Embracing the Knowledge Economy: The Dynamic Transformation of the Finnish Innovation System (New Horizons in the Economics of Innovation)

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Embracing the Knowledge Economy


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NEW HORIZONS IN THE ECONOMICS OF INNOVATION Series Editor: Christopher Freeman, Emeritus Professor of Science Policy, SPRU – Science and Technology Policy Research, University of Sussex, UK Technical innovation is vital to the competitive performance of firms and of nations and for the sustained growth of the world economy. The economics of innovation is an area that has expanded dramatically in recent years and this major series, edited by one of the most distinguished scholars in the field, contributes to the debate and advances in research in this most important area. The main emphasis is on the development and application of new ideas. The series provides a forum for original research in technology, innovation systems and management, industrial organization, technological collaboration, knowledge and innovation, research and development, evolutionary theory and industrial strategy. International in its approach, the series includes some of the best theoretical and empirical work from both well-established researchers and the new generation of scholars. Titles in the series include: Innovation and Small Enterprises in the Third World Edited by Meine Pieter van Dijk and Henry Sandee Innovation, Growth and Social Cohesion The Danish Model Bengt-Åke Lundvall The Economics of Power, Knowledge and Time Michèle Javary Innovation in Multinational Corporations in the Information Age The Experience of the European ICT Industry Grazia D. Santangelo Environmental Policy and Technological Innovation Why Do Firms Adopt or Reject New Technologies? Carlos Montalvo Corral Government, Innovation and Technology Policy An International Comparative Analysis Sunil Mani Innovation Networks Theory and Practice Edited by Andreas Pyka and Günter Küppers Systems of Innovation and Development Evidence from Brazil Edited by José E. Cassiolato, Helena M.M. Lastres and Maria Lucia Maciel Innovation, Competence Building and Social Cohesion in Europe Towards a Learnng Society Edited by Pedro Conceição, Manuel V. Heitor and Bengt-Åke Lundvall The Dynamics of Innovation Clusters A Study of the Food Industry Magnus Lagnevik, Ingegerd Sjöholm, Anders Lareke and Jacob Östberg Technological Systems and Intersectoral Innovation Flows Riccardo Leoncini and Sandro Montresor Inside the Virtual Product How Organisations Create Knowledge Through Software Luciana D’Adderio Embracing the Knowledge Economy The Dynamic Transformation of the Finnish Innovation System Edited by Gerd Schienstock


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Embracing the Knowledge Economy The Dynamic Transformation of the Finnish Innovation System

Edited by

Gerd Schienstock Research Professor and Scientific Director, Work Research Centre University of Tampere, Finland

NEW HORIZONS IN THE ECONOMICS OF INNOVATION

Edward Elgar Cheltenham, UK • Northampton, MA, USA


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© Gerd Schienstock 2004 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited Glensanda House Montpellier Parade Cheltenham Glos GL50 1UA UK Edward Elgar Publishing, Inc. 136 West Street Suite 202 Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library Library of Congress Cataloguing in Publication Data Embracing the knowledge economy : the dynamic transformation of the Finnish innovation system / edited by Gerd Schienstock. p. cm.— (New horizons in the economics of innovation) Includes index. 1. Knowledge management—Finland. 2. Information technology—Economic aspects—Finland. 3. Technological innovations—Economic aspects—Finland. 4. Industrial policy—Finland. 5. Finland—Economic policy. I. Schienstock, Gerd. II. Series. HD30.2.E46 2004 303.48'33'094897—dc22 2003055843

ISBN 1 84376 307 9 Printed and bound in Great Britain by MPG Books Ltd, Bodmin, Cornwall


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Contents List of figures List of tables List of contributors Preface List of abbreviations PART I

vii ix xi xii xiv

CONCEPTUAL ASPECTS

1 From path dependency to path creation: A new challenge to the systems of innovation approach Gerd Schienstock 2 Towards a theory of social innovation and structural change Timo Hämäläinen PART II

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INDUSTRIES AND FIRMS

3 The evolution of the Finnish ICT cluster Laura Paija and Petri Rouvinen 4 Innovation and absorptive capability in the traditional industries: The case of the Finnish wood products industry Christopher Palmberg 5 Knowledge services in the Finnish innovation system Aija Leiponen 6 Nokia: A giant in the Finnish innovation system Jyrki Ali-Yrkkö and Raine Hermans 7 The flexible production model in Finnish companies: Trends in production management, work organization and employment relations Tuomo Alasoini PART III

3

47

65 85 106

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REGIONS AND INSTITUTIONS

8 The emergence of a regional innovation network: BioTurku in Turku, Finland Henrik Bruun v

147


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9 From the national industrial heartland towards a node in the global knowledge economy: The case of Tampere Region Mika Kautonen, Pasi Koski and Gerd Schienstock 10 Universities and science-industry relationships: Making a virtue out of necessity? Mika Nieminen and Erkki Kaukonen 11 Polytechnic reform: A response to the learning economy Kari Kekkonen 12 Education as an asset in the labour market Asko Suikkanen and Ritva Linnakangas 13 Regulation and innovation: Competition law Kalle Määttä 14 Finnish science and technology policy Tarmo Lemola PART IV

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196 219 242 254 268

THE NATIONAL LEVEL

15 The Finnish model of the knowledge economy Gerd Schienstock

287

Index

315


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Figures 2.1 3.1 3.2 3.3 3.4 3.5 4.1 4.2 5.1 5.2 6.1 6.2 6.3 6.4 6.5 6.6 9.1 9.2 9.3 9.4 9.5 9.6

Social innovation process 30 ICT sector value added, employment and R&D 48 ICT cluster framework 49 Development of the ICT cluster versus the economy as a whole 1990–2001 53 Export shares by industry group 53 Tekes funding to Nokia: Volume (millions of euros at 2000 prices) and share of Nokia’s R&D (%) 57 Contribution of different industries to the volume of production of the Finnish manufacturing sector 1995–2001 (ETLA database) 66 The product segments of the Finnish wood products industry in 2000 70 Dimensions of organizational knowledge 92 Operationalization of knowledge in the service firm 92 Tekes funding and its share of Nokia’s total R&D expenditure 108 Share of Tekes financing in all its company projects and Nokia projects 109 Nokia’s R&D personnel in Finland and abroad 110 Nokia’s co-operation network in Tekes’ ETX and TLX programmes 115 R&D expenditures relative to GDP (%) 121 Monetary value flows between Nokia and the public sector in Finland 1995–2000 (at 2000 prices) 124 Selected indicators of regional development in Finland, 1999 171 Industrial production in various sectors in Tampere Region in 2000 (%) 173 Changes in Tampere Region’s share of workforce and value added, of Finland as a whole, 1995–2000 (%) 174 Share of companies having frequent (Likert-5, values 4–5) co-operation with some selected universities or research institutes 179 Changes in R&D expenditure shares by region between 1995 and 2000 (%) 180 Domestic patent applications filed by business enterprises in Finland by inventor’s address by region 1995–2001 (%) 181 vii


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Share of companies located in Tampere Region having frequent (Likert-5, values 4–5) co-operation with selected intermediary and financing organizations 184 9.8 Development of total turnover in industries belonging to the Tampere Region Centre of Expertise Programme, 1995–2000, index 186 9.9 The regional innovation system environment in Tampere Region 187 9.10 Companies’ views of their own competitive strengths in Tampere Region 189 11.1 The Finnish VET reform in the 1990s 225 11.2 Finnish education system 229 11.3 A framework for network analysis of VET institutions: Actors and forms of interaction 231 11.4 Working-life-related theses 232


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Tables 2.1 Structural competitiveness of nations in the new techno-economic paradigm 2.2 Mental and structural change in Finland during the 1980s and 1990s 5.1 Service firms’ strategic choices 5.2 Descriptive statistics of main survey variables 5.3 Service firms’ contracts with key clients 5.4 Knowledge resources in KIBS industries (survey means) 5.5 Mean indicators of Finnish KIBS industries’ service development activities 5.6 Means of a set of variables concerning KIBS firms, for different values of the control rights variable 5.7 Means of independent variables for innovators, non-innovators 6.1 Nokia’s most important partner universities by country, 2001 7.1 Different types of corporate co-operation agreements in Finnish industry (%) 7.2 Opportunities for influencing one’s own work in Finland (%) (proportion of those who can influence ‘a lot’ or ‘quite a lot’) 7.3 Delegation of responsibility, teamwork and job rotation in the Nordic countries (%) (proportion of workplaces with 50 employees or more which responded positively) 8.1 Indicators of regional performance in biotechnology-related research 9.1 Types of innovation networks among firms in Tampere Region (%) 9.2 Changes in employment in different sectors 1970–1998 (%) 10.1 External funding of university research by source 1991–2000 (%, at 2000 prices) 11.1 Concepts of learning and knowledge in the framework of formal education 11.2 Supply of education in upper secondary and higher education in Finland 1999 12.1 The share of Finnish people in normal employment calculated with reference to different groups ix

35 41 88 89 90 94 97 98 99 119 133 136

137 154 189 191 202 222 230 244


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12.2 The development of employment according to educational levels in the years 1988–1997 in Finland 245 12.3 The proportion of the Finnish labour force (excluding entrepreneurs) in normal employment by level of education in the years 1990, 1993, 1995 and 1998 246 12.4 The incidence of unemployment in the Finnish labour force by level of education in the years 1990, 1993, 1995 and 1998 247


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Contributors Alasoini, Tuomo, Ministry of Labour, Finland Ali-Yrkkö, Jyrki, Research Institute of the Finnish Economy ETLA, Finland Bruun, Henrik, Helsinki University of Technology, Finland Hämäläinen, Timo, Finnish National Fund for Research and Development Sitra, Finland Hermans, Raine, Research Institute of the Finnish Economy ETLA, Finland Kaukonen, Erkki, University of Tampere, Finland Kautonen, Mika, University of Tampere, Finland Kekkonen, Kari, University of Tampere, Finland Koski, Pasi, University of Tampere, Finland Leiponen, Aija, Cornell University, USA Lemola, Tarmo, Advansis Oy, Finland Linnakangas, Ritva, University of Lapland, Finland Määttä, Kalle, University of Joensuu, Finland Nieminen, Mika, University of Tampere, Finland Paija, Laura, Research Institute of the Finnish Economy ETLA, Finland Palmberg, Christopher, Research Institute of the Finnish Economy ETLA, Finland Rouvinen, Petri, Research Institute of the Finnish Economy ETLA, Finland Schienstock, Gerd, University of Tampere, Finland Suikkanen, Asko, University of Lapland, Finland

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Preface This book reflects to a great extent work pursued in the Research Programme on the National Innovation System in Finland launched by Sitra (The Finnish National Fund for Research and Development). The aim of the book is to give a broad overview of the Finnish Innovation System and its recent development trends. Of course, while the various articles cover a great number of aspects, we cannot claim to present a full picture. This is partly due to the fact that the system model itself is a rather vague concept. Instead of aiming for completeness, we have integrated a great variety of different levels of analysis. For example, two articles in the book deal with various organizational aspects on the firm and inter-firm level, which has not been a focal area of research so far. We have put great emphasis on the institutional level, including among others, labour market aspects and competition law. Some of these institutional aspects are not always dealt with in standard textbooks. To include the industrial level goes without saying, as Finland is the most specialized country in telecommunications. In addition, we have included traditional industries and the emerging sector of knowledge-intensive business services. But Finland also provides some examples of successful regional specialization processes, as the two articles on Tampere Region and Turku Region demonstrate. Last but not least, we have included an article on Finnish science and technology policy, which created a favourable environment for the emerging knowledge economy. The title of the book reveals that a dynamic analysis is pursued. The aim is to demonstrate Finland’s capability to create a new knowledge-based national development path, in a country that in the 1980s was known as a forest economy. Finland is one of the very few countries that managed to catch up with the most advanced industrial countries within a very short period of time. By applying a systemic transformation approach, Finland has become a leading country in the new knowledge paradigm. This was achieved without major cutbacks in the highly developed welfare state. Due to this very balanced development, Finland is described as a specific model of the knowledge society, being monitored very closely by other countries. The intention of the dense description of the Finnish innovation system was not, however, to present a model that could be copied easily by other countries. During the last few decades we have seen too many models, such as the Japanese and German ones, which have failed in the end. The book can be seen, however, as a contribution to reflexive benchmarking. This means that by reflecting on the xii


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solutions Finland has developed for specific problems and fields of the innovation system, other countries may be able to gain a better understanding of their own solutions, their strengths and weaknesses. Finland is definitely a good example of successful reflexive benchmarking, as many of its institutions and political processes have been developed in the light of solutions in other countries. The authors who have participated in the book share an interest in the national systems of innovation approach. But they also share the view that the approach is often applied in a rather narrow sense. There is a need to take more seriously the open character of the innovation system, which means that research needs to focus more on relationships and interactions of the innovation system with other economic and social subsystems. As innovation and learning is not necessarily a positive-sum game, more attention needs also to be given to the negative aspects of a high innovation dynamic. Finland, with its still rather high unemployment rate, can also be seen as an example of the fact that the transformation into a knowledge society does not take place without serious social problems. Therefore innovation can no longer be associated with economic growth only; instead it needs to be recognized also as a means with which to solve social and ecological problems. This implies that more emphasis has to be given to non-technical innovations, including social, organizational, service and regulatory innovations. The broadening of the innovation concept implies a great challenge for innovation policy and governance. The traditional idea of a sequential policy process, which first concentrates on supporting innovation processes and afterwards deals with the negative consequences, can no longer be applied. Policy-makers, being confronted with large-scale changes, have to deal with the various problems simultaneously, which demands cross-departmental co-operation and a highly flexible political system. This book would not have been possible without Sitra’s Research Programme on the National Innovation System in Finland, as most of the articles rely on material collected in this programme. Therefore Sitra deserves to be mentioned as the initiator of the book. I also thank the Work Research Centre and the Research Institute for Social Sciences, University of Tampere, for financial support for this publication. Also, Marjukka Virkajärvi has continuously accompanied the process of the book’s production and has produced the final manuscript. Joan Lofgren has taken on the function of checking the language of the various articles. Both should be thanked for their patience in the preparation of the book. Dymphna Evans of Edward Elgar Publishers should be thanked for her encouraging support for the project. And what would have happened without Annikki’s loving support in the sometimes very stressful process of editing this book? Gerd Schienstock Tampere, Finland March 2003


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Abbreviations AGIL

Adaptation Goal Attainment Integration Latency Function and Pattern Maintenance Scheme AMKOTA A statistical database of the polytechnic system maintained by the Finnish Ministry of Education ASIC Application-specific integrated circuit CERN European Organization for Nuclear Research CRST Clinical Research Services Turku DCC Data City Centre EEDCs Employment and Economics Development Centres EFTA European Free Trade Association EIRA European Industrial Regions Association ESA European Space Agency ESF European Social Fund ERDF European Regional Development Fund ETLA The Research Institute of the Finnish Economy EU European Union ETX Electronics for the Information Society FDI Foreign Direct Investment FISPA Finnish Science Park Association GDP Gross domestic product GNP Gross national product GSM Groupe Spéciale Mobile, later Global System for Mobile Communications GSM MoU GSM memorandum of understanding HE Hallituksen esitys (government bill, Finland) HSE Helsinki Stock Exchange ICTs Information and communications technologies IPR Intellectual property rights ITU International Telecommunications Union KIBS Knowledge-intensive business services KM Komitean mietintö (Committee Report, Finland) KOTA A statistical database of the university system maintained by the Finnish Ministry of Education LAN Local area network LVL Laminated Veneer Lumber xiv


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Abbreviations

MNCs MTI NAFTA NIS NMT OECD OKO PTO PreFA R&D RJV RPM S&T Sitra SME Tekes TLX TTC TUT UK USA UMTS UTA VET VC VTT WLAN 3G

xv

Multinational companies Ministry of Trade and Industry North American Free Trade Association National Innovation System Nordiska Mobiltelefongruppen Organisation for Economic Co-operation and Development A venture capital consortium led by a private OKO Bank Group Public telecom operator Preclinical Pharmacology Research Unit, University of Turku Research and development Research joint venture Resale price maintenance Science and technology The Finnish National Fund for Research and Development Small and medium-sized enterprise The National Technology Agency of Finland Telecommunications: Creating a Global Village Turku Technology Centre Tampere University of Technology United Kingdom United States of America Universal Mobile Telecommunication System University of Tampere Vocational education and training Venture capital Technical Research Centre of Finland Wireless local area network Third generation mobile technology


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Schienstock 01 chap01

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PART I

Conceptual aspects

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1. From path dependency to path creation: A new challenge to the systems of innovation approach Gerd Schienstock 1.1

INTRODUCTION

There is wide agreement that we are currently living through a period of fundamental and rapid economic transformation. Not only single elements of national economies are becoming the target of restructuring; instead the way the whole system is organized is changing. The ICT revolution is being given an important role in the transformation process; at the same time not only the established best practices of designing intra- and inter-organizational production processes, but also the existing institutional support structures, the functioning of political systems and even national cultures are fundamentally changing. Of course the fact of fundamental change also has major implications for research on techno-economic development and national systems of innovation. While up to now the systems approach concentrated mainly on the aspect of path dependency where the dominant feedback loops are self-reinforcing, in the current period research has to focus more on processes of unlocking and path creation (Garud and Karnoe 2000). The aim of this chapter is to contribute to such a re-conceptualization of the national systems of innovation framework. At the same time the chapter will raise some methodological problems and will point to some substantive aspects, which are dealt with in the following chapters of the book. Finland provides a good example of the successful creation of a new national development path, having been able to transform its resourcebased economy into a knowledge-based one (Castells and Himanen 2001). In the following section I will briefly discuss the traditional path dependency perspective and will take up the ‘lock-in’ phenomenon. The major part of the chapter is devoted to the development of a conceptual framework with which to analyse processes of path creation. I understand the development of a new national development path as the result of an interaction between socioeconomic pressures, critical change events, and endogenous change processes. The chapter will also deal with changes in the functioning of the political system 3


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as part of the creation of a new path. In the second part of the chapter I will give a short overview of the other chapters of the book.

1.2

THE PATH DEPENDENCY PERSPECTIVE AND THE PROBLEM OF ‘LOCK-INS’

The strength of the path dependency perspective is that it does not separate technological innovation from past developments, but assumes some kind of continuity in the process of technological change. New innovations line up with earlier technological changes; they have historical antecedents of novelty (David 1985, 332). Today’s technological advantages, as Foray argues, lay the foundation for succeeding rounds of progress (1997, p. 65). In other words, knowledge generation produces ‘positive externalities’; the more a specific kind of knowledge has been produced and is embodied in new product and/or process technologies, the easier it becomes to produce even more related knowledge, a phenomenon which is characterized as the ‘increasing returns logic’ (Arthur 1996). Continuous accumulation of knowledge leads to the formation of a technological trajectory, which delimits the options for further development. The concept of trajectory expresses the idea of channelled change, a change limited by constrained technological opportunities (Metcalfe 1997). In this respect, we can speak of the path dependency of technological development (David 1985). Path dependency embodies strong prescriptions about which direction of technological change should be pursued and which should be neglected. There is evidence that institutional differences across countries play a crucial role in shaping technological change (Lundvall 1992; Nelson 1993). The distinction between a general technological paradigm on the one hand and various national trajectories (Dosi 1982) or development paths on the other hand underlines the argument that technological development is not determined by a specific scientific or technological logic but that there is room for social structures and critical incidents as well as social choices to shape its direction. While the cumulative nature of the process of technological development narrows down the range of potential choices, national trajectories increase differentiation and diversification as offshoots from the main development path (OECD 1992). The concept of path dependency therefore provides us a way of viewing innovation activities as being temporally located and socially embedded (Garud and Karnoe 2000). While Dosi puts the technological dimension of national development paths at the forefront, Kogut (1991) among others expresses the idea that countries also differ in their organizational arrangements, which, according to the author,


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tend to persist for a long time. Taking up this argument, Castells suggests considering – parallel to the notion of technological trajectories – ‘the development of different organizational trajectories, namely specific arrangements of systems of means oriented towards increasing productivity and competitiveness in the new technological paradigm and in the global economy’ (1997, p. 153). Organizational change is channelled in the same way by the national institutional framework as technological innovations; it is as difficult to transfer organizational innovations from one economic system to another (Hämäläinen 2003; Strambach 2001).1 The idea of an organizational trajectory points to the importance of nontechnical aspects in the process of economic development. However, in what way technological and organizational trajectories are related to each other is still highly controversial. While Pavitt (2000) seems to support the position of technological determinism, other authors argue that technology has to be adapted to the needs of the emerging new organization model (Brousseau and Rallet 1998). Independent of whether we assign technology a leading role in the transformation process or not, it is important to understand the interaction and processes of mutual influence taking place between technological and organizational changes in a fundamental transformation process.2 A well-established techno-organizational paradigm, as the concept of national trajectories assumes, tends to form a synergistic combination with the society’s institutional structure.3 According to Freeman and Perez (1988), the synergistic complementarities among technological, organizational and institutional paradigms provide a sound basis for long-term economic growth. As the prevailing norms, values and policies are continuously reinforced by the positive experiences and feedback stemming from the evolutionary phases of technological, organizational and institutional development, people tend to have internally consistent ‘mental sets’ similar to each other. We may speak of a ‘mental paradigm’ shared by most economic actors (Hämäläinen in this volume). Path dependency, however, always carries the risk of turning into a so-called ‘lock-in’ (Grabher 1993; Johnson 1992). An old technology, but also a traditional organization model can lock the economy of a country into an inferior option of development and may in the long run result in a loss of competitiveness and the retarding of economic growth. Path dependency from a firm’s perspective implies that it has developed a degree of commitment to the setting up of learning mechanisms with the aim of exploiting particular technological and organizational opportunities. The commitment to a specific learning structure and associated competencies can explain a company’s inability to adjust to an emerging new design configuration based on a different knowledge paradigm (Metcalfe 1997). From a regional or national perspective we may distinguish between a ‘structural’, a ‘political’ and a ‘cognitive’ lock-in (Grabher 1993). A ‘structural


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lock-in’ exists when most of the resources of an economy are bound to one or only very few technologies, and when the organizational and institutional setting is mainly tied to this technology, which leaves no room for diversification and the development of new technological paths. We may talk about a ‘political lock-in’ when the dominating power structures have a vested interest in the dominant techno-organizational path and resist changes. Finally, we can speak of a ‘cognitive lock-in’ if economic actors, because of earlier success, continue to adhere to the existing national development path even if it can no longer ensure global competitiveness and economic growth. Under the conditions of a shift in the techno-organizational paradigm we can no longer talk about a channelled change, as the institutional setting in which the traditional trajectory was embedded becomes itself increasingly fragile. The unfolding of a new technological paradigm within national trajectories can only take place, as Perez argues (1983; see also Freeman 1987), together with not only fundamental organizational, but also institutional and cultural changes. It is likely that the institutional and cultural framework, which is hospitable to one set of technologies and/or organizational forms, will not be suitable for radically new ones. Whereas incremental innovations can be accommodated easily, this may not be the case with fundamental technoorganizational changes, which by definition involve an element of destruction. The negative economic consequences of a technical and/or organizational ‘lockin’ suggest giving more attention to the problem of unlocking and path creation (Garud and Karnoe 2000).

1.3

NEW OPPORTUNITIES, ECONOMIC PRESSURES, AND CHANGE EVENTS

The transformation of a new techno-organizational paradigm into a national trajectory is not an easy task; it cannot be explained by referring to single factors or simple models. Instead it emerges out of the interaction between general economic forces, change events and courses of action within the system. In the following I will first focus on external aspects of path development. The existence of ‘a window of new opportunities’, opened up by an emerging new techno-organizational paradigm, is decisive for the creation of a new development path. Currently the emerging information and communication technology (ICT) paradigm, based on a constellation of radical innovations in computers, electronics and telecommunications, is opening up a new window of technological opportunities (Freeman 1987; OECD 1988). At the same time, we can identify the development of a new organizational paradigm represented by the network model, providing opportunities to signif-


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icantly increase the efficiency of the production process (Castells 1997). The new network paradigm also includes new work regulations based on the idea of flexibility and self-regulation. A kind of symbiosis exists between the new technical and the new organizational paradigm, as the OECD among others argues (1998). We can only gain from the new technological paradigm if together with the wide use of modern ICT we also introduce new organization forms based on the network paradigm (ibid.). The two paradigms combined can become the basis of a new national trajectory incorporating a production logic that is much more effective than the old one. Companies and countries, however, will not automatically make use of the window of new technological and organizational opportunities. These new opportunities do not trigger major transformation processes themselves, as they are associated with high uncertainty and generally entail nothing more than a promise. Countries may therefore differ with respect to speed, extent and substance in their attempt to realize the advantages of the new paradigm. Economic globalization is a very important factor that drives countries to undertake a fundamental transformation influenced by the new techno-organizational paradigm, as globalization not only contributes to the stiffening of competition, but also establishes new rules and criteria of the competition game. In a globalizing economy companies as well as countries can no longer expect that their successful products and production practices of the past will keep them viable in the future. Instead they have to look for new opportunities to stay ahead in harsh global innovation competition. Still, leadership in the old paradigm may be an obstacle to the swift diffusion of the new one, as leading countries may feel less pressured to fundamentally change their successful national development path due to earlier success. They may also hesitate to undertake major changes as they are bound to the traditional development path, which has absorbed most of the available resources (Dosi, Pavitt and Soete 1990). In addition institutions have some kind of natural inertia strengthened by past successes and vested interests. Countries having fallen behind in the old techno-organizational paradigm on the other hand may take the opportunity to catch up with the leading countries in the emerging new paradigm and even to bypass them more eagerly. However, as radical, growth-enhancing innovations become increasingly difficult to make along the established techno-organizational trajectories, the leading countries in the old paradigm may increasingly suffer from ‘decreasing returns on investment’ and may therefore also feel forced to adapt to the new paradigm. It can be argued that only when lagging behind in the new emerging paradigm results in a serious economic crisis do countries feel pressured to undertake more fundamental changes and to adapt to the new techno-organizational paradigm. A serious economic crisis is often mentioned as an important ‘change event’ that can trigger fundamental and path-creating transformation


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processes. In an economic crisis it may become riskier for companies as well as countries to stay put than to move, even if it is in the wrong direction (Sabel 1995). Under these circumstances economic actors are forced to take high risks to survive and stay in the market. Therefore an economic crisis is not only destructive but it may also be functional from the viewpoint of creating a new development path.

1.4

ENDOGENOUS CHANGE PROCESSES

It is quite obvious that the development of a new national development path cannot be explained by referring only to objective factors such as new technological and organizational opportunities, general economic forces and major change events. Instead we have to emphasize the importance of the human will (Bassanini and Dosi 2000). But under the threat of a fundamental change, people often develop cognitive rigidity, which gets them to stick to the old technoorganizational trajectory and the embedding traditional institutional setting. Only if this ‘cognitive lock-in’ is broken open successfully can the transformation process get well under way. As Perez (1997) puts it: ‘a shift in “common sense” about the efficiency principles in an economy is necessary for the new paradigm to make its way into business reality’. The change from the traditional to the new paradigm is of course a very complex and often contradictory process; along the way to the new paradigm very many stumbling blocks are to be expected. An understanding of the characteristics of the new paradigm offers the best criteria for guiding social and institutional creativity in viable direction (Perez 1997). Therefore the transformation process to a great extent depends on the engagement of certain people being particularly good in imaginative exploration and creation (Johnson 1992). Among these social pioneers, intellectually flexible scientists have a very important role to play in such a process of breaking open mental rigidities (Hämäläinen in this volume). The fact is that techno-organizational opportunities do not fall like manna from heaven (Freeman 1987); they have to be created by the scientific community. Early involvement in the development of a new paradigm makes its transformation into a new national trajectory easier and it is likely to strengthen global competitiveness.4 Therefore anticipatory institutional change in the field of science becomes a very important part of the transformation process (Galli and Teubal 1997). Universities and public research institutes have to refocus their research activities, to be able to produce the scientific talents that are needed for participation in the globally organized knowledge creation process (Audretsch 2001). Schumpeter in his early writings (1934) saw the will of the entrepreneur as decisive for the creation of a new techno-organizational development path.


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Even if there are many scientific talents in a specific region or country familiar with the new paradigm, the lack of an entrepreneurial culture may become a decisive hindering factor for the development of a related development path (Audretsch 2001). The niche concept (Kemp 2002) stresses the importance of localized learning; it implies that entrepreneurs are searching for opportunities to apply new knowledge within the existing economic structures. Therefore specialized knowledge, developed within the old paradigm, becomes an important input in the transformation process. New techno-organizational trajectories often grow out of existing ones as the process of transforming a new paradigm into a new development path builds on what is available and is shaped by this. The concept of ‘localized learning’ gives the regional level an important role in the transformation process, as is the case with biotechnology, for example. Regions with special knowledge in the field of agriculture turn to green biotechnology while other regions turn to red biotechnology due to their specific pharmaceutical knowledge. Entrepreneurs’ preparedness to engage in transformational innovation processes depends on the existence of a technological but also of a market niche. Market niches are likely to emerge when the inhabitants of a region or country are open to novelties and eager to make use of fundamentally new products such as, for example, mobile phones. This means that a technology-friendly national or regional culture is important for the development of market niches. Summing up, we can argue that the path creation perspective differs from the path dependency perspective in the way in which economic actors are perceived. Rather then treating them as passive observers within a stream of events – as the concept of path dependency does – they are seen as knowledgeable agents with a capacity to reflect and act in ways other than those prescribed by the existing social rules and taken-for-granted technological artefacts. Path creation is seen as a process of a mindful deviation; it implies an ‘ability to disembed from existing structures defining relevance and also an ability to mobilize a collective despite resistance and inertia that path creation efforts are likely to encounter’ (Garud and Karnoe 2000, p. 235). The authors mention de-framing and unlearning, mobilizing minds, spanning knowledge boundaries, generating momentum, the chunking of objects, enlisting core people, mobilizing time, evoking images of the future, and applying a strategy of ‘bricolage’ as strategic processes in the creation of a new development path. 1.4.1

From Individual Champions to Innovation Networks

However, the so-called ‘big man theory’ (Schienstock 1975), which links techno-organizational development with specific characteristics of exceptional entrepreneurial personalities, hardly reflects the real world; instead, due to


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increasing specialization, new technological trajectories develop within innovation networks (Freeman 1991; Hämäläinen and Schienstock 2001). The increasing complexity of technological development, which combines specialized knowledge from different scientific and technological fields, makes it impossible for individual entrepreneurs or single high-tech small firms to become the only driving force in the process of creating a new development path. Instead the process of transforming a new paradigm into a national trajectory must become an inter-organizational enterprise in which different actors are involved. Linkages and cooperation are important for the development of a new trajectory. These linkages have to include intensive knowledge flows between entrepreneurial firms, between the scientists involved and these firms, between firms and universities, and between high-tech small firms and large established firms. But particularly knowledge-intensive business services (KIBS) have an important role to play in the process of knowledge diffusion, as they can take up a bridging function between the different actors involved in the transformation process and make knowledge flows more effective (Strambach 2001). They can function as some kind of ‘gatekeeper’ by reducing the possible mismatch in language and cognitive orientation amongst collaborators (Palmberg in this volume). However, efficient flows of information and knowledge mediated by KIBS firms are often not enough to substantially improve the exchange of information and knowledge. Due to the fact that faceto-face interaction is still an important part of knowledge communications (Leiponen in this volume), scientists and workers need to be prepared to move among several organizations. For the development of a new trajectory, both regional as well as global networks are important. Often university-based scientists have an important boundary-spanning role in innovation networks as they connect universities with regional or national industry. The fact that the knowledge demanded for creating a new trajectory is seldom available in one space only but is actually globally dispersed, also gives university-based scientists a boundary-spanning role on the global level, connecting regional innovation networks with other innovation networks all over the world. Of course, researchers working in large, globally acting companies can to some extent also assume the same role. These social pioneers can transform regional or national economies from spaces of knowledge-creating places into spaces of knowledge flows in order to accelerate the transformation process (Castells 2000). Pioneering entrepreneurs and innovative networks can take up the function of a trailblazer in the transformation process; however, a full transformation of the whole economy has to include the vast majority of companies of a national or regional industry and of other economic actors (Galli and Teubal 1997). The knowledge, information and experiences of those leading companies in the


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frontline of techno-organizational development and of the support organizations they are cooperating with need to be diffused throughout the whole economy. Such a collective learning process demands a process of institutional reembedding; a new institutional infrastructure needs to be developed that can support the creation of a new trajectory5 (Teubal 1998). It is important to reestablish a good match between the new techno-economic potential and the institutions that regulate and facilitate its full deployment through unleashing a multitude of social and institutional innovations. Here we can mention for example the need for new technology transfer institutions. As long as the underlying problems of the old institutional framework are not recognized and admitted by a great number of economic actors, the mismatch between the new techno-organizational paradigm and the stagnant institutional framework will continue to grow (Perez 1997). Without major institutional changes, which have to take place together with companies’ restructuring processes, a ‘homing’ of the majority of companies into the evolving trajectory is not possible; it is very likely that the path creation process will lose momentum and the whole transformation process will fail. 1.4.2

Users as New Social Actors

The systems of innovation approach, while putting particular emphasis on the demand side (Lundvall and Borrás 1997; Metcalfe 1997), does this only in a very restricted way. ‘In general the customer is constructed more as a passively demanding object and as a source of information that has to be explored …’ (Sörensen 2002, p. 70), while the active part is left to the producers. While it is assumed that new technological developments are influenced and controlled by the demand side, the relationship between producers and users is configured in an asymmetric manner. Producers are expected to take demand into account when they develop new technologies, which means that users do not play an active part in the creation of a new techno-organizational trajectory. Producers and users, however, act within different ‘frames of reference’ comprising a set of beliefs, standards of evaluation, and behaviour (Bijker 1987). Both groups often apply very different criteria in judging the opportunities and threats of a new techno-organizational paradigm and its transformation potential. A new technology, for example, which from a technological and economic perspective may have great future potential, may not do justice to the evaluation criteria applied by users, as their frames often consist of multiple meanings, including, for example, aspects of social and ecological sustainability. It is highly unlikely that an existing techno-organizational path can be transformed fundamentally or even replaced by a new one without users or concerned citizens being actively involved, as they are the ones that are confronted with


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and affected by these deep changes in the first place. It is therefore important to give up the traditional asymmetric configuration of the producer/user relationship and to conceive of user groups and concerned citizens as independent social actors within the process of path creation. The concept of ‘social practice’ (Brown and Duguid 1991) gives users a much more active role in the process of change, as it assumes that novelties become innovations only when they start playing a significant role in meaningful social practices (Tuomi 2002). 1.4.3

The Transformation Process as ‘Contested Terrain’

Transformation periods must be seen as periods of trial-and-error experimentation and of confrontation between the forces of change and those of persistence, as it is widely indeterminate in which direction a new national techno-organizational trajectory develops. Evolutionary thinking admits the social shaping of a new development path,6 which also implies that different interests are at stake. Still there is hardly any mention of the fact that fundamental transformation processes are also fraught with many conflicts spurred by widespread uncertainty and instability (Perez 1997). But the transformation process cannot be conceptualized as a rational decision-making process; instead it involves ‘vested interests’ and ‘power games’. If we take this into account, the development of a new national trajectory must be conceived of as a ‘contested terrain’. For example, already the question whether and to what extent the national scientific community should engage in the development of a new knowledge paradigm may create serious problems; one should not underestimate the stability of scientific institutions and the mental inertia of highly specialized scientific communities. Consequently the issue of whether anticipatory institutional change in the field of science should take place or not, may trigger serious conflicts. We can also anticipate a confrontation between the representatives of the old techno-organizational regime and the propagators of the new development perspective associated with the new paradigm, in which not only the growth and competition model is at stake but also the existing division of power. For the representatives of the past unlearning and leaving behind much of the earned experience and accepting change is particularly painful and will cause resistance in various forms (Perez 1997). Additional conflict can result from the fact that a new paradigm can be transformed into different trajectories and that different actors favour different pathways of techno-organizational development. It is not at all sure that the best solution will always win out; in fact technologically and organizationally inferior solutions may emerge from the ‘contested terrain’ in the long run, simply because the actors that favour these inferior solutions have the strongest power position.


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13

THE EXOGENOUS DIMENSION OF THE INNOVATION SYSTEM

The innovation system as an open system (Lundvall 1992) is part of a comprehensive hierarchy of systems. It itself consists of a number of subsystems and is linked to other subsystems of the economic system which represent the higher-level system. Consequently, when analysing the development of a new path and its institutional embedding, we also have to take into account the external dimension of the innovation system. In a situation of dynamic change we have to look at processes of co-evolution and mutual adaptation between and within the various economic subsystems.7 Besides the innovation subsystem, the economic system consists of the production system, the resource supply system, including the human capabilities-creating system, and the management or regulatory system as other subsystems.8 As a subsystem, the innovation system has a particular focus: the generation of change in the economic system, by acquiring, producing, and diffusing new knowledge (Hauknes 2000).9 It therefore contributes to the creation of economic growth and social welfare only indirectly, by producing and distributing knowledge that is used to modernize and renew the production system, its products, services, and processes.10 Whether a new development path can be established successfully or not, therefore, very much depends upon the effective management of the interface between the innovation system and the production system. Only if the new knowledge accumulated and created is applied and transformed into new products and techno-organizational production structures and leads to significant improvements in productivity and competitiveness, can we speak of a successful transformation. The innovation system, on the other hand, acquires its structures, ways of operating and functionality through the other economic subsystems. Whether new scientific and other knowledge will be produced within the innovation system (and the production system), very much depends on the capacity of the resource supply system to provide various types of new capital, including in particular the creation of new human capital. Without the allocation of new resources, the innovation system will hardly be able to initiate the development of a new national growth path. Also the management or regulatory system has to take part in the transformation process, as incentives associated with traditional regulations may channel resources in the wrong direction and become a hindrance to the development of new knowledge. On the other hand, eliminating regulations that restrict cooperation can open up new channels for knowledge creation and dissemination (Määttä in this volume). So far research on systems of innovation has rarely considered negative feedback from the creation of a new development path (Hage 1999; Lundvall


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and Archibugi 2001). However, we cannot treat innovation and particularly fundamental techno-organizational changes automatically as a positive-sum game (Boden and Miles 2000). There are always opportunities and risks, winners and losers in a fundamental transformation process. We have to look for example at problems and strains in other social systems and economic subsystems caused by the increasing innovation dynamic. Unintended consequences of a growing innovation dynamic are important to identify, as they may actually question the advantages and gains derived from the establishment of a new development path. A new innovation dynamic released through a changeover to a new national trajectory may create new jobs in emerging new industries, but a ‘skill-biased technical change’ (Bresnahan et al. 1999) may also increase the risk of social exclusion for other groups of employees (Schienstock 2001). And Freeman (1992) has pointed out that together with a new techno-organizational paradigm and its transformation into a national trajectory, new ecological challenges may occur, destroying the prospects for high economic growth. The question of sustainability in economic, social and ecological terms has to come to the forefront in the scientific and political debate on national innovation systems.

1.6

INNOVATION POLICY IN THE TRANSFORMATION PROCESS

1.6.1

The New Role of the State

Often the state is given a decisive role in the process of creating a new technoorganizational path. Stable and lasting processes of path creation can only emerge, as we have argued above, if all actors of an economy are becoming involved and are marching in the same direction. In this respect the state has an important role to play, as companies may not be able to develop the generative impulse that is required to set a path creation process in motion. In a situation of great uncertainty companies often hesitate to undergo major changes, trying to avoid a wrong move (Sabel 1995). However, the old policy recipes do not work any longer, the transformation process not only puts the economy but also the political system under enormous pressure for change. We therefore have to conceptualize the role of the state in the process of technoorganizational development in a new way (see also Hämäläinen in this volume). Traditional direct technology policy saw the state as a sovereign economic actor exercising control over the dynamics of technological progress either through the setting of new research incentives or by establishing publicly owned research institutes, which allowed direct intervention in the process of techno-


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logical development (Schienstock 1994). However, in a period of fundamental change, uncertainty becomes a key issue for policy-makers, as for all other participants. ‘There can be no presumption’, as Metcalfe argues, ‘that the policy maker has a superior understanding of market circumstances or technological information; rather what he does enjoy is superior co-ordination ability across a diverse range of institutions’ (1997, p. 274). A new policy perspective sees the state as a partner in the adventure of exploring a new development path. This does not necessarily mean that the state loses its influence in steering the process of techno-organizational development. In a situation of fundamental transformation, where companies due to great uncertainty about future developments have difficulties in acting strategically, the state has to take the leading role in helping companies to get out of path dependency due to its superior co-ordination ability. This means that while the significance of technological macro-economic management may decrease, the role of the state in the process of path formation remains strong (Hirst and Thompson 1992). The new role of the state can be described as a catalyst for innovation processes, a supporter of ongoing research and innovation activities, a facilitator of cooperation in research and innovation processes, a moderator of diverging interests, an organizer of a dialogue between various economic actors on future developments and as an initiator of questions and new tasks (Schienstock 1994). From what we have said so far, we can conclude that the creation of a new national trajectory needs new forms of co-ordinating various innovation activities; the state no longer controls the innovation process directly through establishing public research institutes and launching large research projects but rather turns to more indirect forms of control (Schienstock 1994). Here we suggest ‘vision creation’ and ‘discursive co-ordination’ as key elements of a new form of steering the transformation process. A systemic vision (Chang and Rowthorn 1995; Schienstock 1999) can be characterized as a set of general ideas of how to transform an economy in order to create economic growth, how to modernize economic structures effectively, and how to restructure production processes in order to increase productivity and innovativeness. It also has a normative dimension, as it becomes the basis of practical restructuring processes. A major advantage of a systemic vision is that it makes communication among social actors possible, even if they have different interests and perceptions. The second aspect of successful co-ordination and transformation management is social discourse among the various interdependent actors of the system. When discursive co-ordination is applied, economic activities are co-ordinated through continuous and rich communication and mutual adjustment. Systemic discourse can be viewed as a platform for jointly creating and exchanging knowledge among different actors. Discursive co-ordination is


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not primarily intended to create consensus among the participants; rather it aims to initiate interactive learning processes. Vision creation and discursive coordination can be seen as forming the framework for connecting existing knowledge stocks and skills, for creating learning opportunities through the exchange of experience, and for opening up new communication channels between the actors in the innovation system (Strambach 2002). 1.6.2

Policy Networks and Policy Learning

The changing role of the state in the process of techno-organizational development reflects the increasing fragmentation of power (Mayntz 1996). This results, on the one hand, from the fact that a growing number of organizations have knowledge relevant for the formulation of innovation policy. The increasing fragmentation of power is, on the other hand, linked to the fact that some organizations have the means to block the implementation of new policy programmes aimed at supporting transformation processes. The state therefore becomes more and more dependent upon other collective actors such as large companies, research institutes, unions and employer associations and is forced to let these organizations participate in the process of policy conceptualization and to integrate them into the process of policy implementation. Because of the growing integration of private and public actors in the process of policy formulation and implementation, policy networks become a new form of governance in the field of technology and innovation policy. They successively replace top-down policy-making in the form of state intervention, as well as more businesslike market-oriented governance (Kickert and Koppenjan 1999; Mayntz 1996, p. 471 ff). Kickert, Klijn and Koppenjan define policy networks as ‘(more or less) stable patterns of social relationships between interdependent actors, which take shape around policy problems and/or policy programs’ (1999, p. 6). The implementation of policy networks gives the state the opportunity to get directly into contact with the relevant actors and to negotiate policy programmes. This means that policy programmes not only profit from a broader knowledge base but also their legitimacy is growing and the probability of successful implementation is increasing due to the binding character of participation. Social actors, having participated in the process of policy formulation, can hardly oppose its implementation, even if the outcome does not support their interests. The emergence of policy networks, we can conclude, cannot only be explained by a weak state. It also demonstrates that the state has become more sensitive to the increasing demand for different expertise in innovation policy, for a growing complexity of political power and the increasing need for joint problem-solving in a path-creating period (Mayntz 1996, p. 474).


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The network-based form of governance is also more and more applied with respect to the internal organization of the policy process. In a situation of fundamental techno-organizational change, innovation policy becomes so complex that a multitude of different and specialized units have to be involved; government agents no longer form a single integrated hierarchy. Particularly when innovation policy takes into account possible negative feedback from the creation of a new national trajectory, steering the policy process through bureaucratic measures of control is no longer an option; instead the increasing complexity can only be coped with by developing intra-organizational networks. Direct communication and knowledge exchange are supported by the growing use of modern ICT within governance processes. Policy formulation within policy networks cannot be understood as strictly rational management of technological change consisting of clearly separated stages: setting goals, developing programmes, and implementing projects (Klijn 1999). Instead we have to conceive of the policy process as a trial-and-error process; there is a strong case for policy experimentation. It is important to guarantee feedback from those experiments to allow for policy-makers and other participants in policy networks to accumulate experiences. Based on the above argumentation, we can characterize innovation policy as a process of policy learning (Lundvall and Johnson 1993, p. 18). ‘The learning approach’, as Lundvall and Borrás argue, ‘... provides a fluid perspective of a policy process in continuous transformation and evolution where no clear stages can be discerned’ (1997, p. 64). Policy learning must be understood as a self-reflexive process. This means more than anticipating new developments and considering them in the development of new strategies; self-reflexivity includes the monitoring of the environment, critically dissociating oneself from the traditional functioning of reality and developing alternative ways of acting (Sabel 1997; Storper 1997). It is, for example, important to reflect on how much deviation from the existing national development path is possible, as major transformation processes, as mentioned before, also cause negative feedback that can undermine all the benefits deriving from the change process. Innovation policy based on reflexive learning can be supported by a set of instruments that allow for continuous self-observation and monitoring the external environment: benchmarking, technology assessment and technology foresight.11 In particular institutional benchmarking has become increasingly popular; governments begin to realize the advantage of institutional adaptation and learning. Freeman has expressed the idea that by comparing various innovation systems and their institutional structures, we might be able to identify ‘good practices’ and ‘new tools’, which could then be ‘borrowed’ by other nations to improve their innovative and economic performance (1987). However, one should not overestimate the chances of being able to identify


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institutional solutions that can easily be transferred from one country to another on the basis of benchmarking activities. This is particularly the case as the institutional setting in most countries becomes increasingly fragile and companies are under pressure to adapt to the new techno-organizational paradigm. In a process of dynamic change it becomes difficult to identify ‘best practices’ or even ‘good practices’ (Porter 1990). Reflexive benchmarking, or intelligent benchmarking as it is also called (Schienstock and Hämäläinen 2001; see also Lundvall and Tomlinson 2001), is less about deciding ‘what is best’ or ‘what universal truth’ can be derived from comparison. The identification of a ‘best practice’ is not the primary goal of reflexive benchmarking; instead it has to do with getting to know more about various institutional solutions in different economic structures. Particularly in a situation of fundamental transformation processes, mechanistic benchmarking is hardly possible, as institutions are becoming increasingly fragile. The aim of reflexive benchmarking is to be able to gain a better understanding of one’s own solutions, their strengths and weaknesses, when seen in light of what others do, and what options they see (Toulmin 1990). Such an understanding can cause policy-makers to assess institutional solutions of their own system much more critically and may help them to deliberately imagine and act on different strategies.

1.7

OVERVIEW OF THE BOOK

We have clustered the chapters of the book into four main parts. In Part One, the conceptual framework that underlies the book is presented. In addition to this introductory chapter by Schienstock, Hämäläinen extends the conceptual framework, presenting particular evidence on a change of national cognitive frames as a precondition for a fundamental transformation of the economy and society. He argues that in an era of fundamental transformation, traditional cognitive frames may become a hindrance to adapting to the new techno-organizational paradigm and pioneering scientists and politicians are needed to come out of the cognitive lock-in. Using Finland as an example, he demonstrates the changeover process from a path dependency perspective to a path creation perspective. Part Two focuses on the industrial and company levels of the transformation process. Paija and Rouvinen focus on the Finnish ICT cluster that has emerged together with Nokia’s development into a global player. Due to its particular strength in telecommunications, Finland has become the most specialized country in the world. The two authors mention strong competition, the unique character of the Finnish telephony market from its opening in 1880, as a key factor that can explain the strength of the ICT cluster to some extent.


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Global orientation and networking are seen as important factors that have sustained the competitiveness of the Finnish telecommunications sector. Despite the radical transformation of the industrial structure due to the development of the ICT cluster, Finland still relies to a significant extent on the more traditional industries such as forestry- and metals-based industries. Based on rich empirical material from case studies, Palmberg concludes that there are significant niches of technological opportunities for the traditional Finnish industries, despite the fact that there is a lower pay-off from R&D investments. To strengthen traditional industries in Finland, Palmberg suggests accelerating the diffusion of new technologies, supporting trans-industry network formation, and improving general framework conditions as key policy measures. Knowledge-intensive business services have become one of the key vectors of knowledge transfer in the innovation system and they are expected to serve as new engines of knowledge-based growth and innovation. Leiponen discusses, based on new data, the development of the KIBS sector in Finland. Although due to its strength in telecommunications, Finland has excellent preconditions for developing a strong KIBS sector, high expectations have not materialized so far. The KIBS sector may be seen as the weak part of the Finnish innovation system. Ali-Yrkkö and Hermans analyse the success story of Nokia, a leading player in the global telecommunications market and Finland’s most famous company. They argue that while the public sector played a significant part in the development of Nokia by funding R&D projects, it profited even more due to a high pay-back ratio to this R&D funding. Furthermore, extensive knowledge exchange takes place within Nokia’s innovation network, which helps all partners to grow very rapidly. Mutual recruitment and exchange of personnel are important channels for distributing knowledge within the network. The authors also mention some problems in the cooperation, such as the allocation of intellectual property rights. Alasoini’s chapter examines the introduction and dissemination of the flexible production model in Finland representing the new organization logic, from a company perspective as well as from the perspective of the national innovation system. The author demonstrates that with respect to production management, work organization and employment relations, Finnish companies have progressed significantly towards a new flexible production model. But he also points to some factors which pose a threat to continuing success: uneven growth in high-tech and traditional sectors, the small number of dynamic mediumsized companies that can take up the role of a system supplier and still unstable cooperation patterns. Part Three focuses on the regional and institutional levels of the transformation process. The success in constructing a flourishing information and telecommunications cluster has encouraged Finland to seek equal possibilities


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in other knowledge-intensive industries. Presently, biotechnology is seen as an auspicious business area. Development in biotechnology is strongly regionally based in Finland, as it is in other countries. During recent years, Turku developed a regional innovation network in this field, as Bruun demonstrates in his chapter. The author sees great growth potential for biotechnology in the city of Turku, due to a strong institutional setting in R&D and increasing interaction among the key network partners. Little production and very little international foreign investment are mentioned as major disadvantages. Tampere Region, as Kautonen, Koski and Schienstock argue, can be seen as a good example of how territories can manage to get out of path dependency and create a new development path. While up until the beginning of the 1990s, smokestack industries dominated in the region, the rapidly developing ICT sector has recently become the driving force of economic growth. The authors argue that in particular the strong cooperation between industry and universities has contributed to the recovery and reinvention of the region. During recent years university reform to increase efficiency can be seen as one of the most important changes in the institutional setting. The renewal of the science system has, as Nieminen and Kaukonen argue, led to a more applied orientation particularly in universities of technology and has stimulated increasing cooperation among universities, research institutes and industry. Although not only industry but also universities have benefited significantly from research cooperation, to what extent universities should focus on applied research is still an open question. The establishment of polytechnics, as Kekkonen argues, can be seen as the biggest reform in the Finnish vocational education system. On the one hand, the polytechnic reform reflects a growing trend towards higher education; on the other hand, it can be seen as a reaction to an increasing need for students that have a strong applied orientation. A side effect is, however, the decreasing attractiveness of secondary vocational education. This may cause some structural problems in future as in many low-tech industries a labour force educated at upper secondary vocational level contributes significantly to value added. In the course of development towards a knowledge-based economy, the labour market is also undergoing significant changes. The traditional idea of lifelong, highly standardized employment, as Suikkanen and Linnakangas demonstrate, has increasingly been challenged as more and more Finns have to accept unstable working careers. However, while the growing dynamic of the labour market is mostly associated with employment risks, it can also be seen as creating new opportunities to strive for more qualified jobs. On the other hand, the still high unemployment rate and particularly the growing share of long-term unemployed can be seen as a major challenge for the Finnish labour market policy.


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Legal regulations and particularly competition law represent an important part of the economy’s management system, which closely interacts with the innovation system. Määttä suggests that the fact that innovation competition has become more common, particularly with respect to high-tech industries, needs to be reflected in competition law. One of his main arguments is that, if technological development is rapid, horizontal and partly vertical collusion by enterprises is not a great threat, as this will keep competition alive. Therefore the author concludes that competition law should focus more on dynamic than on static efficiency also in Finland. Although Finnish economic success during the 1990s is often associated with companies’ specialization strategies, the science and technology policy of the Finnish government, as Lemola argues, also had a significant influence on the fact that the country came rather strongly out of the deep depression at the beginning of the last decade. In general, Finnish science and technology policy was based on a strategy of copying and adapting successful models from elsewhere. This strategy has helped Finland in its catching-up process and has placed it among the leading industrial countries. Successful further development, on the other hand, becomes a great challenge to future policy-making, as imitation is no longer an option for Finnish science and technology policy. Lemola argues that the policy in this field should be built more on exploitation. In the last chapter, in Part Four, Schienstock tries to fill the conceptual framework developed at the beginning of the book based on the material presented in the various chapters. Not least due to the systemic approach, Finland was able to successfully develop a new national trajectory and to become one of the leading countries in the new knowledge paradigm. However, Schienstock also points to major shortcomings that suggest being less enthusiastic when the Finnish knowledge-based society model is discussed. The case of Finland, as Schienstock argues, at the same time demonstrates that scenarios anticipating the end of the welfare state are also fairly exaggerated, although cutbacks have taken place.

1.8

CONCLUSION

The aim of this introductory chapter is to reorient research based on the systems of innovation approach, which has concentrated so far on the aspect of path dependency. While the strength of this perspective is that it does not separate technological innovation from past developments, but assumes some kind of continuity in the process of technological change, it assigns too much weight to history, and therefore inadequately characterizes the fragility of national techno-organizational trajectories and the embedding institutions. Particularly in a period of an emerging new knowledge paradigm, research needs to focus


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more on unlocking and path creation, as path dependency may lead to serious lock-ins. The process of path creation is a highly complex process; it cannot be explained by referring to single factors or simple models. Economic pressures, major change events and endogenous change processes must be taken into account when studying the process of developing a new national trajectory. Concerning endogenous processes, attention has to be given to both technoorganizational restructuring on the firm level as well as institutional change. Also new forms of policy-making, attempting to indirectly control the innovation process through policy networks, can be seen as part of the systemic transformation currently taking place. The following chapters provide valuable pieces of the mosaic of the Finnish transformation process towards a knowledge economy. In the end we will try to analyse more closely the changeover from path dependency to path creation in the Finnish economy.

NOTES 1. For example, flexi-Fordism can be seen as a specific trajectory of the Fordist organization paradigm developed in Germany due to its specific institutional environment (vocational training system and a strong position of unions in collective bargaining). 2. In the following I will mainly use the concepts of techno-organizational change or a technoorganizational trajectory, as technological and organizational changes in general co-evolve. 3. For the distinction between organizations and institutions, see Edquist and Johnson (1997). 4. There is empirical evidence that ICT or biotechnology-related production has an intensifying concentration tendency and that laggards in the two technologies rarely catch up, let alone leapfrog the leaders (Koski, Rouvinen and Ylä-Anttila 2002 and Audretsch 2001). 5. Here we refer to the innovation system in a narrow sense. For a distinction between the innovation system in a narrow and in a wider sense see Lundvall (1992). 6. This perspective distinguishes economic evolutionary theory from biological concepts (see for example Nelson 1993). 7. Here we face the problem of boundary-drawing. A wider concept of the innovation system, for example, conceives of parts of the other economic subsystems as belonging to the innovation system. 8. We here refer to the AGIL scheme (see Parsons, Bales and Shils 1953). The authors identify four functional requirements that represent the basis for social subsystems in general and for subsystems of the economic system in particular: adaptation, goal attainment, integration and pattern maintenance. We associate the innovation system with the adaptation function, the production system with the goal attainment function, the management system with the integration function, and the resource supply system with the pattern maintenance function. Functional systems represent abstract wholes, which – contrary to structural systems that represent concrete organizations – can only be identified and distinguished from their environment analytically. The identification of different system requirements and therefore also of different subsystems represents a subjective decision made by each author. 9. While the emergence of specialized subsystems was seen as an important phenomenon of modernity, we can now identify a new element of modern societies. Specific functions of an economy are no longer the domain of specialized subsystems only; instead, polycentricity becomes a more common phenomenon. This means that while specialized subsystems are still important, they are increasingly forced to cooperate with other subsystems in carrying out their particular function. For example, the creation of new knowledge takes place not


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only in the innovation system but also in the production system through various types of learning. There is no room here to further develop the methodological aspects of polycentricity. 10. Nelson argues that there are sets of intertwining terms and characterizations that make a focused analytical discussion very difficult (1993, p. 518). Particularly the fact that innovation systems are directly associated with competitiveness, growth, and social welfare is seen by him as a major problem. He claims that it is important to be able to regard innovation apart from the overall competitiveness of national economies. 11. Both instruments, technology assessment and technology foresight, have passed through a functional change. There is considerable promise in deploying foresight as a platform for sharing perceptions and as a tool for learning and networking. The original idea of using foresight as a tool for selecting promising technologies and setting priorities in innovation policy, on the other hand, is difficult to realize, if at all. Similarly, technology assessment, first seen as an early warning system, has developed into a concept of shaping technology through social discourse.

REFERENCES Arthur, B.W. (1996), ‘Increasing Returns and the New World of Business’, Harvard Business Review, July–August, 100–9. Audretsch, D.B. (2001), ‘The Role of Small Firms in U.S. Biotechnology Industry’, Small Business Economics, Special Issue, 1–2 (17), 3–15. Bassanini, Andrea P. and Giovanni Dosi (2000), ‘When and How Chance and Human Can Twist the Arms of Clio’, in Raghu Garud and Peter Karnoe (eds), Path Creation and Path Dependency, Nahwah, NY: Lawrence Erlbaum Publishers, pp. 41–68. Bijker, Wiebe E. (1987), Of Bicycles, Bakalites, and Bulbs: Towards a Theory of Sociotechnical Change, Cambridge, MA.: The MIT Press. Boden, Mark and Ian Miles (2000), ‘Conclusions: Beyond the Services Economy’, in Mark Boden and Ian Miles (eds), Services and the Knowledge-Based Economy, London and New York: Continuum, pp. 247–64. Bresnahan, Timothy F., Erik Brynjolfsson and Lorin M. Hitt (1999), ‘Information Technology, Workplace Organization and the Demand for Skilled Labor: Firm-level Evidence’, Working Paper 7136, National Bureau of Economic Research, NBER Working Paper Series, May. Brousseau, Eric and Alain Rallet (1998), ‘Beyond Technological or Organizational Determinism: A Framework to Understand the Link between Information Technologies and Organizational Changes’, in Stuart Macdonald and Gary Madden (eds), Telecommunication and Socio-economic Development, Amsterdam: North-Holland, pp. 245–62. Brown, J.S. and P. Duguid (1991), ‘Organizational Learning and Communities-ofPractice: Towards a Unified View of Working, Learning and Innovation’, Organization Science 2 (1), 40–57. Castells, Manuel (1997), The Rise of the Network Society, First edition, Oxford: Blackwell Publishers. Castells, Manuel (2000), The Rise of the Network Society, Second edition, Oxford: Blackwell Publishers. Castells, Manuel and Pekka Himanen (2001), The Finnish Model of the Information Society, Sitra Reports Series 17, Vantaa: Tummavuoren Kirjapaino Oy.


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Chang, Ha-Joon and Bob Rowthorn (1995), ‘Role of the State in Economic Change, Entrepreneurship and Conflict Management’, in Ha-Joon Chang and Bob Rowthorn (eds), Role of the State in Economic Change, Oxford: Oxford University Press. David, P. (1985), ‘Clio and the Economics of QWERTY’, Economic History, 2 (75), 227–323. Dosi, Giovanni (1982), ‘Technological Paradigms and Technological Trajectories: A Suggested Interpretation of the Determinants and Directions of Technological Change’, Research Policy, 11 (3), 147–62. Dosi, Giovanni, Keith Pavitt and Luc Soete (1990), The Economics of Technical Change and International Trade, London: Harvester Wheatsheaf. Edquist, Charles and Björn Johnson (1997), ‘Institutions and Organizations in Systems of Innovation’, in Charles Edquist (ed.), Systems of Innovation: Technologies, Institutions and Organizations, London: Pinter Publishers, pp. 41–63. Foray, David (1997), ‘Generation and Distribution of Technological Knowledge: Incentives, Norms, and Institutions’, in Charles Edquist (ed.), Systems of Innovation: Technologies, Institutions and Organizations, London: Pinter Publishers, pp. 64–85. Freeman, Chris (1987), Technology Policy and Economic Performance: Lessons from Japan, London: Pinter Publishers. Freeman, Chris (1991), ‘Networks of Innovators: A Synthesis of Research Issues, Research Policy, 4 (20), 499–514. Freeman, Chris (1992), ‘A Green Techno-Economic Paradigm for the World Economy’, in Chris Freeman (ed.), The Economics of Hope, London: Pinter Publishers, pp. 190–211. Freeman, Chris and Charlotta Perez (1988), ‘Structural Crisis of Adjustment: Business Cycles and Investment Behavior’, in Giovanni Dosi, Chris Freeman, Richard R. Nelson, G. Silverberg and Luc Soete (eds), Technical Change and Economic Theory, London: Pinter Publishers, pp. 38–66. Galli, Riccardo and Morris Teubal (1997), ‘Paradigmatic Shift in National Innovation Systems’, in Charles Edquist (ed.), Systems of Innovation: Technologies, Institutions and Organizations, London: Pinter Publishers, pp. 342–70. Garud, Raghu and Peter Karnoe (2000), ‘Path Creation as a Process of Mindful Deviation’, in Jussi T. Koski and Suvi Marttila (eds), Proceedings: Conference on Knowledge and Innovation, 25–26 May, Helsinki: Helsinki School of Economics and Business Administration, Center for Knowledge and Innovation Research, pp. 234–67. Grabher, Gernot (1993), ‘The Weakness of Strong Ties: The Lock-in of Regional Development in the Ruhr Area, in Gernot Grabher (ed.), The Embedded Firm: On the Socio-economics of Industrial Networks, London: Routledge, pp. 255–77. Hämäläinen, Timo (2003), National Competitiveness and Economic Growth: The Changing Determinants of Economic Performance in the World Economy, Cheltenham: Edward Elgar. Hämäläinen, Timo and Gerd Schienstock (2001), ‘The Comparative Advantage of Networks in Economic Organization: Efficiency and Innovation in Highly Specialized and Uncertain Environments’, in OECD (ed.) Innovative Networks: Cooperation in National Innovation Systems, OECD Proceedings, Paris: OECD, pp. 17–45. Hauknes, Johan (2000), ‘Dynamic Innovation Systems: What is the Role of Services?’, in Mark Boden and Ian Miles (eds), Services and the Knowledge-Based Economy, London and New York: Continuum, pp. 38–63.


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Hirst, P. and G. Thompson (1992), ‘The Problem of Globalization: International Relations, National Economic Management, and the Formation of Trade Blocs’, Economy and Society, 4 (12), 357–96. Johnson, Björn (1992), ‘Institutional Learning’, in Bengt-Åke Lundvall (ed.) National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning, London: Pinter Publishers, pp. 23–44. Kemp, René (2002), ‘Environmental Protection through Technological Regime Shifts’, in Andrew Jamison and Harald Rohracher (eds), Technology Studies and Sustainable Development, Munich, Vienna: Profil Verlag, pp. 95–126. Kickert, Walter J.M., Erik H. Klijn and Joop F.M. Koppenjan (eds) (1999), Managing Complex Networks. Strategies for the Public Sector, London, Thousand Oaks, CA and New Delhi: Sage. Kickert Walter J.M. and Joop F.M. Koppenjan (1999), ‘Public Management and Network Management: An Overview’, in Walter J.M. Kickert, Erik H. Klijn and Joop F.M. Koppenjan (eds), Managing Complex Networks. Strategies for the Public Sector, London, Thousand Oaks, CA and New Delhi: Sage, pp. 35–61. Klijn, Eric H. (1999), ‘Policy Networks: An Overview’, in Walter J.M. Kickert, Eric H. Klijn and Joop F.M. Koppenjan (eds), Managing Complex Networks: Strategies for the Public Sector, London, Thousand Oaks, CA and New Delhi: Sage, pp. 14–34. Kogut, B. (1991), ‘Country Capabilities and the Permeability of Borders, Strategic Management Journal, Special Issue 1–3 (12), 33–47. Koski, H., P. Rouvinen and P. Ylä-Anttila (2002), ‘ICT Clusters in Europe: The Great Central Banana and Small Nordic Potato’, Information Economics and Policy, 14 (2), 145–65. Lundvall, Bengt-Åke (1992), ‘Introduction’, in Bengt-Åke Lundvall (ed.), National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning, London: Pinter Publishers, pp. 1–22. Lundvall, Bengt-Åke and Daniele Archibugi (2001), ‘Introduction: Europe and the Learning Economy’, in Daniele Archibugi and Bengt-Åke Lundvall (eds), The Globalizing Learning Economy, Oxford, New York: Oxford University Press, pp. 1–20. Lundvall, Bengt-Åke and Susana Borrás (1997), The Globalising Learning Economy: Implications for the Innovation Policy, EUR 18307, Brussels: European Commission/TSER. Lundvall, B.-Å. and B. Johnson (1993), ‘The Learning Economy’, Journal of Industrial Studies, 1 (2), 23–42. Lundvall, Bengt-Åke and Mark Tomlinson (2001), ‘Learning by Comparing: Reflection on the Use and Abuse of Benchmarking’, in G. Sweeney (ed.), Innovation, Economic Progress and Quality of Life, Cheltenham: Edward Elgar, pp. 120–36. Mayntz, Renate (1996), ‘Policy-Netzwerke und die Logik von Verhandlungssysteme’, in Patrik Kenis and Volker Schneider (eds), Organisation und Netzwerk: Institutionelle Steuerung in Wirtschaft und Gesellschaft, Europäisches Zentrum, Vienna, Frankfurt, New York: Campus, pp. 471–96. Metcalfe, Stan (1997), ‘Technology Systems and Technology Policy in an Evolutionary Framework’, in Daniele Archibugi and Jonathan Michie (eds), Technology, Globalisation and Economic Performance, Cambridge: Cambridge University Press, pp. 268–96. Nelson, Richard R. (ed.) (1993), National Systems of Innovation: A Comparative Study, Oxford: Oxford University Press.


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OECD (1988), New Technologies in the 1990s: A Socio-economic Strategy, Paris: OECD. OECD (1992), Technology and the Economy: The Key Relationships, Paris: OECD. OECD (1998), Technology, Productivity and Job Creation: Best Policy Practices, Paris: OECD. Parsons, Talcott, Robert F. Bales and Edward A. Shils (1953), Working Papers in the Theory of Action, Glencoe, IL.: Free Press. Pavitt, Keith (2000), ‘Innovation Routines in the Business Firm: What Matters, What’s Staying the Same, and What’s Changing?’ Paper for a keynote speech at the meeting of the Schumpeter Society in Manchester, 1 July, 2000, SPRU, Science and Technology Policy Research, Brighton. Perez, Charlotta (1997), ‘The Social and Political Challenge of the Present Paradigm Shift’, Paper presented for the Norwegian Investorforum, 15–16 May, Oslo. Porter, Michael (1990), The Competitive Advantage of Nations, New York: Free Press. Sabel, Charles F. (1995), ‘Bootstrapping Reform: Rebuilding Firms, the Welfare State and Unions, Politics and Society, 1 (23), 5–48. Sabel, Charles F. (1997), ‘Constitutional Orders: Trust Building and Response to Change’, in Rogers J. Hollingworth and Robert Boyer (eds), Contemporary Capitalism: The Embeddedness of Institutions, Cambridge: Cambridge University Press, pp. 154–88. Schienstock, Gerd (1975), Organisation innovativer Rollenkomplexe, Meisenheim am Glan: Anton Hain. Schienstock, Gerd (1994), ‘Technology Policy in the Process of Change: Changing Paradigms in Research and Technology Policy’, in Georg Aichholzer and Gerd Schienstock (eds), Technology Policy: Towards an Integration of Social and Ecological Concerns, Berlin and New York: Walter de Gruyter, pp. 1–23. Schienstock, Gerd (1999), ‘Transformation and Learning: A Perspective on National Innovation Systems’, in Gerd Schienstock and Osmo Kuusi (eds), Transformation Towards a Learning Economy. The Challenge for the Finnish Innovation System, Sitra 213, Helsinki: Hakapaino Oy. Schienstock, Gerd (2001), ‘Social Exclusion in the Learning Economy’, in Daniele Archibugi and Bengt-Åke Lundvall (eds), The Globalizing Learning Economy, Oxford and New York: Oxford University Press, pp. 163–76. Schienstock, Gerd and Timo Hämäläinen (2001), Transformation of the Finnish Innovation System: A Network Approach, Sitra Reports Series 7, Helsinki: Hakapaino Oy. Schumpeter, Joseph A. (1934), The Theory of Economic Development, Cambridge, MA.: Harvard University Press. Sörensen, Knut H. (2002), ‘Providing, Pushing and Policing. Towards a New Architecture of Technology Policy’, in Andrew Jamison and Harald Rohracher (eds), Technology Studies and Sustainable Development, Munich and Vienna: Profil Verlag, pp. 65–94. Storper, Michael (1997), The Regional World: Territorial Development in a Global Economy, New York: The Guilford Press. Strambach, Simone (2001), ‘Die Veränderung von Innovationssystemen in der globalen Ökonomie: wissensintensive unternehmensorientierte Dienstleistungen und organisatorischer Wandel dargestellt an Deutschland und Grossbritanien’, Universität Stuttgart, Institut für Geographie, unpublished manuscript.


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Strambach, Simone (2002), ‘Change in the Innovation Process: New Knowledge Production and Competitive Cities – The Case of Stuttgart’, European Planning Studies, 2 (10), 215–31. Teubal, Morris (1998), Enterprise Restructuring and Embeddedness – An Innovation Systems and Policy Perspective, CRIC Discussion Paper No 15, Manchester: University of Manchester. Toulmin, Stephen E. (1990), Cosmopolis. The Hidden Agenda of Modernity, New York: Free Press. Tuomi, Ilkka (2002), Networks of Innovation. Change of Meaning in the Age of the Internet, Oxford: Oxford University Press.


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2. Towards a theory of social innovation and structural change* Timo Hämäläinen 2.1

INTRODUCTION

The world economy is currently undergoing a major techno-economic transformation that is comparable to the first and second industrial revolutions. The rapid advance and diffusion of information and communication technologies (ICTs), the increasing global specialization of value-adding systems, new cooperative and skill-intensive forms of organization as well as the growing differentiation of demand patterns have challenged the old economic and social structures of industrialized countries. In this rapidly changing environment, the performance of socio-economic systems at different levels of analysis – organizational sub-units (departments, divisions), organizations (private, public, third sector), organizational fields, sectors and clusters, geographical subregions, national economies and supranational governance structures (EU, NAFTA, etc.) – depends on their capacity to renew their socio-institutional structures. A rapidly and coherently changing system can develop complementarities and synergies among its core elements and those of the environment. The dynamic match between the system and its environment can produce learning, scale and external economies that lead to an ‘increasing returns’ regime characterized by rapid productivity growth and sustainable competitive advantage (Arthur 1994; Kogut and Parkinson 1993; Lipsey 1997). On the other hand, slow, partial or incoherent structural adjustment may lock the system into a ‘decreasing returns’ regime of slow productivity growth and eroding competitiveness.1 The importance of structural adjustment capacity for economic performance underlines the need to understand the nature of socio-institutional change processes. Unfortunately, such systemic change processes have not been the focus of any branch of social sciences in recent decades. The rather stable postwar years favoured scientific specialization and static theoretical frameworks. For example, mainstream economics became increasingly mathematical and took for granted the gradually evolving institutional framework 28


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within which economic activities take place (Heilbroner and Milberg 1997). At the same time, political scientists focused their attention on political behaviour within established institutional structures. Their research involved voting behaviour, party formation and public opinion (Scott 2001, p. 7). Even the ‘new institutionalism’ in organizational research developed a rather static approach by analysing how institutions initially emerge and diffuse and then shape organizational behaviour in particular fields (Powell and DiMaggio 1991). Until recently, this research paid little attention to ‘de-institutionalization’ and ‘re-institutionalization’ processes, that is, the replacement of established institutions by new ones (Scott 2001, p. 181). As Seo and Creed conclude, ‘during the past two decades, institutional theorists have been able to offer more insights into the processes that explain institutional stability than those that explain institutional change’ (Seo and Creed 2002, p. 222). The first part of this chapter sketches a theory of social innovation that lays out the main phases, drivers and constraints of structural change processes. We define social innovations as changes in social structures that lead to improvements in a system’s economic and social performance. The social structures include: (a) the policy regime (the system’s public goods and services); (b) the regulatory framework (codified behavioural rules such as laws, regulations, collective agreements, industry standards, and so forth); and (c) organizational principles and arrangements. The second part of the chapter elaborates the theory with an interesting case of structural adjustment in Finland during the 1980s and 1990s. After an economic growth miracle comparable to those of Japan and Germany during the postwar decades, Finland plunged into a severe depression in the early 1990s. The crisis led to a major structural transformation of Finnish industries and the public sector that catapulted Finland to the top of the world competitiveness rankings in the mid-1990s, where it has stayed ever since. The Finland case emphasizes the importance of changes in collective frames, values, norms and theories for structural adjustment capacity. Structural change is preceded and to a large extent determined by change in collective mental structures. Although we elaborate our theory at the level of a nation, our aim is to develop a more general theory of social innovation and structural change. Similar mental and structural change processes take place in socio-economic systems of very different scope and function: organizational departments and divisions, firms and government agencies, industrial sectors and clusters, regions and nations, and even supranational organizations. The common denominator of these systems is a group of human beings faced with a changing environment. The different fields of socio-institutional change offer a rich arena for future research and the elaboration of our theory.


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TOWARDS A THEORY OF SOCIAL INNOVATION

During periods of evolutionary environmental change, the technological, economic and institutional structures of socio-economic systems tend to form a rather stable and coherent system (Figure 2.1). The various elements of the system develop incrementally without creating major tensions or adjustment problems. The behaviour of individuals and organizations is highly routinized along historical patterns. Feedback information

Attention & rigidities

Cognitive frames Values & norms

Performance

Behavioural patterns (practice)

Strategies & organizational arrangements

Policy regime & regulatory framework

Theoretical & ideological paradigms

Changing natural, technological & economic environment Figure 2.1

Social innovation process

The established behavioural patterns can be highly successful in a stable context. The good performance of the system provides positive feedback information that strengthens the shared cognitive frames, values (moral, ethical, aesthetic) and behavioural norms. These, in turn, support the generally accepted theoretical and ideological paradigms. This collective ‘mental paradigm’ shapes the formal political and regulatory structures of the society. The policy regime and regulatory framework tend to form a coherent extension and elaboration of the mental paradigm during evolutionary periods of socio-economic development. They include the principal duties of the government (public goods and services) and the codified behavioural rules of the system (such as laws and regulations, collective agreements, standards). Organizational strategies are formulated in a changing natural, technological, economic and institutional environment. When environmental change is slow, the organizational strategies and arrangements tend to form a good match with the established mental, political and regulatory frameworks. The day-today behaviour (practice) of individuals takes place within these established mental, political, regulatory and organizational structures. Once established, diffused and shared, these behavioural patterns form distinct styles or routines


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in different spheres of life (lifestyles, artistic styles, organizational routines, and so forth). Since individuals usually belong to multiple communities with varying mental paradigms and institutional structures, the dominating behavioural constraints and incentives are determined by the activity in question and the social context within which it is conducted.2 Major changes in the natural, technological, economic and social environment of human and organizational behaviour challenge the established structures of the society.3 The old behavioural patterns and mental paradigms begin to cause increasing problems in a rapidly changing environment. Moreover, new technologies and organizational innovations may not reach their full potential in the established political and regulatory framework. Increasing tensions emerge among the different parts of the socio-economic system. As a result, the performance of organizations begins to decline and the whole system experiences poor economic performance (decreasing returns). The signs of declining performance may go unnoticed for a while, as people are used to good performance and do not expect negative feedback. Moreover, changing one’s cognitive frame, values and norms is not easy. Being the basis of one’s personal security, changing them creates psychological distress and uncertainty. As a result, the first signs of performance problems are often swept under the rug with ad hoc explanations. The declining performance of established practices creates widespread uncertainty and collective cognitive dissonance among individuals who, locked into their established mental paradigm, tend to have problems identifying and understanding the true source of the problems. Their established cognitive frames focus attention on traditional variables and explanations that may no longer be relevant in the changed environment. These mental rigidities may be increased by the one-sided information of special interest groups who stand to lose from structural change (Olson 1982). They attempt to strengthen the old mental paradigms that underpin the established institutional structures that benefit them. Individuals may pursue several strategies to reduce the cognitive dissonance and insecurity caused by negative feedback information (see Festinger 1957). They may attempt to avoid information, experiences, social situations and environments that could increase their cognitive dissonance and seek others that would be consonant with their established mental frameworks. Since natural, technological and economic environments are rather difficult to change, the dissonance-reduction strategies of individuals tend to focus on their own mental structures and the social environment. Thus, they may change a problematic element of their own cognitive frame, decrease another element’s importance, or add a new consonant element to their established frame. Individuals may also be able to change their cognition about the socio-economic environment by actively seeking the support of social groups who share their views. In the


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extreme, strong social support may even allow the ‘denial of reality’, in other words the ignoring of clear evidence. Individuals may also reduce their insecurity by clinging to traditional ideologies and values (such as nationalism, family, religion), devoting themselves to specialized cults and movements with strong values and behavioural rules (environmental activists, extreme political parties, motorcycle gangs, and so on), or by calling for strong leaders who promise to restore stability (‘law and order’) in the society (Hitler, Mussolini, and others). All of these strategies provide simple solutions to complex personal and social problems, and reduce the personal uncertainty and insecurity related to them. Due to these uncertainty-reducing strategies, there seems to be a threshold of poor performance below which individuals and organizations will not change their mental structures and behavioural patterns (Schienstock and Hämäläinen 2001). A major crisis is often needed before individuals are ready to discard their old mental structures and adopt new ones. Since structural change is usually preceded by mental change, major structural transformations are often preceded by economic or other crises. The structural problems are often first recognized by the new or young members of the system who have not yet been fully socialized into the established mental paradigm. The poor performance of the established structures makes the serious consideration of alternative structures increasingly legitimate (Oliver 1992; Scott 2001). The old members have well established mental frameworks that guide their behaviour and attention to activities that tend to further strengthen these frameworks. The longer the positive experience they have of the old behavioural patterns and structures, the harder it is for them to change their mental frameworks and behavioural patterns. This creates a growing mental gulf between the old and young members of the socio-economic system during periods of rapid environmental change. The varying pace at which people recognize and deal with their cognitive dissonance creates tensions within the system. The pioneers of the ‘new age’ may adopt new cognitive frames, values and norms and become dissatisfied with the old political, regulatory and organizational structures. The conservatives at the other end of the spectrum may suffer from increasing mental distress but cling to their established mental paradigm and resist structural change. Many others undergo the psychologically difficult process of readjusting their old mental frameworks to better match the changing environment. Since the frames, values and norms of different groups of people are at least partially incommensurable, they have problems understanding others’ points of view and often end up in conflicts. The heterogeneity of mental frameworks is further increased by the growing specialization of socio-economic activities, as well as the integration of previously separate systems (Parsons 1966).


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Once they gain wide support, the new collective frames, values and norms tend to be codified into new behavioural principles, ideologies and theories that will guide individual and collective behaviour. The prevailing mental paradigm of the system shapes the political decisionmaking process that determines the collective goods and services provided and the behavioural rules implemented. Together these mental, political and institutional structures form the social constraints and behavioural incentives for individuals and organizations in different fields. Historical analyses of structural change processes in different socio-economic systems tend to find rational explanations for each step in the change process. These explanations run directly from the emergence of a particular structural problem (reflected in poor performance) to the new institutional arrangement that solves it (see Figure 2.1). The intervening process of collective learning and reframing through which the shared mental paradigm (frames, values, norms, ideologies and theories) is changed is neglected. In the following case study we argue that the rapid structural upgrading in Finland in the early and mid1990s was triggered by the severe economic crisis at the beginning of the decade. However, the structural transformation of the 1990s would not have been possible without the prior emergence and diffusion of a new mental paradigm in Finland during the 1980s. This new paradigm provided a worldview, values, norms, an ideology and economic theories that challenged those of the established post-war paradigm. Once the economic crisis had seriously discredited the old paradigm, the competing one was adopted as a basis for new policies, institutions and organizational arrangements. The next section describes the structural change process in Finnish society, while the subsequent section analyses the mental paradigm shift that made the structural changes possible.

2.3

STRUCTURAL ADJUSTMENT AND INCREASING COMPETITIVENESS IN FINLAND

The post-war growth experience of Finland resembles the contemporary growth miracles of Japan and West Germany. After the lost war and heavy war reparations, the Finnish economy industrialized very rapidly on the back of heavy investments in export-oriented basic industries such as paper and pulp, basic metals and chemicals. There was a national consensus on the investment-driven growth strategy that rapidly brought Finland closer to the world technological frontier and created new technological capabilities among Finnish firms (Pohjola 1996). The acquisition of foreign machinery and equipment played a key role in the technological catching up process. Equally important was the


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determination with which the national education system was developed. The growth strategy was also supported by: tightly regulated capital markets (low interest rates); generous tax exemptions for investments; flexible exchange rate policies; and the highly profitable barter trade with the Soviet Union. The Finnish welfare state was modelled according to the successful Swedish example. At the end of the 1980s, Finland had reached the league of the wealthiest countries in the world as measured by GDP per capita. Her catching up process was perhaps even more impressive than those of West Germany and Japan, because Finland was not an industrialized economy before the war like these two other countries. However, at the same time, the structural inefficiencies and distortions created by the investment-driven growth strategy also began to emerge. The deregulation of financial markets (increasing real interest rates) and the collapse of the Soviet Union revealed the structural inefficiency of the Finnish economy in the new techno-economic environment. The fact that Finland was the most expensive OECD country both in 1989 and 1990 in Purchasing Power Parity comparisons reflected this inefficiency. Table 2.1 shows how the overall structural competitiveness of Finland deteriorated from 9th place to 14th place among the OECD countries between the early 1980s and early 1990s. The overall competitiveness index is an average of seven competitiveness factors in the new economic paradigm, shown below. These factors were synthesized from the vast competitiveness and growth literature in economics, strategy, management and innovation (see Schienstock and Hämäläinen 2001). 1. New productive resources (venture capital, human capital, scientific knowledge, ICT infrastructure); 2. New technologies (R&D inputs, innovations, adoption of ICTs); 3. New organizational arrangements (allocative, technical, co-ordination and dynamic efficiencies); 4. New product market characteristics (sophistication of demand, product market institutions, user-producer co-operation); 5. Degree of economic internationalization (foreign direct investment, international trade, cross-border alliances); 6. Institutional incentives (taxation, regulation, returns to education); 7. Role of government (expenditure on efficiency and competitiveness versus equity-related tasks). The numerical values for each competitiveness factor were calculated as a weighted average of several normalized indicators (hence their range from –1 to +1). The normalization made possible the comparison and combination of indicators with very different measurement scales.

Structural competitiveness of nations in the new techno-economic paradigm

Competitiveness Rank

Schienstock and Hämäläinen (2001)

USA Switzerland Japan Germany Great Britain Sweden Canada Netherlands Belgium Australia France Finland Denmark Austria New Zealand Norway Ireland Portugal Italy Spain Greece Turkey

1.27 1.19 0.7 0.65 0.62 0.6 0.52 0.52 0.14 0.08 0.01 –0.02 –0.06 –0.12 –0.17 –0.24 –0.3 –0.79 –0.8 –1.0 –1.18 –1.6

Early 1990s Japan USA Sweden Netherlands Canada Switzerland Denmark Germany Great Britain New Zealand Belgium Australia Norway Finland Austria France Ireland Portugal Turkey Greece Spain Italy

0.82 0.69 0.47 0.45 0.42 0.38 0.34 0.29 0.27 0.2 0.16 –0.04 –0.05 –0.08 –0.12 –0.13 –0.18 –0.63 –0.63 –0.66 –0.9 –1.1

Mid-1990s Sweden Finland USA Canada Switzerland Great Britain Japan Norway Denmark Netherlands Australia New Zealand Germany France Belgium Ireland Austria Portugal Spain Italy Greece Turkey

0.85 0.71 0.62 0.59 0.56 0.5 0.44 0.41 0.34 0.32 0.22 0.21 0.1 0.01 –0.02 –0.04 –0.09 –0.75 –0.83 –1.06 –1.47 –1.62

Late 1990s USA Finland Switzerland Canada Netherlands Denmark Australia Sweden Ireland Norway Japan Great Britain Belgium Germany New Zealand Austria France Portugal Spain Turkey Italy Greece

1.1 0.88 0.72 0.55 0.55 0.42 0.41 0.36 0.28 0.24 0.23 0.22 0.11 0.06 –0.09 –0.28 –0.38 –0.46 –0.62 –1.33 –1.34 –1.64

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Canada 0.62 Switzerland 0.46 Australia 0.43 USA 0.42 Sweden 0.41 Japan 0.23 Germany 0.2 Netherlands 0.18 Finland 0.15 Great Britain 0.11 New Zealand 0.1 France 0.01 Norway 0.01 Austria –0.01 Denmark –0.02 Belgium –0.06 Greece –0.27 Ireland –0.27 Spain –0.38 Portugal –0.62 Italy –0.63 Turkey –1.05

Late 1980s

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Early 1980s

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22


Table 2.1


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In the autumn of 1990, the Finnish economy collapsed into the most severe depression in independent Finland’s history. Numerous firms filed for bankruptcy, thousands of over-borrowed households defaulted on their debts and the banking system went into deep crisis. The unemployment rate peaked at 20 per cent and the state ran a massive budget deficit. Very soon, the state finances were at the mercy of international lenders. The crisis was too deep to be swept under the rug; ad hoc explanations would no longer restore people’s trust in the old institutions and ways of doing things. It became clear the Finnish economy and society required major structural changes. In the early 1990s, Finnish firms laid off their workers en masse, reorganized their business processes, and considerably improved their productivity and competitiveness. And all this took place almost without new investments. The government made drastic cuts in public expenditures that had not been possible in better economic times. At the same time, the export competitiveness of Finnish firms was re-emphasized as a key policy goal. Also, individual citizens changed their behavioural patterns: people began to pay back their debts, work harder and many sought new training opportunities to upgrade their skills. As we can see, the Finnish economic crisis came with a silver lining: it reduced the society’s mental rigidities toward adjustment. Moreover, being a late-industrializing country, Finland had not become as deeply embedded in the old techno-economic paradigm as many older industrialized countries had. Thus, Finnish society has been quite flexible in its adjustment to the new technoeconomic environment. Some observers even think that Finland is a leading information society in the world (Castells and Himanen 2001). The internationalization of Finnish firms during the 1990s had an important impact on the competitiveness and growth of the Finnish economy. There were major changes in international trade patterns, portfolio investments and foreign direct investment (FDI) flows. In the 1990s, Finnish exports were characterized by increasing knowledge intensity. The share of high technology products in total exports increased from 6 per cent in 1991 to 21 per cent in 1999. Most of this increase can be attributed to the rapid growth of the telecommunications cluster. At the same time, the share of exports in GDP nearly doubled from 22 per cent in 1991 to 43 per cent in 2000. The rapid growth of high technology production and exports has created a ‘third leg’ for the Finnish economy besides the traditional forest and basic metal industries. Global markets have facilitated the specialization of Finnish firms into their core activities and narrow product niches, resulting in increasing scale and learning economies. Finnish capital markets also became more international in the 1990s. The liberalization of the Finnish capital markets began in the mid-1980s and the last restrictions on cross-border capital flows and foreign ownership were removed in 1993 (Pajarinen, Rouvinen and Ylä-Anttila 1998). Since then, the foreign


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ownership of the Helsinki Stock Exchange (HSE) listed shares has increased rapidly and approached 70 per cent in 2001 (HSE 2002). This makes the HSE one of the most internationalized stock exchanges in the world. The rapid growth of foreign portfolio investment has improved the availability of equity capital for Finnish firms and made the Helsinki Stock Exchange a more liquid marketplace (Pajarinen, Rouvinen and Ylä-Anttila 1998). The increased foreign ownership has also pushed the corporate governance practices of large Finnish firms toward the Anglo-Saxon ‘shareholder value’ approach. Thus many firms have terminated their supervisory boards and restructured their management boards. In the latter, external expert members have increasingly replaced management representatives. The Finnish firms have also created new incentive mechanisms (such as stock options) for their managements to meet the demands of international investors (Huolman, Walden, Pulkkinen, Ali-Yrkkö, Tainio and Ylä-Anttila 2000). The new efficiency-oriented governance practices mark a clear break from the stakeholder-oriented and corporatist governance structures of the 1980s. Both outward and inward direct investment began to grow more rapidly in Finland in the mid-1980s. However, the outward FDI flows outpaced the inward flows as many large Finnish firms operating in sheltered domestic markets (such as insurance companies and banks) as well as some state-owned companies holding monopolistic market positions (chemicals, oil) increased their foreign investments. The poor financial performance of these investments and the subsequent disinvestments suggest that many of the original investments were made without the necessary ownership-specific advantages underlined by the established FDI theories (see Dunning 1993). These investments can be better explained with some less well-known theories of FDI that emphasize the monopolistic rents of large firms in domestic markets and their exploitation by the management in foreign countries (Cowling and Sugden 1987). After a brief pause in the early 1990s, the rapid growth of outward and inward FDI resumed in 1993. The outward flows continued to outpace the inward flows during the rest of the decade. In the late 1990s, the stock of outward investment was about two times larger than the stock of inward investment. Pajarinen, Rouvinen and Ylä-Anttila (1998) discuss the impacts of FDI on the Finnish economy during the 1990s. The economic impacts of outward FDI are not very clear but empirical research suggests that the cross-border expansion of large Finnish firms improved their international competitiveness in most cases. However, at the same time, the investments also somewhat reduced the firms’ domestic employment. The growth of inward FDI had more positive than negative effects on Finnish industry. On average, foreign-owned firms in Finland have grown faster and they have been more profitable than indigenous firms. Foreign firms have also provided new technology as well as new


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marketing and organizational skills to their Finnish subsidiaries. All this has reinforced the competitiveness of the Finnish economy. The role of government in the Finnish economy was also reshaped after the crisis of the early 1990s. Instead of physical investments, the new strategy emphasized economic efficiency, innovation and growth (MTI 1996). Using Dunning’s (1992) term, Finland moved towards a ‘macro-organizational’ policy approach that emphasizes the reduction of market failures as the core responsibility of the government. With the severe economic crisis in the background, this strategy was easy to understand. The Finnish economy was increasingly exposed to foreign competition and could not compete without world-class efficiency, productivity and value-adding capacity. Furthermore, the popular welfare state could not be financially supported without an efficient and competitive economy. Having a strong engineering orientation, the Finnish value-adding strategy was based on technological innovation. Policy-makers wanted Finland to become a true ‘knowledge-based society’ and the early success of the telecommunications cluster showed the potential of this strategy. As a result, the role of technology policy became central in the new growth strategy. Perhaps as a reflection of the old input-driven strategy, increasing national R&D inputs became the central goal of technology policy in the late 1990s.

2.4

EMERGENCE OF A NEW MENTAL PARADIGM IN THE 1980s

The structural transformation of the Finnish economy and society in the early 1990s was triggered by the economic depression. However, the rapid advance and broad scope of this transformation can be explained by the availability of a competing and respectable mental paradigm that could be adopted once the postwar mental paradigm was discredited by the economic crisis. The key elements of this new market-oriented paradigm had already emerged in public discussion in the 1980s but they did not gain widespread support until the economic crisis. During the great uncertainty and insecurity of the early 1990s, the new paradigm offered clear guidelines for the restructuring process. Table 2.2 compares and contrasts the main characteristics of the postwar and the new mental paradigms in Finland. The two paradigms represent the shared cognitive frames, values and norms of the Finnish people before and after the economic crisis. The characteristics of the two paradigms are based on empirical studies of public discussion during the postwar period (Alasuutari 1996; Alasuutari and Ruuska 1999), interviews of key decision-makers right after the crisis (Kantola 2002), empirical research on the changing values of Finns during the 1980s (Helkama 1997) as well as the author’s own observations as an active


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member of Finnish society. The table also relates the mental paradigm shift to some of the key structural changes that took place during and after the crisis in the 1990s. The post-war mentality of Finnish society has been characterized as a period of ‘planned economy’ (Alasuutari 1996). There was a deep trust in the effectiveness of hierarchical planning as the key co-ordination mechanism in all sectors of society. It was generally felt that the small national economy needed to be protected and closed off from foreign influences and competition. A strong regulatory hand of government was also preferred in domestic markets. There was a general consensus that the Finnish economy was based on two main sectors, forest and metal industries, which produced the majority of the country’s export revenues. Due to the capital intensity of the main sectors, decision-makers viewed physical investments as the key competitiveness strategy of the Finnish economy. These investments were supposed to yield cost advantages through increased scale economies. As a result of the cyclical volatility of the leading sectors, occasional currency devaluations were accepted as a necessary complement to this strategy. Particularly in the 1960s and 1970s, the main policy goal of government was generally believed to be social and regional equality. Sweden was considered to be a good policy-making benchmark with its highly developed welfare state. The strong role of government was reflected in assumptions about the role of citizens. They were considered to be mere governance subjects who do not always know what is in their best interest. This gave rise to paternalistic alcohol, education, mass communication and cultural policies. Since the late 1960s, central labour market organizations were also considered to be legitimate partners in the public policy-making process. Finnish national culture was very homogeneous during the postwar decades. Collective, conservative and protectionist values were widely shared and supported the other elements of the mental paradigm. The key elements of the new mental paradigm emerged in the 1980s when the growing structural problems and inefficiencies of the Finnish economy made the discussion of new ideas increasingly legitimate. This new paradigm was based on the belief in the efficiency of free, open and competitive markets as a co-ordination mechanism of advanced economies and societies. The new market-oriented policy regimes in the United States and the United Kingdom gave Finland a practical example of the new paradigm in use. The demise of Keynesian economics in the stagflation of the 1970s and the subsequent rise of neoclassical economics provided scientific support for the new ideas. The new mental paradigm involved a new engine of economic growth: the high technology industries. The growing problems with the investment-driven growth strategy focused attention on the emergent high technology sector that was not as dependent on price and cost advantages and successive devaluations


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as the forest and basic metal industries. The strategy of knowledge-intensive, high technology, and high value-added production was increasingly seen as the only viable one for a country with an increasing standard of living and high cost levels. The new mental paradigm also included new thinking about the role of government. The idea of the citizen as the customer of public sector services has gained ground since the early 1980s. However, a more fundamental philosophical shift did not take place until the economic crisis of the early 1990s. In that shift, economic growth and efficiency replaced equity as the most important goal of government activities (MTI 1996). The economic crisis also challenged the active role of general labour market organizations in public policy-making. The idea of a clear ‘division of labour’ between the labour market organizations and the public policy-makers became increasingly popular among economists and policy-makers themselves. Many felt that the labour market organizations had gained too much political power in society and had become the key stumbling blocks to structural adjustment. Also, the homogeneity of Finnish national culture began to unravel in the 1980s. Individualism, readiness-for-change, freedom and openness became increasingly important for Finns during the 1980s (Helkama 1997). As we can see from Table 2.2, the structural changes made in the 1990s were based on the new mental paradigm. However, some features of the old paradigm have remained strong in the changed techno-economic environment. In particular, the goal of social and regional equity is still very important among Finns and large parts of the population still favour corporatist decision-making that gives the central labour market organizations considerable political power. Indeed, after a pause during the economic crisis, the government renewed its support for central labour market agreements and corporatist policy-making.

2.5

CONCLUSION

This chapter has argued that a system’s capacity for structural change is the key to its economic performance in a rapidly changing environment. The structural change capacity depends on the collective learning and ‘unlearning’ processes through which the members of the system change their collective frames, values, norms, ideologies and theoretical frameworks, their shared mental paradigm. Although most industrial economies are struggling with structural adjustment problems, there is surprisingly little research on the social innovation processes which link changes in mental paradigms, socio-institutional structures and economic performance (see for example Huff and Huff 2000; Huntington and Harrison 2001). More research about social innovation processes is urgently needed.4

Mental and structural change in Finland during the 1980s and 1990s Structural changes

Co-ordination mechanism

Hierarchical planning

Market mechanism

New organizational arrangements (corporate governance reform, networking), new public management (privatization, management by objectives, decentralization, law on public procurement)

National economy

Closed and regulated

Open and competitive

Deregulation of financial markets and foreign investments, increasing exports and FDI by Finnish firms, EU membership, deregulation of markets for goods and services, improvements in competition law and its enforcement, EMU membership

Key sectors of economy Forest and metal industries High technology sectors Rapid growth of the telecommunications sector Physical investments and currency devaluations

Knowledge and technology

Main goal of government

Social and regional equality

Economic efficiency, Reform of industrial policy (reduction of investment and regional innovation, and growth subsidies, increase in R&D subsidies, improving effectiveness of competition policy, development of service sector), cuts in public income transfers (incl. reduction in ‘incentive traps’)

Role of citizens

People to be governed

Customers to be served Decentralization and reform of public sector activities (management by objectives, one-stop service)

Role of labour market organizations

Strong participation in labour market and public decision-making (corporatism)

Collective agreements Two successive rounds of industry-level agreements in the early 1990s, then return to the old paradigm and to economy-wide on industry or firm basis; no participation agreements in public policy-making

Culture

Homogeneous values and preferences, collectivism, conservatism, national protectionism

Heterogeneous values and preferences, individualism, readiness for change, freedom and openness

Abolishment of paternalistic regulation of alcohol, communication (TV, radio), education and cultural policies and growth of foreign immigration to Finland

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Rapid growth in R&D investments, development of VC markets, creation of the polytechnic system, management by objectives introduced in universities, increasing numbers of new PhDs

Competitiveness strategy

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Table 2.2


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Future research could examine the nature of social innovation processes at different levels of analysis: organizational subunits, firms, sectors, regions, nations and supranational organizations (such as the EU, NAFTA). Although we expect the general change process to be rather similar in different types of systems, differences in scope, history and context could elaborate it with interesting new elements and nuances. The new studies should pay special attention to the links among mental changes, structural changes and performance. How exactly do mental changes influence structural decisions and these, in turn, economic performance? Social innovation processes are shaped by many factors that could not be analysed in this chapter. The media, civil society (social movements, political parties, special interest groups), education and socialization systems and research institutions play a major role in bringing new issues onto the public agenda and influencing the shared frames, values, norms and ideologies of different systems’ participants. Their role needs to be analysed carefully in different contexts. Many policy-makers are finding it very difficult to deal with structural change issues. Better knowledge about the nature, drivers and constraints of social innovation processes could help them to formulate policies that facilitate structural change and promote the economic success of their systems. It is rare that a social scientist has such a strong social demand for his or her research.

NOTES * The theoretical part of this chapter has benefitted from discussions with Professor Risto Heiskala. The theory and case study contain some previously published material from Hämäläinen (2003a and 2003b). 1. There are numerous historical examples of both rapidly adjusting and successful and stagnant and deteriorating socio-economic systems during major environmental transformations. At the firm level, the declining competitiveness and performance of the once mighty IBM in the late 1980s and its subsequent recovery in the mid-1990s provide an example of both trends (Hämäläinen and Laitamäki 1993; see also Christensen 1997). The decline of the US auto industry in the 1980s illustrates the fate of a stagnant national sector in the face of a rapidly changing competitive environment (Dertouzos, Lester and Solow 1989; Womack, Jones and Roos 1991). Silicon Valley and Massachusetts provide examples of dynamically adjusting regional systems (Best 2001; Saxenian 1994), whereas Baden-Württemberg represents a stagnant and gradually declining region (Cooke and Morgan, 2000). The rapid structural change and good economic performance in the United States in the late 19th and early 20th centuries and the institutional rigidity and relatively poor performance in Great Britain during the same period provide examples of national systems during transformation (Freeman 1995). In the current transformation, the rapid structural change of Finland (Section Two of this chapter) can be contrasted with the decade-long stagnation of Japan and the structural rigidities of Germany. 2. Sometimes the multiple roles of individuals as members of different communities get mixed up and they may face contradictory frames, incentives and behavioural rules. This may create an unpleasant feeling of uncertainty and cognitive dissonance (Festinger 1957). The presence of


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overlapping and competing institutional frameworks may also undermine the stability of each (Scott 2001, p. 183). 3. Changes in social environment may involve changes in collective needs and preferences or in the distribution of power among different groups (Oliver 1992). 4. The Finnish National Fund for Research and Development, Sitra (www.sitra.fi), started a research project on collective learning, social innovations and structural adjustment in autumn 2002. This project involves both theory development and national, regional and sectoral case studies.

REFERENCES Alasuutari, Pertti (1996), Toinen tasavalta: Suomi 1946–1994, Tampere: Vastapaino. Alasuutari, Pertti and Petri Ruuska (1999), Post patria: Globalisaation kulttuuri Suomessa, Tampere: Vastapaino. Arthur, Brian W. (1994), Increasing Returns and Path Dependence in the Economy, Ann Arbor, MI: University of Michigan Press. Best, Michael H. (2001), The New Competitive Advantage: The Renewal of American Industry, Oxford: Oxford University Press. Castells, Manuel and Pekka Himanen (2001), Suomen tietoyhteiskuntamalli, Helsinki: WSOY. Christensen, Clayton M. (1997), The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Boston, MA: Harvard Business School Press. Cooke, Philip and Kevin Morgan (2000), The Associational Economy: Firms, Regions, and Innovation, Oxford: Oxford University Press. Cowling, K. and R. Sugden (1987), Transnational Monopoly Capitalism, New York: St. Martin’s Press. Dertouzos, Michael L., Richard K. Lester and Robert M. Solow (1989), Made in America: Regaining the Productive Edge, New York: Harper Perennial. Dunning, John H. (1992), ‘The Global Economy, Domestic Governance, Strategies and Transnational Corporations: Interactions and Policy Implications’, Transnational Corporations, 1, 7–45. Dunning, John H. (1993), Multinational Enterprises and the Global Economy, New York: Addison-Wesley. Festinger, Leon (1957), A Theory of Cognitive Dissonance, Evanston, IL: Row, Peterson and Company. Freeman, Christopher (1995), ‘History, Co-Evolution and Economic Growth’, IIASA WP-95–76, September. Hämäläinen, Timo (2003a), National Competitiveness and Economic Growth: The Changing Determinants of Economic Performance in the World Economy, Cheltenham: Edward Elgar. Hämäläinen, Timo (2003b), ‘A Theory of Systemic Adjustment and Economic Growth: The Case of Finland’, in H. Peter Gray (ed.) Extending the Eclectic Paradigm in International Business: Essays in Honor of John Dunning, Cheltenham: Edward Elgar. Hämäläinen, Timo and Jukka Laitamäki (1993), ‘A Value-Added Theory of the Firm: An Explanation for the Destruction of Large Hierarchies in the Computer Industries’, Paper presented to Strategic Management Society Conference, September, Chicago. Heilbroner, Robert and William Milberg (1997), The Crisis of Vision in Modern Economic Thought, New York: Cambridge University Press.


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Helkama, Klaus (1997), ‘Arvojen ja ihmiskuvan muutos’, in Timo J. Hämäläinen (ed.), Murroksen aika: Selviääkö Suomi rakennemuutoksesta?, Helsinki: WSOY, pp. 241–64. HSE (2002), web-pages of the Helsinki Stock Exchange at: www.hse.fi Huff Anne S. and James O. Huff (2000), When Firms Change Direction, Oxford: Oxford University Press. Huntington, Samuel P. and Lawrence E. Harrison (2001), Culture Matters: How Values Shape Human Progress, New York: The Free Press. Huolman, Mika, Pia Walden, Matti Pulkkinen, Jyrki Ali-Yrkkö, Risto Tainio and Pekka Ylä-Anttila (2000), Omistajien etu – kaikkien etu?, Helsinki: Taloustieto. Kantola, Anu (2002), Markkinakuri ja managerivalta: Poliittinen hallinta Suomen 1990luvun talouskriisissä, Tampere: Loki-kirjat. Kogut, Bruce and David Parkinson (1993), ‘The Diffusion of American Organizing Principles to Europe’, in Bruce Kogut (ed.), Country Competitiveness: Technology and the Organizing of Work, New York: Oxford University Press. Lipsey, Richard G. (1997), ‘Globalization and National Government Policies: An Economist’s View’, in John H. Dunning (ed.), Governments, Globalization, and International Business, London: Oxford University Press. MTI (1996), ‘A New Outlook on Industrial Policies: From Global Economic Change to Sustainable Growth’, Finnish Ministry of Trade and Industry Publications, 4/1996. Oliver, Christine (1992), ‘The Antecedents of Deinstitutionalization’, Organization Studies, 13, 563–88. Olson, Mancur (1982), The Rise and Decline of Nations, New Haven, CT: Yale University Press. Pajarinen Mika, Petri Rouvinen and Pekka Ylä-Anttila (1998), Small Country Strategies in Global Competition: Benchmarking the Finnish Case, Helsinki: ETLA/Sitra. Parsons, Talcott (1966), Societies: Evolutionary and Comparative Perspectives, Englewood Cliffs, NJ: Prentice Hall. Pohjola, Matti (1996), Tehoton pääoma, Helsinki: WSOY. Powell, Walter W. and Paul J. DiMaggio (1991), The New Institutionalism in Organizational Analysis, Chicago: The University of Chicago Press. Saxenian, Annalee (1994), Regional Advantage: Culture and Competition in Silicon Valley and Route 128, Cambridge, MA: Harvard University Press. Schienstock, Gerd and Timo Hämäläinen (2001), Transformation of the Finnish Innovation System: A Network Approach, Sitra Report Series 7, Helsinki: Sitra. Scott, Richard W. (2001), Institutions and Organizations, Second edition, Thousand Oaks, CA: Sage. Seo, M. and W.E. Douglas Creed (2002), ‘Institutional Contradictions, Praxis, and Institutional Change: A Dialectical Perspective’, Academy of Management Review, 27(2), 222–47. Womack, James P., Daniel T. Jones and Daniel Roos (1991), The Machine that Changed the World: The Story of Lean Production, New York: Harper Perennial.


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PART II

Industries and firms

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3. The evolution of the Finnish ICT cluster Laura Paija and Petri Rouvinen 3.1

INTRODUCTION

Despite bankrupted dotcoms and collapsed market valuations of technology companies, it is generally agreed that information and communication technologies (ICTs) have indeed induced a new techno-economic paradigm or the third industrial revolution. Consequences of this revolution have been particularly pronounced in Finland. In the late 1990s Finland, besides the United States, became known as the leading new economy, or a country where ‘… the 21st century is in beta’ (Wired magazine, September 1999). This reputation was primarily earned by the rapid growth of and heavy specialization in mobile telecommunications equipment manufacturing. As a user of ICT, Finland is advanced but not exceptional as compared to other high-income countries (see, for example, Koski, Rouvinen and Ylä-Anttila 2002a). Koski, Rouvinen and Ylä-Anttila (2002b) show that ICT-related production has an intensifying concentration tendency and that laggards in ICT provision rarely catch up, let alone leapfrog the leaders. In other words, originally ICTspecialized countries tend to become more so. Finland is a rare exception to this rule. During the 1990s it went from being one of the least ICT-specialized industrialized countries to becoming the most specialized one. Figure 3.1 below shows the situation in the year 2000. Finland is the only country that ranks high according to all of the three indicators considered. This chapter studies the evolution of the Finnish ICT sector as well as the dynamics and interactions behind its success. We also discuss future developments and speculate as to what might lie ahead.

3.2

NATIONAL INNOVATION SYSTEM AS A BASIS FOR COMPETITIVENESS

Success in the Finnish ICT sector cannot be considered exclusively an internal phenomenon of the branch. Rather, the growth of ICT provision in Finland to 47


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Industries and firms ICT value added (% of business sector tot., 2000)

Ireland Finland Korea USA New Zealand Sweden Hungary UK Netherlands Belgium Japan Czech Rep. Norway Canada Denmark France Portugal Austria Australia Spain Italy Germany Mexico Slovak Rep. Greece

Finland Sweden Canada Japan UK Netherlands Belgium France Norway Denmark Austria USA Korea Italy Australia Czech Rep. Spain Mexico Germany Portugal

0 4 8 12 16 Total Communic. & other eqt Computer & other eqt Services

Source:

ICT employment (% of business sector tot., 2000)

R&D in ICT (% of business sector tot., 2000)

Finland Korea Sweden Japan USA Canada Ireland Netherlands Germany France Belgium UK Denmark Norway Italy Australia Spain Czech Rep. Poland

0 2 4 6 8 Communic. & other eqt Computer & other eqt Services

10

0 1 Manufacturing Services (for those avail.)

2

OECD (2002)

Notes: ICT sectors as defined at the source. The reference year may vary. See the original source for further notes

Figure 3.1

ICT sector value added, employment and R&D

its present status should be considered by acknowledging cross-sector interactions in the national innovation system. Evidence from international comparisons (EU 2000; OECD 1999) indeed suggests that co-operation between Finnish companies and research organizations is exceptionally broad. We argue below that one of the key strengths of the Finnish ICT sector is intense interorganizational co-operation both within the industry and with other industries and the research sector. While the transition of Finland from a resource-based economy into one driven by knowledge may seem sudden, its foundations were in fact laid as far back as in the 1800s. Yet, behind the evolution of the ICT cluster, there is a complex and self-strengthening development process; it is apparent that the major processes were set in motion by public sector decisions. The promotion of industrial policy aims was not always the reason for these decisions, although the Finnish ICT cluster looks, in hindsight, like the result of an industrial policy master plan. Actions of public bodies have indeed been mostly beneficial to the Finnish ICT cluster despite the fact that the goals and focal areas of industrial policy have undergone major changes in postwar Finland.


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The evolution of the Finnish ICT cluster

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In what follows we use Porter’s (1990) cluster concept with some refinements (see Hernesniemi, Lammi and Ylä-Anttila 1996) to carry out our analysis. We view clusters as networks of organizations, public and private, in which competitive advantage grows from dynamic interaction between actors. Cluster relations disobey sectoral boundaries – they spur innovation and upgrading through spillovers and knowledge transfers. Generally speaking, the competitiveness of a cluster is dependent on the political, institutional and cultural environment within which it operates. The growth potential of a cluster is also dictated by changes in the international environment, not to mention incidental events, as we shall see below in the context of the Finnish ICT sector.

3.3

THE STRUCTURE OF THE ICT CLUSTER: GULLIVER AMONG LILLIPUTIANS

The structure of the Finnish ICT cluster may be depicted as in Figure 3.2. Firms producing ICT equipment and services form the key industries of the cluster. The convergence of networks, terminals, services and industries has made it increasingly difficult to categorize firms in traditional industries. It is therefore more convenient to consider them en bloc, or as a value chain producing information and communication services as their final output. Looking at the firms in the core of the cluster, totalling approximately 6000, Nokia is in a class of its own. There are few other Finnish ICT companies whose Supporting industries Contract manufacturing Components Education and R&D

Associated services

Key industries Digital content Packaging Network infrastructure

Related industries Traditional media Entertainment Other services

Applications software Operation Buyers/Appliers

ICT consultancy VC finance Standardization

Source:

End-user terminals Portals

Paija (2001)

Figure 3.2

ICT cluster framework

Individuals Organizations


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sales, in general, exceed 200 million euros, while Nokia’s domestic sales were over 450 million euros in 2001. The operator sector is highly competitive and has been undergoing a strong restructuring process during recent years – which, in fact, is rather the rule than an exception during its 100-year history of multi-operator market structure. Three camps of national operators share the market. The largest camp, led by Sonera, the former public posts and telecom office, has around half of the total market revenue and connections, while the second largest camp holds one third, and a group of small local operators has practically grabbed the rest. Foreign entrants have not succeeded in gaining any significant position (status as of early 2003). The government had a long-standing objective to find a partner to Sonera in a major foreign operator. Finally in 2002, a merger agreement with Swedish Telia was reached. Finding a partner was delayed during the dotcom boom by inflated, and then after the bust, by deflated stock valuations and a heavy financial burden left behind by Sonera’s aggressive growth attempts. Indeed, Sonera has been so far the only national operator to make major attempts to become an important actor on the international stage. These have included joint ventures in several foreign markets, and particularly, acquisitions of stakes in high-priced 3G licences that later lost most of their market value. The company also made significant investments in its endeavour to establish a global position as a provider of mobile transaction security and mobile Internet applications. The eventual failure of Sonera’s ambitious international expansion and the consequent public and political turmoil it stirred up may have obscured somewhat the fact that the company has highly advanced technological knowhow accumulated over its long history. As we shall discuss below, Sonera has been one of the pioneering developers of mobile technologies and a major sparring partner of the early Nokia. Despite advanced and even pioneering expertise in some application areas, few Finnish software companies have gained global recognition. However, Linux is a particular chapter in Finnish ICT history: initiated by a Finnish student, Linus Torvalds, in the 1980s, the open-source operating system has been the only one to challenge the predominance of Microsoft. Other actors with an international position operate mainly in narrow but fast growing niches, such as data security, and network management and service applications. Digital content provision includes content creation and ‘packaging’, that is, combining and tailoring contents and services for various users and channels. In this part of the value chain we encounter actors from various ICT subsectors: software companies, operators, equipment manufacturers and media houses. Indeed, there is a battle over access to end-users among content, service and terminal providers, since it has been regarded as an opportunity to direct the development of the business.


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In our cluster framework, however, content substance is primarily created in related industries, which, by definition, are those whose products are complementary to those of the key industries. Therefore, companies using ICT infrastructure as a distribution channel can be loosely referred to as ‘content producers’. It is common to count, for instance, museums, libraries, printing houses, business consulting firms, and the whole of the music and motion picture industries in ‘the content industry’, yet only a fraction of their production is digitally available on the network. However, all speech, messages, data, and pictures carried in the communications system have content. From this viewpoint, all mobile subscribers are content producers. In the same vein, for example, transportation companies publishing their time schedules, or business companies offering their annual reports digitally are important content providers. Despite the difficulty in defining content-producing industries, however, there is little dispute over the decisive role of content in generating consumer demand for sophisticated communications equipment, which will ultimately determine the value of ICT business and investments. Yet, to date, somewhat simple applications, such as ringing tones, icons and short message services, represent the most popular mobile services. The cluster also embraces those sectors that enhance the competitive advantage of the key industries or improve their functional preconditions. In the Finnish context these include, for example, technology suppliers. Along with Nokia’s focused divestment of non-core activities in the 1990s, the role of suppliers became more central in ICT cluster development. During the 1990s the sector developed specialized competencies in certain technology areas (such as ASIC, automation, hybrid circuits, printed circuit board production and surface mounting technology, precision mouldings, rf-filters, and silicon wafers). Finnish supplier products are typically highly customized, while in using standard components the equipment manufacturers rely on mass producers’ imports. In the wake of Nokia’s global success, local suppliers have had no choice but to swiftly internationalize their operations, since a global presence is crucial for efficient outsourcing. For many suppliers it has opened up unforeseen business growth and raised the level of business skills. The Finnish education system has succeeded in producing critical human skills to nourish the development of the cluster. The main universities were already established by the end of the 1960s. Today, there are 12 postgraduate schools providing education in information technology. Since the 1980s Nokia has systematically promoted to the public its idea of education and knowledge as the basis of national advantage. The government has indeed been responsive to the demands of the ICT industry as to the content and volume of related education. During the second half of the 1990s, the intake in higher-level technical education increased to the extent that there were concerns about watering down the level of education with excessive intakes and stagnant budget


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financing. As universities are important recruitment forums, company representatives have also taken part in the planning and implementation of education. Lively interaction between science and industry has long traditions, yet there was a period of statutory separation around the 1970s when publicly financed science was kept clear from business interests. R&D between industry and universities, both collaborative and outsourced, has been since then an integral part of new technology development. Finally, the overall economic impact of ICT is likely to be even more powerful on its users than on its producers, since innovative applications of the technology are about to revolutionize traditional business models and increase productivity. In Finland, economies of scale have thus far benefitted mainly the supply side of mobile technology. The next critical question pertains to Finland’s capability to exploit advanced technology on the user side in order to enhance productivity in the rest of the economy.

3.4

THE ICT CLUSTER AS PART OF THE FINNISH ECONOMY

The impact of the ICT cluster growth on the Finnish economy was momentous during the 1990s. The share of GDP of the ICT cluster value added rose from 4 to 10 per cent.1 The increase was driven by the ICT manufacturing sector. Its value added grew by a multiple of 17 during the period, while total manufacturing did not even double (Figure 3.3). Nokia has an estimated 3 per cent share of GDP. In services, the difference between the ICT and total value-added growth rates was also large, but less dramatic. While the economy as a whole has failed to recover from the persistent unemployment that started during the recession of the early 1990s, recruitment in the ICT sector has been strong (Figure 3.3). It picked up in the mid-1990s, eventually exhausting the supply of skilled labour towards the turn of the millennium. The labour shortage was, at least temporarily, ‘resolved’ by the sudden global decline of the industry. The evolution of the structure of exports reflects Finland’s rapid metamorphosis from a resource-based into a knowledge-based economy (Figure 3.4). The ICT sector developed during the 1990s into the third main pillar of exports at the expense of the traditional metal and forest-based industries. Nokia accounts for approximately 20 per cent of national exports. The intensive increase in national R&D expenditure (see discussion below) has been driven by the ICT sector, and notably by Nokia. Excluding Nokia’s share of total R&D expenditure decreases Finland’s R&D intensity (R&D per GDP), according to one estimate, by one percentage point, to 2.4 per cent (Ali-


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The evolution of the Finnish ICT cluster Value added (note scale)

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OECD/STAN See Note 1 for ICT cluster definition

Figure 3.3 Development of the ICT cluster versus the economy as a whole 1990–2001 (1990=100)

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Figure 3.4

Export shares by industry group


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Yrkkö and Hermans 2002). Still, even without Nokia, Finland would rank above the EU average in R&D intensity.

3.5

MULTI-ACTOR MARKET CULTIVATED TECHNOLOGICAL EXPERTISE

Even in worldwide comparison, the structure of Finnish telephony markets, originally established in the 1880s, was exceptional up until the worldwide telecom liberalization in the 1990s, as it enabled interaction between operators and equipment suppliers, unlike in most other countries which resorted to monopolies. The origin of the exceptional market structure was the fruit of the insight of the Finnish Senate, which was under the Russian Tsar’s reign at the time. Under the Telephony Decree of 1886, the Senate distributed numerous private licences to engage in telecommunications activity that circumvented Russian telegraph regulations. Indeed, at the peak of the 1930s there were over 800 private operators in Finland. After gaining independence in 1917, a state telecom operator was established to operate the telegraph and military telephone network left behind by the Russians, but the role of the private operators remained intact. Thus, from an early time on, private and public telecom markets co-existed in Finland, providing a favourable foundation for equal competition once the markets were liberalized in the 1990s. When monopoly markets were opened up elsewhere in the world, complicated ‘transitory’ regulation was often necessary to support the emergence of equitable competition (such as the breaking up of Ma Bell into baby bells in the US and price regulations in the UK). Additionally, Finnish telecom equipment markets were open to foreign suppliers, unlike in some other countries, where national equipment suppliers enjoyed a monopoly position. In Finland, the large number of operators enticed leading equipment suppliers to test their latest technology in Finland. Indeed, the interestedness of private operators in state-of-the-art technology was underpinned by the threat of the regulator-PTO’s (public telecom operator) takeover of under-performing telephony companies. As a result, the national telephony infrastructure quickly reached relatively high standards, and the first automated exchanges were introduced as early as in the 1920s (yet full automation of the national network continued until 1980). In order to integrate different manufacturers’ network equipment, operators had to develop technological expertise. This know-how was later exploited by the budding domestic component industry, in other words the ancestors of the later Nokia.


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3.6

55

CHALLENGING DEMANDS OF PUBLIC SECTOR INDUCED HIDDEN EXPERTISE

In three companies established around the turn of the 1920s – Salora, Suomen Kaapelitehdas (Finnish Cable Works) and Valtion Sähköpaja (State Electrical Workshop, later known as Televa) – radio technology was practised on the sidelines of main business activities by fervent engineers, often under the suspicion and opposition of conservative colleagues (Mäkinen 1995). In 1963, a call for tenders by the Finnish Army for a battlefield radio finally spurred companies into giving physical expression to their accumulated, but up until then somewhat hidden, expertise. Although the Army did not ultimately have the resources to purchase the system, its prototypes were later developed into the first commercial handsets. Later, several public bodies, such as the National Defence, the State Railways and the Coast Guard called for tenders for their demanding communications requirements, thus fostering the development of radio technology expertise.

3.7

NORDIC COLLABORATION IN NMT DEVELOPMENT GOT COMPANIES STRIVING

Co-operation between public authorities and the telecommunication equipment industry culminated in the creation of the NMT (Nordisk Mobil Telefon) network in the 1970s. Nordic telecommunications authorities aimed at creating competitive cross-country markets, and therefore the standards were made open and features such as roaming were included. At the start of the 1980s the Nordic countries formed the largest mobile communication market worldwide in terms of the number of subscribers, the equipment needs of which were served by a dozen suppliers. Mobira, a joint venture of Nokia and Salora, supplied the first handsets for the network. However, Finnish companies were neither ready nor willing to supply network technology in the starting phase of the NMT project. Eventually, under pressure from Finland’s national Post and Telegraph authority, Mobira, and later Tele-Nokia, started to manufacture network equipment (see for example Mäkinen 1995; Toivola 1992) – which was later to become the cornerstone of their development. The NMT system spread extensively to Europe and Asia, guaranteeing the Nordic companies an advantageous position in the new telecom industry. In certain countries, national equipment monopolies developed their own closed standards, which almost invariably remained local curiosities, while in the USA, AT&T spent years trying to persuade American telecom authorities of the


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potential of wireless communication. Application of the fixed telephony pricing principles we are used to (time-based, caller pays, no terminal subsidies by operators) created ‘normal’ mobile markets, unlike in those countries where divergent pricing distorted the structure of demand.

3.8

AMBITIOUS AND TARGET-ORIENTED INNOVATION POLICY HAS LONG ROOTS

A ‘high-road’ strategy, based on technology and expertise, has lifted both Finnish R&D investments and the networking of public and private actors to new heights. In the 1980s, long before the rise and fall of the ‘new economy’, Finnish technology policy began to emphasize information technology. The importance of science in national development was also more explicitly acknowledged. Somewhat ambitious target-oriented R&D policy was initiated in the early 1970s to lift Finland from its status as a below-average R&D investor (under 1 per cent of GDP at the time) to being among the leaders. This objective was first frustrated by the economic recession of the 1970s, but was obtained during the next decade when public appropriation to R&D increased yearly by some 10 per cent, being the OECD record rate. This was reflected in the knowledge intensity, technical development and productivity of industrial production: the share of high-tech exports rose from 4 to 11 per cent, while the output of the electric and electronics industry grew by 150 per cent. (Jääskeläinen 2001; Lemola 2001) Between 1985 and 1999, the share of R&D expenditure as a share of GDP doubled, reaching €3.75 billion. With its 3.5 per cent share in 2002, Finland ranked second, after Sweden, in the world in R&D input. During the 1990s, the share of the public sector fell from the 40 per cent target level to under 30 per cent of total R&D expenditure, being below the EU and OECD averages, owing partly to intensive private business investments. In 1987 the Science and Technology Council of Finland was established (on the basis of the Science Policy Council founded in 1963) to co-ordinate planning of policy on expertise and innovation. It brings the main economic stakeholders – government, industry, science and the labour markets – together around the same table and has a prominent position in shaping, co-ordinating and resourcing science and technology policy (Romanainen 2001). Given its broad and prestigious representation it is, even from an international perspective, an exceptional body. Finland’s persistent investment in technological development, even during the worst recession years of the early 1990s, is


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probably partly a result of the knowledge-driven national vision conceived at a ‘round table’. The changing direction of science and technology policy at the turn of the 1980s was also reflected in the establishment of the National Technology Agency (Tekes) in the administrative field of the Ministry of Trade and Industry. It prepares, co-ordinates and funds applied technological research and industrial R&D, and is in this field the main source of public funding. From the outset Tekes’ programmes have been influential forums for collaboration between research and business organizations. Tekes’ funding bears a catalytic effect on private R&D outlay: in company projects participants finance some 60–70 per cent of the budget. Nokia has been an important participant in Tekes’ projects, both in frequency and substance. Even though Nokia’s public funding through Tekes projects has, in monetary terms, experienced a growing trend over the past two decades, its share of the company’s sizeable total R&D investments has become insignificant (Figure 3.5). While one may wonder at the justification of public support for a highly profitable global market leader, one should, on the other hand, consider the returns on the public investment over time. First, Nokia’s programme participation has been crucial for the collaborative development of advanced communications technology with the intended side effect of producing spillovers between participants. Secondly, investments in such a company with 20

15

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Häikiö (2001)

Figure 3.5 Tekes funding to Nokia: Volume (millions of euros at 2000 prices) and share of Nokia’s R&D (%)


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advanced know-how and innovative capability have generated important social returns through positive impacts on employment, tax revenues, and the stock of national knowledge (Ali-Yrkkö and Hermans 2002), and have contributed to fundamental industrial restructuring. Another notable element in the national innovation system is the network of Centres of Expertise, which was initiated in 1994 to promote regional collaboration between the business, research, education, and public sectors. However, R&D activity is still highly concentrated around three urban areas, Helsinki, Tampere and Oulu, which account for almost 70 per cent of total expenditure.

3.9

LIBERALIZATION UNLOCKED TELECOM SERVICE DEVELOPMENT …

In Finland, the liberalization of telecom competition, being among the first in the world, took place between 1988 and 1994 and prompted a breakthrough in digital communications. Competition pressed prices down and led to mass markets for wireless communication and a test laboratory for the equipment industry. The impetus for the liberalization came from the private telecom sector, which since the 1960s had criticized the state monopoly in many new telecom services. The Imperial Telephone Decree, valid since 1886, could not give an unambiguous answer to the question of who had the right to transfer data and images on a network. In 1985, the establishment of a data carrier, Datatie, by certain operators and their corporate customers without a licence, set the wheels in motion for a series of changes in the telecommunications law. The liberalization of telecom competition culminated in the GSM (Global System for Mobile Communication) licence in 1990 granted to Radiolinja, founded by the private camp. Private companies had previously been refused an NMT licence due to the supposed social benefits arising from a ‘natural monopoly’. Radiolinja, too, had been established without a country-wide licence in 1988. Because regional licences permitted the construction of local mobile networks, telephone companies began to construct networks in their own areas, believing that the right to operate nationally would eventually be granted. The private licence application also caused much political wrangling. The Posts and Telecommunications authority put up heavy resistance – the demand for NMT services was just beginning to heat up. (Häikiö 1998; Toivola 1992; Turpeinen 1996) Eventually, on 1 July 1991, both Finnish mobile operators, Telecom Finland and Radiolinja were among the few who opened their GSM networks in accordance with the original schedule set up by the GSM MoU (memorandum of understanding; the group of organizations initiating GSM development). Nokia


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made its international premiere on the same occasion by providing Radiolinja’s network. In answer to Radiolinja’s challenge, Telecom Finland brought forward the launch date for their GSM services. Its original intention had been to keep in step with the other GSM development projects in Europe (Häikiö 1998).

3.10

… AND RESTRUCTURED COMPANY FINANCING

The liberalization of the capital markets and the ensuing rapid increase in venture capital gave decisive impetus to the growth, diversification and internationalization of the ICT cluster (Hyytinen and Pajarinen 2002). The lack of venture capital had been a major brake to new business activity right up until the 1990s. In 1995, over 80 per cent of small and medium-sized enterprises still had bank loans, but this figure had dropped to less than 50 per cent by 2000. During the same period private equity investments grew over tenfold, to €404 million (Rönkkö 2001). The subsequent phenomenon of mobile Internet companies surging to the forefront would not have been possible in financial markets like those of the past. Even Nokia would not exist in its current form without having had access to external capital. The Finnish National Fund for Research and Development (Sitra), to name one of the several state-owned investment organizations, has become an important venture capital investor, with a focus on seed financing and growth companies. Finnish Industry Investment Ltd, in turn, was founded in the 1990s to funnel the privatization proceeds of state-owned companies into the advancement of technology innovations through direct company and fund investments.

3.11 UNIVERSITIES AS HATCHERIES OF INNOVATIVE ACTIVITY Finns’ fascination with technology, reflected in the fact that they had, until quite recently, the highest penetration of mobile phones and the Internet in the world, has received its inspiration from the university world. Under the umbrella of academic freedom, the right to free education and an advantageous student grant system, there has been ample opportunity for innovative activity. Academic inventors also have the property rights to their own ideas, which is not the case in a number of other countries. Universities and the technology parks that sprout up around them have in some localities become major sources of new business activity. Academic careers often turn into entrepreneurial ones, in order to commercialize an innovation. Traditionally, students have done research for their theses in local companies and


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have already created jobs for themselves before graduating. Thus, the dynamo of pure and applied science has turned the innovation generator. In the 1980s, students brought the Internet, then a largely unknown concept, from the US to Finland before it went anywhere else. The world’s first graphicbased Internet browser was developed in the IT class of the Helsinki University of Technology in 1992, a year before Mosaic and Netscape. The inventive students were not, however, sufficiently interested in commercializing the browser. But IT students Tatu Ylönen (SSH encryption programme) and Linus Torvalds (Linux operating system) went on to become legends in their own time. The main reason why Nokia thrives in Finland is that it can draw on the local environment of advanced expertise in ICT. Despite Nokia’s global network of research units, a good 60 per cent of the company’s R&D work is carried out in Finland. Towards the turn of the millennium it seemed that the shortage of experts was going to be the biggest challenge to the Finnish ICT cluster. As a swift response to the demands of the industry, the government multiplied openings in higher education institutions: between 1993–98, the total intake in universities nearly doubled, and in polytechnics it almost tripled. However, growth in educational resources did not keep pace with the growth in enrolment. Finland ranked 14th – well below the OECD average – in a 1997 comparison of expenditure per student at the tertiary level (OECD 2000). The recent economic slowdown has alleviated, superficially, the labour shortage in the sector. But this is no lasting solution. The building of the information society requires years and an increasing range of employees who, in turn, will need to master increasingly demanding technologies, not only in the ICT-producing sectors but also in those applying the technology.

3.12

COINCIDENTAL EVENTS INTERVENE IN CLUSTER DYNAMICS

Coincidental events are also an important factor in explaining the success of the cluster, as illustrated by the following cases. Radiolinja’s GSM licence, gained at the beginning of the 1990s, was perfectly timed – although it was hardly noticed then – to coincide with the beginning of world telecom market liberalization. Finland offered a digital mobile phone service, among the first in the world, on a network it had built itself. The international attention gained by the event brought Nokia back from the brink of collapse and thrust it into an export market spiral. As telecom monopolies crumbled around the world, the new arrivals eagerly invested in competing networks. Competition caused lower prices and, hence, a boom in the demand for mobile phones. It is funny to think


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where Finland would be now if private telecom companies had been granted the analogue NMT network licence. The simultaneous recession caused the labour force in Finland to move swiftly into the new growth sector. The global IT breakthrough and, particularly, the commercial expansion of the Internet both coincided with this cycle, thus providing a new development platform for Finnish technology innovations. The integration of mobile and Internet technologies turned Finland into a digital icon. In hindsight, it seems almost ludicrous that the political wrangling over the GSM licence at the beginning of the 1990s was largely an ideological debate that did not even raise the issues – which were later obvious – of the economic and social effects that mobile communications competition and an early transition to digital telecom services would have. It is hard, however, to blame the decision-makers of the time for being short-sighted. At the beginning of the 1990s both the Finnish economy and Nokia were still in a very depressed state before the real take-off started. As this very general examination of the evolution of the ICT cluster shows, the development of the competitiveness of a country and its companies is closely bound up with the operating environment and its internal dynamics. A study coordinated by the OECD (2001), comparing the competitiveness of ICT clusters from different countries and the economic policy that affects it, confirmed this view. There is no such thing as a universally applicable ‘cluster policy’ panacea. The best way to encourage more innovation and competitiveness is to create a framework for uninhibited interaction between cluster operators, both private and public.

3.13

FINNISH ICT CLUSTER AT A CROSSROADS

Although the scope of the Finnish ICT cluster has broadened in recent years, it remains highly specialized in mobile telecommunications. The cluster has benefitted greatly from having a powerful locomotive and system integrator, Nokia. Although smaller Finnish companies have made efforts to decrease their dependence on their key customer, their fortunes are still tied to it. Nokia has been able to maintain and even strengthen its position in global competition, but the fact that the whole sector is in crisis remains. Liberalization and de-regulation of telecommunications fuelled the roaring 1990s. Another important policy-related issue was standardization. The Finnish ICT cluster benefitted greatly from the introduction of NMT as the Scandinavian-wide first-generation (1G) standard, although Motorola retained its leadership over Ericsson and Nokia in the analogue era. Upon the transition to digital technologies, Nokia especially bet heavily on GSM as the second-


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generation (2G) standard, which eventually commanded three quarters of the worldwide user base. In the mid-1980s, the International Telecommunications Union (ITU) assumed an active role in the introduction of the third-generation (3G) standards. Although ITU pushed for one worldwide standard, eventually three became accepted in International Mobile Telecommunications (IMT2000) guidelines: W-CDMA (better known as UMTS, Universal Mobile Telecommunication System), CDMA2000 (promoted in particular by the US provider Qualcomm) and the Chinese TD-SCDMA. Europe attempted to maintain its lead in mobile telecommunications by pushing for rapid deployment of UMTS. In many European countries radio spectrums for 3G operations were auctioned for over €100 billion in total. It soon became clear that deployment and diffusion would be slower, network building costs higher and expected revenue per user lower than the licensees had anticipated. While the auctions were designed to maximize the immediate payoff for the public good, the long-term effects were unanticipated. The rules of the auction explicitly prohibited secondary trading and defined how and when and by whom the 3G networks were to be set up. Thus, the operators were not making a technology or even a business decision – they were deciding whether they wanted to be in the (mobile) telecommunications business, in other words, it was a question of existence. Currently the operators’ indebtedness due to auctions combined with the bearish financial market is holding back the deployment of 3G networks. The main benefit of 2G as compared to 1G is improved voice quality. The key promise of 3G is improved data communication. So far voice has been the key driver of mobile communication, although data is gaining ground. Upon bidding for a spectrum, the operators seem to have assumed a rapid and large shift from voice to data. Whereas in Europe the ‘mobile Internet’ was largely considered a telecommunications extension, the US discussion revolved around expanding the wire-line Internet architecture (wireless local area networks, WLANs, also known as 802.11x, where x refers to the version) to the wireless world. Arguably a combination of 2G and WLAN could be used to reach the goals of 3G in a most cost-efficient manner, although it is expected that 3G and WLANs will co-exist and complement each other. They also embody somewhat different business models: ‘smart’ networks, ‘dumb’ terminals and closedness characterize the telecommunications world, while the information technology world features the opposite. As a consequence, the respective leaders of their industries, Nokia and Microsoft, are increasingly at odds. Nokia has responded to the challenge by attempting to imitate the success of open-source software; Microsoft is trying to leverage on the vast user base of its PC operating system(s). In the late 1990s there was over-investment in virtually all ICT-related activities. In hindsight it is clear that at some point the maturing of the market would naturally end the era of double-digit annual growth rates. Thus, some


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levelling-off was expected. The worldwide recession and the failed introduction of 3G added to the insult. From the point of view of the Finnish ICT cluster, however, the key question is, how will the wireless culture at large evolve, in other words, what kind of blend of information technology and telecommunications will the wireless future be? Depending on the actual configuration, Finland may stay on the cutting edge and continue to serve as a useful testing ground for new technologies or it may have to play catch up with respect to some other hotspots.

NOTE 1. We approximate the ICT cluster with the following branches (SIC-95): 30 Office, accounting and computing machinery, 32 Radio, TV and communications equipment, 64 Post and telecommunications, 72 Computer and related activities.

REFERENCES Ali-Yrkkö, Jyrki and Raine Hermans (2002), Nokia Suomen innovaatiojärjestelmässä, Discussion paper 799, ETLA (The Research Institute of the Finnish Economy). EU (2000), Towards a European Research Area (COM (2000)6). Finnish National Board of Customs, ‘Statistical Service’. Häikiö, Martti (1998), Alkuräjähdys – Radiolinja ja Suomen GSM-matkapuhelintoiminta 1988–1998, (The Big Bang of the GSM Mobile Phone Revolution. The Story of Radiolinja, Finland, 1988–1998, with an English summary), Helsinki: Edita. Häikiö, Martti (2001), Nokia Oyj:n historia, (The History of Nokia plc), Helsinki: Edita. Hernesniemi, Hannu, Markku Lammi and Pekka Ylä-Anttila (1996), Advantage Finland, Helsinki: Taloustieto. Hyytinen, A. and M. Pajarinen (2002), Financing of Technology-intensive Small Businesses: Some Evidence on the Uniqueness of the ICT Industry, Discussion paper 813, ETLA (The Research Institute of the Finnish Economy). Jääskeläinen, Jari (2001), Klusteri tieteen ja politiikan välissä – teollisuuspolitiikasta yhteiskuntapolitiikkaan, (Cluster – Between Science and Policy: From Industrial Policy to Social Policy, with English summary), ETLA Series A33, Helsinki: Taloustieto. Koski, Heli, Petri Rouvinen and Pekka Ylä-Anttila (2002a), ‘ICT Clusters in Europe: The Great Central Banana and Small Nordic Potato’, Information Economics and Policy, 14 (2): 145–65. Koski, Heli, Petri Rouvinen and Pekka Ylä-Anttila (2002b), Tieto ja talous – mitä ‘Uudesta taloudesta’ jäi, Sitra Series, 253, Helsinki: Edita. Lemola, Tarmo (2001), Tiedettä, teknologiaa ja innovaatioita kansakunnan parhaaksi, Working paper 57/01, Espoo: VTT (Technical Research Centre of Finland). Mäkinen, Marco (1995), Nokia Saga, Jyväskylä: Gummerus. OECD (1999), Science, Technology and Industry Scoreboard – Benchmarking Knowledge-based Economies, Paris: OECD.


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OECD (2000), Education at a Glance, Paris: OECD. OECD (2001), Innovative Clusters: Drivers of National Innovation Systems, Paris: OECD. OECD (2002), Measuring the Information Economy, Paris: OECD. OECD/STAN, ‘Structural Analysis Industrial Database’, (online subscription service), Paris: OECD. Paija, Laura (2001), ‘The ICT Cluster in Finland – Can We Explain It?’, in Laura Paija (ed.), Finnish ICT Cluster in the Digital Economy, Helsinki: Taloustieto. Porter, Michael. E. (1990), Competitive Advantage of Nations, London: Macmillan Press. Romanainen, Jari (2001), ‘The Cluster Approach in Finnish Technology Policy’, in OECD (ed.), Innovative Clusters: Drivers of National Innovative Systems, Paris: OECD. Rönkkö, Perttu (2001), ‘Growth and Internationalization of Technology-based New Companies: Case Study of Eight Finnish Companies’, in Laura Paija (ed.), Finnish ICT Cluster in the Digital Economy, Helsinki: Taloustieto. Toivola, Keijo (1992), Poimintoja teletoimen historiasta (Former Telecom Finland’s mobile communications network unit), Vol. 4, TELE Matkaviestinverkot. Turpeinen, Oiva (1996), Yhdistämme, Vol. 1–2, Helsinki: Edita.


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4. Innovation and absorptive capability in the traditional industries: The case of the Finnish wood products industry* Christopher Palmberg 4.1

INTRODUCTION

The exaggerated fixation on a narrowly defined set of so-called high-tech industries, both in empirical research and in policy discussion, undeservedly takes attention away from the more traditional and less R&D-intensive industries that still constitute a major sector in most industrialized countries. Finland is an interesting country in this respect, since the industrial structure underwent a rather radical transformation in the 1990s, mainly due to the emergence of diversified electronics, as well as ICT-related, industries. In statistics produced by the OECD, this transformation is reflected in the doubling of Finland’s share of total exports of high-tech products during the same period (OECD 1999). Despite this indisputably positive trend, there is more to it once we get behind the data. In particular, the role of one firm – namely the role of Nokia – in this transformation is striking. At the turn of the century, Nokia accounted for close to one third of the total R&D spending, as well as roughly one fourth of the total Finnish exports (Ali-Yrkkö et al. 2000; Ali-Yrkkö and Hermans 2002). Furthermore, when looking at the contribution of different industries to the total volume of production in the manufacturing sector, it is clear that Finland still to a significant extent relies on the more traditional industries, such as the forestry- and metals-based industries, despite the emergence of the electronics and ICT-related industries (Figure 4.1). Thus, the further fostering of the high-tech industries is not the only issue of concern in the Finnish context. The renewal of the traditional less R&D-intensive industries, and an understanding of the conditions and processes that support this renewal, are equally important. This chapter relates to a larger research project on the characteristics of innovation and industrial renewal in the traditional industries in Finland (see Palmberg 2001). The purpose of this chapter is to focus the discussion of the 65


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100 90 80 70 60 % 50 40 30 20 10 0

Electronics Chemicals, glass, ceramics Machinery, equipment Metals, metal products Foodstuffs Forestry-based Textiles, clothing Other 1995

1997

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2001

Figure 4.1 Contribution of different industries to the volume of production of the Finnish manufacturing sector 1995–2001 (ETLA database) renewal of traditional industries on the concept of absorptive capability, as exemplified through firm-level case studies drawn from the wood products industry. Absorptive capability is commonly considered as an important byproduct of R&D. It might be defined as ‘firms’ ability to recognise the value of new, external knowledge, assimilate it, and apply it to commercial aims’ (Cohen and Levinthal 1990, 128). Thus, absorptive capability also contributes to the renewal of industries by enabling firms to turn knowledge into innovations, as the sources of firm performance and expansion. The interest of this chapter in this concept stems from the fact that absorptive capability appears to be especially important in the traditional industries, since such industries typically assimilate and apply knowledge originating from upstream high-tech industries (Orsili 2001; Pavitt 1984). Yet, the traditional industries are typically characterized by lower levels of dedication to R&D, even though there are numerous examples of firms that apply advanced technologies and innovate persistently (Karnoe et al., 1999; Laestadius 1996; Maskell 1996).1 In this chapter I argue that the conventional understanding of absorptive capability has to be broadened in the context of the traditional less R&D-intensive industries, for the advancement of a better understanding of innovation and industrial renewal, as well as the conditions and processes supporting them. The chapter is structured as follows. In Section 4.2 I discuss the concept of absorptive capability and various previous empirical contributions that explicitly attempt to broaden the concept in various dimensions. In Section 4.3 I briefly


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discuss the characteristics of the forestry-based industries, as well as the Finnish wood products therein, before proceeding to a presentation of the firm-level case studies. Section 4.4 concludes by analysing the case studies with reference to the previous theoretical and conceptual discussion, while Section 4.5 provides policy implications that might be drawn from the findings.

4.2

THE MANY FACES OF ABSORPTIVE CAPABILITY – A CONCEPTUAL DISCUSSION AND REVIEW OF PREVIOUS RESEARCH

The point of departure taken by Cohen and Levinthal (1990) is the fact that external sources of knowledge and related opportunities are critical to an innovation process, whatever the organizational level at which the innovating unit is defined. Thus, one might, in principle, identify absorptive capabilities at the level of entire nations (the case of Japan is an often cited example, see for instance Freeman 1987), industries and networks (Eliasson 1995, 1999; Laestadius 1998), or firms and their functional units (Bosch et al., 1999; Pennings and Harianto 1992). Nonetheless, the focus of Cohen and Levinthal (1990) is on the firm level. Drawing on the observation of the cumulative nature of learning implies that their second point of departure is that absorptive capability is largely a function of the prior knowledge base of the firm. Moreover, the developing of absorptive capability is considered a by-product of investments in R&D. In developing their theoretical model, Cohen and Levinthal (1990) note that firms’ incentives to invest in R&D for developing their absorptive capabilities depend on two factors. The first factor is the necessary quantity of external knowledge to be assimilated and exploited for commercial ends. This quantity depends on the general level of technological opportunities, or the richness of the scientific and technological knowledge base that firms draw upon in developing particular innovations (see Klevorick et al. 1995 for a discussion on the nature of technological opportunities). The second factor is the ease of learning. The ease of learning depends on the cost of absorption of the relevant knowledge with direct feedback on the amount of R&D required to develop absorptive capability. Cohen and Levinthal (1990) dissect the ease of learning into four underlying dimensions of the nature of the scientific and technological knowledge that firms seek to assimilate and exploit. The first dimension is the complexity and targeted nature of knowledge. When external knowledge is less targeted and more complex, with respect to the firm’s particular needs, R&D-related absorptive capability becomes more important, and vice versa. The second dimension captures the degree of cumu-


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lativeness of the external knowledge, implying that fields characterized by discontinuous scientific and technological change induce the development of R&D-related absorptive capability, while greater continuity diminishes it. The third dimension is the pace of scientific and technological developments, suggesting that a faster pace of knowledge generation makes R&D-related absorptive capability more important. Finally, the fourth underlying dimension for the ease of learning is the degree to which knowledge is implicit or tacit rather than explicit or codified, and thus increases the incentives to develop R&D-related absorptive capability. In this context, Cohen and Levinthal (1990) draw on the discussion of tacit knowledge in Nelson and Winter (1982). The concept of absorptive capability opens up a discussion on the dual role played by R&D, both for the sources of innovation and the capability of firms to recognize, assimilate and apply related external knowledge. This discussion is important especially in the traditional industries, where firms typically are considered to largely rely on the absorption of embodied and disembodied technology originating from collaboration with upstream suppliers of machinery and equipment (Orsili 2001; Pavitt 1984). Nonetheless, the equating of R&D with absorptive capability by Cohen and Levinthal (1990) is apt to bias against industries, such as the wood products industry studied in this chapter, where firms might be persistent innovators and users of external knowledge despite their lower R&D-intensities. Thus, the purpose of this chapter, to go beyond the R&D-intensity of firms in understanding the nature and organization of innovation and absorptive capability, justifies a broader review of the extant literature. In this context, Garud and Nayyar (1994) propose that a firm’s ability to exploit external technologies is not sufficient to sustain innovation in the longer run due to the fact that external knowledge also tends to become available to other firms as time passes. In contrast, knowledge related to in-house technologies is not widely accessible, thereby forming a more long-lasting basis for competitiveness. Exploiting available in-house technologies requires the transfer and continuous reactivation of technology over time in response to changes in the environment of firms. This ability is what Garud and Nayyar (ibid.) label transformative capability. They propose that a viable distinction can be made between absorptive capability, which captures the ability to recognize, assimilate and apply external technological opportunities, and transformative capability, which captures the ability to recognize and exploit technological opportunities created inside a firm. The emphasis on the transformation of in-house technologies comes conceptually very close to a range of other studies that also identify differences in the capability to create entirely new knowledge through R&D, and the capability to recombine existing knowledge and technologies in novel ways. Schumpeter, for one, included new combinations in his definition of innovation (Schumpeter


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1912). More recently, Henderson and Clark (1990) argue that innovations are typically constituted of a number of different components, related technologies and knowledge. Innovation can concern the components themselves, but might also concern the way that the different components are linked together. They coin these types of innovations as architectural. They involve architectural capabilities to combine available components, related technologies and knowledge in new ways. Based on a case study of an anchor chain producer in Sweden, Laestadius (1996) goes further by arguing that the capability to introduce new combinations of available technologies involves quite different types of knowledge compared to that typically captured in the R&D accounts of firms. This type of knowledge is often tacit and involves solving practical engineering problems amongst workers, technicians and engineers on the shop floor. Laestadius (ibid.) suggests that this type of knowledge can support the absorption of external scientific and technological knowledge, for example through collaboration with universities or suppliers of machinery and equipment. One important question in this context concerns the conditions that enable the transfer of knowledge within networks characterized by the unequal distribution of absorptive capability. Important contributions here are Allen (1977) and Tushman and Katz (1980), who touched on the issue by emphasizing the role of ‘gatekeepers’ at the interface of the firm and its environment. The point made is that such gatekeepers are able to reduce the possible mismatch in language and cognitive orientation amongst collaborators and thus contribute to absorptive capability. In summation, these insights suggest that the development of absorptive capability should not be merely viewed and analysed at the firm level. Rather, absorptive capability might also be built collectively through collaboration spanning both industrial and institutional boundaries. They also point towards a ‘collective’ component of absorptive capability, which might be especially important in the less R&D-intensive industries as exemplified here by wood products and the glue-lam timber industry.

4.3

THE CASE OF WOOD PRODUCTS AND THE GLUE-LAM TIMBER INDUSTRY

4.3.1

The Forestry Cluster and Characteristics of the Wood Products Industry

Altogether forestry-based industries accounted in 1999 for roughly 30 per cent of total Finnish industrial production, and contributed some 10 per cent to GDP (Finnish Forest Industry Federation 2000). The dominating role of the pulp and paper industry is clear from the fact that close to half of the value of exports of


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forestry-based industries in Finland originates from various finished paper grades, while wood products account for roughly one fifth. Moreover, the lion’s share of R&D, production and exports originates from a few multinational pulp and paper conglomerates. Nonetheless, the lower R&D-intensity of the wood products industry conceals a relatively diversified industry in terms of product segments and related degree of value added of the end products (Figure 4.2). 3% 18%

46%

19%

Sawing Panels Joinery Furniture Others

14% Source:

www.forestindustries.fi

Figure 4.2 The product segments of the Finnish wood products industry in 2000 According to the figure, bulk-sawn timber accounts for the largest share of total production of the Finnish wood products industry (46 per cent of total production). Sawn timber mainly consists of sawn logs graded according to size and quality, and then dried and debarked for end-use. In the wood panel industry (14 per cent of total production), sawn logs are peeled or chipped down to the core of the log. The thin sheets of veneer or the wood chips are then treated in various ways, dried, graded into different quality categories, and finally glued together to form plywood, particleboard or fibreboard. In the joinery industry (19 percent of total production), the products range from jointed sawn or panel-wood timber to complete building systems, such as wooden roof structures or log houses. The furniture industry is yet another segment of relative importance in Finland (18 per cent of total production), which lies closer to the end-consumers (Finnish Forest Industry Federation 2000). By and large, the joinery and furniture industries share the highest level of value added, compared especially to the sawing and panels industries. Even though the different segments share obvious synergies downstream in the valueadded chain, the selection of raw materials, capital investments and related


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barriers to entry determine within which segments firms can viably position themselves. Of these segments, the most dynamic part of the industry consists of medium-sized firms and some larger ones, involved in sawn timber, wood panels and joinery to a certain extent. These firms are also most actively connected to the research infrastructure due to the higher value added of the related products. The remaining large share of small firms is more focused on specific niches, primarily within sawn products (specific wood qualities). Despite product segmentation, the primary user of wood products is the construction industry. Recently, the level of public R&D funding has risen significantly, relatively speaking. This rise in public funding has mostly been channelled through four recent research programmes commissioned by the National Technology Agency of Finland (Tekes) and including firms and various research groups from the Technical Research Centre of Finland (VTT) and the technical universities. Furthermore, the research infrastructure has gradually been consolidated through the establishment of the Otawood group in 1995. Otawood is a research consortium involving research groups from the main research organizations and technical universities involved in structural engineering, building physics, wood technology and construction (Paajanen 1998). An explicit strategy underlying these initiatives is to increase the value added of the end-products through innovation, as well as to aim for turn-key deliveries of complete building systems, such as wooden houses and standardized construction solutions (Finnish Forest Industries Federation 1999). While the basic technologies and techniques in use in the wood products industry have been around for quite some time, new opportunities mainly emerge related to the use of new ICT-based solutions in timber handling and logistics, the increasing applicability of chemical engineering to the structural analysis and modification of the durability of wood, as well as the new combination of composites, polymers and wood for use especially in construction (Paajanen 1998). Another important source of innovations is regulatory change and standardization in connection with the use of wood in construction that open up new markets. Concrete and steel have traditionally been the dominating raw materials in the construction industry. The glue-lam timber industry, the focus of this chapter, is a common name given to wood products made from the gluing together of softwood veneer or solid timber to form long-span supporting beams for architecturally demanding structures. The end products of the glue-lam industry thus belong to the joinery segment in Figure 4.2 with applications in the construction industry. The core capabilities involved in the development of glue-lam relate to gluing and jointing techniques that homogenize the wood, enhancing its durability and fire resistance, and enable the production of beams with accurate dimensions. The glue-lam timber industry is constituted of a handful of firms, of which the two


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case study firms are examples of successful and progressive ones, despite differences in terms of their size, ownership structure and scope of activities. They are thereby interesting cases for the purpose of this chapter.2 4.3.2

The Development of Glue-lam Timber Bridges

The first case study firm, Vierumäen Teollisuus Oy, is a relatively self-sufficient wood products integrate involved in most activities along the value-added chain, from raw material handling to the conversion of sawn timber into semi-finished solid wood glue-lam components for the construction industry. Treated and precision-cut sawn timber accounts for roughly 60 per cent of total sales. Wood products processed to various degrees of value added make up the remainder. The main processed wood products include glue-lam beams and bridges, and various impregnated products such as poles, noise barriers, fence posts and landscaping fences. More than 50 per cent of the total output is exported. In 1999, the firm employed 420 people at four operating locations, all situated in Finland (Annual Report 2000). The firm became involved in impregnated wood products in the mid-1960s. A few years later, the first jointing techniques were developed. Through these developments, the product palette gradually diversified towards various impregnated wood products, such as telephone and power poles, bridges and beam structures with higher value added. In the late 1970s and early 1980s, the sawmill operations expanded further through the founding of two new sawmills as well as new wood-drying facilities. In the 1990s modernization continued with the aim of increasing productivity in bulk-sawn timber and setting aside more resources for processed wood products. Altogether the firm had a sawing capacity of roughly 550 000m3 in 1998 compared to 120 000m3 in 1990. Sawn timber is increasingly used for various glue-lam wood products, in particular as beam structures for public buildings or bridges for rural roads and overpasses, as well as smaller-scale impregnated wood products (Fyhr 1999). The investments in machinery, modernization and the expansion of activities through the founding of new sawmills are paralleled by a gradual development of capabilities within the core areas of the firm, namely the sourcing of wood, impregnation, glue-laminating and jointing techniques. The development of these capabilities has depended critically on the development of production methods through in-house processes of learning by using and doing, combined with investments in new sawing machinery. The related process innovativeness enabled the sawing of wood in new dimensions, which in turn broadened the product range and customer base. These characteristics of innovation and related capability building are best illustrated through development work related to wooden bridges, a product group that became increasingly important to the firm in the 1990s.


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The technological opportunities enabling the development of wooden bridges were related to the modernization of sawing machinery and the development of jointing and impregnation techniques within the firm. This enabled the sawing and sorting of wood by length and grade, as well as the customized joining and impregnation of glue-laminated wood to fit specific bridge designs. However, the expansion of the business area was limited by the dominant use of concrete and steel as building materials, as well as the lack of construction standards stipulating durability and compatibility parameters for wooden bridges, and had to await new market openings. These emerged in the late 1980s, as the use of wood in construction received increasing attention through various promotional schemes and publicly funded research consortia initiated in Finland at the time. One such consortium consisted of representatives of the glue-lam and wood panel industry, the laboratory of bridge engineering at the Helsinki University of Technology, the Finnish Wood Research Centre and the Finnish National Road Administration. The aim of this consortium was to investigate new techniques for developing wooden bridges of longer spans, which could compete with the traditional construction materials, and was subsequently expanded to the Nordic level through funding from the Nordic Industrial Fund and Tekes. Apart from exploratory research undertaken during 1994–98, with the aim of surveying the state of the art in wooden bridge building around the world, the consortium in Finland was also activated around specific bridge-building projects. The consortium developed techniques for the construction of so-called wood-concrete composite bridges and X-connector arch bridges, which provided a cost-effective advantage over previous wooden bridge designs. These projects have also involved construction contractors and designers. The typical division of labour within R&D in these projects has been one in which the procurers, designers and the firm produced a basic design. Thereafter, the compatibility of the design and prototype with prevailing construction norms and standards is tested and accepted by the Finnish National Road Administration, in collaboration with the research groups at the technical universities and research organizations. The participation of Vierumäen Teollisuus in this division of labour depended to a significant degree on a couple of engineers who were able to translate theoretical models used to calculate the durability values of different constructions into practical bridge-building techniques, thus incorporating construction standards into product development. These insights, in turn, have fed back on the needs of the firm to source specific types of wood timber, the fine-tuning of sawing, glue-lamination and jointing techniques, and have thereby added to the cumulative stock of experience in these techniques. Altogether the firm has delivered 30–60 bridges per year, and smaller pedestrian bridges are also exported. The work within the research consortium culminated in the


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construction of the largest wooden bridge in the world, with an arch-span of 182 meters, a significant innovation in the context of wooden building design (Nordic Timber Council 1999). 4.3.3

The Development of Laminated Veneer Lumber

The second case study firm, Finnforest Oy, is a much larger wood product integrate, covering the whole value-added chain of wood processing within various segments of the sawn timber and the wood panel industry. Although relatively autonomous, the activities of the firm are organized under the conglomerate umbrella of Metsäliitto Oy, presently the third largest forest industry company in Finland. In 2000 the firm employed about 4000 people at 25 production units, the majority of these situated in Finland. The turnover rose throughout the 1990s, mainly due to the profitability of the sawn timber, DIY, and LVL (laminated veneer lumber) businesses. Over 80 per cent of the total turnover is exported, mainly to Europe. (Annual Report 2000; Finnish Federation of the Forest Industries 2000) Laminated veneer lumber is a particularly expanding product area. LVL is made by gluing together peeled softwood veneer to form solid beams and boards for different construction applications, including public and residential buildings, large hall-type structures, warehouses and agricultural buildings, as well as recently for concert halls and wooden bridges. LVL is durable, lightweight and precision-machined, and thus superior to traditional sawn timber. (Mäkynen 1999; Annual Report 2000) The strong position that the firm holds in Europe with LVL is a result of continuous in-house development in the underlying structures of the material, in jointing and glue-lam techniques, and in the visual appearance of the product. These incremental developments and related innovations have, in turn, expanded the usage of LVL towards a range of new and specific applications in construction. Another important source, inducing innovation, has been related to the standardization of LVL to different construction regulations and standards, as well as market niches. These efforts have been reflected in extensive networking with research organizations, universities, retailers and customers both in Finland and abroad. (Kairi 1999) The history of LVL and the associated business area dates back to the early 1970s, when the conglomerate host actively looked for new processed products to increase the value added to timber in the face of rising stumpage prices and increasing price competition. The idea behind LVL as such was not new. In the US, the Forest Products Laboratory had published articles on related techniques, and production of this type of product had already commenced a few years earlier. These experiences and publications from the US led to the initiation of a research project at the corporate R&D unit in collaboration with the forest product laboratories at VTT and Helsinki University of Technology.


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During the early phases of development the main concerns related to standardization and safety regulations regarding the durability of the material. LVL was a completely new concept in construction and one of the first processed wooden building components on the Finnish market. Meanwhile, development work related to process technology was initiated, and the first pilot production line was set up in 1975. In the same year the first product approvals were granted for marketing the product in Finland. Close collaboration with both VTT and Helsinki University of Technology continued throughout the 1970s and 1980s, and resulted in several dissertations and publications. During the pilot phase the LVL concept was revised several times. A production method that allowed for continuous sawing and glue-lamination was developed and patented, and this made the product more suitable for specific applications in construction. The raw material was also changed from birch to conifer, which has higher durability values. (Rakennustaito 1995) More emphasis was given to marketing and exports, since the product had to pass through various tests and modifications for acceptance as a new construction material in various export markets. Technologically, the further in-house development of LVL as a business area has primarily related to investments in machinery and the fine-tuning and adjustment of production methods and related machinery in order to broaden the application areas from simple beam structures towards more complex building components and systems. By 1999, the LVL production capacity had risen to approximately 100 000 m3 compared to 10 000m3 in 1985. In 2001, the fourth production line added some 70 000m3 in capacity. Meanwhile the share of exports in total turnover rose from 20 per cent to 80 per cent during the same period. (Kairi 1999, Annual Report 2000) Alongside investments in machinery, the development and adjustment of production methods and the broadening of application areas, new collaborative partners have entered the network. During the 1990s, LVL evolved in a succession of phases whereby its visual appearance was enhanced. To a large extent, these incremental innovations occurred in close collaboration with research groups at Helsinki University of Technology and VTT in connection with the Otawood research consortium. This collaboration has largely evolved around the same key people at the firm, involved with LVL right from the start, due to their role in translating research into applications, and vice versa. The firm has also participated in using LVL in the construction of glue-lam bridges. Recently the focus has increasingly been on developing turnkey building systems and solutions for customers within the construction industry (annual report 2000). The strong position of LVL on European markets stems largely from the fact that the firm has managed to develop a technological advantage in terms of process technology and the high degree of finish on the product, which in turn has broadened the applicability of LVL to various construction sites.


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Nonetheless, the fact that LVL represents a new concept and building material, as well as a competitor to traditional materials, such as concrete and steel, has implied that each new market opening has been preceded by an extensive partnership with various foreign research organizations and retailers. Hence, an extensive repertoire of standardized and customized applications of LVL has been developed to cater to various national construction standards, regulations and practices.

4.4 4.4.1

THE NATURE OF INNOVATION AND ABSORPTIVE CAPABILITY – A CONCLUDING DISCUSSION Technological Opportunities and Sources of Innovation

Despite the advantages of case studies in highlighting processes and conditions supporting innovation and industrial renewal, there is a problem of generalization (Yin 1994). In this chapter the subsequent conclusions thus relate to commonalities arising from both case studies, as well as the general insights of the wood products industry based on the interviews and available literature. Even though generalization thereby is enhanced, it should nonetheless be noted that the case studies are ‘snapshots’ of innovation within two quite different types of firms in a broader industry. With these caveats in mind, it seems safe to conclude that the glue-lam timber industry appears to be characterized by relatively depleted technological opportunities as the basic timber-gluing and -jointing techniques have been around for quite some time, as well as by the price-competitive nature of the markets. Developments in the sciences and technologies, which firms draw upon during innovation, are slow-paced and highly cumulative. The assimilation and application of the related external knowledge is targeted to the development and fine-tuning of production methods and process technology in order to raise productivity. Hence, and in line with the model proposed by Cohen and Levinthal (1990), the firms indeed appear to have fewer incentives to become engaged in R&D during innovation and absorptive capability building. Nonetheless, the continuous development of sawing, gluing and jointing techniques has added new characteristics to the end products, increasing their value added, use and novelty in the market. Moreover, the competitive nature of the markets has induced a great deal of ingenuity on the part of firms with respect to the capabilities to run and continuously readjust their machinery and equipment. These capabilities are largely related to processes of learning by doing and using within the firms, as discussed in greater detail by Rosenberg (1982). They appear to compensate for depleted technological opportunities in


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the external environment of the firms (compare to Laestadius (1998) and his discussion of knowledge creation in the pulp and paper industry). Furthermore, these learning processes are relatively unsystematic and routine-like, rather than strictly goal-oriented. They are clearly not registered as R&D expenditures in the first place, as these are defined in the OECD Frascati Manual (OECD 1993). Even though depleted technological opportunities might be an overarching feature of the wood products industry as a whole, the cases clearly also highlight ‘pockets’ of opportunities related to development in the sciences and technologies external to the firms. The firms have been engaged in research programmes and collaboration with universities and research organizations in order to gain access to this knowledge. These opportunities relate to the structural engineering of wood, and the combining of wood with polymer, metals and other materials. As Rosenberg et al. (1994) also note, wood is, in fact, a very complex and demanding raw material in terms of its chemical structure, whereby basic research comes to bear on problems in process and product development. A further issue arising in connection with the case studies is the role played by regulations and standards. The firms need to recognize, assimilate and apply various construction standards and regulations regarding the durability, fire resistance, and stress tolerance of wooden construction in the development of product innovations. Accordingly, regulations and standards add to the complexity of the learning environments in which the firms develop capabilities and innovate. They also promote collaboration with regulators, procurers, and engineering houses, as well as end-customers. 4.4.2

The Nature of Absorptive Capability

Based on the discussion above, there thus appear to be at least two further dimensions to absorptive capability, in addition to those captured in the model proposed by Cohen and Levinthal (1990), that matter for the renewal of the firms and industry studied in this chapter. First of all, there seems to be a shift in the attention of firms given to assimilating external knowledge towards exploiting knowledge already residing within the firms. Above, the close association between process and product innovations was discussed from the viewpoint of learning by doing and using. With reference to Cohen and Levinthal (ibid.), these learning processes compensate for the lesser importance of R&D-related absorptive capability, and contribute to the capability of the firms to innovate persistently, despite depleted technological opportunities. These capabilities might be considered as the efficiency factor of absorptive capability, giving leverage to external knowledge as it is applied in the context of lower levels of technological opportunities. They also closely resemble what


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Garud and Nayyar (1994) call transformative capabilities, or the capabilities of firms to transfer and continuously reactivate in-house technologies over time. The case studies give some nice illustrations of the relationships between absorptive and transformative capabilities. The purchase of machinery and equipment from other related industries is an important part of the assimilation of external knowledge. Nonetheless, the capabilities to actually integrate and continuously readjust this machinery and equipment in anticipation of changes in the external environment of the firm, are paramount to incremental innovation and long-term competitiveness. This concerns the use of different sawing, gluing and jointing techniques to achieve different applications, ranging from simple glue-lam beams, to architecturally complex roof structures, complete buildings and bridges with greater span-width. As suggested previously, these capabilities also closely resemble what Henderson and Clark (1990) call architectural capabilities to recombine existing knowledge in novel and creative, albeit sometimes very complex and demanding ways, even though they fall outside the definition of R&D. Hence, greater attention should be given to the sectoral specificity of absorptive capability. The results arising from the case studies dealt with in this chapter suggest that the relative importance of absorptive capability and the transformative capability to innovate might vary according to the features of the industries that one looks at. Moreover, striking a balance between developing these two supposedly distinct types of capabilities might represent a profound challenge in industries where there are few incentives to set aside resources for long-term R&D. 4.4.3

The Organization of Absorptive Capability

Turning now to the second dimension of absorptive capability, it seems to be poorly captured by the model of Cohen and Levinthal (1990). This concerns the organization of absorptive capability, and the collective component of absorptive capability embedded in the collaborative networks that the firms are engaged in. In particular, the firms are confronted with a range of challenges relating to the integration of machinery and equipment into their production routines, to the combination of different vintages of technologies during product development, as well as to the mastering of regulations and standards. In the case studies, these show up in collaboration with universities and research organizations aimed at gaining access to technological opportunities, as well as in collaboration with suppliers, procurers, regulators and customers aimed at overcoming bottlenecks in production, choosing the optimal raw material for different end-products, or innovating in line with regulations and standards. Collaboration enables the firms to dip into external knowledge without having to develop R&D-related absorptive capability of their own. This collective component of absorptive capability arises due to a division of labour during


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collaboration. The sourcing of the raw material, the development and adjustment of production methods, and the scaling of prototype production to an industrial scale are core capabilities of the firms. The more analytical R&D-related activities are typically undertaken jointly with research groups at the universities and research organizations. These kinds of activities concern the basic understanding of the chemical structure of wood, its durability and response to chemical and biological treatment. This division of labour during collaboration suggests that a similar knowledge base among the partners is not a necessary prerequisite for developing ‘collective’ absorptive capability. Rather, learning by doing and using also contributes to firms’ abilities to participate in this type of collaboration for the development of absorptive capability, even though it is largely non-R&Drelated and occurs in areas close to the existing knowledge base. More significantly, however, it would seem that the firms have managed to ‘outsource’ some parts of their absorptive capability, especially to research groups at the universities and research organizations. The cases provide ample evidence underlining the important role of the public research infrastructure, as well as research programmes. In this context, the role of technological gatekeepers has been crucial to transferring knowledge across organizational boundaries. Allen (1977) characterizes a technological gatekeeper as a key person within a firm with the ability to translate and communicate relevant external scientific or technological knowledge throughout the firm. Typically gatekeepers are well versed in the relevant literature and recent developments, have a supervisory role vis-à-vis product development, as well as a long employment history with extensive contacts within the firm. Thus, they are able to reduce the possible mismatch in language and cognitive orientation within the type of networks described above (Tushman and Katz 1980). The gate-keeping role of the individuals in the case studies was to communicate their experience-based knowledge of the practical properties and application of glue-lam in various architecturally demanding structures to scientists involved in research on the chemical structure and durability of different glue-lam end-products. Likewise, they have contributed to bridging the ‘cognitive gap’ between traditional construction heuristics, based on the use of steel and cement, and new ones, based also on the use of wood for complex constructions, such as high-rise houses or heavy traffic bridges.

4.5

POLICY IMPLICATIONS

Despite the problems in generalizing the case studies, it seems fair to conclude that a starting point for a policy discussion is that traditional industries, such as


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the wood products industry, are not necessarily doomed to stagnating demand and non-renewal, despite the fact that depleted technological opportunities imply lower pay-offs from R&D. Quite the contrary, there are significant niches of technological opportunities and expansion that should be nurtured further, of which the glue-lam timber industry discussed in this chapter might serve as one example. An especially important issue seems to be related to the diffusion of new emerging technologies as a means of transforming and renewing existing areas of strength in traditional industries. This would suggest that the focus of policy should be on network-facilitating policies that connect engineering communities from different industries around different vintages of technologies (highand low-tech combined). Nonetheless, the case studies also give some good illustrations of the potential problems that the policy-maker might face during the set-up of such collaborative projects. Reference can be made to the confrontation of paradigms, or heuristics, that is evident in the case of the integration of science-based communities and explorative research with the more experience-based engineering heuristics and exploitation that appears to prevail in the wood products industry (for a discussion of paradigms and heuristics, see Dosi 1988). Apart from the importance that both public R&D subsidies and research and technology programmes can play in industries such as the one studied here, it seems clear that general framework conditions also matter for renewal, even if they sometimes remain outside the sphere of influence of innovation policy. Specifically, the case studies point towards the importance of a range of other activities complementary to R&D subsidy and technology programmes. Thus, there appears to be a particularly strong case here for the co-ordination of different types of policies in the overall policy framework. One problem in this context appears to be a shortage of engineers with the necessary skills. Therefore educational policies have a role to play in catering to the peculiar demand that many firms seemingly have, for example in the wood products industry. The role of regional initiatives, polytechnics and vocational schools is probably especially important since many smaller firms and sawmills are deeply rooted in their local milieu, not least due to their reliance on locally sourced raw materials and their dependence on minimizing transportation costs. A related problem concerns the sustainability of the research infrastructure. While a certain degree of crowding-out of the traditional sciences from the curriculum of universities might be warranted due to the evident growth in the importance of others, it would seem to be of great importance to secure a necessary level of basic research. This is essential since firms rely on collaboration to access the more explorative type of research that is undertaken at the universities due to their lesser incentives to become engaged


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in systematic in-house R&D activities. Thus the erosion of the research infrastructure would also seriously undermine the absorptive capability of the firms. Finally, standardization and legislation is another area where much could be done to foster innovation. Clearly, the wood products industry would benefit greatly from the further development of national construction standards, as well as the creation of a pan-European wooden construction standard. While standardization and legislative change is a possible and viable policy measure in the national context, international efforts are more problematic from the small country perspective. The creation of European standards in the field of wooden constructions is a case in point, due to fragmented markets, competition, as well as tendencies towards protectionism in some countries.

NOTES * This chapter builds on Palmberg (2001). Financing from the Finnish National Fund for Research and Development (Sitra) is kindly acknowledged. 1. The definition of R&D used in this paper relies on the OECD’s Frascati Manual (OECD 1993). In this manual R&D is defined as ‘creative work undertaken on a systematic basis in order to increase the stock of knowledge of man, culture and society, and the use of this stock of knowledge to devise new application’. The main point in this context is the focus of this definition on quantifiable monetary expenditures on systematic and goal-oriented activities, to the neglect of activities of a more unsystematic nature that nonetheless contribute to innovation (see Laestadius (1996) for a lengthier discussion of the pros and cons of the Frascati Manual). 2. The selection of case study firms relied on interviews with experts at VTT, the National Technology Agency, as well as the Finnish Forest Industry Federation. The case studies rely on 14 semi-structured interviews covering representatives of the firms, universities, and other relevant actors in the field, complementing publicly available material. The case study descriptions have been circulated amongst the firms to secure consistency. For a lengthier methodological discussion, see Palmberg (2001).

REFERENCES Ali-Yrkkö, Jyrki and Raine Hermans (2002), Nokia in the Finnish Innovation System, ETLA Discussion Paper no. 811. Allen, Thomas (1977), Managing the Flow of Technology, Cambridge, MA: MIT Press. Bosch, Frans, Henk Volberda and Michiel de Boer (1999), ‘Coevolution of Firm Absorptive Capacity and Knowledge Environment: Organizational Forms and Combinative Capabilities’, Organization Science, 10 (5) 551–68. Cohen, Wesley and David Levinthal (1990), ‘Absorptive Capacity: A New Perspective on Learning and Innovation’, Administrative Science Quarterly, 35 (1) 128–52. Dosi, Giovanni (1988), ‘The Nature of the Innovation Process’, in Giovanni Dosi, Christopher Freeman, Richard Nelson, Gerald Silverberg and Luc Soete (eds) Technical Change and Economic Theory, London: Pinter Publishers. Eliasson, Gunnar (1995), Teknologigeneratorer eller nationellt prestigeprojekt? Exemplet svensk flygindustri, Stockholm: University Press.


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Eliasson, Gunnar (1999), Undervattensteknologi i industriell tillämpning – projektet Viking som nordisk industriell kompetensgenerator, Forskningsrapport TRITA-IEOR 1999:12. Finnish Forest Industries Federation (1999), Visio 2010, Askonpaino: Meridian X Oy. Finnish Forest Industries Federation (2000), Key to the Finnish Forest Industry, Helsinki. Fyhr, Pekka (1999), ‘Vierumäen Teollisuus rakentaa Heinolaan Pohjoismaiden suurimman liimapuutehtaan’, Puumies, 10, 9. Garud, Rahud and Praveen Nayyar (1994), ‘Transformative Capacity: Continual Structuring by Intemporal Technology Transfer’, Strategic Management Journal, 15, 365–85. Henderson, Rebecca and Kim Clark (1990), ‘Architectural Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Established Firms’, Administrative Science Quarterly, 35, 9–30. Henttinen, Annastiina and Anneli Havén (1996), Laivalaudasta liimapuuhun, Lahti: Markprint Oy. Kairi, Matti (1999), Kertopuun tarina. Personal notes. Karnoe, Peter, Peer Kristensen and Poul Andersen (eds) (1999), Mobilizing Resources and Generating Competencies, Copenhagen: Copenhagen Business School Press. Klevorick, Alvin, Richard Levin, Richard Nelson and Sidney Winter (1995), ‘On the Sources and Interindustry Differences in Technological Opportunities’, Research Policy, 24, 185–205. Laestadius, Staffan (1994), Ramnäs Ankarkätting AB – världsledande tillverkare av avancerad lågteknologi, Royal Institute of Technology, TRITA-IEO R 1994:2. Laestadius, Staffan (1996), Är Sverige lågteknologiskt? – reflektioner kring kunskapsbildning och kompetens inom industriell verksamhet, Forskningsrapport TRITA-IEO R 1996: 2, KTH, Stockholm. Laestadius, Staffan (1998), ‘Technology level, knowledge formation and industrial competence in paper manufacturing’, in G. Eliasson and C. Green (eds), Microfoundations of Economic Growth – A Schumpeterian Perspective, Ann Arbor: University of Michigan Press. Maskell, Peter (ed.) (1998), Competitiveness, Localised Learning and Regional Development: Specialisation and Prosperity in Small Open Economies, London: Routledge. Massau, Ali (1993), Advantage Finland – Sawmill Industry, ETLA Discussion papers No. 442. Mäkynen, Jarkko (1999), ‘Vaneria kellon ympäri – yhä puhtaimmissa olosuhteissa’, Puumies, 6, 9–30. Nelson, Richard and Sidney Winter (1982), An Evolutionary Theory of Economic Change, Harvard, CT: Harvard University Press. Nordic Timber Council (1999), Timber Bridges – A Presentation of 22 Nordic Timber Bridges. OECD (1993), Frascati Manual, Paris: OECD. OECD (1999), Benchmarking Knowledge-based Economies, Paris: OECD. Orsili, Marsili (2001), The Anatomy and Evolution of Industries – Technological Change and Industrial Dynamics, Cheltenham: Edward Elgar. Palmberg, Christopher (2001), Sectoral Patterns of Innovation and Competence Requirements – A Closer Look at Low-tech Industries, Sitra Reports Series 8, Helsinki: Sitra. Paajanen, T. (1998), ‘Mekaanisen metsäteollisuuden erityspiirteet toimialana’, Pnumarkkinapäivä, 13 (12).


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Pavitt, K. (1984), ‘Sectoral patterns of technical change – towards a taxonomy and theory’, Research Policy, 13 (6) 343–73. Pennings, J. and F. Harianto (1992), ‘Technological networking and innovation implementation’, Organization Science, 3, 356–82. Rakennustaito (1995), Kertopuutuotannosta yli 80% vientiin, Puumies, 9, 28–9. Rosenberg, Nathan (1982), Inside the Black Box: Technology and Economics, Cambridge: Cambridge University Press. Rosenberg, Nathan, Peter Ince, Kenneth Skog and Andrew Plantinga (1994), ‘Understanding the Adoption of New Technology in the Forest Products Industry’, in Nathan Rosenberg (ed.) Exploring the Black Box: Technology, Economics, and History, Cambridge: Cambridge University Press. Schumpeter, Joseph (1912), Capitalism, Socialism and Democracy, Harper & Brothers, New York: Harper Colophon Books, 1975. Tushman, Michael and Ralph Katz (1980), ‘External Communication and Project Performance: An Investigation into the Role of Gatekeepers’, Management Science, 26 (11), 107–85. Yin, Robert (1994), Case Study Research – Design and Methods, London: Sage.


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APPENDIX: R&D INTENSITY OF FINNISH INDUSTRIES (OECD 1999) R&D expenditure as a percentage of value added in 1990 and 1995 (the wood products industry in italics) Industries

1990

1995

Pharmaceuticals Radio, TV & communication equipment Electrical machinery Other transport equipment Professional goods Office & computing machinery Electrical apparatus Fabricated metal products Chemical products Non-electrical machinery Rubber & plastic products Machinery & equipment Chemicals excluding drugs Motor vehicles Non-metallic mineral products Non-ferrous metals Petroleum refineries & products Transport equipment Basic metal industries Metal products Iron & steel Foodstuffs Paper, paper products & printing Textiles, apparel & leather Wood products Shipbuilding & repairing

28% 26% 17% 8% 19% 9% 9% 8% 9% 6% 5% 6% 9% 4% 2% 5% 6% 4% 4% 2% 3% 3% 2% 1% 1% 2%

39% 35% 26% 21% 13% 13% 11% 11% 9% 7% 7% 7% 7% 5% 4% 4% 3% 3% 2% 2% 2% 2% 1% 1% 1% 1%


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5. Knowledge services in the Finnish innovation system Aija Leiponen 5.1

INTRODUCTION: KNOWLEDGE-INTENSIVE BUSINESS SERVICES IN THE DEVELOPMENT AND CIRCULATION OF KNOWLEDGE IN THE INNOVATION SYSTEM

This chapter examines the role of knowledge-intensive business services (KIBS) in the innovation system based on new data concerning Finnish business service firms. These services have become one of the key vectors of knowledge transfer in the system, and they are expected to perform as new engines of knowledge-based growth and innovation. Are these expectations realistic; can the KIBS sector deliver accordingly? This chapter explores how KIBS firms create new knowledge in the innovation system and how these firms influence their clients’ performance. Knowledge-intensive business services are a fascinating object of research also because their ‘products’ are information and competencies. These are the building blocks of the knowledge-based economy. Understanding how KIBS firms and industries operate will give us a ‘sneak preview’ into the strategies and issues emerging in the future as the knowledge intensity of the whole economy grows. Knowledge is a very special economic good because of its intangibility. We define knowledge here as consisting of codified information and tacit competencies. In contrast to information, the codified expression of competencies is frequently expensive if not altogether impossible. As a consequence, transferring knowledge from a business service provider to a client can take extended periods of time and require the client’s close co-operation and contribution, contrary to the situation in most tangible goods markets. The study of these kinds of knowledge transactions is only beginning but it is very promising, because it can illuminate collaborative innovation activities more generally. Innovation, like knowledge-intensive service transactions, depends often on collaboration among distinct organizational partners. 85


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Research on KIBS industries and firms has been growing in recent years. Miles’ work on the service economy and KIBS industries identified the main differences between service and manufacturing industries (Miles 1994; Miles et al. 1995). Other scholars have provided descriptive and conceptual analyses of KIBS (Gallouj 1997; Hauknes 1998; Sundbo 1997; Tordoir 1995). On the other hand, management and technical consultancies have been studied for some time (Hansen, Nohria and Tierney 1999; Mowery 1983). Similarly, professional services, such as legal and accounting services, have been investigated particularly in the sociology of professions (such as in Eliot Freidson’s work, 1998). An emerging perspective is to view KIBS, a subset of professional services, as an important element in systemic innovation (Hauknes ibid.). The current study contributes to this avenue of research by using one of the first cross-sectional datasets to analyse the effects of KIBS firms’ characteristics and client relationships on their innovation activities and performance. Innovation in services is a new area within the multidisciplinary field of innovation studies. Barras’ (1986; 1990) early work on innovation in financial services set the stage for more explicit and detailed analysis of different kinds of service industries. The new Community Innovation Survey data that have been collected in a number of European countries have enabled large-scale studies of service innovation, akin to the ones in which innovation scholars have been engaged concerning manufacturing industries. Using these data for Italian industries, Evangelista (2000) proposed that innovation activities in service and manufacturing industries have more commonalities than differences. In fact, variation within these two broad sectors appears to be larger than that across sectors. His results thus suggest that we do not need a whole new toolset to study innovation in service firms, although we may need to be sensitive to the special characteristics of services. KIBS firms both create new knowledge themselves and learn from their clients and other organizations. Knowledge obtained in these ways can be recombined into new service offerings. Knowledge is thus transferred in both directions within client relationships. This makes strategic and contractual considerations of managing and controlling knowledge in service relationships critical. This chapter examines, first, the innovation and knowledge management activities of KIBS firms themselves, and second, the nature of service firms’ creative interactions with their clients. The discussion is largely based on Leiponen (2001). Readers interested in more scholarly publications are also referred to Leiponen (2002; 2003; 2004). The aforementioned three studies provide more detailed information about the collection and characteristics of the survey dataset. The next section introduces the service and client strategies identified in the study. Section 5.3 describes the knowledge bases of business service firms using the Finnish survey data. KIBS firms’ innovation activities and relation-


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Knowledge services in the Finnish innovation system

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ships with clients are examined in Section 5.4. Finally, implications for innovation policies are elaborated in the last section.

5.2

INTERNAL AND EXTERNAL KNOWLEDGE CREATION IN BUSINESS SERVICES: RESEARCH APPROACH

This chapter examines knowledge creation and transfer by KIBS firms on three levels of study. The first level concerns innovation activities within the service firm itself. The second level explores the interaction between KIBS firms and their clients, with particular emphasis on service strategies and contractual arrangements. The discussion on these two levels that follows is based on a new survey dataset of 167 Finnish KIBS firms, complemented with some interview data (for a description of the survey data, see Leiponen 2001; 2004). The third level of analysis draws on five interviews with client firm managers concerning the nature and significance of co-operative service relationships with KIBS providers. These levels of analysis and data sources yield a multifaceted picture of the role of KIBS firms in the knowledge economy. 5.2.1

Service Firms’ Competitive Strategies

KIBS firms’ internal activities are approached from three closely related points of view. First, the most prominent service strategies identified are in terms of firms’ orientation towards either pure expert services or packaged service solutions. Service ‘packaging’, in other words some degree of conceptualization and standardization, facilitates the organization of knowledge in and transfer from the service-providing firm. Expert services, on the other hand, enable more intensive customization and client-specific problem-solving. Second, competitiveness strategies are characterized through survey questions that inquire whether the firm’s operations are primarily based on organizational, in other words collective (knowledge) resources, or whether skills and learning embedded in individual experts are more crucial for the firm’s success. The role of experts in the firm has far-reaching implications, among other things, for the firm’s growth potential. The third strategic dimension identified here is represented by the modes of learning employed by the company. Here, the polar strategies include, on the one hand, the combination of internal and external knowledge sources, and on the other hand, incremental and highly cumulative learning by doing. A combinatory strategy enables more radical innovations than local and incremental learning. These strategies are summarized in Table 5.1. The performance implications of these strategies are assessed through their


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effects on innovativeness, as reported in Section 5.4. The results obtained suggest that strategic choices with respect to services, competitiveness, and learning influence the firm’s direction and speed of evolution. Table 5.1

Service firms’ strategic choices

Service strategy

Competitiveness strategy

Learning strategy

Expert services

• Operating as outside expert in clients’ projects

Service solutions

• ‘Packaging’ of services • Service concepts

Individuals’ skills

• Higher education • Personal know-how

Organizational resources

• • • •

Innovation Service development Marketing Team know-how

Incremental learning

• On-the-job training • Learning by doing

Recombination of knowledge

• Team-based knowledge • Internal cooperation • External collaborative innovation

Table 5.2 presents descriptive statistics of the main variables related to service, competitiveness and learning strategies. The first four variables give basic information about the survey sample in terms of firm size, age, structure, and export orientation. On average, business service firms tend to be small and domestically oriented. Many have group affiliations, however. The next three variables describe the responses to questions about the service firms’ role in client relationships. On a scale of 0 to 3, respondents indicated that expert services are the most prevalent mode of operation with clients. Many firms also suggested that they carry out service projects relatively independently of the client. Fewer firms provide explicit solutions to their clients. These firms develop and supply more standardized service packages. Education, in-house training, and investments in service development describe the basic modes of knowledge creation in firms in any service industry.


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KIBS firms’ employees are very highly educated, and even investments in R&D exceed the average for manufacturing industries. Moreover, on-the-job training, measured here as number of days spent in training events, averages nine days per year, which is a substantial monetary investment for these small firms. It is thus evident that the firms in the sample are highly knowledge-intensive. Table 5.2

Descriptive statistics of main survey variables

Variable

Mean

Standard Minimum Maximum deviation

Employees Export share of sales revenue (%) Age (years) Service group subsidiary (%) Service solutions Expert services Independent Share of employees with higher education degrees (%) Training investments (days) R&D investments/sales (%) Competitiveness: Education Learning on the job Training in-house Marketing Reputation Teams’ capabilities

41 12 17.2 38 1.3 2.1 1.9

81.8 26 13.7 49 0.8 0.8 0.8

1 0 1 0 0 0 0

590 100 90 100 3 3 3

33 8.8 3.3

31 8.3 9.6

0 1 0

100 60 100

2.3 2.8 2.4 2.1 2.7 2.2

0.6 0.4 0.6 0.7 0.5 0.7

1 2 1 0 0 0

3 3 3 3 3 3

As regards how KIBS firms themselves perceive the sources of their competitiveness, the traditional view of incremental learning in client projects was emphasized by the sample firms. Reputation and in-house training are also factors that KIBS firm managers believe are important for their success. Thus, the popular view of KIBS firms, illustrated by these surveyed firms, places a lot of emphasis on individuals’ skills and expert strategies. 5.2.2

Management of Client Relationships

Relationships between KIBS firms and their clients were assessed with various qualitative measures as well as contractual features. For example, the nature of co-operation can be described through examining the role of the service


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provider in the relationship. Characteristics such as how early the service supplier is brought into the project, how actively it contributes to the project planning and specifications development and how close the co-operation is in the project define the service supplier’s relationship with the client. Is the service firm simply a source of temporary skilled labour, or can it provide the client with more strategically important knowledge such as project design and management know-how? The latter types of knowledge are more difficult to create and deliver, and they are also likely to enhance the profitability implications for the service provider. The contractual features assessed in this study include the division of rights to intellectual assets generated in the joint project, and possible (partial) exclusive dealing clauses required by the client. These kinds of control rights influence the service supplier’s motivation to expend effort and develop new services. Table 5.3 describes these basic contractual features. Control rights to intellectual assets generated in joint projects are given to clients in most firms and industries, although as illustrated in Table 5.3, this is not as self-evident in R&D services, management consulting, and engineering industries as it is in industrial design. Partial exclusivity clauses usually require that the service firm not supply to certain competitors of the client firm. Again, R&D services and industrial design represent the extremes among industries studied here. In Section 5.4 I will argue that the nature of the knowledge base in R&D services is different in specific ways from that in industrial design, and this is the reason for differences in client contracting (see also Leiponen 2004). Table 5.3

Service firms’ contracts with key clients

Type of contract

All Industrial Advertising Machine Electrical Management R&D firms design & process engineering consulting services

Control rights to client

2.2

2.8

2.4

2.2

2.1

2.1

1.7

Partial exclusivity

1.8

2.5

1.8

2.0

1.7

2.0

1.6

Scale: 0 (never) – 3 (always)

5.2.3

Why Outsource Service Activities?

The fundamental strategic decision by client firms related to service activities is whether to develop service competencies in-house or outsource them from external suppliers. The most relevant factors that affect the choice are the longterm implications of competence development and utilization. By outsourcing service functions, firms benefit from a broader selection of competencies and


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from the possibility to make suppliers compete against one another. Thus, outsourcing strategies can improve quality and cost effectiveness. However, if the service activities in question are strategically sensitive or unique, they are more likely to be supplied internally. Of course, this approach can be called a ‘core competence strategy’, whereby client firms internalize services that are in some sense ‘core activities’ and outsource other activities (Prahalad and Hamel 1990). The practical challenge with the core competence strategy is implementation: how to define what is core and what is not. In fact, it can be very difficult to identify the long-term performance ramifications for learning and innovation that arise from these strategic decisions. Additionally, interviews with Finnish business service clients indicate that most manufacturing firms do not have a service procurement strategy. This would facilitate the efficient utilization and internal sharing of knowledge obtained from external service suppliers. For example, division managers in large firms are generally not aware of the service suppliers of other divisions, even though synergies might arise from scale economies in procurement, efficiencies in contracting (transaction costs), and the development of trust between the firm and its suppliers.

5.3 5.3.1

MANAGEMENT OF KNOWLEDGE IN KIBS Knowledge Accumulation in Business Services

Clients are the most important source of knowledge for KIBS firms. It is, therefore, of utmost importance to record and share learning from client projects. Practices related to organizational knowledge and learning have been called knowledge management in the strategic management literature. Essentially, knowledge management entails practices to enable cumulative learning and the circulation of knowledge within the organization. Managing knowledge and competencies also necessitates the sharing of work practices and solutions to client problems. Thus, knowledge management is about converting individuals’ skills and learning into collective resources for the organization. One strategic implication is that the firm needs to concentrate on clients and projects that support the accumulation of a certain kind of knowledge. Even an expert organization supplying highly customized services is better off specializing in a clearly defined area of competence, in which it has a chance to gain a strong market position. Individual versus organizational resources have been studied by Spender (1996), among others. His analysis focuses not only on the distinction between knowledge held by individuals or an organization, but also on whether knowledge is tacit or codified. Figure 5.1 illustrates these dimensions in a matrix


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of effective knowledge types. Figure 5.2 operationalizes these concepts for the case of business service organizations. Individual

Organizational

Expertise, skills

Routines, processes

‘Automatic’

‘Collective’

Education, professional knowledge

Intellectual property, products, services

‘Conscious’

‘Objectified’

Tacit

Explicit

Source:

Modified from Spender (1996) and Cook and Brown (1999)

Figure 5.1

Dimensions of organizational knowledge

Individual

Tacit

Explicit

Organizational

External expert operation

Team-based knowledge/routines

Education levels

Service solutions and concepts Technology licensing

Figure 5.2

Operationalization of knowledge in the service firm

An empirical study reported in Leiponen (2003) examines the effects of these knowledge types on innovation and intellectual asset ownership. While the literature on organizational knowledge and learning (for example Grant 1996; Nonaka 1994; Spender 1996) often finds similar categories, analysis of what organizational purposes each of the knowledge types fulfils has been lacking. These performance effects are the focus of this research.


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Table 5.4 displays the survey indicators by industry to illustrate the tendency of different industries to emphasize different types of knowledge. For instance, industrial design is clearly oriented towards individual designers’ explicit and tacit skills. R&D services, on the other hand, emphasize both kinds of explicit knowledge; individual (formal education) and organizational (codified technologies). Finally, advertising is based on both kinds of tacit knowledge; individual (expert skills) and organizational (knowledge residing in teams). The internal structure of service firms influences their knowledge creation activities. The data in Table 5.2 indicate that some 40 per cent of the surveyed firms are subsidiaries in a service group. Many more firms participate in looser networks of service providers. Participation in an international network or group of companies can be particularly valuable, as emphasized by interviewed service firms and clients. International service groups tend to have training programmes, centralized research facilities, extensive shared databases, and service concepts that are made available to all subsidiaries. Even less formally organized service networks make a broad set of competencies available to clients of individual firms. Experts from diverse fields or different countries participating in the network may be called on to provide specialized knowledge in demanding projects. These kinds of international business group structures are very common in advertising and management consulting. Individual firms that are partners or members of these groups tend to be more successful in new service development, so the effects of the group structure are tangible. Technical service areas use international structures less frequently, although it is easy to imagine that potential benefits from the exchange of competencies and local presence can be substantial. 5.3.2

Motivation of Highly Skilled Professionals

Most knowledge-intensive business services employ highly educated experts, whose skills are strongly in demand in the labour market. One of the service firms’ key management goals is to help these experts fulfil themselves, and keep them motivated by offering stimulating assignments and various kinds of incentives. In addition to monetary and qualitative incentive systems, commitment can be enhanced by using certain features of employment contracts such as no-compete clauses and partnership or partial ownership schemes. Most business service managers, however, emphasize the importance of maintaining a collegial and creative work atmosphere and thus stimulating the intrinsic motivation of individualistic experts. Incentive systems need to be sensitive to whether individual employees or groups and teams are to be motivated. This determines the possible measures of performance. Measuring individuals’ performance creates strong incentives,


Knowledge resources in KIBS industries (survey means)

Resources

Advertising

Machine & process engineering

Electrical engineering

Management consulting

R&D services

9:50 AM

69.0

24.5

22.0

21.6

67.0

37.1

2.4

2.3

1.9

1.9

2.1

2.1

0.6 0.20

1.3 0.07

1.3 0.24

1.2 0.24

1.9 0.22

0.9 0.29

2.0

2.6

2.1

2.1

2.2

2.3

Scale: 0 (not important) – 3 (very important), except for higher education levels (%) and technology licensing (0/1 binary variable)

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Individual explicit: Higher education degrees (% of employees) Individual tacit: Expert skills Organizational explicit: Service solutions Technology licensing (out) (0/1) Organizational tacit: Competitiveness based on knowledge in teams

Industrial design

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Table 5.4


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but it may hamper co-operation and knowledge-sharing in the organization. Team- or firm-level performance measures dilute incentives to a degree, but the work and co-operative atmosphere may be enhanced. Team incentives are particularly important if the basis of the firm’s competitiveness is collective knowledge instead of individuals’ skills (see Figures 5.1 and 5.2). Another management challenge in business service organizations is to strike a balance between individualistic experts and the needs of the organization as a whole. The goals of individuals and the organization are not perfectly aligned, despite possible incentive schemes. Typically, in a small knowledge service firm, the founder is a strong personality and an exceptionally talented designer, researcher, or analyst. In the early stages of the firm this is immensely valuable, as the firm needs to build its reputation, collect client references and find collaboration partners. However, dependence on a ‘star designer’ is also a long-term risk for the organization. When the star retires, the organization may be left without a sufficiently broad knowledge base on which to continue operations successfully. Therefore, effective knowledge management is highly critical for start-up service firms with growth aspirations. Knowledge that is accumulated in projects as well as management responsibilities should be shared, intrapreneurship should be encouraged and rewarded and joint practices should be developed right from the start. 5.3.3

Pricing Under Asymmetric Information

Contracting with clients is an interesting and challenging problem in an area of highly asymmetric information such as KIBS. Clients cannot know very precisely in advance how skilled and dutiful the service provider is in its activities. Even if the firms were to attempt to write explicit and detailed project contracts, there frequently arise unexpected circumstances, particularly in projects that involve innovation. Co-operation thus needs to be flexible and based on mutual trust. However, developing the firm’s reputation and trustbased client relationships can take a long time. Startup service providers can try to speed up the formation of client relationships by designing contracts that include performance guarantees and bonuses. Then the client pays less for services if substandard levels of productivity or quality are observed, or it pays more if goals are exceeded. These kinds of arrangements shift the project risk to the service supplier and naturally require measurement of performance. The potential advantage is that the credibility of the service provider is strengthened. Overall, however, performance measures and bonuses are used relatively rarely in service supply relationships. One of the reasons is that the client’s contribution to the success of the project may even surpass that of the service supplier, in which case strong incentives to the service firm do not much affect


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the outcome. Here, one could imagine setting up a temporary profit unit by combining the client’s and service supplier’s project teams. All members of this combined project team could be rewarded with bonuses for exceeding their goals. However, even this solution does not work, if performance in the project is very difficult to measure. An alternative approach is quality control applying various kinds of quality management systems and the standardization of service processes and output. Finally, risk can be shifted to the service firm by setting a fixed price for the project, which enhances incentives. Then, the service provider will operate efficiently since it will obtain the residual between the price and the total costs of operation. According to the Finnish survey information, small service firms use performance bonuses more often than their large counterparts. The reason may be exactly the kind of signalling of quality discussed above. Using performance bonuses is also more frequent in firms where customer satisfaction is assessed on a regular basis and project management and standardization are explicit areas of development. This kind of ‘codification’ of project management and performance expands the possibilities to use performance measures in client contracts. Performance pricing itself can be a means to express the value of successful project output to the client. Without these kinds of mechanisms of control, describing the service and its impact may be difficult. Performancebased standards, measurement and pricing may thus be useful tools for growth-oriented knowledge service firms.

5.4

INNOVATION IN FINNISH KNOWLEDGE SERVICE FIRMS

Finnish knowledge service providers invest significant resources in service development (Table 5.5). Competencies are created through training and R&D activities as well as joint innovation projects with clients or other service firms. Additionally, software and equipment suppliers are important innovation partners for some service firms. Universities are a relevant source of knowledge and collaborators particularly for R&D service providers. As a result of various investments in service development, over 40 per cent of the firms surveyed introduced new services in the markets, and more than half of the firms report having significantly improved existing services in the three years preceding the survey. Interestingly, these shares of innovating firms in the population do not much differ from Finnish manufacturing industries surveyed by Statistics Finland (1998). Among the business service industries studied here, management consulting and R&D services were most frequently engaged in the development of new kinds of competencies and services. Firms


Table 5.5

Mean indicators of Finnish KIBS industries’ service development activities Advertising

Machine & process engineering

Electrical engineering

Management consulting

R&D services

54 20 3.3

27 20 2.2

48 12 1.3

67 21 2.1

43 24 2.3

61 24 2.7

65 20 12.7

74 47 12 44 30 45 54

55 33 0 22 22 55 18

74 54 5 37 10 47 64

81 35 5 57 35 46 54

74 52 15 56 22 27 40

78 39 22 28 22 61 82

60 55 25 40 75 48 50

5.8

6.5

5.1

7.2

2.4

7.3

5.3

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Design

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97

R&D investments > 0 (%) R&D department or team (%) R&D investments/sales (%) Collaboration: With customers (%) With service firms (%) With competitors (%) With suppliers (%) With universities (%) Service innovations (%) Service improvements (%) Share of sales from innovative services (%)

All firms

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Indicator


98

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in advertising, industrial design, and technical (engineering) services were more likely to rely on incremental learning in client projects, in which case the probability of more radical service innovations is small. The service and competence strategies introduced in Sections 5.2 and 5.3 seem to have an impact on how client relationships are organized. One concrete aspect is how control rights to knowledge created in projects are split between the client and the service supplier. For instance, if the project generates patents, software, or ideas for new services, can the service firm control these assets and sell them to other clients or not? This division of rights depends, among other things, on the nature of the underlying learning processes (see Table 5.6). Service firms based on incremental learning tend to yield the rights to control knowledge assets to clients, while firms that learn and innovate by combining diverse internal and external sources of competence tend to retain rights to both service output and knowledge associated with it. Additionally, firms that develop standardized service solutions often retain control rights to intellectual assets, while firms supplying pure expert services are more likely to yield the rights to clients. Table 5.6 Means of a set of variables concerning KIBS firms, for different values of the control rights variable Variable

Control rights sometimes or always kept by the KIBS firm

Employees Sales per employee (1000 euro) Business group member (%) Solutions providers (0–3) Expert service providers (0–3) R&D intensity (%) Knowledge accumulation through internal and external co-operation* Knowledge accumulation through incremental learning* Observations

Control rights always obtained by the client

36.6 126 35 1.3 1.9 8.4

46.3 106 42 1.2 2.2 1.8

0.11

–0.16

–0.25 100

0.36 67

* denotes variables derived from a principal component analysis of collaboration, training, education, and R&D activities.

Furthermore, the statistical analysis reported in Table 5.7 suggests that control rights to intellectual assets are associated with innovation performance.


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Although the statistical difference between innovators and non-innovators seems small here, in a regression analysis this difference becomes statistically significant (see Leiponen 2002). The interpretation suggested here is that control rights create incentives to invest in R&D and develop new services and technologies, since the service firm can appropriate the returns by selling the novelty to many clients and cumulatively build on it over extended periods of time. If clients insist on obtaining rights to the service supplier’s innovative ideas, the supplier is not so motivated to develop new ideas. Indeed, clients should keep in mind that today’s control rights allocation may impact the service supplier’s innovativeness in the future. Clients’ attempts to excessively control the supplier may suppress the prospects of success in the relationship in the long run. Table 5.7 Variable

Means of independent variables for innovators, non-innovators No Improvement No Innovation improvements innovations

Employees 29 Business group (%) 27 Output control rights to client (scale 0–3) 2.3 Partial exclusivity (scale 0–3) 1.7 Knowledge accumulation through internal and external co-operation* –0.61 Knowledge accumulation through incremental learning* 0.00 Higher educated employees (%) 22.8 Expert skills (scale 0–3) 2.0 Service solutions (scale 0–3) 1.1 Technology licensing (%) 11 Team-based knowledge (scale 0–3) 2.1 R&D department (%) 8 R&D intensity (%) 1.7 Observations 66

56 51

30 34

61 48

2.1 1.9

2.2 1.9

2.1 1.7

0.48

–0.49

0.63

–0.2 36.0 2.2 1.5 27 2.3 29 5.0 86

0.30 26.2 2.1 1.2 16 2.1 16 2.4 85

–0.38 35.7 2.0 1.4 24 2.4 24 4.9 67

* denotes variables derived from a principal component analysis of collaboration, training, education, and R&D activities.

The statistics in Table 5.7 also demonstrate that learning strategies as well as types of organizational knowledge correlate with innovation performance. Few service firms with emphasis on incremental learning launch service innovations. Co-operative (combinatory) knowledge creation strategies are more conducive to innovation. Service firms launching new or significantly improved services are also more likely to provide service solutions than non-innovating firms. Additionally, higher education (explicit individual knowledge), technology licensing and R&D activities (explicit organizational knowledge), and team-based knowledge (tacit organizational knowledge) are correlated with


100

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successful innovation. Thus, three of the four types of knowledge identified are useful for innovation; only tacit individual knowledge is not valuable as the sole basis for learning and innovation. Future research could examine in more detail if different technological fields require different types of knowledge for successful innovation. In any case, the nature of learning and the business strategies of service firms are closely intertwined with innovation. Learning may have considerable long-term implications for the evolution of firms and their services. The Finnish survey data (not reported here; see Leiponen 2001) also suggest that service strategies influence firms’ capabilities to adopt and use new technologies. Suppliers of service solutions appear to benefit more than suppliers of expert services from business opportunities opened up by improved information and communication technologies. Standardization of service processes and practices to assess and articulate service quality associated with packaged service solutions are more conducive to using information and communication technologies in these processes and in searching for new clients. Strategic differences among KIBS service suppliers have implications for the broader innovation system too. Service solutions are more likely to generate increasing returns to scale, and hence they may facilitate growth and internationalization of firms. Growth and international operation of Finnish service firms would generate positive externalities for industries using services. A more diverse and higher quality supply of knowledge-intensive business service solutions influences the client firms’ competitiveness positively. Expert services, meanwhile, are an important knowledge and competence resource, particularly for manufacturing firms. Expert service firms form a reserve of highly educated and skilled employees, which also provides the valuable functions of circulating existing knowledge in the economy and producing new insights based on learning from service operations. These kinds of experts may be highly valued partners in their clients’ innovation projects.

5.5

POLITICS AND POLICIES OF KNOWLEDGEINTENSIVE BUSINESS SERVICES

The European Union and the OECD have been studying and debating the economic importance of knowledge-intensive business services in recent years. The shares of service sectors in the gross domestic products of industrialized economies have been growing steadily for the past several decades. KIBS are among the industries that grow most rapidly. Within the OECD, employment in business services has grown at an average rate of 10 per cent per year, although the share of these services in total employment remains below 5 per cent. Nevertheless, high growth is expected to continue, particularly in computer-related services. Moreover, KIBS and computer software industries


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represent the ‘high technology’ among service industries in terms of their knowledge intensity. Other sectors benefit from this concentration of competencies, as according to recent studies, KIBS inputs improve productivity in user sectors (Luukkainen and Niininen 2000; Tomlinson 1999). KIBS are ‘high-tech’ also in the sense that information technology is expected to revolutionize these services, even more pronouncedly so than other service industries. For example, the Finnish Science and Technology Policy Council has recently stated that the adoption of information technologies in business services is one of the special challenges of the innovation system (STPC 2000). It thus appears that KIBS industries are expected to operate as a kind of an engine of the ‘new’ economy, where efficiencies are derived from the use of modern information and communication technologies, facilitating the spread of new knowledge from KIBS industries to other industries using service inputs. 5.5.1

Information Technology in Knowledge Services

The empirical material collected in Finland indicates that some of the expectations placed on KIBS industries may be overstated. The data referred to here suggest that information and communication technologies improve the efficiency of service processes and communication with clients. However, technology is not likely to be successfully used as the main basis for knowledge services. Service firms’ clients interviewed in the project emphasized the need for personal contacts and face-to-face communication. The more complex and longer-lasting the service project, the more important it is to meet in person, particularly in the early stages of the project. Face-to-face meetings facilitate the creation of personal relationships and trust, which can be essential especially in projects where innovation is a substantial component. Generating new ideas and solving complex problems in collaboration can be achieved only in part through electronic communication. Information technologies are also expected to help increase service exports. However, exporting from a home base may not be the main mode of internationalization for knowledge-intensive business service firms. According to international statistics, foreign direct investments are clearly more important than exports in services (OECD 1999). In most service industries, it is still crucial to have a local presence in order to be close and visible to the users. This is accentuated in KIBS, the operations of which are entirely based on transferring competencies and maintaining and building reputation. 5.5.2

Business Competencies and Innovation Policy

Finnish political decision-makers have repeatedly expressed their concern over deficiencies in the areas of marketing and business competencies in Finnish


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industries, particularly in the case of small and medium-sized manufacturing companies (STPC 2000). More research is called for in the fields of business strategy, management, and marketing. The interviews with service executives carried out in this study indicated that the connections between business service firms and academic scholars of business studies are almost non-existent. It is surprising that not even management consultants and advertising designers, who seek and use business competencies and knowledge very intensively, find conversations with academic researchers to be useful. This might be a fruitful area of political intervention. For instance, policies could support joint research projects between KIBS firms, their clients, and academic business researchers, thus facilitating potentially fruitful connections. These kinds of universityindustry research consortia have been successfully ongoing between technical universities and the manufacturing sector for decades. However, if the reason for the lack of connections is deeper and results from a weak applicability of Finnish academic business research, perhaps a longer-term reorientation of research investments and emphases is necessary. 5.5.3

Incentives and Support for Service Innovation

To what extent should KIBS firms’ innovation activities be supported by public funding? The usual logic behind the argument that innovation in general should be supported by governments is that firms’ knowledge tends to leak to their competitors, and as a result, investments in knowledge creation – innovation – are considered to be suboptimal because innovators do not take into account the benefits they create for other organizations. The fundamental assumption is that all innovation is productive and useful from society’s point of view. These ideas originated in the new theories of economic growth, where innovation either enhances product value or reduces production costs. Do service innovations fulfil these criteria? Inherent uncertainty in all innovation activities implies that not even in manufacturing do firms know beforehand if the project will result in a useful new product or technology. Many inventions fail the test of markets. The same applies for service innovations: new services may turn out to be useless or of low value, but if there is a realistic chance that service innovations increase the productivity and efficiency of firms using the services, they may generate positive externalities for firms and sectors. The types of business services identified in this study (expert services and standardized solutions) have different needs in terms of innovation policy. Expert skills are built through learning on the job, formal education and jobrelated training. Personal skills cannot be expected to generate equally important externalities as codified and conceptualized information. It is thus possible that investments in these skills by experts themselves and their employers are already


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in some sense closer to optimal levels without additional public intervention. Besides, education is heavily supported by the Finnish government – all degree programmes, not to mention primary and secondary education, are free of tuition fees. In contrast, service concepts easily spill over to competing service providers, which implies that investments in their development are likely to be substantially below the ‘optimal’ level. In this line of thinking, innovation policy could thus support the development of innovative and ‘packageable’ service solutions or technologies, in the same way as the development of more tangible products and technologies is supported. Perhaps surprisingly, public funding for KIBS innovation activities is already quite prevalent. One in every four service firms in the survey sample participates in the national innovation system as a recipient of funding from the National Technology Agency (Tekes) or another governmental source. These funds tend to be directed to R&D and engineering firms, however: very few management or advertising service firms receive support for their innovation activities. Firms in management and advertising industries perhaps compensate for the lack of innovation support by engaging in international service chains and networks. From the innovation system’s point of view, however, it might be useful to include the most innovative firms of management, design, advertising and marketing services within the research consortia and networks of support, in order to engage and improve marketing and business competencies within the innovation system. Thus, a suggestion for policy intervention is to experiment with innovation programmes for business service innovations, or alternatively, engage management professionals in technology programmes. Investments could initially be limited in order to simply learn about collaborative innovation processes in this area. Most business service firms would probably not be interested in such innovation programmes, but firms with strong competencies and creative ideas but limited resources to develop and implement their ideas would benefit and consequently generate externalities on other service firms as well as the whole innovation system. KIBS firms could also play a role in commercializing technological innovations of small high-tech manufacturing firms. Available reports point out that small and medium-sized firms use business services less than large firms, and they thus do not gain access to the knowledge available in service industries. Small firms may have financial constraints or they may lack the internal competencies that are necessary in order to even benefit from highly knowledge-intensive services. Additionally, service firms themselves tend to prefer large firms with sizeable service budgets as clients. Therefore, small firms’ procurement of knowledge services might be a relevant object of public support. For example, the commercialization of new technologies by small start-up companies, another identified weakness in the Finnish innovation


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system, might be accelerated by providing access to marketing, management, and design services.

REFERENCES Barras, Richard (1986), ‘Towards a Theory of Innovation in Services’, Research Policy, 15, 161–73. Barras, Richard (1990), ‘Interactive Innovation in Financial and Business Services: The Vanguard of the Service Revolution’, Research Policy, 19, 215–37. Cook, Scott D.N. and John Seely Brown (1999), ‘Bridging Epistemologies: The Generative Dance Between Organizational Knowledge and Organizational Knowing’, Organization Science, 10 (4), 381–400. Evangelista, Rinaldo (2000), ‘Sectoral Patterns of Technological Change in Services’, Economics of Innovation and New Technology, 4, 183–221. Freidson, Eliot (1988), Professional Powers: A Study of the Institutionalization of Formal Knowledge, Chicago: University of Chicago Press. Gallouj, F. (1997), ‘Innovation in Services’, Research Policy, 26, 537–56. Grant, R.M. (1996), ‘Toward a Knowledge-Based Theory of the Firm’, Strategic Management Journal, 17 (Winter Special Issue), 109–22. Hansen, M.T., N. Nohria and T. Tierney (1999), ‘What’s your Strategy for Managing Knowledge?’, Harvard Business Review, (March–April), 106–16. Hauknes, Johan (1998), Services in Innovation – Innovation in Services, Research report, Oslo: STEP Group. Leiponen, Aija (2001), Knowledge Services in the Innovation System, Helsinki: ETLA. Leiponen, Aija (2002), ‘Control of Intellectual Assets in Client Relationships: Implications for Innovation’, unpublished manuscript, Ithaca, NY: Cornell University. Leiponen, Aija (2003), ‘Organizational Knowledge and Innovation in Business Services’, Applied Economics and Management working paper 03–22, Ithaca, NY: Cornell University. Leiponen, Aija (2004), ‘Organization of Knowledge Exchange: An Empirical Study of Knowledge-Intensive Business Service Relationships’, Economics of Innovation and New Technology (forthcoming). Luukkainen, Sakari and Petri Niininen (eds) (2000), Teknologiaintensiiviset palvelut ja kansallinen kilpailukyky, Espoo: VTT Group for Technology Studies. Miles, Ian (1994), ‘Innovation in Services’, in Mark Dodgson and Roy Rothwell (eds), The Handbook of Industrial Innovation, Aldershot: Edward Elgar, pp. 243–56. Miles, Ian, Nikolaos Kastrinos, Rob Bilderbeek and Pim den Hertog (1995), KnowledgeIntensive Business Services: Users, Carriers and Sources of Innovation, European Innovation Monitoring System (EIMS) Report. Mowery, David C. (1983), ‘The Relationship between Intrafirm and Contractual Forms of Industrial Research in American Manufacturing, 1900–1940’, Explorations in Economic History, 20, 351–74. Nonaka, Ikujiro (1994), ‘Dynamic Theory of Organizational Knowledge Creation’, Organization Science, 5 (1), 14–37. OECD (1999), Benchmarking Knowledge-Based Economies, Paris: OECD Science, Technology and Industry Scoreboard. Prahalad, C.K. and G. Hamel (1990), ‘The Core Competence of the Corporation’, Harvard Business Review, 68 (3), 79–91.


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Spender, J.-C. (1996), ‘Making Knowledge the Basis of a Dynamic Theory of the Firm’, Strategic Management Journal, 17 (Winter Special Issue), 45–62. Statistics Finland (1998), ‘Innovaatiotutkimus 1996’, Helsinki: Statistics Finland. STPC (2000), Tiedon ja osaamisen haasteet (Review 2000: The Challenge of Knowledge and Know-how), Report, Helsinki: Science and Technology Policy Council of Finland. http://www.minedu.fi/tiede_ja_teknologianeuvosto/eng/publications/Review_2000. html#2.4. Sundbo, J. (1997), ‘Management of Innovation in Services’, Service Industries Journal, 17 (3), 432–55. Tomlinson, Mark (1999), ‘A new role for business services in economic growth’, Paper for the TSER Conference on the Globalising Learning Economy, Manchester: ESRC Centre for Research on Innovation and Competition. Tordoir, Pieter P. (1995), The Professional Knowledge Economy: The Management and Integration of Professional Services in Business Organizations, Dordrecht: Kluwer Academic Publishers.


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6. Nokia: A giant in the Finnish innovation system* Jyrki Ali-Yrkkö and Raine Hermans 6.1

INTRODUCTION

In the 1990s, Nokia grew to become one of the world’s leading high-tech companies. Despite the fact that Nokia has become multinational, a significant share of its activities is still located in Finland. In the latter part of the 1990s, the most visible impact of Nokia on the Finnish economy was its contribution to GDP growth. In 2000, the contribution of Nokia to growth peaked, exceeding 1.6 percentage points. In the same year, Nokia accounted for 2.8 per cent and 20 per cent of Finnish GDP and total exports, respectively (see Ali-Yrkkö et al. 1999). In 2001 the global recession in the telecommunications industry hit Nokia, too, and the company’s contribution to GDP growth dropped close to zero. However, in addition to GDP, GDP growth and exports, Nokia also has an important role in the Finnish innovation system. Nokia’s role is two-sided. On the one hand, Nokia utilizes resources from the innovation system. But at the same time the company produces innovation resources that diffuse outside the company. To evaluate this role more precisely, in this chapter we examine Nokia’s influence on the innovation activities of other companies and universities as well as on public sector income and expenditures. ‘Innovation system’ refers to the operation and interaction of universities, research institutes, other public sector organizations, and private businesses, which together influence the creation, diffusion, and utilization of novel know-how. This study aims to provide answers to the following questions: – How has Nokia influenced the know-how and innovation activities of universities in Finland? – How has Nokia influenced the know-how and innovation activities of other companies? – How has the public sector promoted Nokia’s innovation activities? – What has been the role of the public sector in Nokia’s R&D projects? – What is the impact of Nokia’s partner network on innovation activities? 106


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A variety of data sources have been used to answer these research questions. One important data source has been official statistics. The study also makes use of information in a book on Nokia’s history (Häikiö 2001) and in its annual reports. In addition, numerical data relating to Tekes have come directly from Tekes. Finally, interviews conducted while this research was going on have been used as qualitative data.1 Interviews were utilized especially where quantitative data were not available or were not measurable. In addition, interviews were used to deepen the analysis of numerical information. The chapter is structured as follows: Section 6.2 examines ‘what Nokia has got from Finland’. The benefits reaped by Nokia in terms of the innovation system form the framework for analysis. Section 6.3 looks at the other side of the matter, that is, ‘what Finland has got from Nokia’. Section 6.4 provides a summary and conclusions.

6.2 6.2.1

FINLAND’S INVESTMENTS IN NOKIA’S GROWTH R&D Funding by Tekes

In Finland, a great majority of public R&D funding to the private sector is channelled through Tekes, which is an organization under the Ministry of Trade and Industry (MTI). In the 1990s Tekes increasingly directed its funding (grants and loans) towards companies in the information and communication technology industry. As a consequence of this development, in 2001 about onethird of the funding by Tekes was targeted at the information and communication industry. Nokia is among the hundreds of companies in Finland that have received public funding for their R&D activities. The amount of Tekes financing received by the company has varied considerably. In 1969 Nokia received a total of the equivalent of 34 000 euros from the MTI Technology Office (Tekes’s predecessor), while in 1999 the respective figure was the equivalent of 18 million euros of Tekes funding. In 2001 Nokia received Tekes funding worth approximately 12 million euros. In the 1970s the share of the MTI Technology Office funding of Nokia’s total R&D expenditures was 7 per cent on average (Figure 6.1). In the first two years of the 1980s Tekes funding gained a significant position in the financing of Nokia’s R&D. In 1980 over one quarter of the company’s total R&D was financed by Tekes, and in the following year the share remained at about 15 per cent. After these peak years, the share of Tekes funding of Nokia’s total R&D spending decreased significantly. During the recession at the beginning of the 1990s, the importance of Tekes funding grew again. With the support of public funding, the Nokia Research

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2001

1997

1993

1989

1985

1977

1973

20 18 16 14 12 10 8 6 4 2 0

EUR, mill.

30 25 20 % 15 10 5 0


1969

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1981


Percent of Tekes funding of Nokia’s total R&D expenditure Tekes funding, EUR, mill. Figure 6.1

Tekes funding and its share of Nokia’s total R&D expenditure

Center managed to sustain the continuity of its research activities even through the most difficult years of the economic slump (Häikiö 2001, p. 96). In the second half of the 1990s the share of Tekes funding of Nokia’s total R&D expenditure was around 1.5 per cent on average. When the amount of Tekes financing is compared relative to Nokia’s R&D activities in Finland, then the share of Tekes financing is slightly below 2 per cent over the same time period. In the 1990s, most of the Tekes funding received by Nokia was directed towards Nokia Research Center projects. In the period 1993–2001 the research centre received 55 per cent on average of all Tekes funding granted to the Nokia Group (Häikiö 2001). Taken together, we can conclude that although the amount of financing granted to Nokia by Tekes increased in nominal terms in the 1990s, its share of Nokia’s total R&D expenditure has decreased significantly. In terms of the number of projects, Tekes-funded Nokia projects have increased. While in the 1970s Nokia received Tekes funding for an average of nine projects annually, in the 1980s and 1990s the corresponding figures were 19 and 37, respectively. Tekes, however, finances only a part of the costs of companies’ research and development projects (so-called company projects of Tekes). Usually, most of the costs of company projects are financed by the company or group of companies. Figure 6.2 examines the share of Tekes financing in all company projects, and separately in Nokia projects. Tekes’ share of financing in company projects decreased towards the 1990s (Figure 6.2). Tekes’ financing share of the company projects has been 32 per cent on average. Hence, around 70 per cent of the financing has come from other sources, mainly from the companies themselves.


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109

60 50 40 % 30 20 10 0 1987

1989

1991

1993

1995

1997

1999

2001

All company projects Nokia projects Source:

Ali-Yrkkö & Hermans (2002)

Figure 6.2 Share of Tekes financing in all its company projects and Nokia projects The share of Tekes financing in Nokia projects has been smaller than in company projects on average. In the 1990s Tekes financed 26 per cent of Nokia projects on average, while the share of other financing, primarily Nokia’s own share, has been about three fourths of the projects’ total costs. In 2000 and 2001 Tekes’ share of financing in Nokia projects exceeded 30 per cent, and has thus been above the average share of financing in company projects. Time series analysis shows that Tekes’ share of Nokia project financing has varied a great deal, and thus it is likely that the current increase is only temporary. Until now, we have considered the financial side of Tekes funding. However, the significance of Tekes’ funding cannot be estimated only through financial flows. Public R&D funding has also had strategic and long-term impacts. In many interviews, it was stated that the effects of Tekes funding has impacted the length and determination of the R&D projects. One interviewee described the impact of this financing as follows: Tekes is a binding force which stabilizes research activity in this turbulent environment. If a decision has been made to start on something, it is out of the question to change direction or start doing something else. It won’t work, because we have a deal [with Tekes]. (R&D manager, Nokia)

6.2.2

Highly Qualified Personnel from Finland

As the significance of research activity has grown in the telecommunications industry, Nokia has tightened its links to universities and research institutes.


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As the need for highly skilled labour has also increased, Nokia has attempted to influence the level and direction of higher education (Häikiö 2001, p. 87). As the need for qualified personnel grew in the 1990s, Nokia’s role in education policy became more effective (Häikiö 2001, p. 98). Through the Federation of the Finnish Electrical and Electronics Industry Nokia strove to increase the number of university starting places available in the fields of electronics, telecommunications, and information technology. For instance in 1997, Nokia estimated that over the years 1997–2000 the need for technically skilled labour in Finland would be about 6500 people (Häikiö 2001). This figure was about two thirds of all the graduates (in Finland) in fields that Nokia considers relevant. In the fields that are central to Nokia, that is electronics, information technology and telecommunications, the number of university starting places available began to grow in the middle of the 1990s. In the 1990s, the company needed highly qualified R&D personnel and the number of people employed in R&D at Nokia increased rapidly. In addition to tripling its overseas R&D in a few years, Nokia also recruited a significant number of R&D employees in Finland (Figure 6.3). Nokia has played an active role in research projects with the Finnish universities of technology. In addition to the acquisition of research information, 20 000 16 000 12 000 8000 4000 0 1993 1994 1995 1996 1997 1998 1999 2000 2001E 2002E R&D personnel in Finland

Sources:

R&D personnel abroad

Häikiö (2001, p. 84) and authors’ estimates

Figure 6.3

Nokia’s R&D personnel in Finland and abroad


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the projects have served as an important form of recruitment. The following quotations describe the significance of research projects as a recruitment channel: Especially during these times after the mid-1990s we [at Nokia] had very frequent recruitment and then all one could get was students about to graduate, or even third or fourth year students, with whom we usually or almost every time ended up with thesis work here. (R&D manager, Nokia). We do have 43 nationalities here [at Nokia Research Centre] and a good many of them have come through university networks and university co-operation. (R&D manager, Nokia).

Quotations show that co-operation has had an important role in screening a potential labour force. Nokia has been able to find new employees with the competencies and the know-how they needed. 6.2.3

Finland as the Test Laboratory for the Latest Technology

The government had a large role especially in the early phases of the development of mobile communications in Finland. At the turn of the 1960s, Nordic postal and telecommunications companies began planning a pan-Nordic automatic mobile communication network, NMT. Open standards and equipment compatibility were focused on in the planning of the NMT. These actions aimed at promoting competition among equipment manufacturers (Häikiö 1998, p. 32). Nordic Telecommunications administrators therefore guaranteed competition between manufacturers, from which the whole industry has subsequently benefitted. At the beginning of the 1980s the Nordic NMT network remained the world’s most extensive mobile network measured by the number of users (Paija 2001). It was also a network where roaming had been contracted for, and a number of operators from various countries took part. Nordic equipment manufacturers got invaluable experience from manufacturing NMT networks and phones, which they have later utilized. The government also had a significant role in the creation of the panEuropean GSM (Global System for Mobile Communication) standard at the turn of the 1970s. In Finland, the Post and Telegraph Office financed GSM research by industry and technical universities, the first of which was conducted in 1981 (Häikiö 1998, p. 39). Tekes also financed these activities, the benefits of which were only realized years later. The first large programme by Tekes was The Convergence of Information Technology [part of a larger framework called ‘The Development Programme for Information Technology’] in 1984. … In that programme, those protocol and database tools were made by teams, which went to Nokia and made GSM. (Professor, university/research institute)


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If we looked at where all those people came from, and then the tools and the knowhow, which were developed in the 1980s, Tekes’ programme [The Convergence of Information Technology] has given birth to incredible results, combined with the business know-how and the competence in NMT centres and terminal equipment that Nokia then had. It was the combination of these competencies. … And the result of this combination is now visible to us. These would never have been accomplished without Tekes. (Professor, university/research institute)

In 1987 thirteen European countries signed a contract in which the implementation of the GSM system was agreed upon. In addition to standardizing those systems that cross borders, governments had another important role in the development of mobile communications, which was the freeing of competition. Finland, among other countries, deregulated its telecommunications industry, which led to more open international competition. In conclusion, we can state that Finland’s early presence in the international mobile networks created a good test field for Nokia. Firstly, NMT was the world’s first automatic mobile network covering several countries. The experiences gained from it could later be utilized. Secondly, the stepwise process to free competition in the telecommunications industry led to the founding of Radiolinja Oy. In 1991 Nokia sold its first GSM network and the customer was Radiolinja. Radiolinja opened its GSM mobile network as the first operator in the world, and the event received a great deal of publicity internationally (Häikiö 1998, p. 130). Opening the world’s first commercial GSM network brought Nokia an important reference for the future. However, there were also other operators opening a GSM network in the same year. Hence, in 1991 Nokia was not the only equipment provider with a working GSM solution. In addition to the development of the NMT and GSM, Finland has probably acted as a pilot country for Nokia in other ways too. In Finland the mobile phone penetration has been one of the highest in the world for a long time. One can presume that the high penetration has partly reinforced Nokia’s belief that it will rise to similar figures in the rest of the world. Faith in high growth rates has possibly also ensured that the company has invested enough in research and development.

6.3 6.3.1

NOKIA’S IMPACTS ON THE FINNISH INNOVATION SYSTEM Transfer of Know-how to Other Companies

Nokia’s own operations are reflected in other companies in Finland. The most central channel concerning the innovation system is Nokia’s co-operation with other companies. Nokia co-operates both in production and in research and


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development with numerous companies. In 2000 there were about 300 companies in Nokia’s ‘first tier’ partner network. There were from 18 000 to 20 000 employees in these companies who worked with products delivered to Nokia (Ali-Yrkkö 2001). One can roughly estimate that, taking into account Nokia’s partners, Nokia’s share of Finland’s employment is slightly below 2.5 per cent. The width and depth of Nokia’s co-operation with other companies has changed remarkably during the past twenty years (for details, see Ali-Yrkkö 2001). This development can be classified into four phases, namely: subcontracting in manufacturing; partnerships in manufacturing; R&D subcontracting; and R&D partnerships. In the 1980s, co-operation with other companies was mostly traditional subcontracting (Phase 1). With the exception of a few companies, very close co-operation did not exist. Nokia used subcontracting mainly as a buffer to stabilize its manufacturing capacity. The 1990s marked profound changes. The global telecommunications market exploded and Nokia also benefitted from this growth. As a response to the changed situation, in the early 1990s Nokia started to rely more on outside suppliers and to search for long-term co-operation partners (Phase 2), which helped the company to respond to the challenge of shortening product life cycles and market expansion. Consequently, co-operation with other companies became more systematic when it was seen as a permanent mode of manufacturing operation. Closer co-operation required frequent and undistorted information exchange between partners. In the latter part of the 1990s, Nokia also started to increasingly use software and R&D subcontractors (Phase 3). Hence, in addition to manufacturing, co-operation with other companies also included R&D activities. However, despite long-term agreements, in many cases the relationship can be classified as subcontracting rather than a true partnership because invoicing is usually based on hours rather than results. Currently, it seems co-operation in R&D and software development will move more toward partnership (Phase 4). Suppliers will take more development risk and if the product is successful, profits will be shared between the partners. In other words, moving toward true partnership will lead to changes in risk- and reward-sharing. Taken together, the scope and depth of Nokia’s networking have shifted considerably. However, these different phases of co-operation do not fully exclude one another. While today the focus is on partnerships, the company continues also to use subcontracting. From the viewpoint of the Finnish innovation system, the most interesting aspects of co-operation are those which at least somehow relate to R&D. Cooperation in R&D can be examined by analysing Nokia’s co-operation in R&D projects financed by Tekes.


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In most of the Tekes-financed Nokia projects there have also been other partners. The projects have not only involved Nokia’s internal research and development; most of the time other parties have been engaged as well. The share of co-operative projects has increased continuously. Currently there are at least some partners involved in almost all of the Tekes-financed Nokia projects. Compared to the mid-1990s, the co-operation with research institutes and universities has increased especially (for details, see Ali-Yrkkö & Hermans 2002). With the help of research and product development co-operation, know-how diffuses from one party to the others. Externalities from R&D activity, that is, the diffusion of know-how from one party to others, have a great significance for society. Public grants directed to research and development are usually justified by these externalities. Figure 6.4 examines Tekes’ latest programmes, which concern the information and communications cluster. The programmes included in the figure are: Electronics for the Information Society (ETX) and Telecommunications: Creating a Global Village (TLX). Both programmes include business projects as well as research projects. The figure includes those Nokia partners that have at least three co-operative projects with Nokia. Figure 6.4 shows that many companies and universities have co-operated with Nokia. There are both small and big companies amongst the partners. Also the partners’ industries vary a great deal. The network includes component and part manufacturers (like Eimo, Aspocomp and Filtronic), contract manufacturers (like Elcoteq and Flextronics), software houses (like Aplac, CCC and SSH Communications Security), production automation manufacturers (like JOT Automation) and operators (like Finnet, Sonera, and Elisa). In addition to the companies shown in the figure, Nokia has co-operated with many other parties regarding the TLX and ETX programmes. These organizations have been involved in less than three projects with Nokia, which is why they are not included in the figure. Among those left out of the picture are both large and small companies. Many of the small companies are young. Based on the interviews, co-operation with Nokia has had various influences. First, during the R&D co-operation companies share their knowledge with each other. Usually, partners have common teams, which meet frequently. Naturally, close co-operation requires deep personal and organizational trust between partners, for the companies often exchange highly confidential information. The following quotations describe the significance of the transfer of know-how. Via Nokia the project group included one foreign company which participated in planning [of the product to be developed]. We got one kind of core technology from them. (R&D manager in a Nokia partner company)


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JOT Automation Oyj Suunto Oy

NetHawk Oy Vaisala Oyj Polar Electro Oy

VLSI Solution Oyj

Ultraprint

CCC Aspocomp Oy

Picopak

Kone Oyj

Fincitec Oy

Elcoteq Network Oyj Benefon Filtronic LK Oy

Eimo Oyj

Satel Oy Flextronics International Finland Oy APLACS Solutions Oy Instrumentointi Oyj

ABB Elektrobit Oy

University of Oulu VTT Nokia Mobile Phones Nokia Research Center Nokia Networks Tampere University of Technology

Helsinki University of Technology Sonera Teleste

Tellabs Oy

Efore Oy

Defence Forces Nokia Multimedia Terminals

University of Helsinki

Finnet Group

Lappeenranta University of Technology TecnomenElisa Communications Intellitel Communications Oy

University of Tampere

SSH Communications Security Ericsson ICL AmiEdu * The figure includes both company ventures and targeted research projects. Included are partners

with a minimum of three projects with Nokia. The information is based on the final reports of the ETX and TLX programmes. The figure is interpreted so that the more projects the organization is involved in, the larger is its circle and the closer it is to the centre. The figure was drawn in the course of the ‘Evaluation of Finnish R&D Programmes in the Field of Electronics and Telecommunications (ETX, TLX and Teletronics I)’ project.

Figure 6.4 Nokia’s co-operation network in Tekes’ ETX and TLX programmes* Concerning the technology, we learned a great deal [in this project]. … I suspect that at this moment we have the world’s top knowledge concerning this [the developed system], which we can present. We also learned about the markets. We acquired contacts in Finland as well as the rest of the world. (R&D manager in a Nokia partner company)

In addition to knowledge diffusion, for many SMEs, Nokia works as a systems provider, into whose solutions their products are incorporated, as the following example shows. We saw it, that we can make the technology, but without the help of Nokia and its brand in the market, we cannot survive alone. Nokia worked as a marketing channel, and in this Nokia was our most important customer, and so we thought that Nokia


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could manage the distribution of these products. (R&D manager in a Nokia partner company)

Because of their limited resources, the significance of marketing channels has been important particularly for SMEs. Although many companies in the ICT cluster operate globally today, there is still much remaining to develop in this aspect. The lack of marketing know-how and channels complicates and inhibits SME internationalization. One interviewee presented it as follows: If I look at this problem of being Finnish, then … we’ve got very thin internationalization. People with international experience, fluent language skills, ability to work with foreign cultures, active contacts in other countries. We have far too few of them. It shows in business [and] it shows on the academic side. Being the best in the observation class [a reference point/standard-setter], … it is not quite enough. (Professor, university/research institute)

However, the incorporation of the SME products into Nokia’s products has caused problems in some cases. These companies have not created their own brand, and do not always own the intellectual property rights, which could be marketed or utilized together with other companies. This may complicate the future growth possibilities of the companies in question, and make the expansion of their customer bases difficult. We will come back to this issue in the next subsection. The co-operation clause set by Tekes for large companies came up in many interviews. The requirement has made an impact, as the following example shows. The starting point with Tekes has been that university co-operation and networking is a must … The fact that Tekes says we must create networks and maintain links to universities begins to be reason enough for Nokia to generally do so … It’s pushing us to remember to do it, because when times are tough it is easy to curl up in oneself. (R&D manager, Nokia)

On the other hand, in more than half of the Nokia projects at which interviews were conducted, co-operation would have taken place regardless of the cooperation clause. In these, it has often been a case of organizations already familiar with each other. The organizations had completed a number of projects together and the same configuration carried on to new projects as well. 6.3.2

Diffusion of Know-how to Universities

Nokia’s co-operation with universities in Finland has mainly focused on the universities specializing in technology and the natural sciences. Most cooperation takes place, as is depicted in Figure 6.4, with the Universities of


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Technology in Helsinki and Tampere, and with the University of Oulu. In addition to these, Nokia co-operates with, for example, the University of Technology in Lappeenranta and with the Universities of Helsinki and Jyväskylä. Nokia also has extensive co-operation with VTT (Technical Research Centre of Finland). In many cases, the co-operation between the partners has a long tradition. It worked well in Oulu then and it still works quite well, [the co-operation] we had with universities, Nokia, and a few other local companies. This tradition of research co-operation with the university is very long. (R&D manager, Nokia) Mobira purchased much outsourcing from universities already at the beginning of the 1980s. It was quite open, and since they did not have the resources, they had much of the work done by universities. (Professor, university/research institute)

Through co-operation know-how has spread to various parties. The exchange of information has been mutual, that is, in many projects the know-how has diffused from universities to Nokia and vice versa. The same concerns the partner companies. The following quotes from interviews describe the diffusion of know-how: The accumulation of knowledge in our organization has been very strong. In this project, almost all of our people are those who are doing postgraduate studies and aiming at a doctoral dissertation. New theories have been developed and new results have been achieved in different areas, thus knowledge in our organization has increased considerably. (Professor, university/research institute) From Nokia’s perspective, they [at Nokia] passed on such knowledge, which they had not created themselves but where their work had explored alternative solutions. In this way their competence was complemented. (Professor, university/research institute) This [project] reinforced on its part our conception of the fact that this university group is especially productive, and we can obtain this type of competence there. That way we had faith, when we later participated in similar projects, that it is worthwhile to get this sort of project done here. (R&D manager, Nokia) For several years the level of research in companies has been the same as in universities. It [the company research], however, focuses on quite short-term issues and concrete matters. Universities have a longer scope. There have been attempts to get them to match. That is one motivation for us researchers ... (Professor, university/research institute)

The latest theoretical knowledge has been passed on to Nokia and other companies through universities. The business sector has been able to provide practical applications, where theoretical knowledge and basic research have


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been utilized in business. In general, it seems that co-operation between universities and Nokia has functioned relatively well. However, the spreading of know-how and competence is not always uninhibited. Especially in the case of applications close to commercialization, the transfer of knowledge is carefully controlled. Some interviewees expressed doubts concerning the spread of knowhow even more widely, as the following example shows: The requirement by Tekes, that there have to be [in large company projects] small businesses involved has caused the result that small slices have been outsourced to smaller companies or universities. The networking requirement has kept this option [Tekes’ financing] open. But how much competence is transferred, that is probably quite little. (Professor, university/research institute)

A central distribution channel for know-how is recruitment. The most common way is that students move from universities to companies, and competence is transferred with them. Many of the interviewed company representatives stated the ability to recruit competent people in the future as an important motive for university co-operation. There has also been some transfer of personnel in the other direction. The following quotes exemplify the significance of recruitment: In this project, there has also been the kind of knowledge transfer that people from this project have moved to be employed by the financing organizations. Similarly it has been that people from the financing organizations have come for postgraduate studies working for us. (Professor, university/research institute) The development of universities is very important from the point of view of the companies, and at least we saw it as very important to be able to direct their research so that it would serve us best. And that the resources there would develop so that we would be able to recruit people from the universities in the future … We have recruited one person from this project from there [the university]. (R&D manager in a Nokia partner company)

What came up in many interviews is that representatives of universities and research institutes felt that they did almost all the work related to the projects. Financing organizations often take part in executive meetings but not in the actual substance of most of the projects. Many interviewees brought up the issue that business partners could play a more active role. The next quote describes these wishes: We would really greatly welcome more active company partners … That is the opportunity of the Tekes projects. That a company, which assigns a person there, who has the right competence, skill, background, commitment, time and who would stay on there. Not only become familiar with the material and come to the meetings prepared and so on, but would maybe go and talk to the people there and work on a paper together and participate. This is extremely rare. (Professor, university/research institute)


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In addition to the co-operation with universities and research institutes in Finland, Nokia co-operates with many universities abroad. Table 6.1 presents the most important universities with whom Nokia co-operates. Table 6.1

Nokia’s most important partner universities by country, 2001

Finland Helsinki University of Technology Tampere University of Technology University of Oulu Denmark Technical University of Denmark Aalborg University Germany University of Dortmund Aachen University Sweden Linköping University Royal Institute of Technology Japan University of Tokyo Tokyo Institute of Technology UK Imperial College Source:

University of Strathclyde University of Surrey United States Massachusetts Institute of Technology University of California, Berkeley Texas A&M University Stanford University China Beijing University of Posts and Telecommunications Tsinghua University Thailand Asian Institute of Technology Hungary Budapest University of Technology and Economics

Häikiö (2001)

In addition to these, Nokia also co-operates with other universities. Cooperation at different levels takes place with over 100 universities. Nokia’s wide network of activity poses a challenge for a small country such as Finland. Particularly from the small country perspective it is important that Nokia maintain its R&D activities in its home country. This is a crucial challenge for many Finnish universities and suppliers as well. A prerequisite for continuing the co-operation is that universities and suppliers are able to stay at the very forefront of technological development. It presents us too with a tough challenge, that we need to choose the right areas and be the world leader in them. Because Nokia is so big, it can take the world’s best from wherever in the world. (Professor, university/research institute) Nokia is a large and international and demanding customer. It requires competence from its own contractors, it demands high competence from universities and research


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institutes, and it sets the standards high. That way the research projects borne by universities are such that we, and our kind of smaller companies, are able to utilize them. (R&D manager in a Nokia partner company)

When examined more broadly, both company and university co-operation is based on the fact that each party feels they benefit from it. The main benefits to universities come from dissertations, academic publications and the accumulation of know-how. The latest theoretical knowledge is passed on to companies through the universities, while the business sector has been able to offer practical applications in which theoretical knowledge and basic research have been utilized in business. The views of the interviewees regarding the utilization of the results of cooperation and especially the division of intellectual property rights (IPR) are split in two. Some did not find IPR problematic while some felt that the biggest challenges of all were related to IPR. The following quotations describe these views: Then when those departure or IPR issues come up, they have been settled in the executive board. They have not caused any big difficulties, rather the opposite. But it requires that the one who participates in the project understands the rules and how the game is played. (Professor, university/research institute) The company concluded that this project was not to be continued. And certainly if the company as the financing party decides not to continue it, it’s of course entitled to do so. But what was sad was that originally it was thought that if they do not commercialize the product, then the university is left with the right to develop it further. Then we could develop something new based on the previous work. In that case we would be able to develop something new on the basis of work already done. What happened was that this right wasn’t granted. The end result was that now certain researchers can’t continue to write their doctoral dissertations, because the work they’ve done is based on the findings of that particular project. Now that the company’s sitting on the findings and not releasing them, the researchers can’t continue working on their dissertations. (Professor, university/research institute) This crisis, which is here in this IPR matter, is extremely serious … It can eat away the basis from this whole thing. (R&D manager, Nokia)

The interview quotes indicate that, both in companies and in universities/ research institutes, IPR-related matters are receiving serious attention. Within this study there was no opportunity to focus more deeply on questions relating to intellectual property. The subject is therefore left for further study. 6.3.3

Finland’s Reputation as a High-tech Country

The share of research and development expenditure of GDP has grown strongly in Finland over the past few decades. Since the beginning of the 1990s,


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relatively more research and development was conducted in Finland than in the EU on average (Figure 6.5). In the latter half of the 1990s Finland overtook the United States in R&D intensity. At the end of the decade, the share of research and development exceeded 3 per cent of GDP, which equals the level of R&D in Japan. Of all the countries focused on in this study, Sweden has invested the most in research and development. 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 Source:

1993 1995 1997 1999 2000 2001e

⎫ Share ⎬ of Nokia ⎭

Finland

Sweden

USA

EU

Authors’ calculations.

Figure 6.5

R&D expenditures relative to GDP (%)

Finland’s high research and development intensity leans mostly on Nokia’s extensive R&D activity in Finland (Figure 6.5). If Nokia’s share were taken out of the figures, in 2001 Finland’s R&D spending would be about 2.3 per cent of GDP. Yet, even then Finland’s R&D intensity would be clearly above the average EU level. To summarize, we can conclude that more research and development takes place in Finland than in the EU countries on average, independent of whether Nokia is taken into account or not. Nokia’s R&D spending has increased strongly since the beginning of the 1990s. Although the company has increased its research and development abroad, R&D expenditures have also grown strongly in Finland. In 2001, the company’s R&D conducted in Finland accounted for approximately half of the total business sector R&D in Finland.

6.4

SUMMARY AND DISCUSSION

Our examinations suggest that Nokia plays a key role in the innovation system of the Finnish ICT cluster. In addition to Nokia’s own innovation activities, the company has an extensive co-operation network in Finland.


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The Significance of Tekes Funding

The share of Tekes funding of the total R&D expenditures of Nokia has varied over time. The MTI Technology Office funded an average of 7 per cent of Nokia’s R&D spending in the 1970s, 8 per cent in the 1980s and slightly below 3 per cent in the 1990s. In 2000 the respective figure was 0.3 per cent. However, it must be noted that by examining only the amounts of Tekes grants, it is not possible to form a complete picture of the significance of Tekes funding. We see that Tekes financing has had strategic and long-term influences. For example, the MTI Technology Office and Tekes financed the early development phases of Nokia’s digital call centre system. In the early years of Tekes, considerable amounts were invested in the development of GSM technology, software tools, and the protocol base at VTT. Another example relates to the deep recession in the 1990s. According to the book on Nokia’s history (Häikiö 2001), Tekes funding during the recession in the early 1990s especially supported the continuity of the operations at the Nokia Research Center. 6.4.2

Learning and the Quest for Innovation Play an Important Role

In addition to money flows such as public R&D funding and taxes, Nokia’s activities are reflected in the Finnish innovation system through education, diffusion of know-how, other companies’ R&D activities, and learning. Nokia has numerous links to organizations that influence the birth and utilization of innovations in both Finland and abroad. Its co-operation network includes other companies (producer-user relations and research co-operation) as well as research institutes and universities (research co-operation). In addition to the R&D co-operation in Finland, Nokia has numerous similar co-operation relationships with foreign companies and universities. Nokia was already involved in research co-operation with universities during the Nokia-Mobira times in the 1980s. Since then universities have conducted numerous co-operative projects concerning the development of mobile phones, networks and their software. Nokia’s success is at least partly a sign that the world’s top class technology has been developed in Finland. It seems that the co-operation between companies and universities/research institutes has functioned relatively well in Finland. The prerequisite for cooperation has been that both companies and universities have felt they benefit from the co-operation. Know-how and competence have been transferred between companies and universities, which has enabled learning for both parties. On the other hand, successful university co-operation and the current high level of competence do not provide guarantees for the future. Some interviewees brought up their concern for the current state of universities. According to them,


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funds are not directed to where they are needed. These views are evident in the following interview quotations: It would be a good message to truthfully bring out the kind of state our country’s now in and where we’re going, because this is a distressing situation. … And then the Ministry of Education states that there are no problems and universities decide themselves on the allocation of funds, as we all know, and we know the consequences of that. We have maybe five years in which to sustain and develop the competence that we have. But after that we won’t be much different from any other European state in this game. … So this is the current state of the Finnish innovation system. (Professor, university/research institute) What we are particularly concerned about is this deterioration of basic higher education. It is crucial that the [university] first and second courses are taught well. … And that is now partly deteriorating due to lack of funds and that is serious. (R&D manager, Nokia)

Nokia has had its influence on the fact that the number of university places in the ICT field has been increased significantly. The company has also played a role in educational planning at universities, and through that influenced the direction of education. By these means Nokia has been able to recruit highly qualified personnel, especially for tasks related to research and development. In addition to universities and research institutes, Nokia co-operates in research and development with other companies. The variety of partners is vast. The network includes component manufacturers, contract manufacturers, production automation manufacturers, software houses and even companies outside the ICT industry. As a result of the co-operation, know-how has flowed in both directions. Nokia has benefitted from partner companies by acquiring components of the latest technology, intermediate products, and software modules for its own end products. This has benefitted Nokia’s R&D activity and production, as well as enabled Nokia to focus on its own core areas. Also the innovation activities of Nokia’s partners have reaped benefits from the existence of Nokia. Nokia has offered applications for various companies’ products. Furthermore, Nokia has served as an international marketing channel for companies. In particular, small firms’ resources would not have sufficed for international operations had Nokia not worked at least partly as a marketing and distribution channel. Thus the products of many smaller companies are incorporated into Nokia’s products. Co-operation with both universities and companies has brought advantages, but problems have not always been avoidable. One issue that raises discussion concerns the utilization and ownership of the results of co-operation. These intellectual property rights (IPR) determine which party has the rights fully to utilize the results in its business. However, the IPR issue could not be thoroughly explored within the framework of this study.


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Success through Interaction

Generally speaking, public R&D funding aims at reaching a high pay-back ratio for the government or social utility for the entire national economy. Nokia has received public R&D funding in the early phases of some risky projects. A number of these projects have later proved to be very profitable. Herewith we estimate the pay-back ratio by formulating a simple mode of monetary flows between Nokia and the Finnish government (Figure 6.6). The figure presents the estimated monetary value of the payments between the Finnish public sector and Nokia during the period 1995–2000 (at 2000 prices). The public sector has offered a common infrastructure and educated personnel that Nokia has utilized. The company-specific monetary support has also been taken into account. On the other hand, Nokia has been a noticeable taxpaying institution and the company has supplied some grants to the Finnish, mostly publicly financed, universities, too. Public sector

Nokia

Universities Source: Authors’ calculations. Source of Statistics: ETLA, Ministry of Education, Nokia, Statistics Finland

Figure 6.6 Monetary value flows between Nokia and the public sector in Finland 1995–2000 (at 2000 prices) R&D grants from Tekes to Nokia totalled slightly below 80 million euros over the years 1995–2000. Over the same time period, Nokia paid corporate taxes of 2.9 billion euros. In addition, Nokia invested in the academic world by financing research and development projects as well as by donating equipment and software to universities. We estimate the total value of these investments


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to be about 18 million euros.2 Nokia’s employees have paid income taxes worth 1.4 billion euros over the years 1995–2000, and taxes on management options worth 1.2 billion euros. Over the same time period, Nokia has paid just below 1.2 billion euros in social security payments for its employees. Altogether, the income taxes, taxes on management options, and social security payments for the employees exceeded 3.8 billion euros over the years 1995–2000. Nokia has, as have all other companies, benefitted from free public services such as higher education. In addition, the companies’ personnel use and utilize free services, transfer payments and infrastructure built by the public sector. The division of these costs, and their calculation for a specific company is of considerable difficulty. Therefore the following calculations should be viewed as exemplifying. We calculate the replacement value of the education of Nokia’s Finnish workforce as the product of the costs of different qualifications and the number of Nokia Finnish personnel with the respective education.3 Calculated this way, the value of the education is 600 million euros. This depicts the amount of money that was required in 2000 to produce the respective level of qualifications. The value of public services and infrastructure directed to the employees of any company of Nokia’s size would be about 1.6 billion euros.4 Both this and the method used to calculate the accounting value of education should be considered as examples, as other methods exist as well. Overall, then, public sector initial R&D investments in the 1980s turned out to be a success for Nokia’s product development. Nokia has, however, paid back multiple times more in tax-type obligations to the public sector than it has received from the government in terms of direct monetary support or general infrastructural government spending. According to our simplified calculations, Nokia has benefitted directly in the amount of 2.3 billion euros during the years 1995–2000. In the same period, the Finnish public sector directly received 6.7 billion euros from the Nokia corporation. To summarize, we can say that the public sector has been involved in the financing of many of the basic technologies important to Nokia. Furthermore, Nokia’s own R&D and marketing investments have grown rapidly. At the same time, Nokia’s co-operation with other companies, universities and research institutes has made it possible for Nokia to focus on its own core competencies. It is probable that without the interaction of these parties Nokia’s know-how would not have realized the current level of returns. 6.4.4

Future

As a result of Nokia’s rapid growth, its position in the Finnish innovation system in the ICT cluster has been highlighted. The latest knowledge in the


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field has also accumulated in other Finnish companies, universities, and research institutes. However, Nokia’s co-operation with other Finnish partners depends on their ability to stay ahead of development in the future also. The Finnish universities compete for the top positions with universities in the rest of the world. Currently Nokia co-operates with over 100 universities around the world, and it can choose its partners. Nokia’s own R&D activity will become more and more global in the future. It is likely that the company’s research and development activities will grow faster abroad than in Finland.

NOTES * This article is strongly based on Ali-Yrkkö & Hermans (2002) 1. There were 42 interviews conducted, of which 19 were with employees of Nokia, 13 with representatives of research institutes or universities, and ten with people employed by companies co-operating with Nokia in R&D. All of the interviewees at Nokia were involved in R&D activities. The interviewees from the universities, research institutes and Nokia’s partner companies had been part of R&D projects with Nokia. The interviews were conducted in December 2001 and January–March 2002. To protect the anonymity of the interviewees, their identities are not published. However, the interviewees being quoted directly are divided into three groups : – R&D manager, Nokia; – R&D manager in a Nokia partner company; – Professor, university/research institute. 2. The estimate is based on the research financing paid by Nokia to Tekes’ ETX and TLX programmes (total of over 50 million FIM [over 8.4 million EUR] over the period 1997–2000). An estimate of research financing in the years 1995 and 1996 is added to this figure, plus an estimate of the value of equipment and software donated by Nokia. 3. The educational distribution of Nokia’s Finnish workforce is estimated as follows: university degree 36 per cent, polytechnic university degree 30 per cent, degree from institute of further education (such as commercial and technical colleges) or vocational school 30 per cent, rest 4 per cent. The costs of education are from figures in the Ministry of Education’s KOTA and AMKOTA databases on the number of graduates in 1995–2000 and the costs of budget-financed activity in 2000. The calculation includes only qualifications higher than basic education, thus costs of basic education are not included. 4. The value of public spending utilized by Nokia’s personnel (GNokia) is directed to Nokia’s employees so that public consumption and investment expenditures as well as transfer payments without pension and employment expenditures (GTotal) over the years 1995–2000 are divided by the number of work-aged people (LWorkAge), which has then been multiplied by the number of Nokia employees in Finland (LNokiaFin). In other words:

G Nokia =

GTotal LWorkAge

⋅ L NokiaFin


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REFERENCES Ali-Yrkkö, Jyrki (2001). Nokia’s Network – Gaining Competitiveness from Cooperation, ETLA B 174, Helsinki: Taloustieto Oy. Ali-Yrkkö, Jyrki & Raine Hermans (2002), Nokia in the Finnish Innovation System, ETLA Discussion paper No. 811. Ali-Yrkkö, Jyrki, Laura Paija, Catherine Reilly and Pekka Ylä-Anttila (1999), Nokia – A Big Company in a Small Country, ETLA B 162, Helsinki: Taloustieto Oy. Häikiö, Martti (1998), (in Finnish) Alkuräjähdys. Radiolinja ja Suomen matkapuhelintoiminta 1988–1998, Helsinki: Edita. Häikiö, Martti (2001), (in Finnish) Nokia Oyj:n historia, Helsinki: Edita. Paija, Laura (ed.) (2001), Finnish ICT Cluster in the Digital Economy, Helsinki: Taloustieto.


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7. The flexible production model in Finnish companies: Trends in production management, work organization and employment relations Tuomo Alasoini 7.1

INTRODUCTION

This chapter examines the introduction and dissemination of the new flexible production model in Finland, from the perspective of companies and the national innovation system. It uses a conceptual framework developed by Bélanger et al. (2002), in which ongoing structural change in business is examined in terms of a transition from a Fordist production model to a new production model through three interrelated dimensions: production management, work organization and employment relations. The concept ‘production model’ is used here as a theoretical abstraction, which may include a wide range of country- and sector-specific variations. In highlighting the special features of trends in Finland, the chapter also examines them in a wider comparative perspective.

7.2

FROM A FORDIST MODEL TO A NEW MODEL – HOW TO CONCEPTUALIZE, MEASURE AND ASSESS CHANGE?

The post-war era up to the early 1970s could be described as the golden age of the Fordist production model. The year 1973 marks the end of this golden age, being the year when the oil crisis put an end to the period of rapid economic growth and accelerating productivity that the advanced industrial countries had enjoyed since the war. The social legitimacy of the Fordist model was based on beneficial interaction between mass production and mass consumption. A powerful accumulation of capital made it possible to modernize the production process, thus generating 128


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The flexible production model in Finnish companies

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a rapid rise in productivity that was acceptable to employees. As a consequence, employees began to focus on the struggle for purchasing power (tending not to strive to influence matters related to management, production or work organization). This boosted demand for consumer goods and further increased the production of capital goods, which enabled companies to maintain their profitability; this in turn caused a further powerful accumulation of capital, and so on. The government contributed significantly to maintaining this ‘virtuous circle’. Government grants and services promoted the renewal of production processes, while income transfers supported the emergence of a consumption norm that guaranteed continuing purchasing power for employees. The breakdown of the self-perpetuating ‘virtuous circle’ of mass production and mass consumption has been explained by changes in the competitive environment, technological and organizational innovations, and growing discontent among employees (Bélanger et al. 2002, pp. 28–30; Elam 1990). As a consequence, companies have actively striven to dissociate themselves from the principles of the Fordist model. In production management, this has meant greater flexibility in production, the standardization of processes, and the dismantling of vertical integration and the conversion of value chains into networks consisting of several companies. The main forces for change have been the increasingly individual demands of clients, the emergence of new management approaches, and the rapid advances in information and communications technology (ICT). In the area of work organization, companies have tried to move towards flatter and leaner structures, to dismantle the detailed division of labour and to deploy the skills of the workforce more effectively through measures such as self-management, multi-skilling, team and project work, job rotation, and job enlargement. Where employment relations are concerned, companies have been pursuing more flexible terms of employment and stronger employee commitment. Companies have been searching for greater leeway in issues such as wages, working hours, job security and job assignments, either by attempting to influence the content of collective agreements or by striving to influence individual employment contracts in ways that bypass the trade unions. The typical means used by companies in striving to boost employee commitment include various forms of direct participation, and pay systems tied to output and quality. How consistently and comprehensively companies have tried to dissociate themselves from the Fordist model, what forms their strategies for change have taken, and what benefits they have obtained in this way vary greatly from one company to the next. Strategies for change involve a variety of tensions and actual conflicts, both within each of the three dimensions discussed and between them. Tensions and conflicts also emerge because the Fordist model has been tied to the institutional structures of society by a variety of means, including the education, funding and labour market systems (Bélanger et al. 2002, pp. 56–68).


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Employment relations, specifically, are an area where a company’s scope for operation is greatly dependent on the extent of and forms taken by government and labour market organization regulation. There are no generally accepted ways of measuring how far companies or countries have moved towards the new production model. Furthermore, definitions and measurement methods on issues such as production networking or new forms of work organization may vary a great deal from one study to another. In any case, individual measures are problematic if only because the various dimensions of a production model make up a complex system of interdependent units. In this chapter, we are prisoners of the existing empirical material. There is no reliable material available on the extent to which many of the characteristics of the new model have been introduced in Finland. Even in cases in which such data are available, there is often limited potential for comparisons both over periods of time and with other countries. There is even less material on the effects of the new model on the companies involved. For all these reasons, we should exercise caution in drawing conclusions about the introduction and spread of the flexible production model in Finland. On the basis of the framework of Bélanger et al. (2002) and the limitations outlined above, this chapter begins with an overview of changes in production management, viewed in terms of network co-operation between companies. The development of work organizations will be examined through teamwork and employee potential for influence and development. Changes in employment relations are examined in terms of changes in bargaining and participation systems. Finally, the adoption and spread of the new model in Finland is assessed from the perspective of the national innovation system.

7.3

PRODUCTION MANAGEMENT – NETWORK CO-OPERATION BETWEEN COMPANIES

The globalization of competition, accelerating cycles of innovation and rapid advances in ICT are driving companies to focus on their core competencies. This, in turn, is leading to a growing need for them to pool their economic resources and expertise. Production co-operation between companies and growing co-operation in research and development concerning both products and production are some of the key changes in the transition from a Fordist model to the new flexible production model. It is, however, difficult to quantify these forms of co-operation as they are so different. Production co-operation between companies can exist on many levels (McHugh et al. 1995). On the lowest level (1), two companies combine forces on a one-off basis to create a product or product range. In this case, their co-


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operation only extends to certain operative functions and is aimed at financial gain in the short term. Co-operation can also be more long-term (2) in the sense that a company might take another company’s wishes, expectations or demands into account in developing its own operations. This co-operation is based on a longer-term agreement that assigns duties to the two parties involved in the development of their own operations, with the ultimate aim of bringing down total costs. More advanced co-operation (3) is achieved when companies are linked together directly through each other’s logistical or product planning, and even product development. Even more advanced co-operation (4) is involved when the companies’ strategic planning is also linked. It is then justified to say that the companies involved are functioning as a business network. Close, long-term co-operation also involves potential problems, such as the danger of ‘lock-ins’, which may make it more difficult even to look for alternatives, and also make it harder for the companies to adapt to rapid changes in their environment (Schienstock 1999). An uneven power balance between the companies may also create dependency between them, and thus produce a disincentive to more open co-operation. For this reason, some experts have in fact issued gloomy forecasts for low-tech SMEs, in particular, as the new production model spreads (Harrison 1994; Semlinger 1992). A company’s interest in seeking competitive advantage by getting involved in production co-operation is influenced by several factors. Primarily, they relate to the pace of change in its environment and how capital-intensive its operations are. The faster and more unpredictable the changes in the environment are, the bigger the potential benefits of co-operation. In such a situation, companies are more reluctant to make investments that will enable them to cover a large part of the overall value chain. It is more attractive to tap into expertise and resources which other companies already possess while concentrating on your own core competence, instead of having to acquire new types of expertise by recruiting more labour or tying up more capital in production technology. An industrial company in a rapidly developing business sector – like Nokia, for instance – can transfer the actual manufacturing process entirely to a specialist contract manufacturer, while itself focusing on product development, marketing and brand management (Ali-Yrkkö et al. 2000). The second important factor in a company’s willingness to network is how capitalintensive its operations are. A company’s interest in networking diminishes with greater capital intensity, because the significance of a high capacity utilization rate as a competitive factor grows. Until the 1980s, the metal and engineering industry took the lead in trying out new production management methods in Finland. In recent years, however, this leading position has clearly been taken over by the electronics industry – or, in a wider sense, the entire ICT cluster – in the wake of Nokia. The exceptional advances made by the ICT cluster compared with other sectors is


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clearly evidenced in its productivity figures: in the 1990s, when labour productivity grew at an average rate of 3 per cent per year in Finland, and 7 per cent per year in Finnish industry, the corresponding figure for the electrical and electronics industry was 15 per cent and, within it, as much as 25 per cent among manufacturers of telecommunications equipment (Ali-Yrkkö et al. 2000; McGuckin and van Ark 2002). The growth figures for productivity in the country as a whole, which are good as such, actually conceal the fact that in many sectors the 1990s were a time of surprisingly slow progress. This indicates problems with the introduction of new technologies and a dearth of innovations in management and work organization. Consequently, in light of productivity figures, the dynamic advances of the ICT cluster remained a unique phenomenon in Finland in the 1990s. A survey by the Confederation of Finnish Industry and Employers (2001), covering 363 companies, is one of the few studies permitting more detailed assessment of the extent of production co-operation between companies, and trends in this area in Finland. Although the sampling is relatively small, the industrial companies represented account for almost 40 per cent of the total industrial workforce and 60 per cent of turnover. The study confirms that cooperation is most widespread in the electrical and electronics industries. Some 88 per cent of all the principal suppliers in the metal and engineering sector and electrical and electronics sector said they were involved in production cooperation, compared with an average of only 71 per cent for industry in general. The lowest incidence of co-operation was found in capital-intensive sectors such as the wood-processing and chemicals industries, where the percentages were 54 and 46, respectively. The data were based on companies’ own information on whether they were involved in co-operation in the manufacture of end products or not. The study also focused on the depth of co-operation and how it had developed. It showed that partnership, that is, co-operation between companies on a longer-term basis than an annual agreement, became far more common in Finland in the 1990s. In 2000, partnership was estimated to account for 38 per cent of all co-operation agreements between companies, compared with only 18 per cent in 1993 (Table 7.1). According to the survey, principal suppliers, systems suppliers and parts suppliers are all interested in expanding co-operation still further. The study showed that companies involved in co-operation had grown faster than other companies from 1998 to 2000, and they also tended to assess their prospects for growth with greater confidence. There were, however, no differences in profitability. The study tentatively suggested that either the companies involved in co-operation focused on boosting their market share or company size, or the benefits of networking might take time to have an effect.


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Table 7.1 Different types of corporate co-operation agreements in Finnish industry (%) Type

1993

1996

2000

Partnership (strategic) Annual agreement Project-based agreement One-time agreement Total

18 47 21 14 100

24 44 20 12 100

38 33 16 12 100

Source:

Confederation of Finnish Industry and Employers (2001, p. 24)

Production co-operation is a new phenomenon in Finland. Its spread is connected with the increased awareness of process management in the early 1990s. This, combined with ever higher demand for tailored customer solutions and shorter delivery times, and the new opportunities created by ICT advances, shifted the focus of corporate production management development from technological and organizational solutions involving the companies’ own production to efforts to streamline the entire order-to-delivery chain (Jahnukainen and Vepsäläinen 1998). In terms of the organization of work and production, this brought about three important changes: (1) The core companies in the value chains concentrated more on their own core competence, which meant that they needed more permanent forms of co-operation, across corporate boundaries, with the companies dealing with outsourced operations and other strategic stages of the value chain. (2) Companies needed forms of work that demanded more intensive co-operation and crossed traditional boundaries between functions, leading to obscuring the boundaries between traditional occupations and personnel groups. (3) In order to boost flexibility and ensure rapid response capacity, new forms of teamwork were needed, giving production workers more power and responsibility for decisions on a day-today basis. The Confederation of Finnish Industry and Employers survey provides some information on the first of these three changes, while the other two will be examined in what follows. The study also indicates that companies in Finland have a very positive attitude toward intensified production co-operation. In such a small country, however, one common practical problem is the difficulty of finding suitable co-operation partners. For example, the number of dynamic medium-sized companies in Finland is small. This means that the number of Finnish SMEs which are potential systems suppliers, or could rapidly become systems suppliers, is very limited; functioning as a systems supplier and being willing to grow in partnership with a major international corporation means that an


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SME must be sufficiently large and, above all, willing to take even considerable risks and able to constantly develop its operations (Lamming 1993). In the Finnish electronics industry, for instance, it is estimated that the total number of first-tier suppliers available over the next few years will only be some 40 (Paija and Ylä-Anttila 1998, p. 110). At best, a solid partnership with a major international corporation offers a systems supplier the opportunity for a valuable learning process. The systems supplier can then pass on what it learns to its own parts suppliers. Systems suppliers can play a strategically important role in conveying information to a wide circle of other companies, concerning anything from product and process technology to management and work organization (Hines 1994). The lack of systems supplier resources may thus be a very serious weakness affecting the entire national innovation system. The Confederation of Finnish Industry and Employers survey showed, perhaps somewhat surprisingly, that systems suppliers in particular, but also parts suppliers, had a more positive view of the advantages of production cooperation than principal suppliers. Far-reaching conclusions on the long-term effects of co-operation should, however, be approached with caution, as the period covered by the survey was a time of rapid growth in Finnish industry. This created unusually favourable conditions for ‘win-win’ co-operation between companies. Even the early 2000s and the economic slowdown it brought demonstrate that a big globally operating company such as Nokia has weathered the recession much better than many of its main Finnish suppliers.

7.4

WORK ORGANIZATION – TEAMWORK AND EMPLOYEES’ OPPORTUNITIES FOR INFLUENCE AND DEVELOPMENT

The spread of teamwork and a general devolution of responsibility are the main features of the flexible production model in terms of work organization. As implied before, the spread of teamwork and network co-operation were part of the same process of change in Finnish business that was linked with the breakthrough of process management. Problems involved in examining the spread of teamwork include the fact that there is no single, generally accepted definition, and that methods for collecting information vary from one study to the next. Even if it were possible to create a generally accepted definition of teamwork, it could still take a number of forms, including differences in the composition of teams, their internal division of labour, leadership, decision-making power and so on. These differences may derive from widely divergent management ideologies or knowledge bases (EPOC Research Group 1997). In Finnish studies, data on


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teamwork are based simply on subjective evaluation by the respondents themselves. These studies also make no distinctions between different forms of teamwork. The annual Working Life Barometer of the Finnish Ministry of Labour has been monitoring how common it is to work in groups (teams, cells, project groups). The barometer is drawn up annually, based on computer-aided telephone interviews with about 1000 wage-earners. The data are representative of all Finnish wage-earners. In 2001, 76 per cent of respondents said employees worked in groups either ‘mainly’ or ‘partially’ in their workplace. The percentage of ‘mainly’ answers had gone up from 34 to 44 per cent in industry and from 22 to 30 per cent in the private service sector between 1995 and 2001 (Ylöstalo 2002, pp. 68–9). Other studies are comparable to the Barometer in terms of the spread of teamwork. Statistics Finland’s 1997 Quality of Work Life Survey supports the findings of the Barometer, showing that teamwork is used in a clear majority of Finnish workplaces. In the Survey, which is based on face-to-face interviews with 2979 wage-earners, 74 per cent of respondents said teamwork was used at their workplace (Lehto and Sutela 1999, pp. 18–19). A postal questionnaire on information work, carried out as part of a study by the University of Tampere in 2000, with 1775 respondents, gives 81 per cent as the corresponding figure (Blom et al. 2001, p. 177). The Ministry of Labour’s Flexible Enterprise study of 1996 differs from the above-mentioned studies in that the respondents in the combined postal questionnaire and telephone interview were management representatives, and it only targeted enterprises. The research material consisted of 1384 privatesector workplaces with at least 10 employees. In this study, 16 per cent of the workplaces had introduced teams, cells, job rotation or quality circles ‘extensively’ and 33 per cent ‘quite a lot’. Workplaces using teamwork accounted for 53 per cent (Antila and Ylöstalo 1999, pp. 59 and 87). The difference from the other studies mentioned above may be a result of the different respondent group, differences in how the questions were worded, or the fact that the sample in this study focused more on small workplaces, where teamwork is rarer. According to the University of Tampere study on information work, the telecommunications sector had the biggest number of respondents (61 per cent) who felt that teamwork had become more common between 1998 and 2000. The lowest number was in the transportation sector (36 per cent). Industry (54 per cent) came close to the average for Finland as a whole (53 per cent). During this time, the telecommunications sector had also introduced more performancebased supplements or wages than other sectors, jobs had been outsourced more and supervisory posts had been cut (Blom et al. 2001, p. 118). The study on information work had included building, mining and energy supply under ‘industry’. This is problematic in terms of examining the spread


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of the flexible production model, because such a widely defined industrial sector includes businesses that are widely different in their dynamic of change. A study by the Helsinki University of Technology in 2000, which charted quality perceptions in five sectors (the textile, furniture, metal and engineering and electronics, building, and hospitality and leisure-time industries) based on 1060 respondents (management, white-collar and blue-collar) showed that the use of quality tools varied considerably between sectors. The metal and engineering and electronics industry came first in terms of all the seven practices included in the study. These were teamwork, continuous improvement, balanced scorecard, statistical quality-control methods, problem-solving methods, qualityaward criteria and the ISO 9000 standard (Tuominen et al. 2000). The findings thus strongly indicate that the ICT cluster is also leading the way in Finland in work organization development and that, in the industrial sector, the metal and engineering and electronics industry is ahead of other branches. If the results of the Quality of Work Life Survey and the 2001 Working Life Barometer are combined, we can draw up a time series of changes in employee perception of their opportunities to influence their own work (Table 7.2). The general trend is for a growth in opportunities, especially in relation to the content of tasks. The biggest exception, meanwhile, is the pace of work, where opportunities for influence were still growing in the 1980s, but have since fallen appreciably. The material available does not allow for more detailed research on whether the changes are connected with the increasing prevalence of teamwork, or with the general tendency for work organizations to become flatter, leaner and more customer-oriented. Table 7.2 Opportunities for influencing one’s own work in Finland (%) (proportion of those who can influence ‘a lot’ or ‘quite a lot’) Aspect Order in which tasks are done Working methods Content of tasks Pace of work Division of tasks between employees Choice of working partner Equipment purchases Source:

1984

1990

1997

2001

68 58 25 59 25 12 20

67 63 37 64 29 18 21

69 65 40 57 31 19 23

n/a n/a 42 48 30 n/a n/a

Combined from Lehto and Sutela (1999, p. 25) and Ylöstalo (2002, p. 126)

Though the findings concerning employee perception of their opportunities to influence their own work are to some extent contradictory, employees still


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felt that their opportunities for self-development at work had consistently improved over the past few years. The percentage of respondents in the Quality of Work Life Survey who felt their potential for development was good went up from 28 per cent in 1984 to 32 per cent in 1990 and 37 per cent in 1997 (Lehto and Sutela 1999, pp. 20–1). The Flexible Enterprise study mentioned above was part of the Nordflex project, which provided a means of comparing work organization changes in Denmark, Finland, Norway and Sweden. The research on individual countries is not fully comparable in all aspects, but it does make it possible to compare the spread of teamwork and job rotation, and employee opportunities to influence their work in the different countries. The figures in Table 7.3 are based on responses from workplace management. The material was collected in the four countries involved between 1995 and 1997. Table 7.3 Delegation of responsibility, teamwork and job rotation in the Nordic countries (%) (proportion of workplaces with 50 employees or more which responded positively) Aspect

Denmark Finland Norway Sweden

Daily planning of their own work by individual employees Weekly planning of their own work by individual employees Employees working in teams More than 50% of employees working in teams Employees with formal job rotation More than 50% of employees with formal job rotation

62

40

20

57/88*

35 75

18 74

10 69

24/71* 91

10 50

30 81

na 40

58 65

6

20

na

24

* The first figure refers to direct production tasks and the second to other activities. Source:

NUTEK (1999), figures collected from different tables.

According to Table 7.3, Sweden is ahead of the other Nordic countries in terms of teamwork and decentralized decision-making, while Norway is lagging behind. Formal job rotation is very widespread in Finland compared with the other Nordic countries. Teamwork appears to be more widespread in Finland than in Denmark and Norway, but decision-making has not been delegated to employees to the same extent as it has in Denmark, not to mention Sweden. A more detailed comparison with Sweden shows that out of 11 aspects of work, Finnish employees had more responsibility only in the case of two: quality control and follow-up of results (NUTEK 1999, Appendix 3).


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It seems that teamwork is less likely to include delegation of responsibility in Finland than in Sweden and Denmark. The data also strongly indicate that organizational changes have been implemented in a less participatory way in Finland. Finnish managers are less likely than their Danish and especially Swedish colleagues to believe that the attitudes of employees and trade unions have had a positive effect on the implementation of organizational change. For instance, a majority (69 per cent) of Swedish executives believe that the trade unions have exercised a positive effect, while only 3 per cent of their Finnish counterparts share this opinion; 75 per cent feel it makes no difference. Comparison also shows that staff in non-executive positions took an active part in restructuring more often in Sweden than in Finland (NUTEK 1999, pp. 108–12). In conclusion, it appears that Finnish companies actively strove to improve the flexibility of their work organization in the 1990s, but that this was motivated to a striking degree by the employers. The improved flexibility involved extensive employee participation or delegation of responsibility to a lesser degree than in Sweden. There may be a number of explanations for this. It is possible that the consent of employees was ‘bought’ in the traditional Fordist manner through pay increases; trade unions in Finland have always taken a strong stand on distributive issues and the exertion of influence directly through the political machinery, and have tended to approve of technological and, to a great extent, organizational changes in the workplace as ‘necessary’ for the modernization of production processes (Koistinen and Lilja 1988; Lilja 1998). The agreement of employees may also have been secured by companies offering their employees good opportunities for improving their skills; in Finland, the percentage of workplaces that had skills development plans was higher than in Sweden and Denmark (NUTEK 1999, pp. 65–6). It could also be that there is generally a stronger belief in experts, authorities and hierarchies in Finland than in the other Nordic countries, which have a stronger tradition of participatory democracy in the workplace. Furthermore, it is possible that Finland’s dismal economic situation and record unemployment gave corporate executives more of a free hand to reorganize in the 1990s, while the situation in the other Nordic countries was different. In Finland at this time, companies’ efforts to boost their competitiveness by overhauling production processes and work organization also had an exceptional degree of social legitimacy.

7.5

EMPLOYMENT RELATIONS – CHANGES IN BARGAINING AND PARTICIPATION SYSTEMS

As stated above, companies making the transition from Fordist to flexible production have worked to achieve more room for manoeuvre in their terms of employment either within collective agreements or by influencing the content


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of individual employment contracts in ways which bypass the trade unions. In Finland, companies have largely followed the former strategy. From 1968 onwards, collective agreements in Finland have been generally based on a centralized incomes policy. In this system the central employers’ organizations and trade union confederations in both the private and the public sector try to find common ground on which to reach sectoral collective agreements. If they manage to reach a central skeleton agreement, sectoral collective agreements are signed in accordance with it. The central agreement is not legally binding, however, and individual unions can diverge from it. When necessary, the government has offered economic, educational and social policy reforms to encourage the parties to reach agreement. Between 1968 and 2002, there was failure only seven times (in 1973, 1980, 1983, 1988, 1993, 1995 and 1999) in reaching a one- or two-year central agreement. In terms of the relative weight of different bargaining levels (intersectoral, sectoral, company), the Finnish system is one of the most centralized in the EU. The main reasons why this centralized system has survived in Finland for more than 30 years are the high union density (about 80 per cent), the positive effects of incomes policy on economic development and welfare, and last but not least, an ideology of national consensus deeply rooted in Finnish society. However, none of these factors can be taken for granted in the future. Trade union membership among young people under 25 has, for instance, fallen sharply in recent years and in many growth industries in the private service sector, union density is well below average (Blom et al. 2001, pp. 120–1; Ylöstalo 2002, pp. 183–4). Though the intersectoral and sectoral level are still the most important levels of collective bargaining in Finland, we can talk of a trend towards ‘centralized decentralization’ (Lilja 1998), the main characteristic of which is that local (plant- or enterprise-level) bargaining gains importance within an institutional framework regulated by the sectoral collective agreements. An important milestone was passed in 1993, when efforts to sign a central agreement failed in the middle of deep economic recession and the subsequent union-level round of negotiations led to sectoral collective agreements, many of which greatly broadened opportunities for local bargaining. Local bargaining has gained ground in Finland mainly on the initiative of the employers, as a response to market demands for greater productivity, quality, customization and flexibility. A survey by the University of Turku, including data on 918 Finnish workplaces, shows that the percentage of companies with five employees or more which had signed local agreements with employees on at least some issues increased from 61 per cent in 1992 to 91 per cent in 1998 (Uhmavaara et. al. 2000, pp. 27–9). This number also contains local agreements through the co-determination procedure, and local agreements on changes in terms of employment with some groups of


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employees or even individual employees. The main hindrance to further expansion in the scale of local bargaining is no longer the legislation, the provisions of intersectoral or sectoral agreements, or other structural or institutional factors, but low-trust industrial relations and an undeveloped ‘bargaining culture’ at the enterprise or plant level. The most common issues on the local bargaining agenda have been working hours and pay. The spread of local bargaining has contributed to the accelerated pace of technological and organizational change by making it easier to agree on changes in pay, working hours, job content, and so on in enterprises. At the company level, there is a strong positive association between the scale of local bargaining and new work organization practices (Uhmavaara et al. 2000, pp. 128–45). It is no coincidence that the metal sector, which was a forerunner in the introduction of new work organization practices in Finland, has played the same role in widening the scope for local-level agreements, too (electronics manufacturers such as Nokia are covered by the same collective agreement). The key agents in local bargaining are company or plant managers and chief shop stewards. The shop steward system was officially established in the 1940s under general agreements drawn up by the central labour market organizations. The formal authority of shop stewards was strengthened in the 1960s and 1970s as more employees joined trade unions and new general agreements were signed between the social partners. Compared with many other European countries, shop stewards and the comparable staff representatives in Finland have a strong position that is also guaranteed by labour legislation, while bodies such as works councils have never gained a significant foothold. According to the survey by the University of Turku, shop stewards are in most cases the key bargaining agents acting for employees, but in one-fifth of all cases local agreements were signed by work groups, teams, employee groups or the whole staff and in another fifth by individual employees (Uhmavaara et al. 2000, pp. 35–6). Employers see the effects of local bargaining more positively than representatives of the personnel, and 78 per cent of employers are ready to further broaden its scope. The majority of employee representatives, on the other hand, are satisfied with the current opportunities for local bargaining (Uhmavaara et al. 2000, pp. 48–51). The difference is probably due to the fact that employers have played a more active role in putting issues onto the bargaining agenda. Many employee representatives feel that they do not have an equal standing with the employers’ representatives, because they lack relevant information on the conditions of the company or know less about legislative and contractual details. Lilja (1998, pp. 182–4) uses the concept ‘competence trap’ to mean a situation in which the unions’ internal organization and the specialized experience of their officials are not well suited to handling issues related to work organization, skills or management, and the unions therefore often have little chance to support chief shop stewards when these issues are negotiated in enterprises.


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The ‘centralized decentralization’ of the Finnish bargaining system has boosted companies’ potential for renewing their production management and work organization. In this area, too, the pioneer was the metal and engineering and electronics industry. The position of trade unions and shop stewards has remained strong, at least formally, in bargaining on traditional distributive issues such as wages or working hours in connection with change. In future, this will require continued high union density and also more expertise among trade unions and shop stewards concerning issues involving work organization, vocational skills and management. Meanwhile, the increased prevalence of teamwork and various development or project groups offer employees new channels for exerting influence over their own employment terms. Whether this will happen at the expense of the traditional bargaining system and representational participation systems, or in a way that supplements these systems, will depend largely on the trade unions’ ability to deal with matters outside traditional distributive issues.

7.6

THE NEW PRODUCTION MODEL AND THE NATIONAL INNOVATION SYSTEM

According to Lundvall and Tomlinson (2002), human resource development and the organization of learning processes in companies and networks has so far been a somewhat neglected area in studies of national innovation systems. This section offers some observations on the introduction and spread of the new production model in Finland, specifically from the point of view of the national innovation system. Although economic trends in Finland in the last few years are often described as a ‘success story’, a look at the three dimensions of the new production model also reveals some factors that pose a threat to continuing success. From the point of view of production management, there are three such factors in particular: (1) The growth in productivity has been very uneven between different sectors. Growth has been rapid in the ICT cluster, but in many other sectors such as service production, specifically, growth has been surprisingly slow. It will become increasingly important to secure good productivity growth in other sectors, too, if we are to keep the Finnish success story going, because the labour supply will begin to fall rapidly as the population ages. This change will be particularly drastic in Finland. A rapid growth in productivity will be needed to compensate for problems arising from labour shortages, which may slow economic growth. (2) The number of dynamic medium-sized companies in Finland is small. This means that there is a risk that only few companies might attain the position of systems supplier. Such companies are, however,


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much needed in networked production as an information link between major international corporations and small parts supplier companies. (3) Production co-operation between companies has expanded in Finland in recent years, boosted by economic growth. Only time will tell how deeply rooted the partnership approach has become in these companies, and what will happen in an economic slowdown. Will the companies stick together through hard times, too, or will they then revert to traditional short-term agreements between companies, designed mainly to achieve immediate cost-benefits? Finnish companies have introduced teamwork extensively and provided staff training in connection with the introduction of new forms of work organization. There are data available on the extent to which teamwork is used, but information on how the new forms of work organization have furthered employee opportunities for learning and development at work is harder to come by. Nevertheless, it is the latter issue that is essential for the national innovation system, as demonstrated by Lundvall and Tomlinson (2002). The results of the Nordflex project (NUTEK 1999) show that the role of employees in the introduction of changes was more modest in Finland, and that delegation, too, has not been carried out in Finland on the same scale as in, say, Sweden. This could be due to a number of factors, as outlined earlier in this chapter. However, delegation of responsibility for planning and development to autonomous teams can, at its best, be a powerful force that promotes learning and innovation in a company. In an insecure, rapidly changing environment, traditional training in the form of courses is in danger of losing its effectiveness compared with the learning that goes on within team-based organizations. Integrating work and learning rather than seeing them as two separate functions taking place in separate arenas is one of the hallmarks of ‘learning organizations’ and ‘high performance work systems’ (Ashton and Sung 2002; Senge 1990). The ‘centrally decentralized’ employment relations system is unlikely to place any major institutional obstacles in the way of corporate improvements to production management and work organization today. Low-trust industrial relations are a much bigger obstacle to the full exercise of the potential for company-level agreement. This is because the parties involved can only make such agreements when both are prepared to do so; otherwise the nationwide sectoral agreements will automatically apply. This means that local bargaining has made the most progress in Finland in companies with good bargaining positions between management and employees. In practice, the prevalence of local agreements on the workplace level shows a positive correlation with employee bargaining power (Uhmavaara et al. 2000). The ‘centralized decentralization’ of the bargaining system contains an incentive for employers to develop trust-boosting forms of employee participation that make it possible to reach agreements on the company level. The corresponding incentive for the trade unions is to strive to maintain enough bargaining power through high


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union density and also through expertise in new areas such as work organization, vocational skills and management practices. Otherwise, companies will soon no longer need a mechanism to enable local bargaining, but will instead begin to seek room for manoeuvre in employment relations increasingly through contracts with individual teams and employees, bypassing the trade unions. This might have far-reaching consequences not only for the entire Finnish employment relations system, but also for the consensual innovation policy climate. It might well undermine the willingness of employees and trade unions to support future changes in corporate production management and work organization, thereby slowing the innovation process in the workplace.

REFERENCES Ali-Yrkkö, Jyrki, Laura Paija, Catherine Reilly and Pekka Ylä-Anttila (2000), Nokia – A Big Company in a Small Country, Helsinki: ETLA. Antila, Juha and Pekka Ylöstalo (1999), Functional Flexibility and Workplace Success in Finland, Helsinki: Finnish Ministry of Labour. Ashton, David N. and Johnny Sung (2002), Supporting Workplace Learning for High Performance Working, Geneva: International Labour Office. Bélanger, Jacques, Anthony Giles and Gregor Murray (2002), ‘Towards a New Production Model: Potentials, Tensions and Contradictions’, in Gregor Murray, Jacques Bélanger, Anthony Giles and Paul-André Lapointe (eds), Work and Employment Relations in the High-Performance Workplace, London and New York: Continuum, pp. 15–71. Blom, Raimo, Harri Melin and Pasi Pyöriä (2001), Tietotyö ja työelämän muutos: palkkatyön arki tietoyhteiskunnassa, Helsinki: Gaudeamus. Confederation of Finnish Industry and Employers (2001), Kohti strategisia yritysverkostoja, Helsinki: Confederation of Finnish Industry and Employers. Elam, M.J. (1990), ‘Puzzling Out the Post-Fordist Debate: Technology, Markets and Institutions’, Economic and Industrial Democracy, 11 (1), 9–37. EPOC Research Group (1997), New Forms of Work Organisation: Can Europe Realise its Potential?, Luxembourg: Office for Official Publications of the European Communities. Harrison, Bennett (1994), Lean and Mean: The Changing Landscape of Corporate Power in the Age of Flexibility, New York: Basic Books. Hines, Peter (1994), Creating World Class Suppliers: Unlocking Mutual Competitive Advantage, London: Pitman. Jahnukainen, Miikka and Ari P.J. Vepsäläinen (eds) (1998), Process Management Works – If only Implemented: Reassuring Experiences of Global, Technology-Intensive Companies from a Finnish Perspective, Helsinki: Systems Group Publications. Koistinen, Pertti and Kari Lilja (1988), ‘Consensual Adaptation to New Technology: The Finnish Case’, in Richard Hyman and Wolfgang Streeck (eds), New Technology and Industrial Relations, Oxford: Basil Blackwell, pp. 263–71. Lamming, Richard (1993), Beyond Partnership: Strategies for Innovation and Lean Supply, New York: Prentice-Hall.


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Lehto, Anna-Maija and Hanna Sutela (1999), Efficient, More Efficient, Exhausted: Findings of Finnish Quality of Work Life Surveys 1977–1997, Helsinki: Statistics Finland. Lilja, Kari (1998), ‘Finland: Continuity and Modest Moves towards Company-Level Corporatism’, in Anthony Ferner and Richard Hyman (eds), Changing Industrial Relations in Europe, Oxford: Basil Blackwell, pp. 171–89. Lundvall, Bengt-Åke and Mark Tomlinson (2002), ‘International Benchmarking as a Policy Learning Tool’, in Maria João Rodrigues (ed.), The New Knowledge Economy in Europe: A Strategy for International Competitiveness and Social Cohesion, Cheltenham, UK and Northampton, MA: Edward Elgar, pp. 203–31. McGuckin, Robert H. and Bart van Ark (2002), Performance 2001: Productivity, Employment and Income in the World’s Economies, New York: Conference Board. McHugh, Patrick, Giorgio Merli and William A. Wheeler (1995), Beyond Business Process Reengineering: Towards the Holonic Enterprise, New York: John Wiley. NUTEK (1999), Flexibility Matters – Flexible Enterprises in the Nordic Countries, Stockholm: Swedish National Board for Industrial and Technical Development. Paija, Laura and Pekka Ylä-Anttila (1998), ‘Elinkeinopolitiikka globaalissa verkostotaloudessa’, in Martin Ollus, Jukka Ranta and Pekka Ylä-Anttila (eds), Yritysverkostot – kilpailua tiedolla, nopeudella ja joustavuudella, Helsinki: Sitra, pp. 90–114. Schienstock, Gerd (1999), ‘Transformation and Learning: A New Perspective on National Innovation Systems’, in Gerd Schienstock and Osmo Kuusi (eds), Transformation Towards a Learning Economy: The Challenge for the Finnish Innovation System, Helsinki: Sitra, pp. 9–56. Semlinger, Klaus (1992), ‘Small Firms in Big Subcontracting’, in Norbert Altmann, Christoph Köhler and Pamela Meil (eds), Technology and Work in German Industry, London and New York: Routledge, pp. 342–58. Senge, Peter (1990), The Fifth Discipline: The Art and Practice of the Learning Organization, New York: Doubleday. Tuominen, Carita, Paul Lillrank and Sami Tuurna (2000), Laatukäsitykset suomalaisissa yrityksissä, Helsinki: Finnish Ministry of Trade and Industry. Uhmavaara, Heikki, Martti Kairinen and Jukka Niemelä (eds) (2000), Paikallinen sopiminen työelämässä, Turku: University of Turku, Faculty of Law. Ylöstalo, Pekka (2002), Työolobarometri 2001, Helsinki: Finnish Ministry of Labour.


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PART III

Regions and institutions


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8. The emergence of a regional innovation network: BioTurku in Turku, Finland Henrik Bruun* 8.1

INTRODUCTION**

Recent changes in the foundations of the international economic system have exposed regions to new challenges. Trends such as the liberalization and globalization of markets, technological development, the growth of the high technology sector and new ways to organize production and innovation have led to substantial changes in the conditions for economic growth in states and regions (Cooke and Morgan [1998] 2000). Capital, technology, firms and people are less and less restricted to traditional political or administrative boundaries, but move in what Castells (2000) calls a space of flows. States and regions need to attract those flows in order to sustain economic development. Since growth has been unevenly distributed across economic sectors, many regions have had to restructure their economies during the past ten or twenty years. The goal has generally been to exploit new growth areas, many of which involve the production and utilization of knowledge-intensive technologies. This chapter is a study of the emergence of a regional innovation network in Turku – a Finnish city undergoing the kind of transformation described above. Turku, just like many other cities that want to increase their competitiveness in the globalizing economy, has faced the challenge of increasing the innovative capacity of its local industry. A basic insight of modern innovation research has been that such capacity cannot be built by focusing on individual companies only. In this view, the source of competitiveness is equally much in the environment of the company as in the company itself (Freeman 1994; Lundvall [1992] 1995; Lundvall and Johnson 1994; Porter [1990] 1998). The notion of a ‘milieu of innovation’ has been used for designating local or regional environments that are successful in stimulating innovative activities (Castells and Hall [1994] 2000; Kostiainen and Sotarauta 2000). Such milieux are characterized by their capacity to create synergy between various elements and to channel this synergy into the generation of new knowledge, new processes and 147


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new products (see also Kostiainen 2000). According to Castells (2000, p. 421), ‘[m]ilieux of innovation are the fundamental sources of innovation and of generation of value added in the process of industrial production in the Information Age’. Turku faced this challenge under rapidly changing conditions for local policymaking. At the beginning of the 1990s, Finland experienced a severe recession, which was particularly hard on Turku as a result of its industrial structure. Local decision-makers were forced to pursue more active industrial policies, targeting investments to prioritized branches. Biotechnology was one of these. The new policies aimed at speeding up the growth of the already existing concentration of local biotechnological research and business. I refer to this concentration with the term BioTurku, a notion that is presently used by the local actors for self-designation. My hypothesis is that BioTurku is a regional innovation network rather than just an agglomeration of research and business. This is a crucial question for policy-makers, because network-oriented policies are quite different from policies oriented to support independently operating entities. A regional innovation network is a geographically embedded pattern of interorganizational interactions that converge around some particular field of innovative activity. In this context, ‘network policy’ means that policy-makers focus not only on regionally significant actors, but also on the complex interactions between them. In addition, a network approach helps to identify smaller actors – be they research organizations, companies, consultancies or something else – that are crucial for the network despite their modest size. In short, in network policies the focus is on interaction and systemic effects rather than on discrete actors. Network policies are appropriate only if there really exists a network of mutual interdependencies (Rip and Van der Muelen 1996). If this is not the case, network policies are likely to be inefficient. The empirical material was gathered through interviews, conducted in 2001, with 23 people from Turku, working in organizations that are parts of BioTurku. In addition to the interviews, various kinds of documents were used as primary material. Examples of such documents are strategic plans, memoranda, assessments, risk analyses, overviews, and so on. I have also benefitted largely from Maria Höyssä’s (2001) study of the building of a biotechnology centre in Turku and from my previous collaboration with her on the topic (Bruun et al. 2001), as well as from Nina Janasik’s comparative work on technology policy in the Nordic countries (not yet published). Information about the most recent events and trends in BioTurku was gathered through regular attendance at various seminars on Finnish biotechnology and biotechnology in Turku. The chapter is structured as follows. Section 8.2 provides the reader with some background information about the structure of biotechnology-related education, research and industry in the city. Section 8.3 accounts for the evolution of BioTurku through a series of ‘critical events’. Section 8.4 accounts


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for and discusses the performance of BioTurku in several performance dimensions: education, research, entrepreneurship, employment, commitment from local politicians and authorities and critical discourse. Finally, Section 8.5 discusses the consequences of the research results from a policy perspective.

8.2

BACKGROUND: LIFE SCIENCE RESEARCH AND THE PHARMACEUTICAL INDUSTRY IN TURKU

With its 172 000 inhabitants, Turku is Finland’s fifth largest city. It is situated in the southwestern part of the country, on the shore of the Baltic Sea. The economy of Turku is diverse, based on five ‘clusters’ structured around locally significant activities – shipbuilding; real estate construction maintenance and business; land and sea transport; publishing and printing; and the pharmaceutical and diagnostics industry. Turku was for a long time a relatively prosperous city and there was little pressure to develop local industrial policies. Things changed, however, in the 1990s when the Finnish economy was thrown into deep recession. Unemployment in Turku rose dramatically within a few years, from 4.2 per cent in 1990 to 22.1 per cent in 1994, and stayed at a high level for the rest of the decade. In 2001 the unemployment rate was still above 13 per cent. An additional problem was that Turku experienced a decline in productivity during most of the 1990s, in contrast to competing cities such as Helsinki, Tampere and Oulu. The City of Turku reacted somewhat slowly and only in 1997 was it ready for proactive measures. A Turku strategy was formulated and accepted by the City Council that year. It identified biotechnology, information technology and culture as strategic focus areas. Four years later, the key position of biotechnology for local industrial policy was confirmed in the second Turku strategy. The city of Turku hosts two universities – the University of Turku (16 200 students) and Åbo Akademi University (almost 7000) – a business school, Turku School of Economics (1900), a vocational high school, Turku Polytechnic (over 6000) and a vocational institute, Turku Vocational Institute (4500). The University of Turku and Åbo Akademi University are both traditional universities with a broad range of disciplines. However, neither of them has a general faculty of engineering (although Åbo Akademi has a faculty of chemical engineering) – a fact that is often used as an explanation for Turku’s inability to exploit the Finnish ICT boom. Instead, both universities are strong in life sciences, with a total of four faculties doing research in the area. This cluster of research and education has been organized in a cross-faculty and crossuniversity organization called BioCity Turku.


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Turku’s biotechnology industry has its background in the establishment of the pharmaceutical industry in the city in the late 1940s (Peldán 1967). Today, two of these firms remain: Orion and Leiras (the latter owned by German Schering AG). Orion Pharma is Finland’s most significant developer of new pharmaceutical drugs and some of its key research functions are still located in Turku. Before the end of the 1970s, the Finnish pharmaceutical industry based its business on acquiring licences for foreign products to be marketed domestically. In a world of national trade barriers, this was a successful strategy. It was also compatible with the general Finnish policy of self-sufficiency in sectors of national importance. However, as pressure towards freer trade increased during the 1970s, several Finnish firms decided to embark on internal drug development (Pirhonen et al. 1982). Some were successful. For instance, the Turku-based Farmos developed the first Finnish medicine for breast cancer in the early 1980s. The company also developed tranquillizers and analgesics for animals during that decade. The pharmaceutical industry saw the new strategy as a way to prepare for the westward exports that seemed necessary for compensating future market share losses in the domestic market. Product development, which is very expensive in the pharmaceutical sector, could be financed by the still profitable domestic market and by the export to Russia that had increased rapidly in the 1970s (Interview 1). The 1980s was a decade of consolidation: two companies, Orion Corp. (with headquarters in Espoo) and Huhtamäki Ltd, bought most of their competitors. Both companies were involved in several product development projects and much of this activity was situated in Turku (Farmos was merged with Orion in 1990; Leiras was merged with Medica Group to form Huhtamäki Pharmaceuticals in 1986; in 1992 Leiras once again became a separate legal entity). The 1990s brought radical changes in the operational conditions for the pharmaceutical industry. The Russian export market was closed and prices on the domestic markets started sinking. Partly in response to this, Orion and Leiras made the strategic decision to target their product development more narrowly, that is, to reduce the amount of R&D projects (Interview 1). In 1996, the Huhtamäki Group sold Leiras to the international pharmaceutical Schering AG (Leiras co-operation with Schering goes back to 1953. See Peldán 1967). Some of the R&D activities were moved out of the country, leaving Orion as the most significant Finnish ethical drug developer. At the same time, there was turbulence within another area of local strength, the diagnostics industry. Wallac Ltd, with a long tradition of R&D in Turku, was sold to PerkinElmer Inc. (formerly EG&G Inc.), a global technology company based in the US. As an effect of this turbulence, highly skilful researchers with considerable experience from working with the industry decided to start their own companies in order to pursue the projects that had been shut down. Many of them operated in Turku. Examples of such companies are Galilaeus Ltd (from Leiras), Focus


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Inhalation Ltd (from Leiras), Juvantia Pharma Ltd (from Orion) and Hormos Medical Ltd (from Orion). The drug discovery companies in Turku are presently doing clinical research on seven drug candidates for treatment of disorders and diseases such as heart failure, general anxiety disorder, Parkinson’s disease, osteoporosis, alcoholism and pathological gambling. Orion Pharma and BioTie Therapies are the only ones conducting Phase 3 studies. The lead products of Juvantia and Hormos are in Phase 2, and Orion and BioTie also have a few drug candidates each in this phase. All companies have product pipelines with several projects in the exploratory or preclinical phases of development. From the perspective of turnover, employment and commercial prospects for the future, the pharmaceutical industry is the cornerstone of the local biotechnology cluster. Yet BioTurku is not all about pharmaceuticals. At the end of 2002 it included 63 companies operating in a broad spectrum of sectors, among them pharmaceuticals (9 companies), diagnostics and biotechnology products (15), instrumentation and equipment (8), biomaterials (4), functional and clinical food products (5), research services (9) and business and innovation services for biotechnology companies (10).1 BioTurku as a whole, including university research, was estimated to employ 3000 people in 2000. According to the targets of the local cluster development company, by 2010 BioTurku should employ up to 10 000 people (Nordic Adviser Group 2000). It is also expected to produce 1–5 new companies a year in 2000–2005 and 5–10 in 2005–2010. By 2010, the target document states, at least one of the young biotechnology companies should have become an internationally significant player. At the time of writing (Autumn 2000) these targets have been reached, despite the economic downturn in 2001 and 2002. According to the estimates of Turku Bio Valley Ltd, 500 new jobs have been created since 2000, mainly in the pharmaceutical industry. In addition, the annual rate of 1–5 new companies has been exceeded.

8.3

THE BIOTURKU TRAJECTORY

BioTurku has no definitive date of birth. There was already collaboration between university and industry in the 1970s (Höyssä 2001). However, in the sense of broad collaboration between different universities, industry and public authorities, BioTurku is a relatively recent creation. The construction of the BioCity building and its facilities for the Centre for Biotechnology in 1989–1992 can perhaps be seen as a kind of birth.2 This was paralleled and followed by a series of other critical events or activities: the emergence of the BioCity Turku research community during the 1990s, the Centre of Expertise Programmes of 1994–1998 and 1999–2006, the City of Turku’s decision in 1999 to found Turku Bio Valley Ltd, the working out of a common strategy for BioTurku in 2000, the redefinition of Turku Bio Valley’s mission in 2001,


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the building of PharmaCity and the first development project in Bio Valley (an area, not the company) that same year. A few words about each of these events are necessary for fleshing out the history of BioTurku, and more particularly for assessing the degree to which BioTurku is constituted by local and regional interorganizational interaction. To recapitulate, the task that I set for myself was to investigate whether BioTurku is an agglomeration of organizations and activities, or whether it should be seen as a true network of interaction, interdependence and mutuality. The organizational chart in the Appendix is provided to facilitate reading. 8.3.1

The BioCity Building

BioCity is a seven-floor technology centre building that was finished in 1992. BioCity represents the first substantial attempt in Turku to create a permanent structure for synergy between biotechnology-related academic research and industry. It can therefore be interpreted as a symbol for the birth of BioTurku. The social interaction surrounding the construction of the building has been described and analysed in Höyssä (2001) and Bruun et al. (2001). BioCity was a real estate project, initiated by a construction firm in collaboration with scientists and people working with the industry. Eventually it became more and more of a university project. Both universities moved departments or parts of departments into the new building. The most path-breaking achievement was perhaps the Centre for Biotechnology – an institute shared by the two universities, with the City of Turku as a significant financier. The Centre, which is administered by a board of its own, soon developed into a kernel for research activities across the boundary between academia and business. Some of its more important research orientations have been structural protein research (protein crystallography), cell biology, molecular biology and, most recently, functional genomics. It also provides access to core technologies, such as DNA micro array technology, for the larger research community and (against a fee) for the local biotechnology companies. This system of sharing expensive instruments seems to have been successful. Recently, an international evaluation panel suggested that the Turku model should be expanded into a system of core facilities covering all biocentres in Finland (Academy of Finland 2002). 8.3.2

Education and Research

As the two universities moved into the BioCity building in 1992, the existing cluster of life science research and education was organized in a cross-faculty and cross-university organization called BioCity Turku. Administratively, BioCity Turku belongs to neither of the universities, but has its own board with representatives from both of them. Industry is also represented on the board.


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BioCity Turku’s mission is to effect collaboration, resource sharing, infrastructure development, and synergies in research and education in the area of life sciences. The model of structured interdisciplinary collaboration has been perceived as successful and it has been suggested that it should be diffused to other faculties and departments within the university (Tomlin 1999). BioCity Turku is presently structured in four research programmes – the Receptor Structure and Function programme, the Centre for Reproductive and Developmental Medicine, the Turku Immunology Centre and the Systems Biology Research Programme. In addition, the two universities host or participate in seven graduate schools3 in the life science area, employing 182 graduate students (2000) from Turku in four-year positions. In 1999, the BioCity Turku community produced 94 doctoral degrees (Working Group for Research and Education 2000), which amounts to 54 per cent of the 1999 doctoral degrees at the two universities and 15 per cent of the corresponding life science degrees in Finland (the KOTA database, Ministry of Education). In 1997, an evaluation panel found 11 (out of 40) research groups at BioCity Turku to be of a high international level. The panel also praised the BioCity Turku structure for being ‘a very effective instrument for bringing both fundamental and applied research together under the same roof’ and urged the community to maintain its ‘excellent tradition of collaboration between groups’ (Saraste et al. 1997). A set of other facts support the positive assessments of the quality of the research. Up to 2002, the community had published 26 articles in scientific journals of impact factor greater than 6.0. Domestic competition is hard, however. Biocentre Helsinki has 28 publications, Biocentre Oulu 30 and the Institute of Medical Technology, Tampere 30 in journals of equal quality (see also Table 8.1). BioCity Turku presently hosts two out of 18 biotechnologyrelated national Centres of Excellence, selected by the Academy of Finland. Further, the community hosts two Academy Professors (Academy of Finland) and is thereby the only organization located outside Helsinki to have researchers with this high rank status in the field of biotechnology. Finally, BioCity Turku has been very successful in applications to the EU biotechnology programmes, with partnership in 47 projects in 1996–20014 (Academy of Finland 2002). All in all, Turku is doing relatively well in a country with hard internal competition for excellence and several regional innovation environments of high standard in biotechnology-related education and research (see Table 8.1). Despite primarily being an academic organization, BioCity Turku has had an important networking role through its emphasis on collaboration across disciplinary, faculty and university boundaries. Turku Polytechnic and Turku Vocational Institute supplement the universities by educating bio- and food technology engineers, medical laboratory technologists, laboratory assistants, and so on. Another important institution is the University Hospital of Turku (TYKS), which is one of five university hospitals in Finland, and which actively


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collaborates with both the local pharmaceutical industry and the Faculty of Medicine at the University of Turku. Further, the local business school, Turku School of Economics, offers a BIO Module (20 credits) within its MBA programme. The module is intended for executives and top-level experts in the life sciences sector. Table 8.1 Indicators of regional performance in biotechnology-related research City

Articles Centres of (i.f. > 9.0)* Excellence (bio)

Helsinki Turku Tampere Kuopio Oulu

24 12 19 10 29

9 2 2 1 2

Academy Professors

Partnerships in EU programmes**

10 2 -

103 49 19 17 19

* Articles in journals with an impact factor greater than 9.0 (= top journals). The numbers include the local Biocentres only (thus, publications produced at departments that do not belong to the Biocentres are excluded). I have assumed that there is a 100 per cent overlap between Biocentrum Helsinki and the Institute of Biotechnology Helsinki. ** EU biotechnology projects in 1996–2001. I have assumed a 100 per cent overlap between the local universities and the local biocentres. The numbers given are for the universities in each city. Source:

8.3.3

Academy of Finland (2002), pp. 29, 36, 38

The Centre of Expertise Programmes

The BioCity building was built as a part of an already existing technology centre organization called Data City Centre Ltd (DCC). DCC was later (1999) renamed as Turku Technology Centre Ltd (TTC). DCC was established in the context of constructing Turku’s first technology centre building, the information technology-oriented DataCity, but its sphere of responsibilities was successively extended to include also the bio-field. The most important source of funding for DCC, and later TTC, has been the National Centre of Expertise Programme. This is a national programme for regional development, administered by the Ministry of the Interior. (It should not be confused with the Academy of Finland’s Centre of Excellence Programme.) Regions can apply for funding for projects carried out within a regional Centre of Expertise framework. The idea is to target funding on focused local efforts. At the regional level, the projects are generally administered by a technology centre, such as the DCC. Turku has participated in both the 1994–98 and the 1999–2006


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programmes, with biotechnology as a key focus. The local projects were designed by various people from the industry and the universities, and were operated by DCC. The provincial federation Southwest Finland and the City of Turku participated in the funding. The target of the first programme of expertise was to improve the local infrastructure for research and entrepreneurship. It led to the establishment of a series of units for preclinical and clinical research services at the University of Turku: Clinical Research Services (CRST), the Preclinical Pharmacology Research Unit (PreFa) and Safety City. CRST and Safety City were later (2001) turned into independent companies (and PreFa was integrated with the latter in 2002). The second programme of expertise, which is still going on, puts more emphasis on creating new workplaces and companies, and on the region’s international visibility. The flagship project is perhaps the establishment of a national cluster organization, the Finnish Pharma Cluster, for companies and universities involved in drug development (Southwest Finland Centre of Expertise 1998). In 2001, the Pharma Cluster published a target programme for the Finnish pharmaceutical industry (Brännback et al. 2001). Despite these activities, DCC never acquired a strong position in BioTurku. DCC had few sources of income and biotechnology was just one of the fields it was supposed to promote. Criticism of DCC and a reorganization of the technology centre led in 2002 to the relocation of the centre of expertise administration of biotechnology projects to a new cluster organization for biotechnology, the Turku Bio Valley Ltd. 8.3.4

Turku Bio Valley and the BioTurku Strategy

As described in section 8.2, the turbulence within the local pharmaceutical and diagnostic industry in the middle of the 1990s strongly vitalized the commercial segment of BioTurku. The BioCity building turned out to be an ideal environment for the new spin-off and start-up companies. It provided them with representative facilities and a stimulating environment in which collaboration with university researchers and providers of research services could be pursued on a day-to-day basis. However, the strong growth of some of these companies, and their expected advances from product development to production, seemed to suggest that the BioCity facilities would soon become too small. The City of Turku, which was now pursuing more proactive industrial policies, and which had defined biotechnology as one of its priorities, decided to found a new company, Turku Bio Valley Ltd, for ‘owning, managing and fixing facilities for the growing high-tech companies in the Turku region’. The name of the company derives from the area, the ‘Bio Valley’, that it was given to develop (Turku City Council 1999). The City of Turku invested 12.6 million euros in Turku Bio Valley. The financial arrangements implied that the city’s shares of


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one of the already existing technology centre buildings were to be transferred to Turku Bio Valley, thus giving it the capital and income (through rents) that DCC/TTC had never had. Juhani Leppä, a former city mayor, was appointed as managing director. Perhaps as a result of being new in the field, Leppä felt that there was a need for gathering local actors in the bio-field in order to help Turku Bio Valley to define its own strategy. Such co-ordination was important in ensuring that a sufficient customer base existed for the risky real estate business of the company. Leppä was afraid that the decision to invest heavily in production facilities had been premature, based on a belief that the cluster was more mature than it really was. He initiated a strategy process in the spring of 2000 and managed to enrol all significant members of BioTurku. Leppä’s initiative was timely because, as a result of the rapid developments at the end of the 1990s, many actors felt a need for getting an overview of the network. Businesses were, of course, also interested in benefitting from the resources that the City of Turku was investing in the field. In addition, they had an interest in guaranteeing a future supply of people with a proper education. At the same time, the vocational schools and the universities needed to know how their educational programmes fitted existing and future labour markets. The city, on the other hand, had a chance to make an inventory of its recently selected priority of industrial policies. The city’s mayor Armas Lahoniitty, deputy mayor Juhani Määttä and trade promoter Ilpo Siro all participated in the strategy work. The strategy work had some unexpected consequences. First, it resulted not only in a strategy for Turku Bio Valley, but also in a strategy for the whole of BioTurku (Working Group for Research and Education 2000). Strategy processes have, of course, no value in themselves and are part of the ordinary life of many organizations. In this case, however, we are not talking about a strategy for some specific organization, but for the regional innovation network as a whole. These kinds of regional cluster strategies are not particularly common – neither in Finland nor in the rest of Europe. The strategy framed BioTurku as an innovation chain – from education and basic research to production – and various weak or missing links were identified. A set of shared targets and recommendations were formulated.5 Most of these concerned projects that had already been started and cannot as such be seen as a result of the strategy work. What was significant, however, was that individual projects could now claim to have back-up from the cluster as a whole. This has, according to several interviewees, been crucial for speeding up many of the endeavours. 8.3.5

Turku Science Park

The strategy process described above revealed that there was no organization taking responsibility for the management of the innovation network as a whole.


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The existing boundary-crossing organizations were all restricted in this sense; BioCity Turku focusing on academic collaboration only, the Centre for Biotechnology being exclusively research-oriented and DCC/TCC being too broad and lacking the resources for any more significant input. Leppä wrote a brief to the city administration in which he argued that the city should take action for ensuring the proper management of the bio-cluster (Leppä 2000). Such measures, argued Leppä, would have consequences for the whole technology centre structure. Leppä’s initiative coincided with another initiative to reorganize the city’s technology centre into a much broader structure, called the Turku Science Park. The new ideas attracted the city administration, which established a working group to plan the new structure. The outcome was a proposition that the technology centre be rearranged in a three-company structure in which a new company, Science Park Ltd, would have responsibility for the development and marketing of the science park as a whole, while two cluster corporations would manage and market ‘the strategic branches’ (‘bio’ and ICT). More specifically, the cluster corporations were assigned responsibility in the following areas: business administration, R&D management, administration of projects and programmes, incubators, pre-seed money, technology transfer, venture capital, facilities, equipment and other services. It was emphasized that the cluster corporations should not be general purpose developers, but operate on a strict customer basis – the customers being ‘branchspecific business groups and their service-providers (including the state, region, sub-region and the city)’ (Working Group for Reorganisation of the Technology Centre Activities 2001). The working group also suggested that Turku Bio Valley’s articles of association be changed so that it could function as the cluster corporation for BioTurku. Things happened quite fast here. In July 2000, Leppä complained to the city administration that ‘unless BioTurku is resolutely managed, Turku Bio Valley Ltd will not have customers’. Eight months later, the City Board was already discussing whether Turku Bio Valley itself should be turned into that resolute manager. Formally, this happened in January 2002. 8.3.6

Real Estate Development

At the same time, BioTurku has been expanded through a series of construction projects. A building called PharmaCity was erected next to BioCity in 2001. PharmaCity, just like its neighbour, contains a mix of academia and business. Some of the young bio-companies (Hormos Medical, Juvantia) needed bigger facilities and moved to PharmaCity. VTT Technical Research Centre of Finland located a new research unit, its first in Turku, in the building. PharmaCity’s basement hosts a test animal service centre. The building is owned by VarmaSampo, a Finnish insurance company, which accepted the purchase of it after Turku Bio Valley committed itself to renting three floors (which are


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leased to the companies mentioned above). Expansion is also occurring in the Bio Valley area (a place in Turku), where Turku Bio Valley (the company) has built office and quality control facilities for Novatreat (2500m2) and a pharmaceutical plant for Focus Inhalation (12 000 m2) – both of which are recently established companies (Novatreat 1997, Focus Inhalation 2000). This section has shown that BioTurku evolved through a series of critical events in which the locus of initiative was in constant shift; from real estate companies and the universities in the phase of planning and constructing the BioCity building; to BioCity Turku during the phase of establishing crossfaculty and cross-university research programmes; to DCC and a mix of university departments and companies as the programmes of expertise were designed and implemented; and, most recently, to Turku Bio Valley and the City of Turku in the strategy-making and science park-building phase. At the same time, all these processes involved interorganizational collaboration. The construction of the BioCity building was initiated by real estate companies in collaboration with scientists from the universities and the industry, while most of the actual planning was done by the two universities together. BioCity Turku formalized collaboration between the universities and encouraged interaction across disciplinary boundaries. DCC used scientists from the industry and the universities to plan the programmes of expertise, and the City of Turku was represented at a high level in the DCC board. Further, Turku Bio Valley has made even more extensive and systematic use of the BioTurku network of people and organizations. Its strategy work involved 70–100 people and in 2002 it acquired the formal position as a cluster organization. In sum, an analysis of the critical events suggests that BioTurku really can be seen as a regional innovation network, rather than as an agglomeration of more or less independent activities. This impression acquires further confirmation from the day-to-day reality of BioTurku, as it was described by the interviewees. People circulate between organizations, transferring knowledge from one to the other. Knowledge is also shared through various forms of collaboration. There are many examples of flows or interactions across organizational boundaries: the universities and vocational schools providing industry with educated people; crossfaculty/cross-university research schools and research programmes; equipment sharing between departments, universities and university and business; shared research projects between university and industry; university researchers doing contract research for the industry; service units providing the industry and the universities with different kinds of research-related services; the business school educating executives of bio-businesses; the business school doing market research for companies; common marketing of the network as a whole and so on.


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8.4

159

PERFORMANCE AND CHALLENGES

What about the performance of BioTurku as a regional innovation network? What has been achieved and what are the challenges for the future? In the following analysis, I will interpret performance in a broad sense, so as to include also non-economic dimensions. 8.4.1

To What Extent do Network Members Benefit from BioTurku?

To evaluate this we must distinguish between direct and indirect benefits. The benefit is direct if collaboration with other parties is instrumental in the achievement of the actor’s immediate goals. The benefit is indirect if an organization benefits from the effects that the network as a whole produces, without necessarily being involved in much concrete interaction with other members. BioTurku gives several examples of both direct and indirect benefit. Local sources of direct benefit are, for instance, shared research projects, instruments and marketing campaigns; the building of facilities for bio-companies; the new incubator for bio-companies and its structure for pre-seed funding; research and marketing services; and the Centre of Expertise Programmes that channel national money to the local community. Beneficiaries of such collaboration are, for instance: university departments and companies, which are able to attract funding from national financiers; entrepreneurs, who acquire valuable help in setting up new companies; and small bio-companies, which need to externalize a substantial part of their R&D. Other actors are more indirectly supported by the BioTurku network. Thus the universities, the city and the larger corporations will be indirect beneficiaries if BioTurku succeeds in attracting regional, national and international flows of people, knowledge and capital. One of Turku Bio Valley’s main challenges, in its role of cluster corporation, will be to maintain and deepen the sense of mutual benefit that exists within BioTurku. 8.4.2

Educational Capacity

BioTurku’s educational capacity has been growing and there is a strong bio-educational chain from vocational schools to universities. Also, training programmes that are specifically designed for the needs of the bio-industry have started occurring, most notably at the vocational schools. However, in relation to the challenges of the future, it seems that further changes are needed, both in the quantity and the contents of education. Several interviewees expressed concern about the universities’ ability to provide industry with the required number of people with the right kind of education. Reaching the target of 10 000 workplaces in 2010 means that employees are needed for at least


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6500 new jobs. Many of these will require competences that are in short supply. The overall development threatens to exceed the capacity of the local educational system, which already fails to meet demand. In 2002, the University of Turku had 322 applicants for 40 positions in biochemistry, 331 applicants for 35 positions in biology and 634 applicants for 160 positions in medicine. The situation is similar in the other Finnish universities operating in related fields (Academy of Finland 2002). As a result, parts of the future workforce must be found from other parts of Finland or from abroad. Considering that there is already strong national and international competition for educated people in the bio-fields, the problem can be serious. Since both universities consider their strength to be in their broadness, it is quite unlikely that the problem of lacking a workforce will be solved by rapid changes in the priorities of the universities. Attracting people from outside areas, on the other hand, requires efforts to make Turku an attractive city for potential employees. BioTurku is thus dependent on city policies in fields like housing, the environment, day care, education and culture. It can be expected that the ability of the network to influence policies across such a broad range of sectors is dependent on the degree to which Turku Bio Valley and Turku Science Park can claim themselves to be spokesmen for the network. Thus a certain degree of concentration of representative authority will be needed. 8.4.3

Research Performance

Research performance is good, as described in section 8.3 – especially in immunology, receptor biology, biophysics and computational biochemistry. However, the universities have been criticized for having conservative structures, lacking, for instance, a proper tenure-track system. According to an international evaluation panel (Academy of Finland 2002), this prevents young researchers from forming their own research groups and minimizes the number of postdoctoral fellows. Furthermore, the quantitative rules for the structure of a dissertation (the four published papers rule), ‘deters students from tackling difficult projects’ in order to safeguard success in meeting the requirement (ibid., p. 73). This is, according to the aforementioned evaluation panel, a disincentive to path-breaking research, which is particularly problematic in a country such as Finland, where research is largely done by graduate students. The panel argues that ‘training scientists should aim to raise their level of ambition to tackle difficult and important problems, where success is not inevitable and is judged by content rather than the number of publications’ (ibid., p. 48). The ‘structural conservatism’ of the universities is not a problem only in Turku, but concerns all Finnish universities. Yet the evaluation panel chose to highlight these problems when discussing biotechnology in Turku, because they are ‘in striking contrast to the inventiveness and co-operativity


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of the [BioCity] community’ (ibid., p. 73). One way of interpreting this state of things, even if the Panel does not mention it, is that there would be better prospects for rapid change in the universities of Turku than in other Finnish cities, if only some of the BioCity spirit could enter the universities. 8.4.4

Entrepreneurship

Turku hosts a large share of new Finnish technology companies (in the sense of knowledge-intensive small companies that are less than five years old) in the life science field. According to Finnish Bio Industries, more than 40 per cent of Finnish start-up companies in the fields of medicine and diagnostics were situated in Turku (Kuusi 2001). These companies have also been successful in attracting venture capital. Finland’s two major venture capital companies in the life science field are Sitra (public) and BioFund (private). Twenty-five per cent of Sitra’s present investment objects in the bio-field, and 18 per cent of the companies in BioFund’s portfolios I and II are situated in Turku. The corresponding numbers for the cities in the much larger capital region (Helsinki and Espoo) are 20 per cent and 18 per cent. However, many expect the entrepreneurial leadership to move from Turku to Helsinki in the next few years as a result of recent investments in innovation infrastructure there. 8.4.5

Employment

BioTurku is estimated to employ some 3500 people. The trend of employment has been positive, but will have to accelerate significantly if the target of 10 000 jobs is to be reached in 2010. Such a development is not beyond the realm of possibility, considering that many of the existing start-up or spin-off companies are working on products that will be commercialized during this decade. Yet commercialization does not automatically mean a dramatic increase in employment, since most companies plan to license their products to producers outside Turku. Some of the interviewees considered the ‘old’ pharmaceutical and diagnostic industry to be more significant for future employment than the new, smaller enterprises. The positive development in the area also makes the arrival of one or two large foreign employers an increasingly likely scenario. In sum, BioTurku’s present performance in employment is not very informative about its employing capacity in the future. 8.4.6

Attracting ‘External’ Organizations and Extra-regional Collaboration

BioTurku has not been successful in attracting multinational companies to start new activities in the area. Both Schering and Perkin-Elmer took over already


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existing companies. On the domestic side, some companies have chosen to relocate to Turku from other Finnish cities. Orion Pharma has expanded its research activities in Turku and in 2001 VTT Technical Research Centre of Finland decided to start a new drug development unit in Turku. The small size of BioTurku might turn out to be a significant restriction in the future. The local perspective on development therefore risks being in conflict with the needs of the industry. A sign of this is the national Pharma Cluster initiative that was taken by the new pharmaceutical industry in Turku. This ‘cluster-network’ organizes collaboration nationally, not locally. BioTurku is simply quite small when compared with other European and American concentrations of bio-industry, and openness to extra-regional collaboration will become increasingly significant. 8.4.7

Public Commitment

Public involvement in BioTurku has increased significantly during recent years. This means that societal approval is becoming more significant for the cluster. Until now, BioTurku has been successful in achieving such approval. There seems to be little criticism of the public commitment, or of the prevailing research orientations and industrial activities. Public approval is mediated by the city’s elected representatives. Worryingly, however, most interviewees felt that local politicians have little interest in, and knowledge of, BioTurku, and that their involvement generally means trouble rather than constructive input. It is striking that none of my 22 interviewees mentioned any City Board or City Council members as people who should be interviewed about BioTurku, and when asked about it, most interviewees had serious difficulties in coming up with even one name. If this reflects the state of knowledge and interest in these matters among local politicians, public involvement in BioTurku might turn out to be provisional only. The commitment to public long-term investments in the science park and its clusters would be threatened whenever an economic downturn makes more immediate problems pressing. Yet, as a result of restrictions in its design, this study cannot verify the interviewees’ statements about the involvement of politicians. Whatever the case, it seems that openness in relation to local political forces would be a sound long-term policy, even if exclusion in this direction were more efficient in the short run. There are important problems to be solved concerning the relation between the public and private domains. Through Turku Bio Valley, the City of Turku promotes private business with huge profit opportunities and high risks. The continued legitimacy of this kind of policy will depend on maintaining taxpayers’ trust in the sincerity of the BioTurku actors and in the control mechanisms related to the use of public money. Policy implementation through public corporations, such as Turku Bio Valley, risks failing to address the issue


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of political involvement and control. Some of the characteristics of the BioTurku network even undermine such control – most notably, the low degree of transparency and the relatively high degrees of density and informality. How can the public sector combine the need for political support and control with its desire to promote a dynamic, competitive and economically successful biocluster? This is a problem that needs to be addressed not only to safeguard the interests of taxpayers, but also to ensure the long-term involvement of the city and consistent public policies. 8.4.8

Critical Discourse

An additional issue related to political legitimacy is openness to criticism. In the hands of Turku Bio Valley, BioTurku is being branded. One of the company’s main tasks is to market the cluster. All interviewees, and particularly city administrators and business people, emphasized the importance of image creation. Image, they argued, is important for attracting students, researchers, funding for research, other investments and companies to Turku. It is also significant for mobilizing local support for the involvement of the city. Images should, according to all interviewees, be based on ‘substance’, because most actors in the field have the capacity to reveal fraud. However, since BioTurku ‘really is a dynamic cluster’, the interviewees felt that this should be highlighted in the communication to internal and external parties. A continuous flow of new steps forward in the building of the cluster is therefore of great importance; ‘something must happen all the time’ (Interview 1). Now, as a social scientist one is inclined to ask to what extent this aspired-to image of smooth development and continuous enthusiasm risks suffocating possible criticism, both related to the city’s involvement in BioTurku and to the ways in which biotechnology is put to use. As BioTurku becomes a part of the city’s identity and economic strategy, it becomes increasingly difficult to neglect the effects of criticism on local success. Thus, integration and consistency, which are important from the perspective of short-term economic performance, might turn out to undermine critical discourse.

8.5

DISCUSSION

This study has shown that BioTurku really can be understood as a regional innovation network rather than an agglomeration of separate activities. At the beginning, BioTurku was a relatively centred6 network, with universities being the powerful actors, while the pharmaceutical industry operated more or less independently. However, in the latter part of the 1990s many new bio-companies were established. At the same time, the City of Turku redefined its interests in


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the bio-field. This has pushed the network in a more decentred direction, with the universities, the new bioindustry and the city as the powerful nodes. It seems reasonable to assume that BioTurku is characterized by a relatively high degree of connectivity, which means that several actors (such as the small biotechnology companies or organizations at the interface of activity domains, such as DCC/TTC, the Centre for Biotechnology and Turku Bio Valley) are in intense interaction with other members of the network, and therefore dependent on it. They also have relatively consistent views of BioTurku and its future. At least there was a large consensus on the goals and the needs of the network, as articulated in the BioTurku strategy and in Turku Bio Valley’s strategy report (Nordic Adviser Group 2000; Working Group for Research and Education 2000). None of my interviewees contested the contents of these documents, and none of them questioned the initiatives taken by the city to establish the science park and the cluster organization for the bio-field. All seemed to accept the role that Turku Bio Valley had taken upon itself as a manager of BioTurku. From the perspective of policy-making, the networked nature of BioTurku means that it should be wise to design policy measures that support interaction and create interfaces between activities and organizations, rather than measures that promote discrete activities or individual actors. This is already happening both at the local and the national levels. At the local level, Turku Bio Valley pursued network policies from the start. At the national level, several authorities do the same. The most significant of them, from the network policy perspective, is the National Technology Agency (Tekes), which is one of the two main financiers of Finnish biotechnology R&D. Thus it seems that the present principles for policy-making are appropriate for meeting the challenges mentioned above. It is important, however, that policy-makers attend to the actual characteristics of BioTurku as a regional innovation network. At the moment, this is done more or less intuitively. I suggest that network policies could be further systematized, explicitly taking into account network features such as concentration, connectivity and goal consistency. Other important network characteristics are ‘openness’ and ‘formality’. BioTurku has a history of being an open and informal network. Today the network is being formalized as a part of the science park structure, which could mean that some of its openness is lost in the future. Several interviewees expressed the fear that the establishment of Turku Science Park, with its two cluster corporations for ‘bio’ and ICT, might give rise to sharpened competition for public resources between the two clusters. This could be detrimental to collaboration across the cluster boundaries in emerging fields such as bioinformatics. Yet another parameter for evaluating network performance is ‘transparency’, referring to the clarity of the overall picture that people have of the organizations in the network and the relation between their activities. Transparency in this sense has always been a problem for BioTurku. Many of the initiatives that


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were taken to develop the network were actually responses to a lack of transparency. The new cluster organization could perhaps remedy this by actively informing about BioTurku to all relevant internal and external parties, and by actively supporting the co-ordination of activities. Under conditions of the rapid growth of the network that is expected to occur the next few years, this could turn out to be quite a formidable task. All in all, this study suggests that network features such as informality, connectivity and goal consistency enhance performance in certain areas, such as education, research and entrepreneurship, while at the same time being potentially problematic for other kinds of performance, for example, broad participation in decision-making, political legitimacy and critical discourse. The latter require openness and transparency and perhaps also a formality that guarantees participation to actors who do not have access to the informal networks. There is also a tension between the need for closure and concentration in order to build lobbying power for the network, on the one hand, and the need for openness and distributed decision-making to maintain flexibility, on the other. These are the contradictions that network policies face, and the future of BioTurku is at least partly dependent on how well its actors can balance between the conflicting needs.

ACKNOWLEDGEMENTS I thank all the interviewees for their participation and positive attitude towards the study, and Turku Bio Valley Ltd for helping me with arranging interviews. I particularly thank Maria Höyssä for her extensive work in commenting on the text. Janne Hukkinen, Andrew Jamison, Richard Langlais, Reija Linnamaa, Terttu Luukkonen, Mikko Rask, Johanna Reiman, Markku Sotarauta, Göran Sundqvist and Knut Sørensen also gave me valuable feedback on earlier versions of the manuscript.

NOTES * Henrik Bruun, Helsinki University of Technology, Laboratory of Environmental Protection, P.O.Box 2300, 02015 HUT, Finland. Tel. +358 9 451 3855, Mobile +358 50 5174160, Fax +358 9 451 2359, E-mail [email protected] ** This research was funded by Nordregio, the Academy of Finland and the National Technology Agency of Finland (Tekes). Earlier versions of the article have been published in the report series of the Helsinki University of Technology Laboratory of Environmental Protection and Nordregio. 1. These numbers are based on Turku Bio Valley Ltd’s list of ‘BioTurku companies’ in early December 2002.


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2. The Centre for Biotechnology was founded already in 1988, and operated on a small scale in the Data City building until BioCity was finished. 3. The Graduate Schools are a part of the national system of higher education. They are administered by the Ministry of Education. 4. Compare with Biocentre Helsinki (22 projects), Biocentre Oulu (12 projects) and Institute of Medical Technology, Tampere, (16 projects). 5. Collaboration between educational organizations on the realization of new training programmes, a strengthening of the Centre for Biotechnology in the area of functional genomics, the establishment of a drug development centre within the framework of BioCity Turku, strengthening the position of the Centre for Biomaterials in the university structure, the establishment of a national food development centre with an interdisciplinary orientation, attracting the VTT Technical Research Centre of Finland to Turku, the quick establishment of an incubator exclusively for bio-businesses, the development of clean room activities, and investigations into how international bio-industry could be attracted to Turku more efficiently. 6. Centred networks are based on asymmetrical relations, such as hierarchies of command or a supplier network that is dominated by one big user. Decentred networks, on the other hand, consist of symmetrical relations: mutual friendship, equal terms for participation, and so on. (Mattila and Uusikylä 1999).

REFERENCES Academy of Finland (2002), Biotechnology in Finland: Impact of Public Research Funding and Strategies for the Future: Evaluation Report, Publications of the Academy of Finland, 11. Bruun, Henrik, Maria Höyssä and Janne Hukkinen (2001), ‘Networks of Ephemeral Empowerment. The Birth of a Biotechnology Centre in Turku, Finland’, in Technology Society, Environment (3), Espoo, Helsinki University of Technology Laboratory of Environmental Protection, pp. 53–70. Brännback, Malin, Pekka Hyvönen, Hannu Raunio, Maija Renko and Riitta Sutinen (2001), ‘Finnish Pharma Cluster – Vision 2010: Target Programme Initiated by the Finnish Pharma Cluster’, Technology Review, 112, Helsinki: Tekes. Castells, Manuel (2000), The Rise of the Network Society, Oxford and Malden, MA: Blackwell. Castells, Manuel and Peter Hall ([1994] 2000), Technopoles of the World: The Making of Twenty-First-Century Industrial Complexes, London: Routledge. Cooke, Philip and Kevin Morgan (eds) ([1998] 2000), The Associational Economy: Firms, Regions, and Innovation, Oxford: Oxford University Press. Freeman, Christopher (1994), ‘The Economics of Technical Change: A Critical Survey’, Cambridge Journal of Economics, 18, 463–514. Höyssä, Maria (2001), Teknologiakeskusta tekemässä: BioCity-hankkeen vaiheet ideasta osaamiskeskuksen osaksi [Making a technology centre: The stages of the BioCityproject, from idea to a part of a Centre of Expertise], Master’s thesis, Turku: University of Turku. Kostiainen, Juha (2000), ‘Helsingin, Oulun ja Tampereen kaupunkiseudut innovatiivisina miljöinä’ [Helsinki, Oulu and Tampere as innovative milieux], in Juha Kostiainen and Markku Sotarauta (eds), Kaupungit innovatiivisina toimintaympäristöinä, Helsinki: Tekniikan Akateemisten Liitto TEK ry, pp. 85–126. Kostiainen, Juha and Markku Sotarauta (eds) (2000), Kaupungit innovatiivisina toimintaympäristöinä, Helsinki: Tekniikan Akateemisten Liitto TEK ry.


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Kuusi, H. (2001), ‘Finland a European Leader in Biotechnology’, Kemia-Kemi, 28 (6), 432–7. Leppä, Juhani (2000), Turun teknologiakeskuksen tulevaisuuden näkymät [The future of Turku technology centre], Turku: 12 July 2000, Brief to Turku City Administration. Lundvall, Bengt-Åke, (ed.) ([1992] 1995), National Systems of Innovation: Towards a Theory of Innovation and Interactive Learning, London and New York: Pinter. Lundvall, Bengt-Åke and Björn Johnson (1994), ‘The Learning Economy’, Journal of Industry Studies, 1 (2), 23–41. Mattila, Mikko and Petri Uusikylä (1999), ‘Mitä on verkostoanalyysi?’ [What is network analysis?] in Mikko Mattila and Petri Uusikylä (eds), Verkostoyhteiskunta. Käytännön johdatus verkostoanalyysiin, Helsinki: Gaudeamus, pp. 7–21. Nordic Adviser Group (2000), Biolaakso: Loppuraportti [Biolaakso: Final report]. Turku, 16 November 2000, Biolaakso Ltd. Peldán, Kerttu (1967), Suomen farmasian historia [History of Finnish pharmacy], Helsinki: Suomen farmaseuttinen yhdistys. Pirhonen, Pentti, Juhani Saraste, Erik Borg, Hannu Helle, Holger Rosenblad and Veikko Sonninen (eds) (1982), Lääketeollisuusyhdistys 1957–1982, Rauma: LTY. Porter, Michael E. ([1990] 1998), The Competitive Advantage of Nations. With a New Introduction, Basingstoke: Macmillan Press. Rip, A. and J. R. Van der Muelen (1996), ‘The Post-Modern Research System’, Science and Public Policy, 23 (6), 343–52. Saraste, Matti, Jonathan Knowles and Ari Helenius (1997), Selection of BioCity Research Groups to form the new Turku Centre of Excellence, Turku: Report to the Advisory Board of BioCity Turku. Southwest Finland Centre of Expertise (1998), Ohjelmaesitys kaudelle 1999–2006 [Programme proposal for the period 1999–2006], Turku: Data City Centre Ltd. Tomlin, Richard (1999), ‘University of Turku – External Impact of Research, Technology Transfer and Regional Liaison Activities’, Publications, 5, University of Turku, Rector’s Office. Turku City Council (1999), Kiinteistöomistajayhtiön perustaminen [Foundation of a real estate owning company], Turku, 11 Janury 1999, 8736-1998 (70, 642, 010), Kv § 18. Working Group for Reorganization of the Technology Centre Activities (2001), Teknologiakeskustoiminnan uudelleen järjestäminen [Reorganization of the Technology Centre activities], Turku: Memorandum, Turku City Administration. Working Group for Research and Education (2000), Turun bioalan strategia [Strategy for the bio-sector in Turku], Turku: Biolaakso Ltd.


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APPENDIX: ORGANIZATIONAL CHART OF BIOTURKU (organizations still existing in bold)

Farmos 1958/1947

Orion Group 1970/1917

Leiras 1949/1946

Galilaeus 1994

Schering AG

Wallac 1950

Juvantia Pharma 1997

Focus Inhalation 1999

Hormos Medical 1997

Cities of Raisio and Kaarina, YIT Data City Patron Ltd ÅA Foundation UTU Foundation

Control Pharma 1998

DCC DataCity Centre 1988 → Turku Technology Centre 1999

PerkinElmer

Valio 1905

Novatreat 1997

Raisio Group 1939

Other companies (some examples) Biotop 1992 HyTest 1994 Biofons 1994 Innotrac Diagnostics 1995 Abmin Technologies 1996 CellTest 1997

City of Turku

BioCity Turku 1999 (informally since 1993) – Research programmes

Science Park 2001

Turku Bio Valley 1999 Centre for Biotechnology 1988

Turku School of Economics and Business Administration – Innomarket

Åbo Akademi University ÅA – Faculty of Mathematics and Natural Science – Faculty of Chemical Engineering

ICT Turku 2001 BioCity S. A. Board 1992 Technology centre buildings DataCity 1988–89 BioCity 1992 ElectroCity 1989 EuroCity 1999 Old Mill 2000 PharmaCity 2001

SafetyCity 2001

University Hospital of Turku

Turku Polytechnic

University of Turku UTU – Faculty of Medicine – Faculty of Mathematics and Natural Sciences – PreFa 1997 – SafetyCity 1997

CRST 1995/2001

BioTie Therapies 2002 (1996/1992)

Turku Vocational Institute

Explanations of arrows and shading: Becomes part of, is merged with

Limited company

Spin-off activity or company

Public research and/or education

Founds, initiates …

Other public organizations


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9. From the national industrial heartland towards a node in the global knowledge economy: The case of Tampere Region* Mika Kautonen, Pasi Koski and Gerd Schienstock 9.1

INTRODUCTION

Numerous studies on the dynamics of firms and industries have been carried out in which variables like technological research, capital investment, corporate organization, labour skills, macroeconomic policy and many others have been exhaustively examined in an attempt to determine firm and industrial performance. As a result, a vast body of important insights has been accumulated. With some minor exceptions, however, the problem as to whether or not firm and industrial performance might also somehow be grounded in geography and location has been mostly overlooked (see for example Scott 1998). This is somewhat surprising for several reasons. First, a considerable proportion of total world output of particular goods is produced in a limited number of highly concentrated regions. Second, firms in particular industries, or firms that are technologically or otherwise related, tend to locate in the same place and form geographically bounded agglomerations (Porter and Sölvell 1998, p. 441). Third, both of these phenomena tend to be persistent over time – even in the case of new knowledge-intensive industries, in which firms are usually highly capable of exploiting the full state-of-the-art possibilities of information and communication technologies. In fact, the local and regional levels seem to increase in importance compared to the national level, as far as innovation processes are concerned. This is due to, for example, EU policies, increased regional endogenous development actions also facilitated by these policies, as well as multinational companies (MNCs) searching for suitable investment locations, in addition to agglomeration advantages, mentioned above. However, this process of regionalization favours those regions that are capable of providing an environment with embedded resources that are valuable, rare, difficult to imitate, and/or hard to substitute (see Barney 1991). 169


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Such an environment may be a source of competitive advantage for existing firms belonging to its networks, and provide a seedbed for new firms to emerge. Therefore, the regional dimension is relevant in a global economy for firms’ innovative activities especially due to the following reasons (see Howells 1999; Lundvall and Borrás 1998; Porter and Sölvell 1998): • formal and informal contacts between network members are made possible through casual information exchanges, planned meetings and customer-supplier relationships • synergies can emerge from the shared cultural, psychological or political perspectives of actors engaged in the same specialization • a localized pool of specialized expertise and knowledge for a certain industrial cluster may contain a considerable amount of tacit knowledge difficult to transfer to other localities. Tampere Region represents a remarkable case of a renewal that is turning the former industrial heart of Finland into a visible node in global knowledge production (see also Kostiainen and Sotarauta 2002). The core idea of the regional strategy is based on Castells’ notion of ‘space of flows’ (1996). The regional government’s ambitious aim is not only to keep the region as a centre of the national ICT cluster, but also to develop it into an independent node in the global knowledge economy and to integrate it tightly into global information and knowledge flows. This chapter analyses the spatial dimension of the knowledge economy from the Finnish viewpoint. First we briefly discuss the increasingly uneven regional development in Finland, with only a few centres of rapid economic growth, including Tampere Region. Next we give an overview of the socioeconomic structure and development strategies of the region. The focal point of our chapter is the transformation process towards a regional knowledge economy. We first describe the creation of the knowledge base of the region. We then analyse the structures and institutions related to the diffusion and intermediation of knowledge in Tampere Region. Next we deal with companies’ capacity to adapt to and make use of the regional knowledge base. We also discuss some problems related to the emergence of the regional knowledge economy, as this process is not a positive-sum game. Finally we sum up our notions and discuss the existing and prospective challenges in Tampere Region.

9.2

GROWTH AND UNEVEN REGIONAL DEVELOPMENT IN FINLAND

One of the most significant phenomena in post-recession Finland is the coexistence of the remarkable growth of knowledge-intensive industries,


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From the national industrial heartland

171

especially ICT, and the rapid acceleration of uneven regional development (Valtioneuvoston kanslia 2000). Figure 9.1 shows how production, employment, and R&D investments accumulated to a great extent in 1995–99 within a few large cities with universities and large research and development facilities or within cities specialized in the production of information and communication technologies. The former include the city-regions of Helsinki, Tampere, Oulu, and to some extent those of Turku and Jyväskylä. In the latter case, the small town of Salo with the large production facilities of the Nokia Group is especially worth mentioning. For many stagnating regions based on traditional industries with low expectations of employment growth, the accumulation has been a very serious problem because they are already sparsely populated. These regions also often suffer from problems with the ageing of the population, as the young generation tends to move to larger cities for education or employment. However, the prospering city-regions are not without problems either. In most cases, they suffer from relatively high structural unemployment due to

Real growth of GNP, 1995–1999, % > 20 10–20 0–10

Embracing the Knowledge Economy: The Dynamic Transformation of the Finnish Innovation System (New Horizons in the Economics of Innovation)

Innovation and the Creative Process: Towards Innovation With Care (New Horizons in the Economics of Innovation)

The Evaluation of the Finnish National Innovation System - Full Report

Asia's Innovation Systems in Transition (New Horizons in the Economics of Innovation.)

Innovation in the Service Economy: The New Wealth of Nations

The Innovation Imperative: National Innovation Stategies in the Global Economy

The Discipline of Innovation

The Myths of Innovation

The Myths of Innovation

Culture and Economics in the Global Community (Transformation and Innovation)

The Economics of Innovation (Critical Concepts in Economics)

Innovation and Growth in the Global Economy

Strategic Management in the Innovation Economy: Strategic Approaches and Tools for Dynamic Innovation Capabilities

Innovation Diffusion in the New Economy: Tacit Component

The Economics of Persistent Innovation: An Evolutionary View (Economics of Science, Technology and Innovation)

Innovation, Growth and Competitiveness: Dynamic Regions in the Knowledge-Based World Economy (Advances in Spatial Science)

Finance at the Threshold (Transformation and Innovation)

The Business of Healthcare Innovation

Inventorship: The Art of Innovation

The European Challenge: Innovation, Policy Learning And Social Cohesion in the New Knowledge Economy

Mastering the Dynamics of Innovation

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