Due to limited resources the SMEs and innovative entrepreneurs are not in a position to quickly and in appropriate way manage these internationalization barriers. This paper’s aim is through a case study research, to identify whether an institutional support facilitates the SMEs and entrepreneurs in developing countries to successfully overcome the obstacles for technology internationalization. In particular, the following obstacles are analyzed: access to information, access to foreign partners and markets, lack of matchmaking and networking and technology transfer promotion. The case study is performed on the European Information and Innovation Centre in Macedonia, an Enterprise Europe Network partner organization. EIICM is an appropriate subject for this case study because of: its relations and experience with large number of innovative SMEs and entrepreneurs from developed and developing countries; it is a Consortium of University, Foundation and Chambers of Commerce; it provides its services for free of charge to the SMEs and; it is co‐financed by the European Union and the Macedonian Government. In our case study, we have analyzed the work of EIICM since its establishment in 2008, through its documentation and annual reports. The outcome is that the SMEs mainly request information for potential partners for technology internationalisation and transfer. Furthermore, the internationalisation is supported through exchange of SMEs technology profiles, direct contacts established with EIICM assistance, networking with foreign companies and promotion of innovative technologies. The conclusion is that the support provided to the SMEs and entrepreneurs by institutions such as EIICM positively influences on the ability of the SMEs to internationalize their technology and innovative solutions. The limitation of this paper is that the research is performed on only one case study and there is a need to extend the cases on which the research will be performed. Furthermore, the results of the research can be supplemented by a quantitative research through surveys in order to generalize the findings. Keywords: SMEs, entrepreneurs, technology internationalization, institutional support, innovation

1. Introduction Managing organizations today is difficult. Organizations today operate in a complex external and internal environment. Vital planning assumptions continuously change due to dynamic developments and events in organizations’ external and internal environments (Karp 2006), such as technological discontinuities (Romanelli & Tushman 1994) and turbulence (Lant & Mezias 1992). Creating and sustaining competitiveness is harder due the challenges of globalisation, changing customer and investor demands and increasing product‐market competition (Jashapara 2004). Furthermore, the pressure on responsiveness, emphasis on product and service quality, diversity and customization increases the level of, ever changing, complexity companies have to manage.

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Viktor Stojmanovski et al. In the current global market economy, the companies, in order to successfully respond to these challenges, need to continuously innovate and create new products that satisfy unmet market needs. Small and Medium Enterprises (SMEs) play a key role for innovations and technology development that are major for creating economy based on knowledge, as well as to produce economic benefits and job creation. The global competitiveness requires development of new innovative products and services that are present on the market. The need for networking of the enterprises and increasing their international activities made a significant initiative on European level to launch a network to help SMEs to develop their innovative capacities and full potential. That is the Enterprise Europe Network which aim was to create a single network that will offer more effective and high‐quality integrated services to make SMEs more competitive. The existence of such network that will gain all services and support for the SMEs was an ideal solution for the national enterprises and organizations to increase their business and technology activities and to help them to expand internationally. Enterprise Europe Network in Macedonia was launched in the year 2008 by the European Commission as a largest network of contact points to help companies enlarge their business, technology and R&D activities, as a nature continues of the previous support networks – Euro Info Centers and Innovation Relay Centers. From the first set up until now, the Network has increased institutionally and regionally connecting more than 600 organizations in more than 50 counties, as well as covering regions beyond European level. The Network also provided chance to the developing countries to show their interest for participation and to join the Enterprise Europe Network. This participation brought higher benefits to the SMEs in these countries that would one expected: firstly, they always have access to information about business and technology development; secondly, they are provided with activities and services offered free of charge for networking and matchmaking by experienced experts; thirdly, because of their exceptional chance to meet foreign business and technology developers and providers and conclude cooperation; and the last but not the least because of the opportunity to be present on international markets and access to finance. The internationalisation of the technology and its distribution to larger number of partners and customers will ensure long‐term success of the company that invented the technology. Prior studies have advanced our understanding how companies can commercially exploit their invention by exploring the factors and the relations that support innovation in the companies. However, the innovative entrepreneurs and SMEs, due to their limited resources face challenges in achieving internationalisation of their technologies, especially those from the developing countries. This paper’s aim is through a case study research, to identify whether an institutional support facilitates the SMEs and entrepreneurs in developing countries to successfully overcome the obstacles for technology internationalization. In the first part of the paper we present a short overview of innovation and technology transfer aspects, and then we provide a glance of the Macedonian context. At the end we present the results from the case study followed with a conclusion.

2. Innovation Innovation can be defined as the management of all the activities involved in the process of idea generation, technology development, manufacturing and marketing of a new (or improved) product or manufacturing process or equipment (Trott 2011). Innovations can range from fairly small‐scale changes to more radical ground breaking innovations. There are three levels of innovations (Andriopoulos & Dawson 2008), as follows:

Incremental innovations: these refer to small changes that are generally based on established knowledge and existing organizational capabilities

Modular innovations: middle‐range innovations that are more significant than simple product improvements

Radical innovations: these typically occur when the current knowledge and capabilities become obsolete and new knowledge is required to exploit uncharted opportunities.

Innovation can also take many different forms, including the following (Andriopoulos & Dawson 2008):

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Product innovations: refer to innovations in the development of a new or improved product

Service innovations: development of new or improved services

Process innovations: these innovations center on improving processes rather than end products or services

Management innovations: creation of new or improvement of management techniques and practices

Market or position innovations: this refers to the creation of new markets and generally overlaps with products and process innovations

Although the innovation has been treated as an organizational issue, it should be noted that the capability of the organizations in initiating and sustaining innovation is to greater extend determined by the wider local and national context within which they operate (Trott 2011). This implicates that innovation is an institutional process (Edquist 2001). The entrepreneur who is responsible for innovation is embedded in a system of institutions that can support him (Kubeczko et al. 2006). According to Heydebreck et al. (2000) the SMEs have four needs bundles for innovation support services:

Technology related services. This bundle consists of technology‐related services for companies that experience a discrepancy between their strategic goals and their actual technological standing. Services that the SMEs need are: realization and management of R&D, technological consultancy, and search for R&D cooperation partners.

Finance related services. The bundle of finance‐related assistance services includes direct financial support as well as support in detecting and accessing external sources of financial means. Support consists of assistance with topics regarding EU, mediation of contacts to financiers, and assistance with the financing of innovation projects.

Soft services. A more general type of support service comprising of seminars and information events, education and training programmes, and consulting and mentoring

Market related services. Services that the company needs are assistance in the marketing of products or technologies, search for customers and suppliers, and assistance with new product launches. This bundle is the one for which the companies express the greatest need.

An important element to the innovation system is the innovation support organizations or innovation intermediaries that can provide services that the SMEs need. Dalziel (2010) defines innovation intermediaries as organizations or groups within organizations that work to enable innovation, either directly by enabling the innovativeness of one or more firms, or indirectly by enhancing the innovative capacity of regions, nations, or sectors. The functions of innovation‐support organizations within innovation systems are directed primarily toward assisting individual firms or groups of firms in the innovation process (Doloreux & Melançon 2009). They achieve this through three categories of activities (Dalziel 2010):

interorganizational networking activities,

technology development and related activities, and

other activities.

Howells (2006) identifies the importance of innovation‐support organizations in scanning and diffusing information related not only to technological development and commercial opportunities, but also to governmental programs, market development, and regulations (Doloreux & Melançon 2009). On the other hand according to Todtling and Kaufmann (2002 through Inkinen & Suorsa 2010), main barriers for using intermediaries are:

lack of information about the support opportunities

costly application procedures and project documentation;

support mechanisms to aid the innovative and successful enterprises and not to encourage other firms to innovate;

support mechanisms often do not consider the regional conditions, i.e. industrial structure.

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3. Technology transfer Technology transfer is the managed process of conveying a technology from one party to its adoption by another party (Souder et al. 1990). In the terms of the Enterprise Europe Network, technology transfer can be best described as the successful application and/or adaptation of a technology developed in one organization to meet the needs of one or more other organizations. The transferred technology shall be innovative for the recipient. A technology transfer not only includes transfer between organizations but also between different industrial sectors. A technology transfer is deemed to have been achieved once a licensing agreement, a joint venture agreement, a manufacturing agreement, and/or a commercial agreement with technical assistance has been signed. The object of the agreement should focus on bringing a competitive advantage to the recipient. The innovative character should be assessed in the context of the recipient, not that of the developer. In terms of the EEN, innovative character of technology can be understood as: new to the recipient’s country, to the recipient’s region, to another industrial or business sector, and a new use for an existing technology. Technology transfer plays an important role in developing countries (Inkpen & Dinur 1998). However transferring technology across borders is a process influenced by a large number of factors such as (Liu et al. 2008):

complexity, specificity, and tacitness

time involvement, organizational structure, organizational culture, and technology and knowledge strategy orientations

trust level between the transferring and accepting parties

cross‐cultural differences and institutional profiles.

4. The setting: Innovation system in Macedonia In the past two decades Macedonia has undergone considerable economic reform and has developed an open economy with trade accounting for more than 90% of GDP in recent years. The key industries in Macedonia are manufacturing, trade and agriculture and the top trading partners for exports (for 2011, in percent of total) according to the National Bank of the Republic of Macedonia (NBRM, 2011) are:

Germany = 27.7%

Kosovo = 12.3%

Serbia = 7.5%

Bulgaria = 6.9%

Italy = 6.5%

Greece = 4.9%

Croatia = 3.1%

Important feature of Macedonian export is that its structure has been practically unchanged within the observed period and it was dominated by low value added products. Textiles, metal and non‐metal minerals have constantly accounted for more than half of all exports from Macedonia. Nearly 99% of the companies in Macedonia are registered as small enterprises, employing nearly 55% of the employees in the private sector. According to the main activity registered, the majority of businesses are in the wholesale and retail trade sector (47%), manufacturing sector (13.1%), and the transportation, storage, and communications sectors (approximately 10%). The largest employer is the manufacturing sector, with 35.6% of the total number of employees in the private sector (Invest in Macedonia, 2011). Furthermore the Macedonian economy is characterized by a continuous high rate of unemployment 31.3% in 2012 (World Fact Book).

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Viktor Stojmanovski et al. According to the World Competitiveness Report 2012‐13 Macedonia is efficiency driven economy and ranks 80 out of 144 economies. Regarding the innovation aspects, Macedonia ranks 110 out of 144 countries. Very low values Macedonia receives for company spending on R&D, 123 out of 144 (Schwab, 2012).

5. EIICM as innovation‐support organization ‐ case study As stated before, Republic of Macedonia joined the Enterprise Europe Network in 2008, connecting the business, technology and R&D community, creating synergy with the academic organizations in cooperation for development, research and transfer of technology and innovation. The Enterprise Europe Network in Macedonia is represented by the European Information and Innovation Centre in Macedonia (EIICM). EIICM now compose of the two largest business communities in Macedonia, the Macedonian Chambers of Commerce and the Economic Chamber of Macedonia, and with the two technology transfer providers and R&D supporters ‐ the Foundation for Management and Industrial Research and the Ss. Cyril and Methodius University in Skopje. The EIICM Consortium comprises 4 partners completely different according to their fundamental activities: public university, foundation and two chambers of commerce. The conjunction of these partners in single consortium results with mixture of completely different cultures of acting as well as different methodologies and approaches to the work itself. Although, all partner organizations in EIICM have different backgrounds in business, technology and research industry they have extensive experience in providing services and helping SMEs. EIICM is the appropriate subject for this study because it is a representation of the triple helix concept. As such EIICM represents new institutional and social format for transfer of knowledge. EIICM provides assistance to clients that are developing a technology or an innovation and are interested to make it available to end‐users abroad in order to carry out a technology request. The process is starting with information about the client that is interested in creation of technology profile and publishing in the EEN database. Exchange of profiles within the Network is also part of this process, i.e. publishing and sending as well as disseminating profiles at the same time. The profiles have quality content as well as information about the client and IPR issues. At the beginning, the Centre was focused on the promotion of the Network and its services offered to SMEs which were fairly unknown to the Macedonian SMEs, and in that period, there was a high interest of the foreign companies for cooperation with Macedonian companies and vice‐versa low interest for cooperation (EIICM 2010). The low interest of the Macedonian companies for cooperation with the foreign ones was due to the fact of the Network’s first occurrence in the area and to the fact that Macedonian companies were in the phase of the trust building with EIICM. Macedonian SMEs did not know how the Enterprise Europe Network functions and how much time is needed for attaining trust for open cooperation. The results show relatively weak output effects achieved considering the fact that it was a start‐up period. Also, as the country is not a part of the EU, consequently the Macedonian SMEs were yet unacquainted with many spheres from the European problems. In terms of the technology internationalization, the Centre in that period show very low results due to the weak response of the Macedonian SMEs to promote new innovations. These services were completely unknown for the Macedonian SMEs, and therefore EIICM has worked intensively on the Network promotion and on its identification and visibility in the Macedonian area. After two years of implementation, EIICM expressed interest to carry on with its support to national SMEs to go international. It proposed new Work Program for the period 2011‐2012 with new targets that express real positioning of EIICM to assist SMEs in their internationalization. The goal was EIICM to increase institutionally, to boost up the linkages between the staff that would ensure implementation of effective mechanisms towards the complementary services, both in the Network and the region, for the benefit of all clients. EIICM set up project management mechanisms at consortium as well as at the activity level and for each partner in the hierarchy of the management is considered a team leader. They are responsible for the activities within the institution and are in close cooperation with the project manager. One of the main characteristics of the project management was establishment of the Working Group concept. These groups were of permanent character and their main task was to make activity level coordination on promotion, event organization, training planning, quality control, follow‐up procedures, etc. Special attention was given to quality control

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Viktor Stojmanovski et al. check and for development of feedback No wrong door principle was considered. Consortium Intranet, a tool for project management, communication and monitoring was already developed and it was the key tool for tracking the realization of the results. Common client database and system for archiving the documents regarding the project on the consortia and partner level was established. Compared to the previous project period from 2008 to 2010 there is an evident progress in all of the segments of the work of EIICM. The communication with SMEs and Network partners went well and there is a better performance. Consortium partners communicated well and intra‐consortium assistance of clients was evident. The Consortium gave good contribution to networking activities on national and international level. Project management developed good tools for tracking the project results (EIICM 2013). The institutional set up, as well as the good management tools made significant approach that brought to positive results comparing to the first period. In this paper, several successful stories will be presented. With regards to the technology transfer, EIICM successfully helped to nine companies to conclude Partnership Agreements with foreign partners. EIICM has reached its targets and has made a significant success supporting the companies and entrepreneurs to internationalize their technology and innovative solutions. Based on the analysis of the partnership agreements we have identified that there are two specific PAs that required EIICM to use it full potential and resources in order to facilitate the process of reaching Partnership agreement. The first one is between individual researcher and University and the second one is between a SME and University. By presenting these examples we show how the process can be facilitated between three different types of stakeholders. The first partner agreement is about a production of new types seed germination products and fertilizers for agricultural products in liquid and/or soil form. A Macedonian individual researcher has brought to develop a technology on utilization of biomass waste and its transformation into new valuable products. The limited ability for promotion of the newly developed technology by the researcher abroad made him to contact EIICM to ask for assistance. The technology provides expertise, problem‐solving, performance measurement and evaluation, but not a support to promote the new products to foreign markets. EIICM provided an ad hoc advice for preparation of technology profile that was promoted in the Network. Very soon, EIICM received Expression of Interest from a University from Italy to establish technological cooperation in order to adopt products from biomass waste for new application in agriculture. This matchmaking done by EIICM, was one of the successful solutions to provide assistance to an individual researcher and author who never knew how to expand its knowledge and inventions in the foreign markets and to get real benefits. The second story is about assisting an SME to expand its own developed technology for production of hard cheese type Gauda. A Macedonian SME has developed a technology for production of specific type of hard cheese and asked for assistance to promote this technology abroad. One Croatian University expressed interest to cooperate with this SME. With the assistance of Enterprise Europe Network, we managed to find partner with expertise in modern cheese technologies and particularly technology for hard cheese production. “The cooperation with EIICM enabled us to adopt new technology (know‐how), develop new product and approach regional markets”‐ says the Macedonian researcher. Through the cooperation with EIICM the company got chance to introduce its new high‐added value product on the foreign market and approach regional markets.

6. Discussion and conclusion For the benefits of increasing innovation and competitiveness among the SMEs in developing countries and technology internationalization the institutional support is crucial to build strong relationships among services providers and clients. The visibility of the institution should also be on high level and should be insured to guarantee that SMEs are aware of its activities and services. An internal integrated structure within the institution and developed tools for management system are also essential to ensure delivering and tracking of results. To enable the successful transfer the supporting institution should have competent personnel. The personnel should have clear understanding about the role and how they can assist in the process of technology transfer. A strong factor that has influence on the start and successful realization of the technology transfer is the trust between the innovation support organization and technology giving and receiving party and the trust between

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Viktor Stojmanovski et al. the technology giving and receiving party. This triangle of trust provides a strong ground for technology transfer. Also the wider context has influence on the opportunities for technology transfer. Based on the Global Competitiveness Report 2012 the companies do not invest in R&D and these results in low number of innovation. Furthermore this undermines the opportunity for out‐bound technology transfer from Macedonia to other markets. To overcome this position and increase the number of out‐bound technology transfers it is needed to develop and strengthen innovation support organizations that will work on with the companies on development of new technologies.

References Andriopoulos, C. & Dawson, P.M.B., 2008. Managing Change, Creativity and Innovation, SAGE Publications Ltd. Dalziel, M., 2010. Why do innovation intermediaries exist. In 2010 DRUID Conference, London, UK. http://www2. druid. dk/conferences/viewabstract. php. Available at: http://www2.druid.dk/conferences/viewpaper.php?id=500976&cf=43 [Accessed April 10, 2013]. Doloreux, D. & Melançon, Y., 2009. Innovation‐support organizations in the marine science and technology industry: The case of Quebec’s coastal region in Canada. Marine Policy, 33(1), pp.90–100. Edquist, C., 2001. The Systems of Innovation Approach and Innovation Policy: An account of the state of the art. In DRUID Conference, Aalborg. pp. 12–15. Available at: http://folk.uio.no/ivai/ESST/Outline%20V05/edquist02.pdf [Accessed April 10, 2013]. EIICM, 2010. Technical Implementation Report (1/1/2008 to 30/6/2009) EIICM, 2012. Technical Implementation Report (2011‐2012) Heydebreck, P., Klofsten, M. & Maier, J., 2000. Innovation support for new technology‐based firms: the Swedish Teknopol approach. R and D Management, 30(1), pp.89–100. Howells, J., 2006. Intermediation and the role of intermediaries in innovation. Research Policy, 35(5), pp.715–728. Inkinen, T. & Suorsa, K., 2010. Intermediaries in Regional Innovation Systems: High‐Technology Enterprise Survey from Northern Finland. European Planning Studies, 18(2), pp.169–187. Invest in Macedonia, 2011. Small and medium size enterprises in Macedonia. http://www.investinmacedonia.com/ [Accessed August 10, 2011] Jashapara, A., 2004. Knowledge Management: An Integrated Approach, Essex: Pearson Education Limited. Karp, T., 2006. Transforming organisations for organic growth: The DNA of change leadership. Journal of Change Management, 6(1), pp.3–20. Kubeczko, K., Rametsteiner, E. & Weiss, G., 2006. The role of sectoral and regional innovation systems in supporting innovations in forestry. Forest Policy and Economics, 8(7), pp.704–715. Lant, T.K. & Mezias, S.J., 1992. An Organizational Learning Model of Convergence and Reorientation. Organization Science, 3(1), pp.47–71. NBRM. 2011. Foreign trade. http://www.nbrm.mk/?ItemID=EA9313A61C028F44B00B681EF302F59D [Accessed August 10, 2011] Romanelli, E. & Tushman, M.L., 1994. Organizational Transformation as Punctuated Equilibrium: An Empirical Test. The Academy of Management Journal, 37(5), pp.1141–1166. Schwab, K. (2012), The Global Competitiveness Report 2012 – 2013, World Economic Forum, Geneva, Switzerland Trott, P., 2011. Innovation Management and New Product Development 5th ed., Prentice Hall. The World Factbook. https://www.cia.gov/library/publications/the‐world‐factbook/geos/mk.html [Accessed April 10, 2013]

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How SMEs Mitigate Risks When Embarking in Open Innovation Projects Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) Academy of Economic Studies, Bucharest, Romania ad_tantau@yahoo.com eliza.paicu@yahoo.com Abstract: SMEs are the engine of economies but slightly overlooked in the open innovation literature, which provides a scarcity of studies on the risks residing in open innovation projects involving SMEs and even fewer attempts to assess the mitigation potential of these dangers Moreover, there is a limited amount of research on the innovation practices of SMEs located in Eastern European countries. In Romania, we were not able to identify one single study reflecting the extent of open innovation projects in SMEs and the risks they face, which led us to attempt to cover this gap. What allures SMEs to embrace open innovation is their resource deficiency, insufficient abilities to explore and exploit technology, major knowledge gaps and the objective of minimizing the risks of innovation. The limited literature written on SMEs and open innovation highlights the motives, the benefits and the barriers these engines of economy confront when embarking in open innovation projects. However, no particular attempt to further the research into managing and mitigating the effective risks triggered by open innovation in SMEs was found. Based on a survey conducted on 211 Romanian SMEs in the Romanian financial services and consultancy sector, this paper both explores the risks affecting the innovation performance of SMEs in collaborative relationships, and seeks to provide a conceptual model for overcoming these threats. Within the survey, our work highlights that open innovation in Romanian SMEs is impeded by risks related to insufficient financial resources, inexperienced, unmotivated and unwilling to cooperate people, poor adaptation to technological advances in the industry, knowledge sharing risks, weak social capital and noteworthy regulation risks. All the risks identified through our research were mapped down in seven categories of risk drivers, with internal and external origin: workforce, collaboration itself, organizational culture / social capital, regulations and market barriers, clients, access to finance, technology advances. The risk mitigation model is centred on the SMEs key strategic advantages: high flexibility, ability for adaptation, people empowerment. The research results support the potential of mitigating risks SMEs face in open innovation projects, and indicate six factors as main risk mitigators: transparent communication among innovators, trust building, people empowerment, organizational learning and investment in knowledge, leadership, vision and convictions, proactiveness towards unethical behaviour. The results of our study can guide an SME to competitive advantage, parting both from the essence of collaboration in the scope of innovation, as well as from the challenge of efficiently managing the risks the process involves. Our model is appropriate to benchmark a financial sector SME. By undertaking this study we aim to contribute to the scarce literature on open innovation practices in Romanian SMEs and to shed light on the factors that a firm needs to approach in order to foster a culture for innovation and, in the same time, reduce the open innovation risks. Keywords: open innovation, SME, risks, innovation performance, collaboration

1. Introduction According to Chesbrough (2003), open innovation highlights the innovative potential of external factors, since valuable ideas can come from inside or outside the company and can go to market from inside or outside the company as well (Chesbrough, 2003). Although the phenomenon of open innovation has increasingly captured the attention of many researchers, we found few studies addressing open innovation from the SMEs perspective and even fewer which deal with this innovation strategy from the risk management point of view. SMEs concentrate the majority of employees and revenues both at European level as at country level, respectively in Romania. The Romanian SME sector consists in 5 million employees (67% of total people employed in enterprises), 100 billion EUR revenues and almost 500.000 companies. The figures suggest a strong innovation potential for SMEs, which hasn’t been yet studied in accordance to their power to mitigate risks encountered in the innovation process itself. According to the Innovation Union Scoreboard 2011, Romania is a modest innovator with a below average performance and one of its majors weaknesses are SMEs introducing product or process innovations and SMEs collaborating with each other, scoring half on EU27 average. This low innovation performance of Romanian SMEs is also correlated with the scarce literature written on the impact of external cooperation on the innovation of Romanian SMEs and especially on their potential of efficiently managing the risks this cooperation involves. To our knowledge, studies focusing on external sources of knowledge as “innovation gateways” for SMEs are relatively scant. Moreover, there is a limited amount of empirical research on the

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) innovation practices of SMEs located in Eastern and Western European countries (Lasagni, 2012). This paper aims to address these research gaps. Given the overall sparse attention given to the dark side of SMEs open innovation form the risk management perspective, we consider worth addressing this deficiency through the challenge of defining first a framework of risks encountered by SMEs in external partnerships and then by defining a theoretical risk mitigation model, moulded on the risks framework we have built.

2. Main purpose of the research Gassmann et al. (2010) emphasizes that SMEs are the largest number of companies in an economy, but they are under researched in the open innovation literature. This article focuses on open innovation risks in SMEs, first seeking to place the concepts of open innovation and risk management in the context of SME, secondly to define a comprehensive structure of internal and external risks residing in open innovation and which are more weighty for SMEs than for larger companies, and thirdly to raise awareness on the factors that help mitigate the risks met by SMEs in their innovation process. Finally, it builds up a theoretical risk mitigation model on the feedback of 211 SMEs which answered to our cross‐sectional survey. The research results support the importance of risk management in open innovation in SMEs, by proposing transparent communication among innovators, trust building, people empowerment, organizational learning and investment in knowledge, leadership, vision and convictions, proactiveness towards unethical behaviour as main factors that need to be addressed in external partnerships involving SMEs in order to avoid the imminent risks. Using a structured questionnaire survey, this paper examines the innovation activities of 211 Romanian SMEs and their awareness of the importance of risk management in the innovation process. We intend our study to make the path for future researches in the risk management area of open innovation in SMEs, analyzed on the background of the developing countries.

3. Theoretical background 3.1 Open innovation risks for SMEs Advocates of open innovation tend to stress benefits, implying that we currently have a limited understanding of the costs of openness (Dahlander and Gann, 2010). As extensive the field of open innovation research is, as diverse are the threats that reside in this open innovation context. Inter‐firm collaboration can thus lead to new risks and threats as well as transaction cost (Lee at al., 2010). The scarce literature written about involvement of SMEs in open innovation projects is more focused on highlighting the barriers for a firm to approach open innovation rather than on depicting the risks which accompany such collaborative arrangements. Then, while generally scholars have focused their research of risks in open innovation on large companies rather than SMEs, there is little knowledge on how the magnitude and impact of open innovation threats are distinct for smaller firms than for larger companies. In our review of literature, we show what impedes a company to perform while involved in external collaborations, regardless of its size. Afterwards, in our practical research, we have specifically addressed these open innovation risks from the SMEs point of view, through our cross‐sectional survey, creating a risk framework designed with the input of SMEs managers. Researchers argue that the following disadvantages can make open innovation less attractive for innovators: secrecy concerns (Thomas and Trevino, 1993); problems in division of contributions and outcomes of cooperation (Keupp and Gassmann, 2009); outsourcing critical dimensions of business (Dahlander and Gann, 2010); developing dependency on partners, loosing technological competence, slowing down self‐ development of innovation (Brockhoff and Brockhoff, 1992); dealing with many sources and ideas at any given moment of time (Laursen and Salter, 2006); difficulty in choosing and combining between numerous alternatives (Laursen and Salter, 2006); difficult to maintain large number of partnerships with different actors (Ahuja, 2000); risk of selecting wrong partners (de Vrande et al., 2009); difficulty in balancing innovation with daily tasks, communication, aligning of partners, organisation of innovation (de Vrande et al., 2009); bureaucracy and conflicting rules (de Vrande et al., 2009); not invented here (NIH) syndrome (Katz and Allen, 1982); organisational resistance and fear of losing control over proprietary technologies (Keupp and

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) Gassmann, 2009); conflicting interests that may alter the message shared‐ a relational risk (Lichtenthaler, 2011); knowledge sharing risks (Islam, 2012); workforce concerns, lack of trust, opportunism. There are a few studies addressing specifically open innovation risks for small firms. Recent empirical evidence on SMEs is provided by Enkel et al. (2009) in a study with 107 companies, equally European SMEs and large enterprises. The study, undertaken in 2008, showed that risks such as loss of knowledge (48%), higher coordination costs (48%), as well as loss of control and higher complexity (both 41%) are mentioned as frequent risks connected to open innovation activities. In addition, there are significant internal barriers, such as the difficulty in finding the right partner (43%), imbalance between open innovation activities and daily business (36%), and insufficient time and financial resources for open innovation activities.

4. Research methodology In order to build the structural risk framework of open innovation risks as well as the theoretical mitigation model, we used a survey which targeted 500 SMEs from the region of Bucharest. In Romania, according to the standard definition of the European Commission, SMEs are firms that hire less than 250 employees and have an annual turnover under 50 million EUR or hold total assets valuing under 43 million EUR. The SME’s targeted in our survey belong in proportion of over 70% percent to the financial sector (non‐banking financial institutions, consultancy firms, insurance firms, money transport companies, IT suppliers). The data were collected via a cross‐sectional survey approach and analyses were done based on 211 questionnaire responses received. The survey was implemented by means of online questionnaire. In this investigation, first respondents were asked to indicate to what extent their firms collaborate with different partners (customers, suppliers, competitors, government agencies, intermediary institutions, and research organizations) in order to boost their innovation potential. The respondents were enquired about their reasons for involving in open innovation projects and barriers to enter such agreements. Furthermore, they were asked to record the main risks encountered during the external partnership and best ways to handle those risks, from their experience. Given the scarce research on the subject approached, we employed open‐ ended questions in our questionnaire. In the second round of our survey, we used the cross‐impact analysis to determine the magnitude and the likelihood of impact of six mitigation variables we asked the respondents about, in correspondence to the main risks identified. The six mitigation factors were assessed with a 5‐point Likert scale, from “1” being “very low” magnitude / possibility of impact upon the structured seven risks to “5” being “very high”. We have chosen the Cross‐Impact Analysis since is a powerful tool for taking a set of events and examining the potential causal impacts that each event may have on others in the set.

5. Research experiences 5.1 Open innovation risks framework for SMEs The open innovation literature shows that the paramount benefit for firms entering collaboration projects with innovative purposes is risk sharing. At the same time, collaboration inherently brings along risks and costs. Our research distinctly points out to a paradox: even if the major motive for SMEs to embark in open innovation projects is risk sharing, in these collaborations may also reside threats that distort the initial objective of pursuing innovations and competitive advantage. An open innovation strategy aims at decreasing the risk inherent to the innovation process but at the same time it may increase the risk inherent to collaboration with different partners. The results of our survey show that that open innovation in Romanian SMEs is impeded mainly by risks related to insufficient financial resources, inexperienced, unmotivated and unwilling to cooperate people, poor adaptation to technological advances in the industry, knowledge sharing risks, weak social capital and noteworthy regulation risks. In order to build a structured risk framework, we mapped down all the risks identified throughout our research into seven broad categories of risk drivers, with both internal and external origin: workforce, collaboration among partners, technology advances, regulations and market barriers, clients, access to finance, organizational culture / social capital. Table 1 depicts the major internal risk drivers for a small company collaborating.

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) Table 1: Internal open innovation risk drivers for SMEs

People related risks are regarded as highest threats by our respondents, since they are the major actors and assets in collaboration projects. Romanian SMEs that innovate are characterized by a shortage of skilled employees who don’t possess critical knowledge in order to manage an open partnership and the new knowledge acquired. Their safety mentality, reluctant to change and innovation, acts as a major risk and its impact is even greater when it is a translation of the top management’s attitude, which shows little support for innovation and low awareness of risks. Under‐trained workforce is a threat for a small firm since it builds up a knowledge barrier from the firms it collaborates with. Lack of trust and adversity to change is often accompanied by internal poor work ethic, which creates an environment which is poorly prepared to absorb and integrate external ideas and technologies, translated into what is very common for SMEs, low absorptive capacity. Our survey revealed that many SMEs have a poor organizational culture, insufficiently oriented towards collaboration and innovation, marked by fear of losing control over its own technologies or knowledge, a sign of poor social capital. SMEs also claim inadequate distributive skills when entering external partnerships, since they find it highly difficult to manage the external innovation process with the daily, routinely tasks, a deficiency which often has a great impact on how they rapidly address the needs of the customers. Table 2 illustrates what external risk drivers are considered most noteworthy for the small companies we surveyed. The external risk drivers can be mapped down to five categories: regulations in the industry and market barriers, clients constantly changing demands, collaboration with partners, difficult access to finance and adaptation to technology advances. Table 2: External open innovation risk drivers for SMEs

A significant part of the questioned SMEs are from the financial sector, which bears a high dependency on national regulations in the field, often burdens for smaller firms unable to cope with the costs entailing volatile regulations, It is also the general case of ambiguous regulations which affects the efficient activity of open agreements, resulting in higher transaction costs. Highly specific to emergent countries, unethical behaviour is common and acts a major business risk, as highlighted by the firms interviewed, facing several corruption issues in regards to their partners collaboration and as well related to state administration bodies. Open innovation is also impeded by a high level of bureaucracy and SMEs find it harder to cover the administrative costs entailed in the external partnerships. The respondents also blamed they couldn’t access key market information properly which generates high

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) commercialization risks. The constant changing needs of the clients require developing strong customer‐ oriented capabilities and a customized offer, which imposes equal constraints on costs and possibility of fast adaptation to the market. One of the major concerns of SMEs involved in collaboration with competitors is related to knowledge sharing: possibility of information leaks regarding valuable internal technologies, key knowledge spilling over to the partner, insufficient protection of intellectual property. This attitude is strictly correlated with the lack of trust in the partner and poor communication among collaborators about common goals and strategies, which finally impedes the innovation process and the performance of the alliance. Opportunism is regarded as high threat for the surveyed SMEs. Even if SMEs partner in order to reduce costs and gain access to a larger pool of resources, they state than even the partnership lacks sufficient financial resources to fund the innovation process. Lack of financial capital is high on SMEs concerns.

5.2 Open innovation risks mitigation model The factors which determine a SME to reduce the threats residing in opening the innovation process are derived from the SMEs structural advantages over large firms, which allow them to cope better with the risks of collaboration: size, speed and flexibility, power of adaptation, entrepreneurial orientation, business specialization, focus, transparency, people empowerment. Small firms are more flexible which enhances rapid adaptation to market shifts, technological advances or to partner requirements. SMEs can specialize their businesses in niche markets and focus on innovative activities on those markets. This is correlated to the entrepreneurial potential of SMEs, which holds both innovation and risk taking as strategic drivers. SMEs have strong and close relationships with their customers, permanently meeting their interests by customizing their offer. Usually, small firms are perceived as having little bureaucracy but this was not cohesive with our research findings. They communicate rapidly with their business partners and have a dynamic management style, more open to innovation. Once more, the results of our survey didn’t validate this general perception since most of SMEs depicted closed mentality management styles, reluctant to change and open communication.

Figure 1: Open innovation risk mitigation model Parting from these advantages SMEs have over larger companies, based on the practical input offered by the 211 respondent SMEs we have further built a theoretical risk mitigation model for SMEs involved in open innovation partnerships, as depicted in Figure 2. This conceptual model shows the key environments

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) important for SMEs in the innovation process, respectively how the main proposed factors address different type of risks, creating a web of risk management in order to increase open innovation performance. There are multiple interactions among the seven proposed risk mitigation factors and the main risk groups identified, further explained. During our research we found that increased entrepreneurial orientation limits the risk of open innovation. Fostering an organizational culture focused on people empowerment and development of workforce skills can boost the SMEs potential for innovation while involved in external partnerships and, in the same time, limit the risks encountered. Highly skilled entrepreneurs reduce the knowledge sharing risks. If people understand the impact of their work on the innovation partnership, the innovation performance will improve and risks better managed. Open innovation equals transparent communication among partners, which enables them to reduce knowledge risks, collaboration risks and misinterpretations of information inside the firm. SMEs questioned were little aware of the importance of this variable but acknowledged the fact that communication stands as a powerful tool to transfer risk information among members of a project team. Hence, communication enhances the risk knowledge sharing among innovation partners, thus improving the risk management process with the knowledge component. Collaboration with innovation partners is based on trust principles and strong personal relationships among partners. A key factor contributing to reducing the risks residing in open innovation is trust built among partners. It is all reduced to how much people choose to open when partnering, or how they use the knowledge gained. In order to avoid risk, they may have to embrace the risk of investing trust in their partners, in order to be successful. Trust translates as a key success factor for competitiveness and building a climate of trust inside the partnership mitigates the knowledge sharing risks. By adopting a customer‐centric approach, SMEs can significantly shift towards involving the client in the process of open innovation by tailoring the products and services on their individual needs and feedback. Continuous learning also ensures rapid adaptation to the changes in regulations affecting the open innovation agreements and a more speedy orientation towards sources of financing. It has also a direct effect on knowledge protection: by obtaining, assimilating, transforming and utilizing external knowledge to innovate, through constant learning, SMEs are better able to protect their intellectual property and to reap the rewards from partnering for innovation purposes. An increase of training costs should also lead to lower transaction costs. Our survey revealed that organizational learning is the only variable that addresses all type of risk in our structural framework, highlighting the importance of investment in knowledge SMEs should place. Clear leadership is needed in order to ensure the pursuit of the partnership’s strategic objectives by providing clear rules, strong vision and ensuring discipline of the collaboration agreement. Strong leadership defines the roadmap and sets attitudes examples for the workforce involved in open innovation. Even if financing the open project remains a constant concern, guidance is essential for making sure the partners use their professional advantages to increase the financial sources. Because of widespread unethical business practices, SMEs refrain from co‐operation. Fostering a social capital which supports ethic behaviour among partners or among the actors in the open innovation process and the state administrative bodies ensures the development of a culture that excludes corruption. Since in Romania corruption is listed as the most important problematic factor for doing business, cultivating work ethic acts upon workforce quality, collaboration performance and upon building a culture based on trust among partners. Through the proposed model we assert that workforce, collaboration and organizational culture risks are more addressed to than the other open innovation threats and show a highest mitigation potential, while access to finance is much harder to be mitigated in the Romanian background. Furthermore, few tools to reduce the threats imposed by technology advances are within reach for small firms.

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5.3 Validation of the open innovation risk mitigation model In our second round of surveying, we have defined six variables that we considered as having major influence in reducing open innovation risks and we asked our 211 respondents about the magnitude and impact of mitigation of these factors on the structured seven main risks. We thus enquired how people empowerment, trust, communication, leadership, learning and ethic behaviour determine a decrease in risks brought about by workforce, organizational culture, collaboration itself, regulations and market barriers, clients, access to finance and technology advances. The six mitigation factors were assessed with a 5‐point Likert scale, from “1” being “very low” magnitude / possibility of impact upon the structured seven risks to “5” being “very high”. Our goal was to assess which of the six factors might have the greatest mitigation impact upon the main threats identified, and which of these risks present the highest potential to be reduced. In order to assign initial probabilities of these risks being mitigated, but also to provide the scale of impact of the six variables and their conditional probabilities, we used the integrated results of the questionnaires. As shown in Figure 3, the first step in our cross‐impact analysis was to estimate initial probabilities of mitigation for the seven types of risks, considered to be independent of one another. These initial probabilities range from 0.10 to 0.85. The six column variables consist in the factors considered to help mitigate the risks identified. Thus, we analyze what is the magnitude of impact of the proposed mitigators towards the seven risk groups.

Figure 3: Trend value matrix For the trend value cross impact matrix we used a scale of 1 to 5 to indicate the level and direction of impact of the six variables. Conditional probabilities, as presented in Figure 4, range from 0.05 to 0.90. The conditional probabilities matrix must be interpreted as such: "if the column events were to occur, then what would be the probability of impact of risk mitigators on the seven types of risk?” The conditional probabilities are assessed by integrating questionnaire results.

Figure 4: Conditional probability matrix The likely cross‐impact matrix represents a multiplication of the trend value matrix and conditional probabilities matrix, as presented in Figure 5. Then, by multiplying this resulted matrix with the initial probability vector, we obtain the expected mitigation impact of each of the six critical variables: people

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) empowerment, communication, trust, learning, leadership, ethic behaviour, as well as the main probabilities of occurrence of the seven risks.

Figure 5: The likely cross‐impact matrix The results emphasize that the risks with the highest potential to be addressed to are collaboration risks, workforce deficiencies and organizational culture risks, considering the highest three impact scores in the matrix: 14,9, 19,2, 13,8. SMEs perceive people related problems to impede the most the innovation potential; additionally our findings support the idea that the human resources deficiencies are the first to be addressed in a risk management strategy. On the other hand, access to finance is a subject hard to be tackled in the Romanian business landscape, SMEs considering this risk the hardest to overcome. We have also empirically tested which of the six risk mitigation factors proposed have the greatest power to diminish external innovation problems. We found that organizational learning and a continuous investment in knowledge diversity results in fewer people related risks, collaboration deficiencies and organizational culture risks. Learning has the greatest impact on workforce deficiencies and it results to be less efficient in trying to overcome insufficient financial resources problems. Alternatively, people empowerment was found to have the lesser power of open innovation risks, especially those related to regulations, technology advances and access to finance. Our research on collaboration risks encountered by firms innovating together highlights the pressure on personnel quality and innovation proneness, top management’s attitude towards risks and innovation, work ethic and string leadership and vision. These findings centred around organizational culture risks are cohesive with the significant work of De Vrande et al. (2009), who asserts that organization and corporate culture‐ related issues that typically emerge when two or more companies are working together are clearly the most important barriers/ that firms face when they engage in open innovation.

6. Conclusion The use of external relationships is increasingly interpreted as a key factor in enhancing the innovation performance of modern enterprises (Lasgani, 2012). Therefore, it can be argued that the ability to access external knowledge resources efficiently and overcoming the risks encountered in the process can become a huge competitive factor for SMEs. On the basis of a sample of 211 SMEs, this paper has empirically explored the risk agenda SMEs encounter in the process of open innovation, specifically pointing to some factors which help decrease the threats. Our findings provide important implications for managers concerned with the risk management of innovation cooperation. Within the survey, our work highlights that open innovation in Romanian SMEs is impeded by risks related to insufficient financial resources, inexperienced, unmotivated and unwilling to cooperate people, poor adaptation to technological advances in the industry, knowledge sharing risks, weak social capital and noteworthy regulation risks. The research results support the potential or organizational learning and investment in knowledge, of solid leadership and ethical behaviour to help cope with the risks smaller firms encounter in external partnerships. On the other hand, access to financing is fund to be difficult even in collaboration agreement. None of the six mitigation factors were proven to have significant impact on reducing the financing risk. Also, SMEs don’t possess enough tools to overcome the market changes risks, the regulations burden or the technology advances which need rapid adaptation to.

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Adrian Dumitru Tanțău and Eliza Laura Paicu (Coraş) The limitations of our study were given by the relatively small sample of SMEs surveyed, in a specific region of Romania. Moreover, the risk mitigation model was defined based on six factor we have provided through the questionnaire, which may have biased the respondents since other influential mitigators could have been identified. As a consequence, we cannot claim that our survey data capture the full domain of external innovation risks. We thus recommend further research on risk management in the case of SMEs open innovation, by expanding the number of firms investigated and furthermore examining the findings in different emerging markets in order to adapt the risk framework.

References Brockhoff, K. and Brockhoff, K. (1992) „R&D Cooperation between Firms‐A Perceived Transaction Cost Perspective”, Management Science, 38(4), pp.514‐524 Chesbrough, H. (2003) “Open Innovation”, Harvard Business School Press, Boston, pp. 43‐62 Dahlander, L., and D. M. Gann (2010) “How Open Is Innovation?”, Research Policy 39 (6), pp. 699–709. De Vrande, V. et al. (2009) “Open innovation in SMEs: Trends, motives and management challenges”, Technovation, No 29, pp. 423–437 Enkel, E., Gassmann, O., & Chesbrough, H. W. (2009) „Open R&D and open innovation: Exploring the phenomenon” R & D Management, 39(4), pp. 311–316. European Commission (2008) The New SME Definition: User Guide and Model Declaration. Enterprise and Industry Publications, European Union Publications Office Gassmann, O., Enkel, E., and Chesbrough, H. (2010) ‘The Future of Open Innovation’, R&D Management, Vol. 40 No. 3, pp. 213‐221. Innovation Union Scoreboard 2011 (2012), European Commision, http://ec.europa.eu/enterprise/policies/innovation/files/ius‐2011_en.pdf Islam, A. (2012) “Methods of Open Innovation Knowledge Sharing Risk Reduction: A Case Study”, International Journal of e‐ Education, e‐Business, e‐Management and e‐Learning, Vol. 2, No. 4 R.Katz, T.Allen, (1982) “Investigating the Not Invented Here (NIH) Syndrome: a look at the performance, tenure and communication patterns of 50 R&D project groups”, R&D Management, Vol.12, No. 1, pp.7‐19 Keupp, M.M. and Gassmann, O. (2009) „Determinants and archetype users of open innovation” R&D Management, 39(4), pp.331‐341. Lasagni, A. (2012) “How can external relationships enhance innovation in SMEs? New evidence for Europe”, Journal of Small Business Management 50 (2), pp. 310–339. Laursen, K, and Salter, A. (2006) “Open for innovation: The role of openness in explaining innovation performance among U.K. manufacturing firms”, Strategic Management Journal 27, no. 2, pp. 131–150. Lee et al. (2010) “Open innovation in SMEs ‐ An intermediated network model”, Research Policy, No 39, pp. 290 – 300 Lichtenthaler, U. (2011) “Open innovation: Past research, current debates, and future directions,” Academy Of Management Perspectives, vol. 25, no. 1, pp. 75‐93 Markman, G., Phillip, P., Balkan, D., and Ganoids, P. (2005) “Entrepreneurship and university‐based technology transfer”, Journal of Business Venturing, 20 (2): 241‐263. Thomas, J.B. and L.K. Trevino (1993) „Information‐Processing in Strategic Alliance Building: A Multiple‐Case Approach” Journal of Management Studies, 30, 779–814

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How Planguage Measurement Metrics: Shapes System Quality Man‐Chie Tse1,2 and Ravinder Singh Kahlon 1,2 1 dkode Limited, London, UK 2 University of Ulster, Ulster Business School, Northern Ireland, UK Man‐Chie@dkode.co Ravi@dkode.co Abstract: It is known for innovative IT projects in the public sector healthcare within the UK to fail and disappoint. The announcement of National Programme for IT (NPfIT) is an example, at a cost of £12.7 billion that ended. The problem of IT projects failing have a destructive impact on wasting resources and at the socio‐economic cost to the tax payers. The aim of this paper is to improve the understanding and inter‐relationship qualities between people, process and technology. A quality healthcare innovation project was to consign new improved services and processes to be more efficient and to deliver value to the stakeholders in a competitive sector. The starting point for quality healthcare innovation to take place, two key elements are required, (1) ideas and (2) the implementations of those ideas that bring the innovation process to fruition and gain benefits to the healthcare organisations. The architect ideas need to be implemented into practice to become a practical reality for innovation to transpire and thrive. The underlying problem within the literature review, of introducing new innovative IT systems implemented, focus on functionality and fail to acknowledge measuring production, efficiency and linking to performance. The challenges are cultural changes, expertise of knowledge, technological advances and practice methods. Furthermore, the poor state of challenges is hindered by inadequate understanding and clarification of requirements analysis in IT projects. An innovative public sector healthcare IT project was successfully delivered using the software engineering management methods by Tom Gilb. The empirical use of Planguage a formal, natural language modelling notation, a quantifiable measurement metrics, addressed the problem area of system innovation within the software engineering discipline. The paper establishes how the technique could integrate towards the risk concepts of introducing a new software system including building quality of performance and design within, as often, aftermath, system innovation quality is ‘designed on top’ rather than ‘designed within. The quantified approach is illustrated by describing Planguage concepts and Impact Estimation method that is fundamental towards evaluation of system management – design, people and control processes to analyse and transform. This method enables addressing stakeholder value and viewpoints more visually and explicitly. Further recommendation is subsequently addressed for future exploration works. Keywords: healthcare innovation, public sector, stakeholder, planguage, measurement metrics performance

1. Introduction The notion of system quality is not as simple as it may seem. Engineering system solutions and delivering successful IT projects have been challenging for the UK public sector healthcare. To engineer a system which delivers the performance expectation, several characteristic qualities are desired, relevant to the perspective of the system value. However, many system designs struggle in handling of quality attributes designed into the system. The concept of quality has been contemplated throughout and still remains an intense topic today. Quality has been addressed in numerous academic and organisation reports and various definitions are yielded. For example, conformance to requirements (Crosby, 1979), fitness for use (Juran, 1989), or “a set of inherent characteristics fulfils requirements” (ISO.org, 2013). The aim of this paper sets to address the importance of designing system quality to support both a process and conceptual innovation to deliver radical change in streamlining performance. The objective of this paper explores the role and application of Planguage, a measurement metric technique. The structure of the paper begins with an overview of digitalising healthcare followed by a case study definition. The case approach is then applied by describing Planguage and Impact Estimation method highlighting design of system performance behaviour to better support the project strategy and shape system quality. The last section concludes with evaluation analysis recommendation on how the technique of the model could play further.

2. The digitalisation of healthcare Digitalisation is utilised in vast volume areas within the healthcare, for example, archiving electronic medical records and medical images, CT Scanners and MRIs to initiate exploratory surgery. An early background review of the digitalisation era and the profound impact analysis in higher education context can be found in Kahlon & Tse (2009) paper.

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Man‐Chie Tse and Ravinder Singh Kahlon With the current economic situation, resources are going to be limited for some time. This brings more challenges to the UK public sector healthcare which means the need to find better innovative ways of delivering services as well as to ensure change will happen. With the advances in technologies, digitalisation provides many opportunities and will continue to drive information in a more sophisticated manner. However, this has generated considerable and useful debate about capability, pace, ambition and inevitably, affordability into question.

3. Case application and methodology This section provides an overview of a healthcare case application and methodology undertaken alongside the process, design and scope.

3.1 Problem background and case definition The nature of today’s environment endures rivalry to be more condensed. The demand for service over the years are dramatically increasing year on year. At present, a fragmented process of manual completion of request forms and transmission of information from one location point to another exists. The process, very time constrained, is no longer a sustainable for the modern age. In addition, instead of utilising employees empowered skills and expertise domain knowledge, providing information, counselling advice to ensure optimal treatment, a mundane process utilised over the past 20 years is still in place, causing obstruction to the workflow. This type of model exists in many other UK public sector healthcares and the model limits clinical activities to one centralised area rather than enabling direct delivery care. 3.1.1 Economical analysis The UK public sector healthcare organisation(s) must find ways to increase productivity. The Quality, Innovation, Productivity and Prevention (QIPP) programme requires England’s healthcare trusts to find efficiency savings of £20 billion by 2014‐2015 and innovation is vital for economic growth. Moreover, local commissioners are placing financial pressure, requiring healthcares to deliver effective services (National Audit Office, 2011; NHS, nd; NICE, 2013; Gov.UK, 2013). There is now a critical mass challenge set by the UK Government to enable digital and go paperless by 2018 to save billions, improve services and obtain efficiency gains. Furthermore, digital information can be used to support various levels of professional stakeholders, in the work environment. If healthcare organisations wish to remain competitive to cover the cost of existing processes and utilise new technology, each will have to offer imperatively, a unique innovative and personalised service.

3.2 Process of study and design scope The objectives of the research were to determine how shaping and designing quality into a new innovative system could improve performance and cost savings for the workforce. Innovation was essential to survive and improve the organisation service by enabling an effective and efficient process. In order to manage and introduce a new system and facilitate innovation to happen, understanding the different ways in which the existing work flow in place operated was important. The process flow was broken down into 3 levels, efforts and measurements were concentrated upon and obtained. Planguage and IE table, which is described in more detail in the next section, was adopted in supporting to quantifying the work flow problem. Exploratory research such as information flow, observation’s, time measures, effects of process delay and interviews was obtained through action research. A systematic review was also conducted on past records to determine the eradication of inefficiency in errors categorised by type and severity over two month duration. Also, a review of practices was conducted to coordinate efforts to share experience and know‐how to harmonise best practices. This enabled understanding people perspective between the type of innovation important and the level of learning required to manage training. The existing process and workflow mainstream activity in the organisation was relatively high risk in volume.

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4. Using planguage in healthcare Planguage (Planning Language) developed by Tom Gilb, was designed to quantify qualitative statements. The use of Planguage arranges qualitative statement into a decomposed hierarchy format. Three fundamental performance types are derived from Planguage, (1) potential resource saving, (2) workload capacity and (3) precision of quality (Gilb & Graham, 1994; Gilb & Finzi, 1998; Gilb 2005). Figure 1 illustrates a selection of system performance requirements in specific to the case study, from a top abstract level broken down to aid more clarity. These three rudiments recognises the expression of a stakeholder’s working practice perspective which are reflected and designed as objective value measures into the system. Planguage comprises 7 stages (Figure 2) to facilitate in specifying the performance attributes. Using the established 7 steps, an impact estimation was formulated which is described in the next section.

Figure 1: System performance characteristics

4.1 Evolving an impact estimation table An Impact Estimation (IE) table encompasses 5 elements (Figure 3), presented in a matrix tabular form. Objective requirements are analysed against impact designs of a system at a particular point in time, but also conforming to costs and duration. The matrix highlights a risk overview of alternative design ideas, either part of system architecture or a whole in comparison to system requirements. An IE provides a two‐fold interrelationship. Firstly, in order to understand and express system quality, the three primary questions required are (a) Who are the stakeholders of the system? (b) What are their objectives or requirements and (c) What resources are available? By establishing and providing responses, a system quality criterion is premeditated to determine the level of improvements in supporting the organisation, people, processes and policy. Secondly, target levels provide a representation in realistic terms of the past, present and future benchmarks. The levels are set on the basis of a collaborative stakeholder agreement to ensure the performance levels strived for are achievable. The information collected, indicated where the impact was the most important and to which stakeholder(s). Using collated information, the performance requirements were allocated down the left hand side column outlining the past level and goal target level. This facilitated comparative measures utilising present information based on facts and compare alternatives. Weaknesses were also discovered to determine the level of contribution the part played.

4.2 Shaping the system The goal of introducing a new system is a major ambition for faster, safer and better delivery of services. The system was engineered and designed to mobilise the workforce, be intuitive, user friendly as well as easy to

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Man‐Chie Tse and Ravinder Singh Kahlon learn. After applying the principle of Planguage and IE table, the quantified results were associated as impact relationships to design in (see Appendix A). The modelling language incorporated performance of the operational processes more effectively, tailoring components to new goal circumstances successfully. Figure 4 shows an IE table of the healthcare system based on captured measurements during action research.

Figure 2: 7 Stages of planguage The three core system architecture objectives were derived (Automate rules, Web self‐service and Decision support) with design requirements (Figure 4). These determined in terms of probable impact alongside which objective provided benefit advantage and where the budget were constrained towards. In this system design, the objective of a web self‐service required 25% of the budget and provided a higher benefit to cost ratio of 6.44. Decision support came second with ratio of 3.51 to enable greater reaction in decision making, whilst

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Man‐Chie Tse and Ravinder Singh Kahlon automating rules came last, required a higher budget allocation and time, but returned a benefit cost of only 2.5.

Figure 3: Impact estimation

Figure 4: Healthcare system impact estimation table

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5. The outcome of the research The existing process efficiency rate effect was running at capacity of 28%, conversely, the implementation led to a level change impact increase between 47% ‐ 50%. Adding innovation to the process has been a multi‐ player game. This involved the need to marry political, technological, environment and legal into creating new services and processes, reducing waste, and changing service delivery, switching from paper to digital correspondence. The study has shown the designed system for the organisation increased productivity of transition of workflow to improve quality and make better use of the skills and expertise knowledge of staff. The incidences of errors were significantly reduced as these were designed into the system rather on top. Fostering new technologies contributed to achieve operational efficiencies, avoiding bottlenecks and streamline work flow to enable more fully interaction with patients. This cohesive system acts as a standardised engine driver of innovation and changing the way employees create, and collaborate with patients at ward level, and most importantly, utilise collective productive resources at a mobility level more effectively and efficiently.

5.1 Limitations of findings The study has limitations; firstly, it was conducted in only one healthcare, which could reduce the generalisation of the findings to other healthcares. However, because the work flow process and findings of errors is of similarity occurrence to other healthcares, it is highly probably that comparable beneficial effects will be achieved when applied to other healthcare settings. In acknowledgement, this study is the first that has investigated the effect of a system into phase one of the three interrelated process levels.

5.2 Evaluation of planguage and impact estimation The value of Planguage technique provided strong identification between the distinction of natural language (people) and system (technology) which enabled a correspondence between process (cause) and system (effect). Analysing the current process produced a dimensional representation of people, process, technology and policy. These four elements are central to system innovation in a healthcare orientated environment as well as modelling static domain knowledge. Planguage technique also stimulated predictability where existing process and bureaucracy fails or may stifle innovation. The method contributed towards evaluating the design, shaping system quality. The IE table defined a set of transition criteria to assess the strengths and weaknesses of potential design ideas. These were correlated to quantified requirements through introducing appropriate direct estimation measures. This helped to determine the percentage efficacy, through factor analysis, of how viable each impact analysis according to each design from current existing level to target goal – the residual gap. The modelled benchmark spectrum contributed a better understanding in addressing and taking into account credibility and uncertainties on the elected design choices. This contributed to support in avoiding failures from happening and pinpointing neglected areas. Further identification of the strengths and limitations of using the technique is shown in Table 1.

6. Conclusion Introducing of a new innovative system is fundamental to service transformation and a degree of risk is involved in any innovation project. Creating an innovative system requires careful design involving various professional stakeholders working together to create a viable system to deliver truly holistic benefit. However, it is important to undertake innovation as they are just as critical for driving long term success. This paper outlined an approach towards designing quality value, in system analysis, operational and system development, recognising the boundaries and accountability. Table 1: Advantages and disadvantages of planguage & impact estimation Strengths Delivers the qualities required for a system Provides a cost effective analysis conforming towards budget costs Illustrates the value relationship between stakeholders and system requirements Enables comparison measure of gap existence

Limitations Can only account for observed Reflects only a snapshot specific in time Requires large sample of data

Depicts the instance impact areas for vital improvement and areas of weaknesses

Does not reflect causal relationships between observed and unobserved Lower information exposure

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Man‐Chie Tse and Ravinder Singh Kahlon Strengths Pinpoints where potential goal may not be met Strong method to measure value Transforms vague requirements into measured and planned format

Limitations Lack of representation in visual format

The IE demonstrated the tangible value of where investment is up taken most and least in the new innovative system. Both Planguage and IE provided greater clarity on shaping when, how, where and what towards the aspiration of system quality. Also, the context of problems, challenges and the realm reality of existing process were ameliorated to make better decisions. The technique illustrated a measurement metrics and its volatility traces to reach that route, providing to offer a rich base robustness for both informal and formal system quality assurance. As for future works, visualisation of Planguage should be an aspect considered for evolvement.

Appendix A Table 2: Design impact relationships

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References Crosby, P. (1979) Quality is Free. McGraw Hill, New York, USA. Gilb, T. & Graham, D. (1994) Software Inspection. Addison Wesley, USA. Gilb, T. & Finzi, S. (1998) Principles of Software Engineering Management. Addison Wesley, USA. Gilb, T. (2005) Competitive Engineering: A Handbook For Systems Engineering, Requirements Engineering, and Software Engineering Using Planguage. Butterworth‐Heinemann, Oxford, UK. Gov.UK, (2013) Making the NHS more efficient and less bureaucratic [Online]. Available from: https://www.gov.uk/government/policies/making‐the‐nhs‐more‐efficient‐and‐less‐bureaucratic [Accessed: 28/03/2013]. ISO.org (2013) ISO 9000 quality management ‐ ISO. [Online] ISO. Available from: http://www.iso.org/iso/home/standards/management‐standards/iso_9000.htm [Accessed: 25/02/2013]. Juran, J. M. (1989) Juran on Leadership For Quality. Free Press, USA. Kahlon, R. S. & Tse, MC. (2009) The Impact of Digitalisation in Higher Education Libraries. In: Proceedings of the 2009 International Conference on the Current Trends in Information Technology ‐ 15 &16 December 2009, Dubai Womans College, Dubai, U.A.E, Volume 1, No. 1, Pp. 184‐189. National Audit Office (2011) National Health Service Landscape Review [Online]. Available from: http://www.nao.org.uk/wp‐content/uploads/2011/01/1011708.pdf [Accessed: 28/01/2013]. NHS (nd). Everyone Counts: Planning for Patients 2013/14 [Online]. Available: http://www.commissioningboard.nhs.uk/wp‐content/uploads/2012/12/everyonecounts‐planning.pdf [Accessed: 28/03/2013]. NICE, (2013) Quality, Innovation, Productivity and Prevention (QIPP) [Online]. Available from: http://www.evidence.nhs.uk/qipp [Accessed: 28/01/2013].

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A Study of Customer Feedback and Employee Driven Innovation Jiro Usugami School of Business, Aoyama Gakuin University, Tokyo, Japan usugamij@busi.aoyama.ac.jp Abstract: This study examined the practical relationship between customer feedback and implementation of service improvements, the problem solving processes and the way of employee participation in customer feedback, the effects of customer feedback on customer service improvement and firm competitiveness, as well as the bottlenecks for employee driven innovation, in the Japanese hospitality industry, based on three case studies: an airport terminal company; an airline company; and a railway company. Firstly, this study has revealed that the majority of the customers’ opinions gathered in our case studies were related to the desires for richer service and easier transfer, and comments on the perceived inconvenience at the facilities. In response to those opinions, various kinds of service improvements have been fulfilled. Our case studies have established similar and systematic customer feedback consisting of three or four steps of problem solving processes from data gathering to implementation including feedback, and related employees have participated in the entire processes. At the implementation step, the participation of cross‐functional employees is significant. Secondly, this study verified the recognition that customer feedback strongly contributed to customer service improvement and firm competitiveness in the Japanese hospitality industry. Thirdly, we investigated which process to be driven by employees was regarded as the hardest one in the four steps of customer feedback: data gathering; data sharing; implementation; feedback, and what was the important issue in customer feedback. Our case studies evidenced that the hardest step to be driven by employees was implementation or data gathering followed by data sharing. This study observed that the bottlenecks for employee driven innovation included conflicts in the cross‐functional implementation and difficulties in the analyses of any opinions concerning customer services. Keywords: customer feedback, customer service improvement, employee driven innovation, hospitality industry

1. Introduction This study discusses whether customer feedback has contributed to practical customer service improvement as well as firm competitiveness, how employees participate in the problem solving processes, and which process to be driven by employees is regarded as the hardest one in customer feedback of the Japanese hospitality industry (e.g. air business), based on case studies. Customer feedback in this study refers to the various organizational activities performed in response to specific desires, complaints or other various comments received from customers as regards the firm’s products, services and facilities. Customer service improvement in this study is identified as a part of employee driven innovation (EDI) of umbrella concept. EDI refers to “the generation and implementation of significant new ideas, products and processes, including the everyday remaking of job‐related and organizational practices originating from the interactions of employees who are not assigned to a particular task. The processes are unfolded in an organization and may be integrated in cooperative and managerial efforts of the organization. Employees are active and may initiate, support or even drive/lead the process (Høyrup, 2012).” There are numerous previous studies on customer feedback and service improvement. Most of them have been conducted in the field of Customer Relationship Management (CRM) and have shown statistical relationships between customer feedback and its outcomes. A few of them reported the three factor interplay of practical customers’ opinions, employee participation and any service improvement in hospitality industry. The first purpose of this study is to reveal the practical relationship between customers’ opinions and customer service improvement in the Japanese hospitality industry. For this purpose, we examined what specific desires, complaints or other comments received from customers in our case studies had resulted in what kinds of real service or facility improvement. The second purpose is to verify whether CRM has contributed to customer service improvement and firm competitiveness in the Japanese hospitality industry through a questionnaire survey for our case studies. The third purpose is to identify which process to be driven by employees of the Japanese hospitality industry is regarded as the hardest one in the four steps of customer feedback: data gathering; data sharing; implementation; feedback.

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Jiro Usugami One of the features of this study is detailing the relationship between real customers’ opinions and service improvement practically fulfilled in response to them. Many of the previous studies have discussed customer feedback from the business performance aspect. This study has evidenced the incremental innovation processes in the Japanese hospitality industry where specific desires, complaints or other comments gathered in our case studies have systematically contributed to concrete implementation of service or facility improvement. Another feature is the analysis of customer feedback by means of the problem solving process approach. The majority of the previous studies have utilized the cause and effect approach. This study examined how employees participated in each step of the problem solving processes of customer feedback in the Japanese hospitality industry. The remainder of the paper is structured as follows: a literature review, the methodology, the results of our case studies, and conclusions.

2. Literature review The literature review for this study is divided into three research streams: CRM and service improvement; employee driven innovation; service innovation in the hospitality industry. The first stream refers to the research discussing how the relationships with customers contribute to service improvement in the hospitality industry. Ngo and O’Cass (2012) explored the interrelationships of service innovation capability, customer participation and service quality, based on the data drawn from services firms in Australia. Their empirical study showed that the customer participation enabled the conversion of technical and non‐technical innovation capabilities into superior service quality. It reported that service quality positively enhanced the firm’s performance. This study did not question the role of employees. Peltier et al (2013) examined the interrelationships of customer data quality, organizational learning processes, and customer and business performance. Their survey results for financial services in the United States indicated that success factors for CRM depended on the organizational culture, cross‐ functional incorporation and customer data quality. This study showed the positive effect of cross‐functional corporation and data sharing across the organization on business performance. These two factors verified the importance of the employee involvement. The second stream concerns EDI. There are some representative papers. The Danish Confederation of Trade Unions (LO) conducted a questionnaire survey for Danish companies targeting both the management and the shop stewards from the same workplace. The results reported that EDI had positive impact on the business performance and job satisfaction. Peter Kesting et al (2010) said, “EDI refers to generation and implementation of significant new ideas, products and processes originating from a single employee or the joint efforts of two or more employees who are not assigned to a task.” This study identified the drivers of employee participation including management support, the environment for idea generation, decision structure, as well as the corporate environment and culture/climate. Teglborg (2012) discussed the advantages and disadvantages of EDI based on case studies. EDI is supposed to encourage employee motivation and competitiveness. However, the results revealed the negative effects of EDI such as a vector of inextricable tensions. Song Chang et al (2011) defined that hiring multi‐skilled core customer‐contact employees and training core customer‐contact employees for multiple skills both had significant positive effects on incremental and radical innovation for hotels and restaurants. This study questioned how hospitality companies promoted incremental and radical innovation through human resource management.

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Jiro Usugami Meng‐Lei Monica Hu (2001) investigated the relationship between hospitality team and service performance. Their employee survey for international tourist hotels found that in order to achieve a high level of service innovation, an organization needed to develop knowledge‐sharing behaviors and a better team culture. Their study pointed out that the studies at that time had focused not on the effects of team work but of individual work. The third stream includes the research on service innovation in the hospitality industry. Halpern (2010) identified the sources of marketing innovation at the airport, based on a questionnaire survey. The results showed that three sources (modifying facilities or service, using strategic marketing partnerships, and targeting airlines for new or existing routes) were more evaluated than others (e.g. improving the management process, promoting a recognized brand). The results also indicated that marketing innovation had a significant positive effect on the marketing performance of airports. Although the author did not question the employee participation, he mentioned the importance of customer related service and support. Grissemann et al (2012) analyzed the interplay of innovation, customer orientation, and business performance in the hotel industry. Their empirical findings evidenced that both customer orientation and innovativeness influenced a hotel’s innovation behaviors. Customer orientation further affects a hotel’s innovativeness, financial performance and customer retention, as well as reputation. In the context of employees in hospitality industry, consumer‐contact staff plays an important role on generating the ideas for innovation. To summarize, major recent studies have reported the positive effects of CRM and/or EDI on service innovation/business performance in the hospitality industry. However, only few researchers showed the practical interplay of customers’ opinions and service innovation, or the bottlenecks in the problem solving processes of customer feedback driven by employees.

3. Methodologies Firstly, we explored the website information and official reports of three case studies in the Japanese hospitality industry in order to research the examples and systems of their customer feedback. We investigated the desires, complaints or other comments gathered from customers and specified in our case studies, as well as the service and facility improvements which they implemented in practice in response to customers’ opinions. We also examined what practical steps were utilized in the problem solving processes of customer feedback by our case studies, from data gathering to feedback, and how employees participated in them (Table 1). Table 1: Problem solving processes and participants Step Process Participants

1st step Data gathering Customers Employees Managers

2nd step Data sharing Employees Managers Specialists

3rd step Implementation Employees Managers Specialists Affiliated organizations

4th step Feedback Employees Customers Managers Specialists Affiliated organizations

Secondly, we conducted a questionnaire survey for our case studies and asked whether customer feedback had contributed to customer service improvement and firm competitiveness, which step of problem solving processes was regarded as the hardest to be driven by employees, and inquired about the important issue in customer feedback.

4. Results of case studies We conducted a research and a questionnaire survey for three case studies in order to examine the practical relationship between customer feedback and service improvement, the role of employees in customer feedback, the recognition concerning the effects of customer feedback, and the important issues of customer feedback including the bottlenecks for EDI in the Japanese hospitality industry. First of all, the exploration of our three case studies in the websites showed that they had established similar and systematic customer feedback. Two out of them have three steps and the remainder has four steps of problem solving processes from data gathering to feedback. However, for the comparative analyses of our

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Jiro Usugami questionnaire survey, the problem solving processes are divided into four steps: data gathering, data sharing, implementation and feedback. At the data gathering step, any desires, complaints or other comments from customers are received by the customer relationship center through the customer feedback box, direct comments submitted to the frontline employees, telephone, email, etc. At the next step, the opinions concerning customer services are analyzed and shared by employees. The third step, or the third and forth step, starts with the project team or customer satisfaction (CS) meeting which consists of team members or cross‐functional employees, including the manager’s commitment, specialist’s participation and cooperation of the affiliated organizations. They discuss the specific desire, complaint or comment from customers and implement a service or facility improvement in response to it, with the result that the customers receive a richer service or use a more convenient facility. The fulfillment of customer feedback is introduced and published in the website and official report of the firm. In each result of our case studies, they detailed a few examples of customers’ opinions and service or facility improvements in response to them, presented the steps of problem solving processes in their customer feedback system as well as the way of employee participation, and reported the answers to our questionnaire survey including the following questions. Q1. Do you think that customer feedback contributes to your customer service improvement? Q2. Do you think that customer feedback contributes to your firm competitiveness? Q3. Which is regarded as the hardest process to be driven by employees in the four steps: data gathering, data sharing, implementation and feedback? Q4. What are the important issues of your customer feedback? Case 1: Company A ‐ an airport terminal company – A is a local airport terminal company in Japan. They say, “We value customer feedback and reflect it in our improvement measures.” Table 2 shows the examples of their practical service improvements fulfilled in response to customers’ opinions. Table 2: Customers’ opinions and service improvements Data gathering Customers’ opinions It is hard to find the local line departure counter without the sign indicating the directions for getting there. It is hard to find the special assistance vehicle stop. The number of baby cars is low. Hoping that the airport has a place to rest and relax, and to take a shower.

Implementation/Feedback Service improvements A new sign indicating the directions for the local line counter has been added. A bigger sign informing the special assistance vehicle stop has been fixed. 16 more baby cars have been added, amounting to the total of 32 baby cars. The country’s first airport relaxation facility to feature natural hot springs has been established.

Company A has three steps of problem solving processes in their customer feedback: data gathering, data sharing and implementation including feedback. At the first step, for the purpose of gathering any desires, complaints or comments from customers, the customer relationship center has fixed a ‘customer feedback box’ with an indication in multiple languages at twelve places at the airport terminal, in addition to their website. At the second step, the customers’ opinions are analyzed and specified in order to be shared by employees. At the third step, the CS meetings driven by appropriate employees, including cross‐functional employees, discuss the implementation of service or facility improvement in response to a specific desire, complaint or

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Jiro Usugami comment from the customers. According to the decision of the CS meetings, a service improvement is fulfilled and provided to the customers. Table 3 presents the answers of Company A to our questionnaire survey. They recognized that customer feedback contributed to their customer service improvement and firm competitiveness. They reported that the hardest process to be driven by employees was implementation, and the important issue was the invisibility of cost‐benefit in their customer feedback. Table 3: Results of questionnaire survey Q1 Q2 Q3

Q4

Do you think that customer feedback contributes to your customer service improvement? Do you think that customer feedback contributes to your firm competitiveness? Which is regarded as the hardest process to be driven by employees in the four steps: data gathering, data sharing, implementation and feedback? What are the important issues of your customer feedback?

Yes. We strongly think so. Yes. We think so. Implementation is the hardest step, followed by data sharing, feedback and data gathering. Cost‐benefit is invisible.

Case 2: Company B ‐ an air line company – B is a large Japanese air line company. They have established a system of service quality management including customer feedback. Table 4 shows the examples of service improvements in response to the customers’ desires for new services and complaints against difficulties in utilizing the service and facility. Table 4: Customers’ opinions and service improvements Data gathering Customers’ opinions Hoping that there are more menus available for the premium class breakfast besides the Japanese style menu. Desiring easier boarding for the passengers with wheelchairs when using a ramp. It is hard to explore the support information for the passengers with physical disabilities. It is hard to see how crowded the security check area is, and to move the baggage from the waiting table to the checking table.

Implementation/Feedback Service improvements Some local lines started to serve both the Japanese and western style breakfast. A wheeled stretcher has also been made available at some airports, besides a passenger boarding lift or a wheelchair stair lift. A new click button ‘for passengers with physical disabilities’ has been placed on the top page of the website. The walls of security check areas at Haneda airport have been changed to clear glass in order for the passengers to see the crowdedness easily. The waiting table has been combined with the checking table for easy moving of the baggage.

Company B strongly values the customers’ opinions and prepares a problem solving cycle for customer feedback, consisting of three steps: data gathering, data sharing and implementation including feedback. At the first step, the customer relationship center named as ‘customer desk’ gathers any opinions concerning customer services directly from customers or through employees. The frontline employees are supposed to report what they notice to the customer desk as well as the submitted customers’ opinions. Both customers’ opinions and employees’ comments are organized, shared and utilized by the employees in the whole company. At the second step, appropriate members of the customer desk identify the desires, complaints or other comments from the customers and frontline employees, and analyze them as organizational issues. At the third step, the plans for solving problems are made and fulfilled by the appropriate sections or the technical team consisting of cross‐functional employees. The most important issues are discussed at the CS promotion meeting. Not a few service improvements are implemented involving their affiliated organizations. The results of our questionnaire survey for Company B are reported in Table 5. They answered that customer feedback strongly contributes to their customer service improvement and firm competitiveness. They indicated that the implementation step was regarded as the hardest process to be driven by employees in their customer feedback, as well as it generated conflicts among cross‐functional employees. In addition,

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Jiro Usugami further creation of consciousness for customer priority and efficient analyses of the opinions concerning customer services were pointed out as the important issues. Table 5: Results of questionnaire survey Q1 Q2 Q3

Q4

Do you think that customer feedback contributes to your customer service improvement? Do you think that customer feedback contributes to your firm competitiveness? Which is regarded as the hardest process to be driven by employees in the four steps: data gathering, data sharing, implementation and feedback? What are the important issues of your customer feedback?

Yes. We strongly think so. Yes. We strongly think so. Implementation is the hardest step, followed by data sharing, data gathering and feedback. Reduction of conflicts in the cross‐ functional project for implementation. Further creation of consciousness for customer priority. Developing appropriate and efficient analyses of customers’ opinions and frontline employees’ comments.

Case 3: Company C ‐ a railway company – C is a representative railway company in the capital area in Japan. They receive more than two million customers’ opinions within the period of one year. Many of them are desires and comments for smoother transfer. The examples of their service improvements in their customer feedback are presented in Table 6. Company C recognizes the customers’ opinions as important business resources and utilizes four steps of problem solving processes in their customer feedback. At the first step, the customer relationship center receives all the customers’ opinions by telephone, email, fax, regular mail and frontline employees, as well as all the comments from the employees concerning service improvement. At the second step, the customers’ opinions and employees’ comments are quickly forwarded to the appropriate members who review and analyze them. The reviewed opinions and comments are regularly reported to all members of the company including the executives. At the third step, the appropriate sections or the cross‐functional teams and meeting groups discuss problem solving plans and implement specific service or facility improvements. At the fourth step, company C publishes information on service improvement based on customer feedback and prepares for responding to further desires or complaints from the customers. Table 6: Customers’ opinions and service improvements Data gathering Customers’ comments Hoping that the passengers with wheelchairs are able to transfer easily at Asakusa station. It takes time to find the exit or the directions for changing trains. The route from a certain entrance to line M is too long and confusing without signs indicating the directions for line M.

Implementation/Feedback Service improvements A new gate has been set up at Asakusa station, so that the passengers with wheelchairs could pass barrier free floors from the train to the gate. The directions for the exit and changing trains are now displayed in a few lines on the screen in advance of arriving at the station. A new sign has been fixed at the entrance in order to indicate the more convenient entrance for line M.

Table 7 shows the answers of Company C to our questionnaire survey. They recognized that customer feedback strongly contributed to their customer service improvement and firm competitiveness. They mentioned the difficulties in data gathering, in linking the problems concerning sectional services with the issues of the whole company, and in analyzing the customers’ opinions and giving them priority.

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Jiro Usugami Table 7: Results of questionnaire survey Q1 Q2 Q3

Q4

Do you think that customer feedback contributes to your customer service improvement? Do you think that customer feedback contributes to your firm competitiveness? Which is regarded as the hardest process to be driven by employees in the four steps: data gathering, data sharing, implementation and feedback? What are the important issues of your customer feedback?

Yes. We strongly think so. Yes. We strongly think so. Data gathering is the hardest step, followed by data sharing, implementation and feedback. Challenges as regards linking the problems concerning sectional services with the issues of the whole company. Challenges as regards analyzing the customers’ opinions and giving them priority.

5. Conclusions This study discussed the practical relationship between customer feedback and service improvement, the problem solving processes and the way of employee participation in customer feedback, the effects of customer feedback on customer service improvement and firm competitiveness, as well as the important issues of customer feedback including the bottlenecks for EDI, based on three case studies. The first purpose of this study was to examine what specific customers’ opinions had resulted in what kinds of real service or facility improvements in the Japanese hospitality industry. The majority of the customers’ opinions gathered in our case studies were related to the desires for richer service and easier transfer, and comments on the perceived inconvenience at the facilities. In response to those opinions, our case studies have fulfilled various kinds of service improvements. For example, they have prepared a new wheel stretcher or set up a new barrier free route in response to the desires for easier and smoother movement from the customers with wheelchairs. They have fixed a new sign indicating the directions or changed the size of the sign informing about a place in response to the customers’ complaints on difficulties in finding the route for a destination or the location of a facility. They have also added natural hot spring facilities or a new meal menu in response to the comments from the customers who desired richer services. The second purpose of this study was to verify whether CRM contributed to customer service improvement and firm competitiveness through a questionnaire survey for our case studies. The results showed that customer feedback strongly contributed to customer service improvement and firm competitiveness in the Japanese hospitality industry. The third purpose was to identify which process to be driven by employees of the Japanese hospitality industry was regarded as the hardest one in the four steps of customer feedback: data gathering; data sharing; implementation; or feedback, based on a questionnaire survey for our case studies. Two out of the three case studies answered that implementation was the hardest process to be driven by employees, followed by data sharing. The remainder indicated that data gathering was the hardest step, followed by data sharing. In addition, our case studies referred to some important issues of customer feedback, such as invisibility of cost‐benefit, reduction of conflicts in the cross‐functional implementation, and challenges as regards appropriate and efficient analyzing any opinions concerning customer services as well as giving them priority. This study concluded that CRM of our case studies contributed to practical customer service improvement and firm competitiveness; appropriate or cross‐functional employees participated in the incremental innovation processes of customer feedback; and the bottlenecks for EDI included the difficulties in data specifying and cross‐functional project, in the Japanese hospitality industry.

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6. Limitations and future research In this study, research data is limited for descriptive analyses based on the case studies. However, the findings from our case studies will be relevant to the other Japanese hospitality industries. Additional quantitative research is necessary in order to examine both similarities and differences of customer feedback and employee driven innovation in the Japanese hospitality industry.

References Chang, Song Yaping Gong, Cass Shum (2011) Promoting innovation in hospitality companies through human resource management practices、International Journal of Hospitality Management,Vol 30‐ 4, December 2011, 812‐818. Grissemann , Ursula, Andreas Plank, Alexandra Brunner‐Sperdin(2013) Enhancing business performance of hotels: The role of innovation and customer orientationInternational Journal of Hospitality Management, Vol 33, 347‐356. Halpern, N. (2010) Marketing innovations: sources, capabilities and consequences at airports in Europe’s peripheral areas, Journal of Air Transport Management, 16(2), 52‐58. Høyrup, S., Bonnafous‐Boucher, M. Hasse, C., Lotz, M., and Møller, K. (eds) (2012)Employee‐Driven Innovation: A New Approach, Palgrave Macmillan Høyrup, S (2012) Employee‐driven Innovation: A New Phenomenon, Concept and Mode of Innovation;A new approach (pp. 3–33),Palgrave Macmillan.; Hu, Meng‐Lei Monica, Jeou‐Shyan Horng, Yu‐Hua Christine Sun (2009) Hospitality teams: Knowledge sharing and service innovation performance, Tourism ManagementVol. 30‐11, 41–50. Kesting, P. and Ulhøi, P. (2010) "Employee‐driven innovation: extending the license to foster innovation", Management Decision,Vol. 48, 65‐84. Ngo, L.V. and O’Cass, A.(2012) Innovation and business success: the mediation role of customer participation, Journal of Business Research, available online 30 March 2012. Peltier, James W. Debra Zahay, Donald R. Lehmann (2013) Organizational Learning and CRM Success: A Model for Linking Organizational Practices, Customer Data Quality, and Performance, Journal of Interactive Marketing, Vol. 27‐1, 1‐13. Teglborg, A, R.Redien‐Collot, C.Viala &M.Bonnafous‐Boucher (2012) Employee‐driven Innovation: Operating in a Chiaroscuro A new approach (pp. 33‐56),Palgrave Macmillan.

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Space Technology Transfer: A Systematic Literature Review Karen Venturini1 and Chiara Verbano2 1 University of San Marino, Republic of San Marino 2 University of Padua, Padua, Italy kventurini@unirsm.sm chiara.verbano@unipd.it Abstract: Technology transfer has been shown to stimulate innovation in business and commerce, support economic growth and provide a return on public investment in R&D. This is particularly true for space technologies characterized by a very high innovative value and production in small quantities. The aim of this paper is to systematically review the space technology transfer literature and to suggest directions for future research. The transfer of space technology has been studied by academic researchers, managers of space agencies and government ministry officials. The range of studies calls for a systematic review of the literature aimed at synthesizing the findings from individual studies or reports in an unbiased manner, so as to present a balanced and impartial summary and to interpret the findings in a way that highlights the research gaps in this important field of research. This paper presents an overview of the dominant thinking (made explicit in the selected articles) from the 1995 until today, indicating problems of analysis, research gaps and a future research agenda. Keywords: space industry, technology transfer, space technology, spinoff

1. Introduction In 2011, NASA reported that approximately 100 companies had used spin‐off technologies. Some of the benefits of this use were more than 12,000 lives saved, more than 9,200 jobs created, and savings of more than $6.2 billion (Space Foundation, 2012). The U.S. space economy grew by 12% in 2011, reaching an estimated total of $289.77 billion. As in past years, the majority of this growth was a result of commercial success rather than increases in government spending (Space Foundation, 2012). The potential inherent in space technologies to be transferred and to generate new innovative processes has been evident since the founding of NASA. In 1960, NASA created an Office of Technical Information and Educational Programs to implement a technology dissemination strategy, and since then it has continued to promote transfer programs, supporting firms in their demands for technology and disseminating information through the annual publication “NASA Spinoffs” (Selly, 2008). Similarly, other countries and their space agencies also began to take an interest in the processes of space product transfer. Over the last 50 years, scholars and scientists have reported, and in some cases analyzed this phenomenon in major international journals. However, no one has ever collected and interpreted this body of publications. The primary objectives of this article are to systematically review the space technology transfer literature and to provide direction for fruitful future research. A systematic review of the literature follows an explicit, rigorous and transparent methodology (Fink, 2005). According to specific criteria of selection, we constructed a database of 40 articles and then we interpreted the database respecting the areas of major interest in the development of technological transfer processes, namely: actors, geographical context and industrial sectors, motivations, space technologies, paths, models and mechanisms, impact/effectiveness, determinants and barriers. The results contain a summary of findings from each area of interest of technology transfer (TT). The paper is organized as follows: firstly, we describe the methodology used for identifying and selecting the papers. Secondly, we review the papers along descriptive characteristics and six topics of interest. Thirdly, the conclusions include those that are referred to in the literature as "future researches”.

2. Methodology The analysis process involved the completion of the following activities (Hackett and Dilts, 2004): a) Selection of databases and identification of papers.

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Karen Venturini and Chiara Verbano To identify the collection of papers for review, we conducted an electronic journal database search. We used the online databases ProQuest ‐ ABI/Inform and ScienceDirect because they store the abstracts and full texts of the majority of ISI management journals. The objective was to conduct a survey of all published research on technology transfer from space companies to the industrial system, written in English between 1995 and early 2012. The search in electronic database required the identification of keywords taken from the definition of the concept of technology transfer. Bozeman (2000) defines technology transfer (TT) as the process that allows the passage of a technology from one organization (donor) to another entrepreneurial organization (receiver), but there are many definitions and synonyms for the concept of transfer such as adoption or acquisition (Brisson, 2006); valorization or adaptation (Autio and Laamanen, 1995), commercialization (Philips, 2002; Williams and Gibson, 1990), diffusion (Rogers and Shoemaker, 1971, Rogers, 2003) and spin‐offs (Szalai, Detsis and Peeters, 2012; Venturini, Verbano and Matzumoto, 2013). In relation to the reference context, the keywords used were as follows: space industry or space sector, aerospace sector and aerospace industry; space programs and space agencies, national research centers and systems integration companies that represent the main promoters of transfer processes. b) Selection of papers. In the second stage of the analysis we selected the articles for review. We decided to investigated the inter‐ firm typology of TT, that is between a space firm and a firm in the recipient sector (Cohendet, 1997). A first selection led to the rejection of articles on the following topics:

International and intra‐firm technology transfer between companies operating in the space sector;

Transfer of aircraft technologies;

Space policy and space activity that did not explicitly refer to technology transfer.

The first database comprised 112 items. A further selection process took place to ensure that the articles selected were completely in line with the research objective. Articles were discarded if the object of research was not the transfer of technology or the scope of the analysis was not exclusively the space sector. c) Classification and analysis. In the last stage we proceeded to analyse the database according to the following parameters:

Descriptive characteristics: journals discipline sector, year of publication, professional field, productivity of the authors and research type (theoretical, empirical, or literature reviewing);

TT topics and results of previous studies: a) Actors, geographical field of reference and sectors involved, b) Motivations and mechanisms, c) Space technologies transferred, d) Paths and models, e) Impact/effectiveness and f) Determinants.

3. The descriptive characteristics of the space TT database The database obtained as a result of the identification and selection of articles is composed of 40 papers (Table 1). The distribution of articles among journals was highly skewed toward journals with an economic perspective, particularly those published in the Journal of Technology Transfer, which devoted an entire issue (in 2002) to the subject of the transfer of technology from space programs and the measurement of its effects. Management and economics experts (who mainly publish in economic journals) were the first to analyze and achieve a greater scientific output on technological transfer in space, having realized the enormous potential of space technologies. The temporal distribution of articles has been fairly constant over time, with the exception of a peak in 2002 with 8 papers, which was due to a special issue dedicated to technology transfer in the Journal of Technology Transfer.

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Karen Venturini and Chiara Verbano In total there are 71 authors of whom five have written two articles and one has written three. 80% of the authors come from academia, especially from economics departments or business studies colleges, while the remaining 20% come from space agencies (with NASA in first place) and from public research centers. Only two authors come from private firms. With regard to the research type, the majority of articles (23) are empirical; specifically: 16 case studies, 2 surveys, 5 with examples while the remaining 16 are theoretical. Table 1: Distribution of articles per journal Journal of Technology Transfer

Acta Astronautica

Technovation Space Policy Advances in Space Research Comparative Technology Transfer and Society IETE Technical Review Mechanical Engineering International Journal of Technology Transfer & Commercialisation Sensor Review The Journal of High Technology Management Research Australasian Physical & Engineering Sciences in Medicine Research Policy Smart Materials Bulletin Earth, Moon and Planets IEEE Transactions on Engineering Management Physics Procedia Professional Safety Long Range Planning Management Research Review

Becerra-Fernandez, Buckingham, Brown, Entessari (2000); Harper and Rainer (2000); Herztfeld (2002a), Hertzfeld (2002b); Bach, Cohendet and Shenk (2002); Amesse, Cohendet, Poirier, Chouinard (2002); Pankova (2002); Kremic (2003); Lundquist (2003); Park, Lee and Lee (2012); Szalai, Detsis, Peeters (2012); Chambers and Prince (1995); students of the International University of Space (1997); Winfield (1997); Sridhara and Shoba (2010) Molas-Gallart and Sinclair (1999); Petroni and Verbano (2000) Goehlich, Blanksby, Goh, Hatano Pečnik, and Wong (2005), Petroni, Venturini and Santini (2010) Bubenheim and Lewis (1997); Bamsey et al. (2009); Sridhara and Shoba (2010) Seely (2008); McMillan (2008) Krishen (2009, 2011) Sharke (2002); Noor and Cutts (2004); Becerra-Fernandez (2002) Hollingum (2011) Adams and Spann (1995) Hughes (2007) Molas-Gallart (1997) Anonymous (2002) Green (2010) Zelkowitz, (1996) Komerath and Komerath (2011) Argabright (1999) Nosella and Petroni (2007) Verbano and Venturini (2012)

4. TT topics and results of previous studies 4.1 Actors, geographical context and sectors involved Actors in the space sector who are able to initiate processes of transfer to the industrial sector (Figure 1) are on the one hand government controlled agencies and public research centers, and on the other, prime contractors or systems integration firms that supply orders or undertake contracts for developing new products that incorporate space technology. Two additional promoters are public authorities such as regional bodies, which can support innovative projects through direct funding or through tax incentives (Petroni et al., 2010), and SMEs that supply large space companies, which in turn are also able to initiate processes of transfer to other SMEs. To facilitate the process of technology transfer a consultancy firm or organisation may be called. Such firms may identify technological or commercial opportunities on behalf of the space firm or the transferee; helping package the technology to be transferred between the two firms; selecting suppliers to make components for the technology; providing support in making the deal between the firms concerned (technology brokers) or taking part in the transfer itself (contract research organisations) (Cohendet, 1997; Watkins and Horley, 1986). Technology brokers can be specialized staff operating within decentralized independent units at space agencies, or private organizations devoted to assess the market needs in areas where there is a potential for exploitation of space technologies. Other actors that can facilitate the transfer process are: incubators, venture capital companies, science and technology parks.

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Karen Venturini and Chiara Verbano The analysis shows that most of the articles investigated either space agencies or public research centers as promoters of technology transfer. Regarding the TT intermediaries, the literature has analyzed especially the role and functions of internal organizational infrastructure to space agencies (Technology Transfer Offices) and finally the geographic context most analyzed is the United States, followed by Canada.

Figure 1: TT actors in the space sector (source: adapted from De Stavola, 2007)

4.2 Motivations and mechanisms Identifying the reasons for the transfer of space technologies by public and private organizations is of primary importance in defining the best methodology and evaluating the effects of transfer. Motives that lead a government agency to undertake technology transfer may be economic or political. The former include the following: pursuing new commercial markets and reducing dependency on public funding (Adams and Spann, 1995), maintaining public relations, evaluating agency performance, sharing costs (Kremic, 2003), and reducing the development time for a new technology (Hughes, 2007). Public agencies have had to confront new patterns of behavior and management that have often upset traditional missions and organizational routines. The request to deal with the side‐effects and marketing of new knowledge has only emerged strongly in recent years and in response to the pressures caused by a reduction in public spending and the political desire to gain popular support for space activities. The motives for technology transfer in a government agency are not uniform across all organizational levels. For a government agency employee, the motivations are achieving self‐realization, completing a task and benefiting research (Kremic, 2003). The political reasons for TT are to amplify the "drip" effect of scientific knowledge and technology acquired during space exploration programs to external contractors, to develop a strong aerospace and industrial space capability, to help SMEs, to encourage companies, universities and research institutions to collaborate and finally, to accelerate innovation (Chambers and Price, 1995; Petroni and Verbano, 2000; Sridhara and Shoba, 2010). Alternatively, the motives for private corporations to implement a TT process include the following: preempting and/or deterring competition, lowering costs, increasing growth, networking, training employees, following customers and responding to content laws and/or legal requirements. Generally speaking, an employee working in a private corporation shares the same motives as the organization itself (Kremic, 2003). When compared, the methods used by a public and private organization are also different. Government agencies try to broadcast their technologies domestically through technology portals, web sites and publications in order to reach as many people as possible, through involving support contractors (contractors employed to build networks, make contacts and to some extant advertise the technologies to potential users), creating consortia or institutes (responsible for sharing technologies among partners and marketing them), licensing agreements, intermediaries, brokers, and encouraging its researchers to submit articles for publication (Kremic, 2003). A private corporation, seek to control access to their technology, and therefore prefer joint ventures, direct investment and other controlled methods of access (Kremic, 2003) and licenses (Kremic, 2003).

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Karen Venturini and Chiara Verbano In synthesis, the TT mechanisms as follows (ISU, 1997):

Financial (direct government funding, royalties, tax incentives);

Legislative initiatives (or regulations) to foster TT from federal government to the private sector;

Contractual: licensing or more complex collaborative arrangements that define the product to be marketed, division of responsibilities among parties and decisions on the handling of IP (Harper and Rainer, 2000; Sharke, 2002);

Organizational infrastructures (TTO, networks, umbrella organizations, Science Parks);

Marketing (brokers, promotion);

Production of documents (Selly, 2008) (i.e. reports, technical notes, memoranda, technical translations, contractors’ reports, conference proceedings, handbooks, monographs etc.);

Education and legal mechanisms.

4.3 Space technologies transferred Verbano and Petroni (2000) stated that there are three areas where technological advancements performed during space exploration matter: the launch of the spacecraft, the construction and control of satellites in orbit, and the processing of data transferred from the satellite during the voyage. The satellite is like as a "technological archipelago", most of which concerns the planning and construction of the so‐called “carriage” and its accessory systems (on‐board computer, orientation systems, antennas for receiving and transmitting data, systems for generation and distribution of energy); in other words, the "container". The content, mainly comprising instruments, is called the “payload”. Technologies for scientific satellites most frequently develop from the integration and upgrading of technological matrices present in non‐space industrial sectors. These technologies are then upgraded for use in space (Petroni, Venturini and Santini, 2010). The need to survive and function in space demands technologies that can guarantee safe operations and perform in extreme environments that include heat, gravity, vacuum, partial atmosphere, solar radiation and particles, planetary dust and storms. They should use less power, have a high degree of autonomy and reliability, and aid humans in achieving a high level of productivity (Krishen, 2009). Other features of space products are miniaturization (to limit size), low weight (to restrict weight on board the spacecraft and satellite) and standardization (to facilitate reuse of the components in other systems). The study of the technological characteristics of space products is also useful for the purposes of transfer because it has been found that the most easily transferable technologies are those that have been the subject of spin‐in and have generic and standardized qualities (Petroni and Verbano, 2000). Technologies that are usually subject to transfer take the following path: spin‐in from Earth sectors – integration and up‐grading for use in space – spin‐out towards the Earth's industrial system with consequent downgrading (Verbano and Venturini, 2012).

4.4 Paths and models At the start of the transfer process in the space sector, consideration should be given to research programs promoted by space agencies, from which transferable technologies emerge. According to Bach, Cohendet and Schenk (2002), ESA programs that generate technology transfer processes can be divided into mission‐oriented projects, aimed at achieving the objectives of the space mission and organized in a hierarchical manner, and diffusion‐oriented programs, promoted by the government to stimulate the economy and promote the possibility of a specific technology in other domains. The flow of knowledge in the space sector essentially travels at the following levels:

1. International: collaboration, strategic alliances, collaboration between space agencies for the implementation of mission‐oriented programs;

2. National: relationships can arise along the space industry production chain a) at high levels, between systems integrator companies and suppliers b) at lower levels, among the various component suppliers. The mechanisms of knowledge transmission takes place through "technical specifications, concurrent engineering, strategic alliances in engineering activities, quality control, shared product development, supplier certification, delivery times, risk sharing, sharing of costs, production volumes and prices "(Giuri, Tomasi and Dosi, 2007).

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Karen Venturini and Chiara Verbano The mechanisms of knowledge transmission in the field of space can be either intra‐ or intersectoral (Figure 2). Intrasectoral knowledge transmission may take place either at a vertical level between systems integration firms and subcontractors, or at the horizontal level as a result of collaboration between large space firms for the development of new programs. Intersectoral knowledge transmission may occur through the transfer of space technologies to other sectors.

Figure 2: The space technologies transfer paths On the basis of this differentiation, the space agencies may promote technological development programs that tend to outsource advanced technology R&D to both industry and universities. In this last case, space agencies promote the transfer of personnel, technologies and knowledge, as well as the demonstration testbed and the technical support for the technology’s adaptation. An important element is the technical and educational support (educational and training materials, workshops and courses) that the government agency has to guarantee (Bubenheim and Lewis, 1997). The private sector should be assisted in long‐term research and development by a public organization that would foster access to facilities and share the financial and technical risks (Chambers and Price, 1995). The high cost of space technologies and the length of time required to develop innovation often pose an obstacle to firms. In order to meet private sector standards, the public space sector needs to reduce the technology development time scale, reduce engineering and manufacturing costs, lower technology performance requirements in order to match them to the recipient's needs, and find an appropriate market for space technologies. Moreover an international standard for describing a new technology should be created (ISU, 1997). The transfer path taken from a government body to a firm is certainly among the most difficult, and to facilitate this the literature discusses organizational infrastructures designed to help it and the adoption of new methodologies such as for identifying potential markets and partners for potential applications. These methods may help the donor company to systematize the process of transfer more successfully and help to identify potential markets for its edge technologies.

4.5 Effects of technology transfer Space programs can generate direct effects, i.e. those that match the objectives of the mission or program of research, or indirect effects. The indirect effects for the private firms which worked in the space programs occur in four areas: technology (sales of the same product to other customers, improvement of current product line based on space technology, new product based on space technology); marketing (reputation and image enhancement after a contract with a space agency); effects on organization and method (the upgrading of a firm’s technological skills, learning or developing standards, methods and management techniques during the collaboration), and critical mass (critical assets such as maintaining or enlarging the number of employees in the space sector) (Bach, Cohendet and Schenk, 2002; Amesse et al., 2002). Some spin‐offs may have a direct economic impact on industry, others may improve public wellbeing or increase public support for the government (Goehlich et al., 2005). Among the tools for measuring economic impact, the relevant parameters are those described as "value added", (defined as sales attributable to the product minus the cost of material input), and the amount of additional R&D. The ROI index should not be used (because the public sector does not count the benefits it generates for civil society, and R&D expenditure is not an government investment), nor should cost/benefit analysis be used since it is similar to the ROI index (Hertzfeld, 2002b). Private benefits that result from spin‐off are mostly those generated by sales of products and services in the commercial market. Public benefits are those widely appropriable by a large section of the community, such as the benefits of regional development resulting from contracts awarded to firms in different areas of the country; social effects such as improved diagnostics or cures for illnesses as a result of space technology, or the discovery of an archaeological site. In other words, benefits that the entire world and future generations can enjoy.

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DETERMINANTS Related to the context – Decline in employment and greater competition (Adams and Spann, 1995); – Presence of an effective intellectual property regulation (Adams and Spann, 1995); – Availability of government financial support (Zelkowitz and Marvin, 1996; ISU, 1997); – Prestige of the sector receiving the technology (Winfield, 1997); – Involvement of leaders from industry, academia and government in problem definition (Winfield, 1997); – Building of infrastructures composed of universities and industrial partners with a coordinator to manage the relationships (Hughes, 2007). Regarding agents involved in the TT process (organizational and managerial determinants): – Availability of financial incentives (ISU, 1997) also for adaptation and marketing activities (Zelkowitz, 1996; Petroni and Verbano 2000); – Market familiarity and identification of user’s needs (Adams and Spann, 1995; Petroni, Venturini and Santini, 2010; Krishen 2011); – Direct linkage between Space and Earth technology development (Bamsey, 2009); – Recipient’s technical and scientific knowledge and R&D staff (Zelkowitz, 1996; Petroni, Venturini and Santini, 2010; Krishen, 2011); – Organizational style and culture (Adams and Spann, 1995; ISU, 1997). Open and less bureaucratic facilities not only ensure a better flow of information but also the creation of new ideas due to crossfertilization across different fields of activity (Bach, Cohendet and Schenk, 2002). Important is also the professional motivations (Zelkowitz, 1996; Krishen, 2011); – Assertive attitude towards technology transfer by managers or CEO (Zelkowitz, 1996); – Management skills for building a good TT process: learning the needs and benefits of each stakeholder, diagnosing the value chains, building a strategic identity for the TT program, setting durable goals and choosing a strategy to achieve these, cultivating agents of change, developing a customer-oriented project, developing communication of TT program, taking care of the process, identifying administrative rules focused on TT (Adams and Spann, 1995; Bubenheim and Lewis, 1997; ISU, 1997; Lundquist, 2003; Krishen 2011); – Creating a flow of information and communication between donor and receiver (ISU, 1997; Bach, Cohendet and Schenk, 2002; Nosella and Petroni, 2007) though specialized information network (Chambers and Price, 1995), multi-functional teams (Hughes, 2007), academic and industry research teams (Krishen, 2011), link between manufacturing and development process (Krishen, 2011); – R&D organization willing to collaborate and ready to supply assistance to recipient. Fundamental to this are the support of engineers and technologists in the transferring firm (Petroniet al. 2010). Related to the technology – The technology to be transferred must be not too mature at the beginning of the program. The technology must also be generic in order to satisfy industrial needs on Earth (Bach, Cohendet and Schenk, 2002). In certain cases, however, successful transfer requires mature technology, or at least its behavior must be known (Zelkowitz, 1996; Petroni,Venturini and Santini, 2010); – Similarity of use based on common requirements. The transfer of technology from space programs occurs especially in those Earth sectors where technological requirements are similar to those in the space sector (ISU, 1997; Winfield, 1997; Bach, Cohendet and Schenk, 2002; Bamsey, 2009; Petroni, Venturini and Santini, 2010); – Suitability and flexibility of the technology to be integrated with other technologies (ISU, 1997; Petroni, Venturini and Santini, 2010); – Versatility, small mass, high reliability level, high performance, cost-benefit relationship (Petroni, Venturini and Santini, 2010); – Technology assessment and application project development (Winfield, 1997); – The diversity and competencies of the technology among both program participants and between sectors. A condition for this recombination requires that the technologies the participants bring to the program have a sufficient level of diversity to widen the area of exploration; in other words, a set of technological opportunities (Bach, Cohendet and Schenk, 2002). BARRIERS Related to the agents involved: – Lack of property rights agreements (ISU, 1997; Hertzfeld, 2002); – Complex and time-consuming federal procurement procedures (Hertzfeld, 2002); – Lack of understanding of the technology and its potential profits (Krishen, 2011); – Profit opportunities not clear or too risky (Krishen, 2011); – Potential licensee not familiar with proposed technical area (Krishen, 2011). Related to the technology − Time constraints. Often prolonged periods of public administration are a deterrent to private firms undertaking shared innovative processes (ISU, 1997); − Development of project driven technologies and not mass production (ISU, 1997); − The dual-use nature of space technologies (ISU, 1997). In particular, barriers faced when organizing defense R&D in the development of dual-use technologies include differences in procurement practices, in regulations, in government accounting rules, the priority given to defense needs and requirements in contrast to civilian needs, and the frustrations of defense researchers in performing TT tasks (Molas-Gallart, 1997; Molas-Gallart and Sinclair, 1999); − A further obstacle is related to adapting the needs of space to the needs of society and industry, and the frequent technological outdatedness of space products compared to that of Earth products (Bach, Cohendet and Schenk, 2002)

Karen Venturini and Chiara Verbano

However, each case is structurally very different and certain benefits cannot be easily translated into numbers; for example, the number of lives saved.

4.6 Deteminants and barriers

Factors that facilitate (determinants) or impede (barriers) the flow of technology transfer are of particular interest to researchers. We can classify the determinants and barriers identified in the database according to the source of origin: context, actors or technology (Petroni, Venturini and Santini, 2010; Verbano and Venturni, 2012) (Table 2). In general the studies reviewed focus attention on some factors that facilitate or hinder the transfer, without analyzing the influence of the same on the success of the transfer. Studies on the determinants of the space technologies transfer are therefore partial (just few determinants are considered) and limited (not confirmed the impact on performance of the TT). Table 2: Determinants of space technology transfer

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5. Conclusions: emerging gaps and future researches The aim of this study is to systematically identify the scientific and academic articles published over the past 17 years on the subject of technology transfer from the space sector to the industrial system. Based on the selection criteria and the limits of the research, such as time frame (1995 to 2012) and scientific validity (peer‐reviewed), we built a database of 40 papers. The first object of the study is to characterize the database obtained. Journals that have published on this topic are mainly managerial journals and for the most part, the authors of the studies are academic researchers in the fields of economics and management. They have been the first and most consistent in producing research on the subject. The most widely used research methodology is the qualitative case study, perhaps because it is more suited to investigating a complex process like transfer, in which motivations, mechanisms and pathways depend on the context in which they occur (Kremic, 2003). The second objective of this research is to examine the articles selected in order to collate what has already been studied in the field and ascertain the gaps in the literature. An analysis of the database revealed the following gaps and proposed the future research topics for researchers and scholars in the field:

Actors, geographical context and sectors: few studies have compared technology transfer in different geographical areas other than the U.S. and Canada. New studies are required that deal exclusively with private promoters (or new public actors such as regions) or private brokers and other organizations devoted to facilitate the transfer such as incubators, venture capital companies, science and technology parks. Discussion on the transfer of space technologies in new industries such as clothing, home automation, design, cultural heritage will useful;

Motivations: The majority of articles are devoted to analyzing the motivations and mechanisms adopted by public agencies and no in‐depth analysis has been made of the motives and mechanisms adopted by systems integrator companies and prime contractors, or small and medium‐sized firms as recipients. Regarding the mechanisms, there has been little investigation of financial, marketing and educational mechanisms.

Technologies: it would be opportune to investigate which space technologies and applications could be transferred to fields other than the medical; for example, sports and clothing design;

Paths and models: The transfer path most analyzed in the articles in question is the one from a government agency to small and medium sized firms and little study has been made into the transfer path from systems integration firms to small and medium‐sized companies, or the processes by which small and medium‐sized companies adapt, learn from and further develop new products that incorporate space technology space. There are also gaps in the analysis of alternative paths of TT, for example from one SME to another.

Effects of TT: no analytical framework exists that is able to take into account the range of spin‐off phenomena and the complexity of the channels through which they make an impact on economic activity and civil society. Design methodologies are also required to provide accurate measurements (Bach et al., 2002). Costs should be publicly known and a detailed calculation needs to be made which takes into account all the different factors and steps involved in the development and marketing phases. Indeed, a high degree of transparency with regard to costs, whether sustained by a government agency or an industry, is often restricted by legal and/or confidential regulations (Szalai, Detsisi and Peeters, 2012).

Determinants: validation of determinants through case studies and surveys is lacking, as are studies that analyze the differences between determinants and their significance with regard to the different technologies and different sectors to which the new technologies are directed. No assessment has yet emerged of the determinants that have greater influence in promoting processes of transfer, nor are there studies that have integrated all the identified determinants in a fragmented literature.

Finally, concerning the system integrators, they generate basically a process of learning between its supplier companies and companies receiving technology. The methods of teaching and learning have not yet been studied.

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The Evolution of Resources in Research‐Based Spinoffs: Learning from a Case Study Chiara Verbano1, Karen Venturini2 and Avi Wasser3 1 University of Padua, Padua, Italy 2 University of San Marino, Republic of San Marino 3 Haifa University, Haifa, Israel chiara.verbano@unipd.it kventurini@unirsm.sm awasser@research.haifa.ac.il Abstract: A great deal of interest and concern has been raised in recent years over the theme of research‐based spinoffs (RBSOs) and their economic and social implications. An RBSO is a new business entity formed to market one or more related technologies generated from the research work of a public research institute. The literature has studied this phenomenon from three different theoretical perspectives: resource‐based, business model and institutional (Mustar et al. 2006), but no studies have integrated the above three theoretical perspectives. Other gaps identified in the literature are the lack of an analytical consideration of the impact of technological resources on RBSO performances and the limited empirical studies on the evolution over time of RBSOs, i.e. considering the resources in the different stages (or phases) of the RBSOs’ development. The aim of this paper is to evaluate the evolution of a spinoff’s resources and institutional linkages over time, adopting the four stages of spinoff development identified by Djokovic and Souitaris (2008): 1) opportunity recognition, 2) entrepreneurial commitment, 3) threshold of credibility and 4) threshold of sustainability. To this extent, the authors have extensively investigated a research‐based spinoff from the Italian ICT sector .This paper provides a thorough and integrated analysis of the research‐based spinoff in terms of resources (including institutional resources), using a longitudinal approach, and highlights the importance of resources during its life‐cycle.

Keywords: spinoff, resources, research‐based spinoff, case study, Italy

1. Introduction A spinoff company is a new business entity formed to commercialize one or more related inventions generated from the research work of a parent institution. If the parent organization is a public research institute, the literature uses the term research‐based spinoff (RBSO), and if the parent organization is a university, the term used is university (or academic) spinoff (USO). The research‐based spinoffs have been particularly analysed in recent years by scholars and researchers for their economic and social implications. Economic implications are due to the fact that marketing of innovation through the creation of a new business permits the public institute to compensate the cost for maintaining R&D Lab, more and more expensive, and to obtain new earnings. The social implications are related to the fact that commercialization of public R&D warrants the dissemination of technological knowledge in the local economy and the related activation of innovative processes. The role of spinoffs is reinforced by the growing involvement of universities and public research organizations in the processes of regional economic development (Piccaluga and Lazzeri 2012). However, the academic and research‐based spinoffs have not been studied in depth until now. Recent evidence has shown that the majority of high‐tech companies, including research‐based spinoffs, has grown slowly (in terms of number of employees and turnover) (Piccaluga and Lazzeri 2012). The spinoff organizations are characterized by both the typical problems of start‐ups and difficulties associated with lack of personnel with a managerial and commercial experience as happens in some cases of technology transfer (Venturini et al. 2013). Studying in detail the successful cases of this kind of organization is, therefore, important to make some proposals in terms of management. The gaps of the literature on the topic of RBSOs are basically the following: firstly the majority of scholars have investigated the spinoff process to a single perspective and secondly they have observed the spinoffs in a moment and not in their long‐term evolution. The aims of this paper are to consider all resources identified by

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Chiara Verbano, Karen Venturini and Avi Wasser different theoretical approaches and to evaluate resources from a longitudinal point of view during the lifetime of the spinoff. To achieve these research objectives we analysed a case study of an Italian spinoff working in the field of ICT. From the analysis of the case interesting insights emerge for public research institutions engaged in enhancing the results of their research through entrepreneurial initiatives and for local and national governments and private firms interested in supporting start‐ups derived from research organizations.

2. Literature review RBSOs involve the creation of ventures based on formal and informal transfer of technology or knowledge generated by public research organisations (Smilor 1990). The definition of an RBSO should specify the outcome of the spinoff process (i.e. the firm formation), the essential parties involved and the core elements that are transferred (Djokovic and Souitaris 2008). Regarding the involved parties, Roberts and Malone (1996) identified the following four: the parent organization from which the technology is extracted, the developer of technology, i.e. the person who brings the technology from basic research to a point at which the transfer can begin, the entrepreneur and the venture investor. The core elements transferred to an RBSO are technology and knowledge incorporated in people. We adopted the following definition: the spinoff is a new company created by staff previously or currently employed in a university (teachers, researchers or students) (USO) or in a public research institution (RBSO), created to exploit a new technology or knowledge produced by research within the university or the public research institution. RBSOs and USOs face two main problems: firstly, the non‐commercial environment such as the public research environment, which typically lacks commercial resources, and, secondly, the venture’s ability to commercially develop the new technology may be adversely impacted by the conflicting objectives of key stakeholders (university, academic entrepreneur, venture management team and suppliers of finance) (Mustar et al. 2006). The literature has studied the phenomenon of spinoffs from three different theoretical perspectives: resource‐ based, business model and institutional (Mustar et al. 2006). The resource‐based perspective identifies four resources that are central to the achievement of competitive advantage: technological, human, social and financial (Djokovic and Souitaris 2008). Technological resources refer to firm‐specific products or technologies; spinoffs may vary in degree of innovativeness, scope, tacitness and stage of development of their technology. RBSOs differ considerably in the newness of their core technology, and innovativeness can be an important source for competitive advantage (Heirman and Clarysse 2004; Shane 2001; Lee et al. 2001). Human capital resources refer to attributes of the founding team, the management team and the personnel of the company. Human resources are measured by the size of the founding team, professional management experience, organizational size and background of the founders. Teams with technical and commercial experience can better address the difficulties related to the marketing of their product (Mustar et al. 2006). Network (or social) resources refer to the spinoff’s government, industry and financial contacts. It is important to establish teams of people who have links with the world outside the university to acquire managerial knowledge and financial resources more easily. It is also important that the spinoff develops different networks during its life cycle (Nicolaou and Birley 2003). Financial resources refer to the amount and type of financing of the firms. It is often difficult for academic spinoffs to get funding from venture capital firms because of the non‐managerial context from which they come, the lack of resources and potential conflicts with a public entity. The business model perspective has characterized research‐based spinoffs on their business models: the articulation of the value proposition, the identification of the market segment, the position in the value chain and the estimated cost structure and profit margin. There are different taxonomies of RBSOs depending on the activity undertaken, on how the technology has been transformed into a commercial value and on their growth orientation (Mustar et al. 2006). For Heirmann and Clarysse (2004), two other elements may affect the organization and configuration of the resources of the spinoff: the complexity of the selling process, i.e. the characteristics of the buying centre in terms of number and accessibility of decision makers and size and geographical dispersion of markets that the spinoff faces. Shane (2001) proposed that the tendency for an invention to be exploited through firm formation varies with the attributes of the technology regime (age of technical field, tendency to market segmentation, effectiveness of patents, importance of complementary assets etc.)

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Chiara Verbano, Karen Venturini and Avi Wasser The institutional perspective studies how the context shapes the starting configuration and the later development of RBSOs and, in particular, it classifies the RBSOs on the basis of their degree of dependence on source technologies (Roberts 1991), the strategic choice made by the parent institute (Boeker 1989) and the organization modes of the parent organization (Clarysse et al. 2005; Power and McDougall 2005), for example considering the presence and the effectiveness of technology transfer office (Bigliardi et al. 2012). Some studies also analysed the government support mechanism for USOs in the U.S. and Europe, and others evaluated the effectiveness of governmental TT policy (Shane 2004a). Considering the evolution of the spinoff during all phases of its life cycle, Vohora, Wright and Lockett (2004) identified four critical junctures between these phases: 1) Opportunity recognition, which is the period from the R&D phase (carried out in the parent organization) until the recognition of business opportunity (verification of technology and understanding of the market potential); 2) Entrepreneurial commitment, in which there is the definition of the strategic plan and business plan, the identification of resources and capabilities possessed and the acquisition (including the entrepreneurial champion) of possible patent protection; 3) Threshold of credibility, i.e the period dedicated to the re‐orientation of the strategic plan, in which the top management of RBSO define the resources and knowledge to integrate or to acquire in order to overcome gaps and weaknesses; and 4) Threshold of sustainability, in which the focus is on generating revenues and economic value over time towards consolidating the company. Regarding the performance measurement of spinoffs, economic‐financial indicators such as sales volume and growth (Schmelter 2004; Egeln et al. 2003; Bigliardi et al. 2013), net cash flow (Ensley and Hmieleski 2005; Bigliardi et al. 2013) and revenue growth (Ensley and Hmieleski 2005, Bigliardi et al. 2013) are used even if some authors claim that in the start‐up phase of the spinoff, the growth can be minimal (Rickne 2006, Smith and Ho 2006). Other indicators used are the number of patents filed (Rickne, 2006), the quality certificates obtained, the number and growth of employees (Rickne 2006; Schmelter 2004; Shane 2004b; Egeln et al. 2003; Bigliardi et al. 2013) and the level of investment in research and development (Baum and Calabrese 2000). An analysis of the scientific literature on the research‐based spinoffs identified the following gaps:

The lack of an analytical study on the impact of technological resources on RBSO creation and development;

The need to integrate the three theoretical perspectives adopted in previous studies: the resource‐based perspective, the business model perspective and the institutional perspective;

The limited empirical studies on the development and evolution over time of RBSOs, following a longitudinal approach;

The identification and evaluation of the resources at each stage of development of the RBSO.

3. Research questions and methodology The first objective of this research is to create a framework that overcomes the gaps of the literature. This framework should consider the four types of resources and the external mechanisms in the four stages of development of an RBSO (Fig. 1). The dimensions of analysis for each type of resource were obtained from the literature review. Next, in order to integrate the resource‐based perspective and the institutional perspective, we included, among the social resources, two resources (derived from the institutional perspective) such as the relation of RBSO with the parent organization and the organizational and supporting mechanisms and policies adopted by the parent organization for the spinoff creation. Following a longitudinal approach to evaluate the evolution of the spinoff’s resources over time, the following four RBSO development stages were considered (Djokovic and Souitaris, 2008): 1) opportunity recognition, 2) entrepreneurial commitment, 3) threshold of credibility and 4) threshold of sustainability. Moreover, among the external mechanisms were included governmental and industrial policies stimulating or facilitating spinoff creation. The second objective of this research is to validate the framework in RBSOs, answering the following research questions:

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How did the four types of resources change in the process of spinoff creation and development?

What are the most important and critical resources for the success of RBSOs along the process of spinoff generation and development?

Figure 1: The comprehensive research framework adopted The resources necessary to the success of RBSOs, are specific to the types of business (Druilhe and Garnsey 2004). For this reason we choose a specific sector such as ICT. We decided to focus on one of the most active and innovative industries in spinoff generation. Moreover, this sector appears to be the most important in regard to the number of spinoffs generated by universities or public research institutes. Therefore, the selection criteria of RBSOs have been defined as follows:

operating in the ICT sector in the Italian context,

generated by a public research institute,

at least 8–10 years old to permit the analysis of all the four stages of development.

RBSOs that have passed the start‐up phase can be considered successful. The single case study methodology has been implemented using retrospective data collection, i.e. asking participants to reflect back upon their experiences and attitudes. Web meeting interviews followed by phone calls with one of the founders responsible for the spinoff were performed to this extent. The interviews were conducted using an interview protocol with a set of open and closed questions, according to the research framework outlined in Fig. 1. Data collection was completed with the analysis of internal documents (business plan, balance sheet, etc.) to complete and verify information emerging from the interview. To answer the research questions, each dimension of the four types of resources were evaluated on the basis of the information collected during the interviews, using a scoring scale (low, medium, high). This evaluation was then reviewed with the founder in the last meeting, obtaining a Table of assessment of each resource in each stage of development. Analysing this Table by rows (along time) and by columns (between resources), the authors have discerned the major changes during time and the most important resources, respectively.

4. Analysis of case study 4.1 General information and stages of development of Aethia spinoff Aethia has been operating since 2000 in the Italian sector of High Performance Computing (HPC), where is recognized as one of the first companies to propose the cluster computing technology. HPC most generally refers to the practice of aggregating computing power in a way that delivers much higher performance than one could get out of a typical desktop computer or workstation in order to solve large problems in science, engineering or business. Aethia has specialised in the realisation of complete and ready‐to‐use systems, offering flexible support services during all phases of system deployment and use, including parallel applications development. This feature is fundamental to exploiting HPC potentialities and turning them into competitive advantages. Now, thanks to a decade of expertise and know‐how, Aethia is one of the main leaders of the sector, able to offer

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Chiara Verbano, Karen Venturini and Avi Wasser turnkey HPC systems to companies, research groups and computational centres. Aethia’s products include clusters for HPC software platforms, servers, storage and workstation solutions. Services include technical advice and personalized training courses for the administration and management of the cluster. Aethia operates in different fields and has an extensive R&D program for the activities developed for its customers to strengthen and enhance its own line of products. The main collaborations with academic and private research institutes has led to the realization of solutions and systems for advanced computing in several application sectors, including computational chemistry, fluid dynamics, theoretical physics, electrical engineering, environmental simulations, data‐mining, genomics and proteomics and bioinformatics. The main characteristics of Aethia activities are: ease of use of the technology cluster even for non‐experts, complete systems of all the necessary software and ready‐to‐use, professional solutions with the best price/performance ratio and remote assistance service after sales to support the management and use of the system. The company profile is presented in Table 1. Table 1: General information on the Aethia spinoff

The main events and stages of development in the history of Aethia are listed in Table 2. Table 2: Main events and stages of development in the history of Aethia

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4.2 Analysis of resources used in the process of spinoff creation and development Following the research framework, the authors divided the resources in technological, human, financial and network ones identifying them together with external mechanisms and performance. Technological resources:

The degree of innovation (i.e. the newness or innovativeness of the core technology compared to technologies in the market) had a decreasing trend from a high level in the first phase to a low level in the last phase. In the early 2000s the technology was highly innovative (created in 1994 in NASA centres), while now it is well known in the ICT industry.

Stage of development of the technology. From an initial prototype form, the technology has been developed to obtain a variety of finished products with related support services. At the beginning, the founders worked on commission; the customer advanced requests to which the founders tried to respond. Then, the founders tried to formulate, with great effort, different packages with different applications. There has been a transition from a technology platform to a finished product.

Ability to patent/protect the technology. The ability to patent or protect the technology was always constant: it is, in fact, very difficult to protect any hardware or software. The only possible protection is the complexity of the know‐how required for the development of the ICT system.

The scope of the technology was high during all four phases. The technologies used for the calculation are inherently applicable in different fields. For the founders, it is important that the technology is open, in order to create different applications. The possible applications arise from the relationship with the customer, who suggests possible uses, and from collaborations and partnerships in research projects funded at the regional and European levels.

Human resources:

Scientific and managerial experience. Both founders came from a scientific background and had a degree in nuclear engineering. Also, both founders had experience in the sector, having worked firstly at university and then with a grant of the Polytechnic of Turin. The initial weakness of RBSO was the lack of administrative, commercial and legal experience of personnel. At the beginning of the spinoff there was a significant discrepancy between technical and managerial level of competence. In addition, the founders had no entrepreneurial experience.

Variety of backgrounds and work experience in the team. In each stage the founders increased the variety of backgrounds of staff team employing additional holders with technical, commercial and managerial experience.

Joint working experience and cognitive diversity of the team. The majority of the team members knew each other and did not have different point of views on how to manage the spinoff, except in the second stage, when one of the founding members left the spinoff because he wanted to make quick profits.

Presence of surrogate entrepreneur. The spinoff did not have any surrogate entrepreneur in the first phases, but in the third phase, three other partners (respectively with technical, commercial and organizational expertise) succeeded in the spinoff management.

Financial resources:

Type of funding. In the second phase (before the foundation), the spinoff project was accepted into the program of INFM’s spinoff support, for which the founders have obtained the reimbursement of legal costs of setting up. The support offered included also some managerial (business plan) and financial services. At the beginning of the third phase, the project was accepted into the incubator program of the Bio‐industry Technology Park of Ivrea, who offered a small fee for the purchase of computer and office equipment. After the incubation period in the technology park, the founders received various funding through participation in European research projects (10% of total funds). The rest of the funding came from business income (90%). In the last phase, the share of funding from participation in European research projects had increased to 15% of total funds, while the rest (85%) came from business income.

Network resources:

Relationship with parent organization (PO). In the first two phases, the support from the parent organization was only on the definition of a strategy. In the early stages, the financial support of the

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Chiara Verbano, Karen Venturini and Avi Wasser parent organization was relatively low, just enough to pay the legal fees for the establishment of the spinoff. The most important resource coming from the PO was management consulting; a business tutor organized meetings for business plan and helped to make decisions on the location and organizational structure.

In the first two phases, the scientific quality of the PO was important for the public recognition of spinoff. In fact, it was prestigious for the spinoff using the trademark INFM. In the other phases, the spinoff did not have any support from the parent organization.

External contacts. In all phases the staff of spinoff created contacts with customers. In the second phase, the staff established relations also with suppliers. In the third phase, contacts with the technology park, financial institutions and venture capitalists were added. The spinoff’s managers failed to have an effective relationship with the venture capitalists because the goal of the spinoff was to build capacity slowly, while the venture capitalists were motivated by financial logic and the maximization of returns in a short time. In the third phase, the spinoff also began to joint with universities as well as other businesses. In the last phase, contacts were developed with institutions that banned funding, such as Regions and the Technological poles of Piemonte Region.

RBSO strategies to access missing resources. In the first phase, the strategy of RBSO was focused to find an incubator. In the second phase, the main goal of RBSO was to find customers (as a result of the scientific quality of the PO). In the third phase, the company worked to establish partnerships and commercial agreements with suppliers and with other research centres and universities in order to apply together research programmes. In the last phase, the spinoff established collaborations with companies that produce complementary technologies or professionals and participated in programmes of regional innovation poles.

External mechanism. The spinoff has enjoyed regional incentives from the second stage onwards, and in the last phase has obtained incentives from national and European projects. Performance. In the second phase, the sales growth rate (average annual) was unique (100%); in the third phase, the sales growth rate (average annual) increased by 10% in relation to the first year. The employment growth rate increased by 150%, and the R&D investments were 5% of total sales (the customers increased from 5 in the second phase to 50). In the last phase, the sales growth rate increased by 18%, the employment growth rate by 80% and the R&D investments up to 15% (thanks to participation in European research projects). The number of customers went up to 150, and there were three business partners. The following table (Table 4) illustrates the level of each resource in the RBSO’s phases. In response to the first research question, i.e. how the resources change in the different stages of spinoff ‘s development, the following considerations emerge:

Technological resources. The degree of innovativeness of the technology, which is high in the early stages tends to fall over the years in accordance with the diffusion of knowledge. In the meanwhile, the degree of empirical development rises until the offer of finished products and related services. The level of protection of the technology and the scope of the technological platform remains constant over time with a score respectively medium for the first resource and high for the second resource.

Human resources. The scientific experience of the team that founded the spinoff is high at all stages of the spinoff’s life, characterizing it as a high tech company, while the managerial experience and background of the team is flawed. The gap between the scientific and the professional management abilities is particularly acute, and to fill this gap, in the third stage managers employed some new partners. These new partners possess, respectively, technical, commercial and managerial skills. The spinoff expands its team with people from different professional backgrounds, and this facilitates the RBSO management. The different competencies enable the spinoff to expand its product line, to add another brand and to better compete in the market.

Financial resources. The parent organization and of the science park give a low financial contribution. The spinoff is funded in the first year of life with its net income. In the third and fourth phases, the RBSO have funds also from participation in regional and European research projects.

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Chiara Verbano, Karen Venturini and Avi Wasser Table 4: Assessment of spinoff resources in each stage of development

Network resources. In general, these resources are widely grown over the years, thanks to the expansion of the management team of the spinoff. The relationship with customers, suppliers and other research centres (such as INFM and the Science and Technology Park) is constant over time. The RBBO’s attempts to approach lenders such as venture capitalists have failed, while, in the last phase, the RBSO has intensified relations with companies engaged in complementary activities to those of the spinoff and with professionals that provide the necessary knowledge. There were no relationships with trading partners and competitors. The same management strategies have evolved from the search for an organization that would support the spinoff to the search of customers, using the prestige of the parent organization, to the establishment of partnerships with suppliers and research institutes and finally to the search of new complementary skills in order to offer a wider product portfolio.

The answer to the second question resulted from the analysis of Table 4:

In the first two phases (opportunity recognition and entrepreneurial commitment), the most important resources seem to be the technological ones. The human resource most relevant is the sector experience of the founders; social resources are instead at a medium level while the other resources have a lower importance.

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In the third phase (credibility), the degree of innovativeness loses importance, even if the ‘stage of development’ and ‘scope of technology’ of the remaining resources remain consistently high, even in the last phase. The importance of human resources (managerial and entrepreneurial experience) and social resources (contacts) increases. It also appears that, to evolve, the spinoff has to acquire at least a medium level of all resources, recovering initial shortcomings. At least in this sector, the financial resources are not particularly relevant.

In the last phase (sustainability), the bond with the parent organization dissolves and does not appear to be a key resource in the maturity stage. Instead, contacts with industrial and commercial actors, government agencies, suppliers and customers in particular are of strategic importance. The diversity of the team in terms of professional experience appears crucial to expand this network of contacts and access new skills.

5. Conclusions This research offers a framework to overcome the limitations of literature on spinoff companies, in that it allows us to analyse the entire process of generation and development of an RBSO. In addition, the framework integrates the resource‐based perspective with the institutional perspective, giving the research a more comprehensive insight. In addition to this theoretical contribution, the following lessons can be derived from the case analysed:

The technological resources seem the most important in the first stages, followed by the social resources, through which are provided managerial and entrepreneurial competencies lacking in the human resources;

In the last phases of credibility and sustainability can be observed a progressive enrichment of human resources (sectorial, managerial and entrepreneurial competences) and social resources, while some technological resources decrease in importance. The spinoff slowly changes identity; the relations with the parent organization and the science park decline while relations with industry stakeholders intensify. The scientific and academic connotations of the spinoff give way to a more managerial connotation.

Financial resources seem the most critical along all the process considered; only in the sustainability phase this resource does reach a medium level of importance. This aspect is typical of the ICT sector, which does not usually require a huge amount of funds invested, compared with other industries. In any case, it was difficult for the spinoff to find financial partners willing to accept a longer period before the achievement of profit. In this case, there is an important role of national, regional and European incentives.

To ensure sustainable development over time, the spinoff should equip itself gradually, arriving at the maturity stage with all four resources considered.

Of course, these are the first indications that emerge from the case analysed, which needs to be supported by other empirical analyses. Further, the proposed framework could be applied to spinoffs belonging to other industries or national contexts. The authors do not have items for the comparison of the Italian case with other foreigner cases, for example, American or British, because framework used for the analysis is new, and has not yet been validated by any other empirical research Future research objectives will be to compare the levels of sustainability and credibility of spinoffs in Italy with those in other countries. However, we believe that the findings of this research have potentially useful implications for those involved in spinoff generation (managers, researchers, public research institutions and universities and governments and government agencies), to deepen the knowledge of mechanisms and conditions supporting spinoff development and to build more profitable policies and practices of technology transfer, useful for strengthening the national industrial system.

Acknowledgements The authors gratefully acknowledge financial support for this research granted by the University of Padua (Research project CPDA109359).

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Companies’ Innovativeness Influenced by Organizational Structures Annika Vesterinen and Kalle Elfvengren Lappeenranta University of Technology, Lappeenranta, Finland annika.vesterinen@lut.fi kalle.elfvengren@lut.fi Abstract: Innovation results from collaboration, collective knowledge and intelligence. Successful innovation process needs organizational structure for the sharing of knowledge and for communication to flow between people. This paper presents the common organizational structures and discusses the potential effects of different structures to the innovativeness of companies. This study helps to understand the link between company's organizational structure and company's innovativeness. The study is based on the findings of a literature research. As a result of this study, the chosen structure could promote and enhance the creation of new innovations. Keywords: innovativeness, organizational structures

1. Introduction There are numerous studies about the effects of organizational structures on a company's performance and operating models. These studies are often considered in Faculties of Political Sciences and Social Sciences, where Faculties of Technology have nothing in common with them. For researchers in the field of technology, innovations have been the main question for a while. First the focus was of the definition on innovation and innovation processes. Innovations are considered as being a task for one person or a one unit. Now, thoughts about innovation are approaching a model of open innovations where they are seen as the result of people and community working together. At the same time, the concept of innovativeness or innovation capability has become a part of the research. Nevertheless, there are few studies about how organizational structures affect companies’ innovativeness. Only a few organizational structures are known which support the innovativeness of a company and researchers have only registered them because those structure models have become more common after open innovation companies became popular. Although there is no knowledge about how those older structures are affecting or do they have an influence at all for innovativeness in companies. This research looks for the links between the theories of organizational structures and innovativeness and which features of the organizational structures benefit and prevent innovativeness. The research begs the question of whether there is a structure that is the best choice for a company that is trying to reach maximum level of innovativeness.

2. Organizations and their structures The key issues of organizational study have always been about what keeps an organization together, with what kind of organization and with which practices the best possible results can be achieved. Studies of organizational structures have been attempts to answer these questions. (Juuti 2006) Organizations’ structures, functions, and internal cultures are affected by many factors. The organization can be said to be a co‐operation system formed by people and it exists for certain goals. These operations are pre‐ defined and repetitive in organization. Organization members and their groups affect the characteristics of the organization, but it is also affected by its environment. (Juuti 2006) Organization structures include information of the repeated organization activities and the hierarchy which is formed by people’s different stations. The organizational structure takes the position of the division of tasks and roles, and defines the various functions and relations between them. The goal of the structure is to assist co‐operation between people and groups so that the division of tasks can be differentiated enough, while maintaining the organization's co‐operation between the different parts. Ultimately, the organization's structure is the relationship between people and their jobs. (Juuti 2006)

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Annika Vesterinen and Kalle Elfvengren The structure of the small organization is the most basic organizational structure. Also, larger companies may take advantage of the structure of the small organization when it can be used as organizing innovative projects. The greatest strength of the structure is its informality and flexibility. This allows the organization to learn and develop within the structure, as well as rapid response to environmental changes. Weaknesses come from the same things: a free‐form organization’s working habits are hard to teach the new members and when the organization is growing, maintaining the model becomes challenging. (Peltonen 2007) The functional structure, the so‐called line organization, separates the different functions (figure 1). There, selected employees focus on their areas of expertise under their own management. The basic idea of the structure is that the employees of each function have often received professional training just for those core areas. The company's distributions of efforts of well‐defined functions are more efficient than those where everyone is learning all the stages of the process. This forms the strengths of the structure. Responsibility for the whole company is in the highest management, which also has the right to make decisions on issues that affect the whole organization. For this reason the company's decision‐making can accumulate to management and its response to environment changes too slow, which is a structural weakness. (Peltonen 2007) A common approach used by large manufacturing companies is to organize the company by product type. Each product has its own functional activities. Each product has its own functional activities. Some functions are centralized across the whole organization to improve efficiency or provide common features. This type of structure supports the notion of product platforms. (Trott 2005)

Figure 1: Functional structure The division structure consists of separate business units, which are formed on the basis of business areas (figure 2). Each business unit has its own management and function structure. Business units can be thought of as their own organizations within a larger organization (Mintzberg 1979). This cleavage of functions under the different business units makes it easier to respond to market fluctuations, but at the same time it hinders the proper utilization of specialties. It can be said that the divisional structure combines large company resources with small company flexibility and simplicity. Integration of the whole organization within the structure may be difficult. (Peltonen 2007) The matrix structures aim to combine two of the structures presented above (figure 3). The structure is flexible and is well suited for many kinds of companies. In the matrix structure, the divisional structure is built on top of the functional structure. The model utilizes both an overall picture and the benefits of specialization. Matrix structures, however, also have conflicts between these two structures. Employees may feel confused, since they are controlled in two different directions – divisional purposes and functional processes. This may cause slowness in an otherwise flexible structure. Preventing and solving the situation requires good communication skills, as well as a shift away from a traditional hierarchical way of thinking. (Peltonen 2007) Companies using the team structure are built around the processes. This changes the functional division of work and company runs the business with project teams which produce and implement processes. Processes can be produced either for an external or internal customer. Thus, the model does not have traditional, hierarchical leadership positions, but each process has its own leader. The executive group is responsible to the company's management. The process structure is suitable for a dynamic and complex environment in which the organization is required to be flexible and informal with the company's internal practices, which

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Annika Vesterinen and Kalle Elfvengren make use of teamwork and different specialties. In many cases, the process teams are only temporarily composed for specific projects. Challenge in the structure is the adoption of the approach, creation of the reward system and define core processes. (Peltonen 2007)

Figure 2: Divisional structure

Figure 3: Matrix structure The network structure is currently a more common organizational structure (figure 4). In it, a part of the company’s operations has been outsourced to specialized firms. This allows for large operation without large investments. The development of telecommunications technology and its ease of use have benefited the network structure. Outsourcing must be done in accordance with the company's strategy, when features that are strategically important to the company's competitiveness will not be outsourced. The management of the network structure is in a central unit, where can be located some of these strategically important and therefore no‐outsourced functions. Management may be difficult in widely networked businesses, because the maintenance of relationship requires a significant part of management work and all workers are not bound to the company. Still, the network model has got rid of unnecessary bureaucracy, and the model is very flexible. In addition, on account of outsourcing, various alliances and partnerships with large and smaller companies have become more common and increased its value. (Peltonen 2007) Often organizations do not have only one model and companies are mixing different organizational structures to match their functions. This combination of several models is called a hybrid structure. Hybrid structures are often complex and difficult to assess. This may lead to the confused image of the company. However, it can show, when it is working, that the result may be greater than the sum of its parts, because it can be combining each of strengths and avoid weaknesses of structures. (Peltonen 2007).

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Figure 4: Network structure

3. Innovations and innovativeness Innovations are seen as ideas or inventions and innovativeness as an idea‐rich environment. Apilo, Taskinen and Salkari (2007) point out that this is not one and the same thing. They claim that anyone can come up with ideas, but not all can be inventors. In addition, individuals have ideas, but the innovations require a participating organization, at best an innovative one that has the ability to combine technologies and market needs in new ways (Apilo and Taskinen 2006). Figure 5 shows that the innovation capability is anyway much linked to the organization. A more detailed study of capability requires a wider vision of the organization, its structures, personnel ability to absorb and capacity of information distribution (Yliherva 2007). This kind of study about the company's operations needs more detailed understanding of the organization. In conclude the organizational structures have also a direct impact on company's innovativeness and innovation capability.

Figure 5: Innovation capability (Paalanen et